From fe02cba606d1329afd8b1e28451b390d678305e8 Mon Sep 17 00:00:00 2001 From: Avasam Date: Wed, 10 Apr 2024 09:12:07 -0400 Subject: [PATCH] Bump mypy-protobuf in sync_tensorflow script and improve generation scripts (#11740) --- scripts/generate_proto_stubs.sh | 17 +- scripts/sync_tensorflow_protobuf_stubs.sh | 138 +++--- stubs/tensorflow/METADATA.toml | 2 +- .../compiler/xla/autotune_results_pb2.pyi | 14 +- .../compiler/xla/service/hlo_pb2.pyi | 445 ++++++++++-------- .../compiler/xla/service/metrics_pb2.pyi | 17 +- .../tensorflow/compiler/xla/xla_data_pb2.pyi | 298 +++++++----- .../example_parser_configuration_pb2.pyi | 33 +- .../tensorflow/core/example/example_pb2.pyi | 15 +- .../tensorflow/core/example/feature_pb2.pyi | 49 +- .../framework/allocation_description_pb2.pyi | 7 +- .../tensorflow/core/framework/api_def_pb2.pyi | 51 +- .../core/framework/attr_value_pb2.pyi | 55 ++- .../core/framework/cost_graph_pb2.pyi | 40 +- .../core/framework/dataset_metadata_pb2.pyi | 7 +- .../core/framework/dataset_options_pb2.pyi | 89 ++-- .../tensorflow/core/framework/dataset_pb2.pyi | 26 +- .../core/framework/device_attributes_pb2.pyi | 35 +- .../core/framework/full_type_pb2.pyi | 13 +- .../core/framework/function_pb2.pyi | 61 +-- .../tensorflow/core/framework/graph_pb2.pyi | 21 +- .../framework/graph_transfer_info_pb2.pyi | 46 +- .../core/framework/kernel_def_pb2.pyi | 33 +- .../core/framework/log_memory_pb2.pyi | 33 +- .../tensorflow/core/framework/model_pb2.pyi | 46 +- .../core/framework/node_def_pb2.pyi | 41 +- .../tensorflow/core/framework/op_def_pb2.pyi | 85 ++-- .../optimized_function_graph_pb2.pyi | 20 +- .../core/framework/reader_base_pb2.pyi | 7 +- .../core/framework/resource_handle_pb2.pyi | 14 +- .../core/framework/step_stats_pb2.pyi | 67 +-- .../tensorflow/core/framework/summary_pb2.pyi | 48 +- .../core/framework/tensor_description_pb2.pyi | 11 +- .../tensorflow/core/framework/tensor_pb2.pyi | 42 +- .../core/framework/tensor_shape_pb2.pyi | 20 +- .../core/framework/tensor_slice_pb2.pyi | 16 +- .../tensorflow/core/framework/types_pb2.pyi | 5 +- .../core/framework/variable_pb2.pyi | 21 +- .../core/framework/versions_pb2.pyi | 8 +- .../core/protobuf/bfc_memory_map_pb2.pyi | 1 + .../tensorflow/core/protobuf/cluster_pb2.pyi | 17 +- .../protobuf/composite_tensor_variant_pb2.pyi | 9 +- .../tensorflow/core/protobuf/config_pb2.pyi | 346 +++++++------- .../core/protobuf/control_flow_pb2.pyi | 43 +- .../core/protobuf/coordination_config_pb2.pyi | 108 ----- .../protobuf/core_platform_payloads_pb2.pyi | 5 +- .../core/protobuf/data_service_pb2.pyi | 21 +- .../core/protobuf/debug_event_pb2.pyi | 104 ++-- .../tensorflow/core/protobuf/debug_pb2.pyi | 38 +- .../core/protobuf/device_filters_pb2.pyi | 22 +- .../core/protobuf/device_properties_pb2.pyi | 28 +- .../distributed_runtime_payloads_pb2.pyi | 81 ---- .../core/protobuf/error_codes_pb2.pyi | 1 + .../core/protobuf/fingerprint_pb2.pyi | 10 +- .../core/protobuf/graph_debug_info_pb2.pyi | 24 +- .../core/protobuf/meta_graph_pb2.pyi | 165 ++++--- .../core/protobuf/named_tensor_pb2.pyi | 10 +- .../core/protobuf/queue_runner_pb2.pyi | 15 +- .../protobuf/remote_tensor_handle_pb2.pyi | 14 +- .../core/protobuf/rewriter_config_pb2.pyi | 41 +- .../core/protobuf/rpc_options_pb2.pyi | 1 + .../core/protobuf/saved_model_pb2.pyi | 8 +- .../core/protobuf/saved_object_graph_pb2.pyi | 158 ++++--- .../tensorflow/core/protobuf/saver_pb2.pyi | 5 +- .../core/protobuf/service_config_pb2.pyi | 41 +- .../tensorflow/core/protobuf/snapshot_pb2.pyi | 36 +- .../tensorflow/core/protobuf/struct_pb2.pyi | 87 ++-- .../core/protobuf/tensor_bundle_pb2.pyi | 19 +- .../core/protobuf/tensorflow_server_pb2.pyi | 24 +- .../protobuf/tpu/compilation_result_pb2.pyi | 8 +- .../core/protobuf/tpu/dynamic_padding_pb2.pyi | 7 +- .../tpu/optimization_parameters_pb2.pyi | 171 +++---- .../core/protobuf/tpu/topology_pb2.pyi | 22 +- .../tpu/tpu_embedding_configuration_pb2.pyi | 30 +- .../protobuf/trackable_object_graph_pb2.pyi | 34 +- .../core/protobuf/transport_options_pb2.pyi | 7 +- .../core/protobuf/verifier_config_pb2.pyi | 5 +- .../tensorflow/core/util/event_pb2.pyi | 54 ++- .../core/util/memmapped_file_system_pb2.pyi | 11 +- .../core/util/saved_tensor_slice_pb2.pyi | 39 +- .../tensorflow/core/util/test_log_pb2.pyi | 1 + .../keras/protobuf/projector_config_pb2.pyi | 31 +- .../keras/protobuf/saved_metadata_pb2.pyi | 15 +- .../python/keras/protobuf/versions_pb2.pyi | 8 +- .../tsl/protobuf/autotuning_pb2.pyi | 52 +- .../tsl/protobuf/bfc_memory_map_pb2.pyi | 25 +- .../tsl/protobuf/coordination_config_pb2.pyi | 16 +- .../tsl/protobuf/coordination_service_pb2.pyi | 165 +++---- .../distributed_runtime_payloads_pb2.pyi | 15 +- .../tensorflow/tsl/protobuf/dnn_pb2.pyi | 58 +-- .../tsl/protobuf/error_codes_pb2.pyi | 1 + .../tensorflow/tsl/protobuf/histogram_pb2.pyi | 8 +- .../tsl/protobuf/rpc_options_pb2.pyi | 7 +- .../tensorflow/tsl/protobuf/test_log_pb2.pyi | 132 +++--- 94 files changed, 2346 insertions(+), 2054 deletions(-) delete mode 100644 stubs/tensorflow/tensorflow/core/protobuf/coordination_config_pb2.pyi delete mode 100644 stubs/tensorflow/tensorflow/core/protobuf/distributed_runtime_payloads_pb2.pyi diff --git a/scripts/generate_proto_stubs.sh b/scripts/generate_proto_stubs.sh index 74aac79a57c8..e0e682bf4b4f 100755 --- a/scripts/generate_proto_stubs.sh +++ b/scripts/generate_proto_stubs.sh @@ -35,6 +35,7 @@ echo "Working in $TMP_DIR" wget "$PROTOC_URL" mkdir protoc_install unzip "$PROTOC_FILENAME" -d protoc_install +protoc_install/bin/protoc --version # Fetch protoc-python (which contains all the .proto files) wget "$PYTHON_PROTOBUF_URL" @@ -67,16 +68,22 @@ PROTO_FILES=$(grep "GenProto.*google" $PYTHON_PROTOBUF_DIR/python/setup.py | \ # And regenerate! # shellcheck disable=SC2086 -protoc_install/bin/protoc --proto_path="$PYTHON_PROTOBUF_DIR/src" --mypy_out="relax_strict_optional_primitives:$REPO_ROOT/stubs/protobuf" $PROTO_FILES +protoc_install/bin/protoc \ + --proto_path="$PYTHON_PROTOBUF_DIR/src" \ + --mypy_out="relax_strict_optional_primitives:$REPO_ROOT/stubs/protobuf" \ + $PROTO_FILES PYTHON_PROTOBUF_VERSION=$(jq -r '.[] | .languages.python' "$PYTHON_PROTOBUF_DIR/version.json") +# Cleanup after ourselves, this is a temp dir, but it can still grow fast if run multiple times +rm -rf "$TMP_DIR" +# Must be in a git repository to run pre-commit +cd "$REPO_ROOT" + sed --in-place="" \ "s/extra_description = .*$/extra_description = \"Generated using [mypy-protobuf==$MYPY_PROTOBUF_VERSION](https:\/\/github.com\/nipunn1313\/mypy-protobuf\/tree\/v$MYPY_PROTOBUF_VERSION) on [protobuf v$PROTOBUF_VERSION](https:\/\/github.com\/protocolbuffers\/protobuf\/releases\/tag\/v$PROTOBUF_VERSION) (python protobuf==$PYTHON_PROTOBUF_VERSION)\"/" \ - "$REPO_ROOT/stubs/protobuf/METADATA.toml" + stubs/protobuf/METADATA.toml -# Must be run in a git repository -cd "$REPO_ROOT" # use `|| true` so the script still continues even if a pre-commit hook # applies autofixes (which will result in a nonzero exit code) -pre-commit run --files $(git ls-files -- "$REPO_ROOT/stubs/protobuf/**_pb2.pyi") || true +pre-commit run --files $(git ls-files -- "stubs/protobuf/**_pb2.pyi") || true diff --git a/scripts/sync_tensorflow_protobuf_stubs.sh b/scripts/sync_tensorflow_protobuf_stubs.sh index 3de1895324a5..4813e3497b0b 100755 --- a/scripts/sync_tensorflow_protobuf_stubs.sh +++ b/scripts/sync_tensorflow_protobuf_stubs.sh @@ -1,79 +1,97 @@ #!/bin/bash +# Based on scripts/generate_proto_stubs.sh. +# Generates the protobuf stubs for the given tensorflow version using mypy-protobuf. +# Generally, new minor versions are a good time to update the stubs. + set -euxo pipefail -# Partly based on scripts/generate_proto_stubs.sh. +# Need protoc >= 3.15 for explicit optional +PROTOBUF_VERSION=25.3 # 4.25.3 +# Whenever you update TENSORFLOW_VERSION here, version should be updated +# in stubs/tensorflow/METADATA.toml and vice-versa. +TENSORFLOW_VERSION=2.12.1 +MYPY_PROTOBUF_VERSION=3.6.0 -# Generates the protobuf stubs for the given tensorflow version using mypy-protobuf. -# Generally, new minor versions are a good time to update the stubs. +if uname -a | grep Darwin; then + # brew install coreutils wget + PLAT=osx +else + PLAT=linux +fi REPO_ROOT="$(realpath "$(dirname "${BASH_SOURCE[0]}")"/..)" +TMP_DIR="$(mktemp -d)" +TENSORFLOW_FILENAME="v$TENSORFLOW_VERSION.zip" +PROTOC_FILENAME="protoc-$PROTOBUF_VERSION-$PLAT-x86_64.zip" +PROTOC_URL="https://github.com/protocolbuffers/protobuf/releases/download/v$PROTOBUF_VERSION/$PROTOC_FILENAME" +TENSORFLOW_URL="https://github.com/tensorflow/tensorflow/archive/refs/tags/$TENSORFLOW_FILENAME" -# This version should be consistent with the version in tensorflow's METADATA.toml. -TENSORFLOW_VERSION=2.12.1 -# Latest mypy-protobuf has dependency on protobuf >4, which is incompatible at runtime -# with tensorflow. However, the stubs produced do still work with tensorflow. So after -# installing mypy-protobuf, before running stubtest on tensorflow you should downgrade -# protobuf<4. -MYPY_PROTOBUF_VERSION=3.5.0 +cd "$TMP_DIR" +echo "Working in $TMP_DIR" -pip install pre-commit mypy-protobuf=="$MYPY_PROTOBUF_VERSION" +# Install protoc +wget "$PROTOC_URL" +mkdir protoc_install +unzip "$PROTOC_FILENAME" -d protoc_install +protoc_install/bin/protoc --version -cd "$(dirname "$0")" > /dev/null -cd ../stubs/tensorflow -mkdir -p repository -pushd repository &> /dev/null - # If the script fails halfway, it's nice to be able to re-run it immediately - if [ ! -d "tensorflow" ] ; then - git clone --depth 1 --branch v"$TENSORFLOW_VERSION" https://github.com/tensorflow/tensorflow.git - fi - pushd tensorflow &> /dev/null - # Folders here cover the more commonly used protobufs externally and - # their dependencies. Tensorflow has more protobufs and can be added if requested. - protoc --mypy_out "relax_strict_optional_primitives:$REPO_ROOT/stubs/tensorflow" \ - tensorflow/compiler/xla/*.proto \ - tensorflow/compiler/xla/service/*.proto \ - tensorflow/core/example/*.proto \ - tensorflow/core/framework/*.proto \ - tensorflow/core/protobuf/*.proto \ - tensorflow/core/protobuf/tpu/*.proto \ - tensorflow/core/util/*.proto \ - tensorflow/python/keras/protobuf/*.proto \ - tensorflow/tsl/protobuf/*.proto - popd &> /dev/null -popd &> /dev/null +# Fetch tensorflow (which contains all the .proto files) +wget "$TENSORFLOW_URL" +unzip "$TENSORFLOW_FILENAME" +TENSORFLOW_DIR="tensorflow-$TENSORFLOW_VERSION" + +# Prepare virtualenv +python3 -m venv .venv +source .venv/bin/activate +python3 -m pip install pre-commit mypy-protobuf=="$MYPY_PROTOBUF_VERSION" + +# Remove existing pyi +find "$REPO_ROOT/stubs/tensorflow/" -name "*_pb2.pyi" -delete + +# Folders here cover the more commonly used protobufs externally and +# their dependencies. Tensorflow has more protobufs and can be added if requested. +protoc_install/bin/protoc \ + --proto_path="$TENSORFLOW_DIR" \ + --mypy_out "relax_strict_optional_primitives:$REPO_ROOT/stubs/tensorflow" \ + $TENSORFLOW_DIR/tensorflow/compiler/xla/*.proto \ + $TENSORFLOW_DIR/tensorflow/compiler/xla/service/*.proto \ + $TENSORFLOW_DIR/tensorflow/core/example/*.proto \ + $TENSORFLOW_DIR/tensorflow/core/framework/*.proto \ + $TENSORFLOW_DIR/tensorflow/core/protobuf/*.proto \ + $TENSORFLOW_DIR/tensorflow/core/protobuf/tpu/*.proto \ + $TENSORFLOW_DIR/tensorflow/core/util/*.proto \ + $TENSORFLOW_DIR/tensorflow/python/keras/protobuf/*.proto \ + $TENSORFLOW_DIR/tensorflow/tsl/protobuf/*.proto \ + +# Cleanup after ourselves, this is a temp dir, but it can still grow fast if run multiple times +rm -rf "$TMP_DIR" +# Must be in a git repository to run pre-commit +cd "$REPO_ROOT" # These protos exist in a folder with protos used in python, but are not # included in the python wheel. They are likely only used for other # language builds. stubtest was used to identify them by looking for # ModuleNotFoundError. -rm tensorflow/compiler/xla/service/hlo_execution_profile_data_pb2.pyi \ - tensorflow/compiler/xla/service/hlo_profile_printer_data_pb2.pyi \ - tensorflow/compiler/xla/service/test_compilation_environment_pb2.pyi \ - tensorflow/compiler/xla/xla_pb2.pyi \ - tensorflow/core/protobuf/autotuning_pb2.pyi \ - tensorflow/core/protobuf/conv_autotuning_pb2.pyi \ - tensorflow/core/protobuf/critical_section_pb2.pyi \ - tensorflow/core/protobuf/eager_service_pb2.pyi \ - tensorflow/core/protobuf/master_pb2.pyi \ - tensorflow/core/protobuf/master_service_pb2.pyi \ - tensorflow/core/protobuf/replay_log_pb2.pyi \ - tensorflow/core/protobuf/tpu/compile_metadata_pb2.pyi \ - tensorflow/core/protobuf/worker_pb2.pyi \ - tensorflow/core/protobuf/worker_service_pb2.pyi \ - tensorflow/core/util/example_proto_fast_parsing_test_pb2.pyi - +rm \ + stubs/tensorflow/tensorflow/compiler/xla/service/hlo_execution_profile_data_pb2.pyi \ + stubs/tensorflow/tensorflow/compiler/xla/service/hlo_profile_printer_data_pb2.pyi \ + stubs/tensorflow/tensorflow/compiler/xla/service/test_compilation_environment_pb2.pyi \ + stubs/tensorflow/tensorflow/compiler/xla/xla_pb2.pyi \ + stubs/tensorflow/tensorflow/core/protobuf/autotuning_pb2.pyi \ + stubs/tensorflow/tensorflow/core/protobuf/conv_autotuning_pb2.pyi \ + stubs/tensorflow/tensorflow/core/protobuf/critical_section_pb2.pyi \ + stubs/tensorflow/tensorflow/core/protobuf/eager_service_pb2.pyi \ + stubs/tensorflow/tensorflow/core/protobuf/master_pb2.pyi \ + stubs/tensorflow/tensorflow/core/protobuf/master_service_pb2.pyi \ + stubs/tensorflow/tensorflow/core/protobuf/replay_log_pb2.pyi \ + stubs/tensorflow/tensorflow/core/protobuf/tpu/compile_metadata_pb2.pyi \ + stubs/tensorflow/tensorflow/core/protobuf/worker_pb2.pyi \ + stubs/tensorflow/tensorflow/core/protobuf/worker_service_pb2.pyi \ + stubs/tensorflow/tensorflow/core/util/example_proto_fast_parsing_test_pb2.pyi \ sed --in-place="" \ "s/extra_description = .*$/extra_description = \"Partially generated using [mypy-protobuf==$MYPY_PROTOBUF_VERSION](https:\/\/github.com\/nipunn1313\/mypy-protobuf\/tree\/v$MYPY_PROTOBUF_VERSION) on tensorflow==$TENSORFLOW_VERSION\"/" \ - "$REPO_ROOT/stubs/tensorflow/METADATA.toml" - -# Cleanup last. If the script fails halfway, it's nice to be able to re-run it immediately -rm -rf repository/ + stubs/tensorflow/METADATA.toml -# Must be run in a git repository -cd $REPO_ROOT # use `|| true` so the script still continues even if a pre-commit hook # applies autofixes (which will result in a nonzero exit code) -pre-commit run --files $(git ls-files -- "$REPO_ROOT/stubs/tensorflow/tensorflow") || true -# Ruff takes two passes to fix everything, re-running all of pre-commit is *slow* -# and we don't need --unsafe-fixes to remove imports -ruff check "$REPO_ROOT/stubs/tensorflow/tensorflow" --fix --exit-zero +pre-commit run --files $(git ls-files -- "stubs/tensorflow/**_pb2.pyi") || true diff --git a/stubs/tensorflow/METADATA.toml b/stubs/tensorflow/METADATA.toml index f9ccf68d4e90..a040d3b32056 100644 --- a/stubs/tensorflow/METADATA.toml +++ b/stubs/tensorflow/METADATA.toml @@ -2,7 +2,7 @@ version = "2.15.*" upstream_repository = "https://github.com/tensorflow/tensorflow" # requires a version of numpy with a `py.typed` file requires = ["numpy>=1.20", "types-protobuf", "types-requests"] -extra_description = "Partially generated using [mypy-protobuf==3.5.0](https://github.com/nipunn1313/mypy-protobuf/tree/v3.5.0) on tensorflow==2.12.1" +extra_description = "Partially generated using [mypy-protobuf==3.6.0](https://github.com/nipunn1313/mypy-protobuf/tree/v3.6.0) on tensorflow==2.12.1" partial_stub = true [tool.stubtest] diff --git a/stubs/tensorflow/tensorflow/compiler/xla/autotune_results_pb2.pyi b/stubs/tensorflow/tensorflow/compiler/xla/autotune_results_pb2.pyi index beee5221bfa6..bc7c054ceb74 100644 --- a/stubs/tensorflow/tensorflow/compiler/xla/autotune_results_pb2.pyi +++ b/stubs/tensorflow/tensorflow/compiler/xla/autotune_results_pb2.pyi @@ -16,9 +16,10 @@ See the License for the specific language governing permissions and limitations under the License. ============================================================================== """ + import builtins import collections.abc -import typing as typing_extensions +import typing import google.protobuf.descriptor import google.protobuf.internal.containers @@ -27,7 +28,7 @@ import tensorflow.tsl.protobuf.autotuning_pb2 DESCRIPTOR: google.protobuf.descriptor.FileDescriptor -@typing_extensions.final +@typing.final class AutotuneResults(google.protobuf.message.Message): """A collection of algorithms for particular dot/convs. Usually this is "the best" algorithm for the particular dot/conv, although that's not strictly @@ -43,7 +44,7 @@ class AutotuneResults(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor - @typing_extensions.final + @typing.final class Entry(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -60,6 +61,7 @@ class AutotuneResults(google.protobuf.message.Message): algorithms returned by cublasLt. Different version of cublasLt -> different list of algos -> different interpretation of results! """ + def __init__( self, *, @@ -67,8 +69,8 @@ class AutotuneResults(google.protobuf.message.Message): hlo: builtins.str | None = ..., result: tensorflow.tsl.protobuf.autotuning_pb2.AutotuneResult | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["result", b"result"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["device", b"device", "hlo", b"hlo", "result", b"result"]) -> None: ... + def HasField(self, field_name: typing.Literal["result", b"result"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["device", b"device", "hlo", b"hlo", "result", b"result"]) -> None: ... VERSION_FIELD_NUMBER: builtins.int DOTS_FIELD_NUMBER: builtins.int @@ -85,6 +87,6 @@ class AutotuneResults(google.protobuf.message.Message): dots: collections.abc.Iterable[global___AutotuneResults.Entry] | None = ..., convs: collections.abc.Iterable[global___AutotuneResults.Entry] | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["convs", b"convs", "dots", b"dots", "version", b"version"]) -> None: ... + def ClearField(self, field_name: typing.Literal["convs", b"convs", "dots", b"dots", "version", b"version"]) -> None: ... global___AutotuneResults = AutotuneResults diff --git a/stubs/tensorflow/tensorflow/compiler/xla/service/hlo_pb2.pyi b/stubs/tensorflow/tensorflow/compiler/xla/service/hlo_pb2.pyi index d3454c8ba0b9..0ece50c39b90 100644 --- a/stubs/tensorflow/tensorflow/compiler/xla/service/hlo_pb2.pyi +++ b/stubs/tensorflow/tensorflow/compiler/xla/service/hlo_pb2.pyi @@ -14,6 +14,7 @@ Unlike most protos, you can't safely change the names of fields, even if you keep the numeric ids the same. This is because we sometimes serialize these protos as JSON, which includes the field names in the serialization. """ + import builtins import collections.abc import sys @@ -214,7 +215,7 @@ MUST_ALIAS: Kind.ValueType # 2 """The buffers must alias at runtime.""" global___Kind = Kind -@typing_extensions.final +@typing.final class HloInstructionProto(google.protobuf.message.Message): """Serialization of HloInstruction. Next ID: 81 @@ -222,7 +223,7 @@ class HloInstructionProto(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor - @typing_extensions.final + @typing.final class SliceDimensions(google.protobuf.message.Message): """Describes the [begin, end) index range and stride for slices.""" @@ -241,7 +242,7 @@ class HloInstructionProto(google.protobuf.message.Message): limit: builtins.int | None = ..., stride: builtins.int | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["limit", b"limit", "start", b"start", "stride", b"stride"]) -> None: ... + def ClearField(self, field_name: typing.Literal["limit", b"limit", "start", b"start", "stride", b"stride"]) -> None: ... NAME_FIELD_NUMBER: builtins.int OPCODE_FIELD_NUMBER: builtins.int @@ -313,51 +314,21 @@ class HloInstructionProto(google.protobuf.message.Message): ASYNC_EXECUTION_THREAD_FIELD_NUMBER: builtins.int name: builtins.str opcode: builtins.str - @property - def shape(self) -> tensorflow.compiler.xla.xla_data_pb2.ShapeProto: ... - @property - def metadata(self) -> tensorflow.compiler.xla.xla_data_pb2.OpMetadata: ... - @property - def literal(self) -> tensorflow.compiler.xla.xla_data_pb2.LiteralProto: - """Literal, only present for kConstant.""" parameter_number: builtins.int """Parameter number is only present for kParameter.""" fusion_kind: builtins.str """Fusion state, only present for kFusion.""" tuple_index: builtins.int """Index for kGetTupleElement.""" - @property - def dimensions(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.int]: - """Dimensions present for some operations that require reshaping or - broadcasting, including Reshape, Reduce, ReduceWindow, and Reverse. - """ - @property - def window(self) -> tensorflow.compiler.xla.xla_data_pb2.Window: - """Describes the window in a windowed operation such as convolution.""" - @property - def convolution_dimension_numbers(self) -> tensorflow.compiler.xla.xla_data_pb2.ConvolutionDimensionNumbers: - """Describes the dimension numbers used for a convolution.""" feature_group_count: builtins.int """The number of feature groups. Used for a convolution. Must be a divisor of the input feature dimension and output feature dimension. If not specified, it will use a default value of 1. """ batch_group_count: builtins.int - @property - def slice_dimensions(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___HloInstructionProto.SliceDimensions]: ... exponent_bits: builtins.int """The bit sizes for a reduce-precision operation.""" mantissa_bits: builtins.int - @property - def dynamic_slice_sizes(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.int]: - """Describes the [start, start + size) range size for a dynamic slice - ('start' is specified dynamically in the second operand of the operation). - """ - @property - def padding_config(self) -> tensorflow.compiler.xla.xla_data_pb2.PaddingConfig: - """The padding configuration that describes the edge padding and interior - padding of this pad instruction. Only set for pad instructions. - """ outfeed_config: builtins.bytes """Outfeed configuration information, only present for kOutfeed.""" distribution: tensorflow.compiler.xla.xla_data_pb2.RandomDistribution.ValueType @@ -385,39 +356,14 @@ class HloInstructionProto(google.protobuf.message.Message): """Name of a external target (eg, global symbol) to call, only present for kCustomCall. """ - @property - def outfeed_shape(self) -> tensorflow.compiler.xla.xla_data_pb2.ShapeProto: - """Shape of outfeed request.""" - @property - def dot_dimension_numbers(self) -> tensorflow.compiler.xla.xla_data_pb2.DotDimensionNumbers: - """Describes the dimension numbers used for a dot operation""" fft_type: tensorflow.compiler.xla.xla_data_pb2.FftType.ValueType """FFT type (FFT, IFFT, etc).""" - @property - def fft_length(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.int]: - """FFT length.""" comparison_direction: builtins.str """Comparison direction only used for kCompare.""" - @property - def gather_dimension_numbers(self) -> tensorflow.compiler.xla.xla_data_pb2.GatherDimensionNumbers: - """Gather dimension numbers.""" - @property - def gather_slice_sizes(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.int]: ... id: builtins.int """The id of this instruction.""" - @property - def operand_ids(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.int]: ... - @property - def control_predecessor_ids(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.int]: ... - @property - def called_computation_ids(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.int]: ... - @property - def sharding(self) -> tensorflow.compiler.xla.xla_data_pb2.OpSharding: ... backend_config: builtins.bytes """Backend configuration for the instruction. Has backend-specific meaning.""" - @property - def replica_groups(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[tensorflow.compiler.xla.xla_data_pb2.ReplicaGroup]: - """Cross replica op fields.""" all_reduce_id: builtins.int """Deprecated, but keeping it for backward compatibility. Use channel_id. Non-positive all_reduce_id is equivalent to no all_reduce_id. @@ -433,45 +379,16 @@ class HloInstructionProto(google.protobuf.message.Message): """ is_stable: builtins.bool """Whether this Sort instruction should be stable.""" - @property - def scatter_dimension_numbers(self) -> tensorflow.compiler.xla.xla_data_pb2.ScatterDimensionNumbers: ... - @property - def precision_config(self) -> tensorflow.compiler.xla.xla_data_pb2.PrecisionConfig: - """Precision configuration for the instruction. Has backend-specific meaning.""" - @property - def source_target_pairs(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[tensorflow.compiler.xla.xla_data_pb2.SourceTarget]: - """Collective permute field.""" - @property - def domain_entry_sharding(self) -> tensorflow.compiler.xla.xla_data_pb2.OpSharding: - """Sharding for kDomain instructions.""" - @property - def domain_exit_sharding(self) -> tensorflow.compiler.xla.xla_data_pb2.OpSharding: ... constrain_layout: builtins.bool """For custom call this indicates that the layouts are constrained. If constrain_layout is true then the 'shape' field must contain a layout, and 'operand_shapes_with_layout' must contain a shape with layout for each operand. """ - @property - def operand_shapes_with_layout(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[tensorflow.compiler.xla.xla_data_pb2.ShapeProto]: ... - @property - def triangular_solve_options(self) -> tensorflow.compiler.xla.xla_data_pb2.TriangularSolveOptions: - """Options for TriangularSolve""" - @property - def cholesky_options(self) -> tensorflow.compiler.xla.xla_data_pb2.CholeskyOptions: - """Options for Cholesky""" - @property - def parameter_replication(self) -> tensorflow.compiler.xla.xla_data_pb2.ParameterReplication: - """Describes how parameters behave with regards to replicas.""" custom_call_has_side_effect: builtins.bool """Whether the kCustomCall instruction has side-effects, only present for kCustomCall. """ - @property - def output_operand_aliasing(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[tensorflow.compiler.xla.xla_data_pb2.OutputOperandAliasing]: - """A list of OutputOperandAliasing pairs that specifies aliasing buffers - between output and operands for kCustomCall and kFusion. - """ custom_call_schedule: global___CustomCallSchedule.ValueType """Specifies the desired schedule for the custom-call. The field is only present for custom-call. @@ -482,9 +399,6 @@ class HloInstructionProto(google.protobuf.message.Message): """Specifies if the gather/scatter indices are guaranteed to be sorted by the caller. """ - @property - def frontend_attributes(self) -> tensorflow.compiler.xla.xla_data_pb2.FrontendAttributes: - """Frontend attributes to pass to the XLA backend.""" unique_indices: builtins.bool """Specifies if all elements updated are guaranteed to be unique by the caller. @@ -516,6 +430,112 @@ class HloInstructionProto(google.protobuf.message.Message): Each HLO module may contain a main thread and one or more parallel threads. Empty async_execution_thread is equivalent to main thread. """ + @property + def shape(self) -> tensorflow.compiler.xla.xla_data_pb2.ShapeProto: ... + @property + def metadata(self) -> tensorflow.compiler.xla.xla_data_pb2.OpMetadata: ... + @property + def literal(self) -> tensorflow.compiler.xla.xla_data_pb2.LiteralProto: + """Literal, only present for kConstant.""" + + @property + def dimensions(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.int]: + """Dimensions present for some operations that require reshaping or + broadcasting, including Reshape, Reduce, ReduceWindow, and Reverse. + """ + + @property + def window(self) -> tensorflow.compiler.xla.xla_data_pb2.Window: + """Describes the window in a windowed operation such as convolution.""" + + @property + def convolution_dimension_numbers(self) -> tensorflow.compiler.xla.xla_data_pb2.ConvolutionDimensionNumbers: + """Describes the dimension numbers used for a convolution.""" + + @property + def slice_dimensions(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___HloInstructionProto.SliceDimensions]: ... + @property + def dynamic_slice_sizes(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.int]: + """Describes the [start, start + size) range size for a dynamic slice + ('start' is specified dynamically in the second operand of the operation). + """ + + @property + def padding_config(self) -> tensorflow.compiler.xla.xla_data_pb2.PaddingConfig: + """The padding configuration that describes the edge padding and interior + padding of this pad instruction. Only set for pad instructions. + """ + + @property + def outfeed_shape(self) -> tensorflow.compiler.xla.xla_data_pb2.ShapeProto: + """Shape of outfeed request.""" + + @property + def dot_dimension_numbers(self) -> tensorflow.compiler.xla.xla_data_pb2.DotDimensionNumbers: + """Describes the dimension numbers used for a dot operation""" + + @property + def fft_length(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.int]: + """FFT length.""" + + @property + def gather_dimension_numbers(self) -> tensorflow.compiler.xla.xla_data_pb2.GatherDimensionNumbers: + """Gather dimension numbers.""" + + @property + def gather_slice_sizes(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.int]: ... + @property + def operand_ids(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.int]: ... + @property + def control_predecessor_ids(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.int]: ... + @property + def called_computation_ids(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.int]: ... + @property + def sharding(self) -> tensorflow.compiler.xla.xla_data_pb2.OpSharding: ... + @property + def replica_groups(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[tensorflow.compiler.xla.xla_data_pb2.ReplicaGroup]: + """Cross replica op fields.""" + + @property + def scatter_dimension_numbers(self) -> tensorflow.compiler.xla.xla_data_pb2.ScatterDimensionNumbers: ... + @property + def precision_config(self) -> tensorflow.compiler.xla.xla_data_pb2.PrecisionConfig: + """Precision configuration for the instruction. Has backend-specific meaning.""" + + @property + def source_target_pairs(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[tensorflow.compiler.xla.xla_data_pb2.SourceTarget]: + """Collective permute field.""" + + @property + def domain_entry_sharding(self) -> tensorflow.compiler.xla.xla_data_pb2.OpSharding: + """Sharding for kDomain instructions.""" + + @property + def domain_exit_sharding(self) -> tensorflow.compiler.xla.xla_data_pb2.OpSharding: ... + @property + def operand_shapes_with_layout(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[tensorflow.compiler.xla.xla_data_pb2.ShapeProto]: ... + @property + def triangular_solve_options(self) -> tensorflow.compiler.xla.xla_data_pb2.TriangularSolveOptions: + """Options for TriangularSolve""" + + @property + def cholesky_options(self) -> tensorflow.compiler.xla.xla_data_pb2.CholeskyOptions: + """Options for Cholesky""" + + @property + def parameter_replication(self) -> tensorflow.compiler.xla.xla_data_pb2.ParameterReplication: + """Describes how parameters behave with regards to replicas.""" + + @property + def output_operand_aliasing(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[tensorflow.compiler.xla.xla_data_pb2.OutputOperandAliasing]: + """A list of OutputOperandAliasing pairs that specifies aliasing buffers + between output and operands for kCustomCall and kFusion. + """ + + @property + def frontend_attributes(self) -> tensorflow.compiler.xla.xla_data_pb2.FrontendAttributes: + """Frontend attributes to pass to the XLA backend.""" + def __init__( self, *, @@ -588,13 +608,13 @@ class HloInstructionProto(google.protobuf.message.Message): async_group_id: builtins.int | None = ..., async_execution_thread: builtins.str | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["cholesky_options", b"cholesky_options", "convolution_dimension_numbers", b"convolution_dimension_numbers", "cross_program_prefetch_index", b"cross_program_prefetch_index", "domain_entry_sharding", b"domain_entry_sharding", "domain_exit_sharding", b"domain_exit_sharding", "dot_dimension_numbers", b"dot_dimension_numbers", "frontend_attributes", b"frontend_attributes", "gather_dimension_numbers", b"gather_dimension_numbers", "literal", b"literal", "metadata", b"metadata", "optional_cross_program_prefetch_index", b"optional_cross_program_prefetch_index", "outfeed_shape", b"outfeed_shape", "padding_config", b"padding_config", "parameter_replication", b"parameter_replication", "precision_config", b"precision_config", "scatter_dimension_numbers", b"scatter_dimension_numbers", "shape", b"shape", "sharding", b"sharding", "triangular_solve_options", b"triangular_solve_options", "window", b"window"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["all_reduce_id", b"all_reduce_id", "async_execution_thread", b"async_execution_thread", "async_group_id", b"async_group_id", "backend_config", b"backend_config", "batch_group_count", b"batch_group_count", "called_computation_ids", b"called_computation_ids", "channel_id", b"channel_id", "cholesky_options", b"cholesky_options", "comparison_direction", b"comparison_direction", "comparison_type", b"comparison_type", "constrain_layout", b"constrain_layout", "control_predecessor_ids", b"control_predecessor_ids", "convolution_dimension_numbers", b"convolution_dimension_numbers", "cross_program_prefetch_index", b"cross_program_prefetch_index", "custom_call_api_version", b"custom_call_api_version", "custom_call_has_side_effect", b"custom_call_has_side_effect", "custom_call_schedule", b"custom_call_schedule", "custom_call_target", b"custom_call_target", "delta", b"delta", "dimensions", b"dimensions", "distribution", b"distribution", "domain_entry_sharding", b"domain_entry_sharding", "domain_exit_sharding", b"domain_exit_sharding", "dot_dimension_numbers", b"dot_dimension_numbers", "dynamic_slice_sizes", b"dynamic_slice_sizes", "epsilon", b"epsilon", "exponent_bits", b"exponent_bits", "feature_group_count", b"feature_group_count", "feature_index", b"feature_index", "fft_length", b"fft_length", "fft_type", b"fft_type", "frontend_attributes", b"frontend_attributes", "fusion_kind", b"fusion_kind", "gather_dimension_numbers", b"gather_dimension_numbers", "gather_slice_sizes", b"gather_slice_sizes", "id", b"id", "indices_are_sorted", b"indices_are_sorted", "infeed_config", b"infeed_config", "is_cross_program_prefetch", b"is_cross_program_prefetch", "is_host_transfer", b"is_host_transfer", "is_stable", b"is_stable", "literal", b"literal", "mantissa_bits", b"mantissa_bits", "metadata", b"metadata", "name", b"name", "opcode", b"opcode", "operand_ids", b"operand_ids", "operand_shapes_with_layout", b"operand_shapes_with_layout", "optional_cross_program_prefetch_index", b"optional_cross_program_prefetch_index", "outfeed_config", b"outfeed_config", "outfeed_shape", b"outfeed_shape", "output_operand_aliasing", b"output_operand_aliasing", "padding_config", b"padding_config", "padding_type", b"padding_type", "parameter_number", b"parameter_number", "parameter_replication", b"parameter_replication", "precision_config", b"precision_config", "replica_groups", b"replica_groups", "rng_algorithm", b"rng_algorithm", "scatter_dimension_numbers", b"scatter_dimension_numbers", "shape", b"shape", "sharding", b"sharding", "slice_dimensions", b"slice_dimensions", "source_target_pairs", b"source_target_pairs", "triangular_solve_options", b"triangular_solve_options", "tuple_index", b"tuple_index", "unique_indices", b"unique_indices", "use_global_device_ids", b"use_global_device_ids", "window", b"window"]) -> None: ... - def WhichOneof(self, oneof_group: typing_extensions.Literal["optional_cross_program_prefetch_index", b"optional_cross_program_prefetch_index"]) -> typing_extensions.Literal["cross_program_prefetch_index"] | None: ... + def HasField(self, field_name: typing.Literal["cholesky_options", b"cholesky_options", "convolution_dimension_numbers", b"convolution_dimension_numbers", "cross_program_prefetch_index", b"cross_program_prefetch_index", "domain_entry_sharding", b"domain_entry_sharding", "domain_exit_sharding", b"domain_exit_sharding", "dot_dimension_numbers", b"dot_dimension_numbers", "frontend_attributes", b"frontend_attributes", "gather_dimension_numbers", b"gather_dimension_numbers", "literal", b"literal", "metadata", b"metadata", "optional_cross_program_prefetch_index", b"optional_cross_program_prefetch_index", "outfeed_shape", b"outfeed_shape", "padding_config", b"padding_config", "parameter_replication", b"parameter_replication", "precision_config", b"precision_config", "scatter_dimension_numbers", b"scatter_dimension_numbers", "shape", b"shape", "sharding", b"sharding", "triangular_solve_options", b"triangular_solve_options", "window", b"window"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["all_reduce_id", b"all_reduce_id", "async_execution_thread", b"async_execution_thread", "async_group_id", b"async_group_id", "backend_config", b"backend_config", "batch_group_count", b"batch_group_count", "called_computation_ids", b"called_computation_ids", "channel_id", b"channel_id", "cholesky_options", b"cholesky_options", "comparison_direction", b"comparison_direction", "comparison_type", b"comparison_type", "constrain_layout", b"constrain_layout", "control_predecessor_ids", b"control_predecessor_ids", "convolution_dimension_numbers", b"convolution_dimension_numbers", "cross_program_prefetch_index", b"cross_program_prefetch_index", "custom_call_api_version", b"custom_call_api_version", "custom_call_has_side_effect", b"custom_call_has_side_effect", "custom_call_schedule", b"custom_call_schedule", "custom_call_target", b"custom_call_target", "delta", b"delta", "dimensions", b"dimensions", "distribution", b"distribution", "domain_entry_sharding", b"domain_entry_sharding", "domain_exit_sharding", b"domain_exit_sharding", "dot_dimension_numbers", b"dot_dimension_numbers", "dynamic_slice_sizes", b"dynamic_slice_sizes", "epsilon", b"epsilon", "exponent_bits", b"exponent_bits", "feature_group_count", b"feature_group_count", "feature_index", b"feature_index", "fft_length", b"fft_length", "fft_type", b"fft_type", "frontend_attributes", b"frontend_attributes", "fusion_kind", b"fusion_kind", "gather_dimension_numbers", b"gather_dimension_numbers", "gather_slice_sizes", b"gather_slice_sizes", "id", b"id", "indices_are_sorted", b"indices_are_sorted", "infeed_config", b"infeed_config", "is_cross_program_prefetch", b"is_cross_program_prefetch", "is_host_transfer", b"is_host_transfer", "is_stable", b"is_stable", "literal", b"literal", "mantissa_bits", b"mantissa_bits", "metadata", b"metadata", "name", b"name", "opcode", b"opcode", "operand_ids", b"operand_ids", "operand_shapes_with_layout", b"operand_shapes_with_layout", "optional_cross_program_prefetch_index", b"optional_cross_program_prefetch_index", "outfeed_config", b"outfeed_config", "outfeed_shape", b"outfeed_shape", "output_operand_aliasing", b"output_operand_aliasing", "padding_config", b"padding_config", "padding_type", b"padding_type", "parameter_number", b"parameter_number", "parameter_replication", b"parameter_replication", "precision_config", b"precision_config", "replica_groups", b"replica_groups", "rng_algorithm", b"rng_algorithm", "scatter_dimension_numbers", b"scatter_dimension_numbers", "shape", b"shape", "sharding", b"sharding", "slice_dimensions", b"slice_dimensions", "source_target_pairs", b"source_target_pairs", "triangular_solve_options", b"triangular_solve_options", "tuple_index", b"tuple_index", "unique_indices", b"unique_indices", "use_global_device_ids", b"use_global_device_ids", "window", b"window"]) -> None: ... + def WhichOneof(self, oneof_group: typing.Literal["optional_cross_program_prefetch_index", b"optional_cross_program_prefetch_index"]) -> typing.Literal["cross_program_prefetch_index"] | None: ... global___HloInstructionProto = HloInstructionProto -@typing_extensions.final +@typing.final class HloComputationProto(google.protobuf.message.Message): """Serialization of HloComputation.""" @@ -608,14 +628,6 @@ class HloComputationProto(google.protobuf.message.Message): IS_FUSION_COMPUTATION_FIELD_NUMBER: builtins.int EXECUTION_THREAD_FIELD_NUMBER: builtins.int name: builtins.str - @property - def instructions(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___HloInstructionProto]: - """The array of instructions is always in a valid dependency order, where - operands appear before their users. - """ - @property - def program_shape(self) -> tensorflow.compiler.xla.xla_data_pb2.ProgramShapeProto: - """The program shape (with layout) of this computation.""" id: builtins.int """The id of this computation.""" root_id: builtins.int @@ -627,6 +639,16 @@ class HloComputationProto(google.protobuf.message.Message): """ execution_thread: builtins.str """The name of execution thread this computation belongs to.""" + @property + def instructions(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___HloInstructionProto]: + """The array of instructions is always in a valid dependency order, where + operands appear before their users. + """ + + @property + def program_shape(self) -> tensorflow.compiler.xla.xla_data_pb2.ProgramShapeProto: + """The program shape (with layout) of this computation.""" + def __init__( self, *, @@ -638,12 +660,12 @@ class HloComputationProto(google.protobuf.message.Message): is_fusion_computation: builtins.bool | None = ..., execution_thread: builtins.str | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["program_shape", b"program_shape"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["execution_thread", b"execution_thread", "id", b"id", "instructions", b"instructions", "is_fusion_computation", b"is_fusion_computation", "name", b"name", "program_shape", b"program_shape", "root_id", b"root_id"]) -> None: ... + def HasField(self, field_name: typing.Literal["program_shape", b"program_shape"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["execution_thread", b"execution_thread", "id", b"id", "instructions", b"instructions", "is_fusion_computation", b"is_fusion_computation", "name", b"name", "program_shape", b"program_shape", "root_id", b"root_id"]) -> None: ... global___HloComputationProto = HloComputationProto -@typing_extensions.final +@typing.final class HloScheduleProto(google.protobuf.message.Message): """Serialization of an HLO schedule. An HLO schedule contains a total order of instructions for each non-fusion computation in the module. @@ -651,7 +673,7 @@ class HloScheduleProto(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor - @typing_extensions.final + @typing.final class InstructionSequence(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -663,9 +685,9 @@ class HloScheduleProto(google.protobuf.message.Message): *, instruction_ids: collections.abc.Iterable[builtins.int] | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["instruction_ids", b"instruction_ids"]) -> None: ... + def ClearField(self, field_name: typing.Literal["instruction_ids", b"instruction_ids"]) -> None: ... - @typing_extensions.final + @typing.final class SequencesEntry(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -680,27 +702,28 @@ class HloScheduleProto(google.protobuf.message.Message): key: builtins.int | None = ..., value: global___HloScheduleProto.InstructionSequence | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["value", b"value"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["key", b"key", "value", b"value"]) -> None: ... + def HasField(self, field_name: typing.Literal["value", b"value"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["key", b"key", "value", b"value"]) -> None: ... SEQUENCES_FIELD_NUMBER: builtins.int @property def sequences(self) -> google.protobuf.internal.containers.MessageMap[builtins.int, global___HloScheduleProto.InstructionSequence]: """Map from computation id to sequence.""" + def __init__( self, *, sequences: collections.abc.Mapping[builtins.int, global___HloScheduleProto.InstructionSequence] | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["sequences", b"sequences"]) -> None: ... + def ClearField(self, field_name: typing.Literal["sequences", b"sequences"]) -> None: ... global___HloScheduleProto = HloScheduleProto -@typing_extensions.final +@typing.final class HloInputOutputAliasProto(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor - @typing_extensions.final + @typing.final class AliasEntryProto(google.protobuf.message.Message): """The following proto describes a pair of aliased an input (described by parameter number and a ShapeIndex of the parameter) @@ -723,16 +746,18 @@ class HloInputOutputAliasProto(google.protobuf.message.Message): PARAMETER_NUMBER_FIELD_NUMBER: builtins.int PARAMETER_SHAPE_INDEX_FIELD_NUMBER: builtins.int KIND_FIELD_NUMBER: builtins.int + parameter_number: builtins.int + """Number of the parameter in entry computation.""" + kind: global___Kind.ValueType + """The kind of alias to be setup.""" @property def output_shape_index(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.int]: """ShapeIndex of the root hlo.""" - parameter_number: builtins.int - """Number of the parameter in entry computation.""" + @property def parameter_shape_index(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.int]: """ShapeIndex of the parameter instruction.""" - kind: global___Kind.ValueType - """The kind of alias to be setup.""" + def __init__( self, *, @@ -741,7 +766,7 @@ class HloInputOutputAliasProto(google.protobuf.message.Message): parameter_shape_index: collections.abc.Iterable[builtins.int] | None = ..., kind: global___Kind.ValueType | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["kind", b"kind", "output_shape_index", b"output_shape_index", "parameter_number", b"parameter_number", "parameter_shape_index", b"parameter_shape_index"]) -> None: ... + def ClearField(self, field_name: typing.Literal["kind", b"kind", "output_shape_index", b"output_shape_index", "parameter_number", b"parameter_number", "parameter_shape_index", b"parameter_shape_index"]) -> None: ... ENTRIES_FIELD_NUMBER: builtins.int @property @@ -751,15 +776,15 @@ class HloInputOutputAliasProto(google.protobuf.message.Message): *, entries: collections.abc.Iterable[global___HloInputOutputAliasProto.AliasEntryProto] | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["entries", b"entries"]) -> None: ... + def ClearField(self, field_name: typing.Literal["entries", b"entries"]) -> None: ... global___HloInputOutputAliasProto = HloInputOutputAliasProto -@typing_extensions.final +@typing.final class DynamicParameterBindingProto(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor - @typing_extensions.final + @typing.final class Binding(google.protobuf.message.Message): """A list of bindings which indicates that the `target_param_dim_num` in the subshape `target_param_index` of parameter `target_param_num` @@ -794,12 +819,12 @@ class DynamicParameterBindingProto(google.protobuf.message.Message): TARGET_PARAM_INDEX_FIELD_NUMBER: builtins.int TARGET_PARAM_DIM_NUM_FIELD_NUMBER: builtins.int dynamic_param_num: builtins.int + target_param_num: builtins.int + target_param_dim_num: builtins.int @property def dynamic_param_index(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.int]: ... - target_param_num: builtins.int @property def target_param_index(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.int]: ... - target_param_dim_num: builtins.int def __init__( self, *, @@ -809,7 +834,7 @@ class DynamicParameterBindingProto(google.protobuf.message.Message): target_param_index: collections.abc.Iterable[builtins.int] | None = ..., target_param_dim_num: builtins.int | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["dynamic_param_index", b"dynamic_param_index", "dynamic_param_num", b"dynamic_param_num", "target_param_dim_num", b"target_param_dim_num", "target_param_index", b"target_param_index", "target_param_num", b"target_param_num"]) -> None: ... + def ClearField(self, field_name: typing.Literal["dynamic_param_index", b"dynamic_param_index", "dynamic_param_num", b"dynamic_param_num", "target_param_dim_num", b"target_param_dim_num", "target_param_index", b"target_param_index", "target_param_num", b"target_param_num"]) -> None: ... ENTRIES_FIELD_NUMBER: builtins.int @property @@ -819,11 +844,11 @@ class DynamicParameterBindingProto(google.protobuf.message.Message): *, entries: collections.abc.Iterable[global___DynamicParameterBindingProto.Binding] | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["entries", b"entries"]) -> None: ... + def ClearField(self, field_name: typing.Literal["entries", b"entries"]) -> None: ... global___DynamicParameterBindingProto = DynamicParameterBindingProto -@typing_extensions.final +@typing.final class CrossProgramPrefetch(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -831,9 +856,9 @@ class CrossProgramPrefetch(google.protobuf.message.Message): INDEX_FIELD_NUMBER: builtins.int OFFSET_FIELD_NUMBER: builtins.int parameter: builtins.int + offset: builtins.int @property def index(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.int]: ... - offset: builtins.int def __init__( self, *, @@ -841,11 +866,11 @@ class CrossProgramPrefetch(google.protobuf.message.Message): index: collections.abc.Iterable[builtins.int] | None = ..., offset: builtins.int | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["index", b"index", "offset", b"offset", "parameter", b"parameter"]) -> None: ... + def ClearField(self, field_name: typing.Literal["index", b"index", "offset", b"offset", "parameter", b"parameter"]) -> None: ... global___CrossProgramPrefetch = CrossProgramPrefetch -@typing_extensions.final +@typing.final class HloModuleProto(google.protobuf.message.Message): """Serialization of HloModule.""" @@ -872,7 +897,7 @@ class HloModuleProto(google.protobuf.message.Message): LAYOUT: HloModuleProto.ProfileType.ValueType # 3 DOT: HloModuleProto.ProfileType.ValueType # 4 - @typing_extensions.final + @typing.final class ProfileInfo(google.protobuf.message.Message): """Information about the optimization profile that this module contains.""" @@ -898,7 +923,7 @@ class HloModuleProto(google.protobuf.message.Message): profile_source: tensorflow.compiler.xla.xla_data_pb2.ProfileSource.ValueType | None = ..., compilation_event: tensorflow.compiler.xla.xla_data_pb2.CompilationEvent.ValueType | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["compilation_event", b"compilation_event", "profile_source", b"profile_source", "profile_type", b"profile_type", "relative_speedup", b"relative_speedup"]) -> None: ... + def ClearField(self, field_name: typing.Literal["compilation_event", b"compilation_event", "profile_source", b"profile_source", "profile_type", b"profile_type", "relative_speedup", b"relative_speedup"]) -> None: ... NAME_FIELD_NUMBER: builtins.int ENTRY_COMPUTATION_NAME_FIELD_NUMBER: builtins.int @@ -919,40 +944,46 @@ class HloModuleProto(google.protobuf.message.Message): name: builtins.str entry_computation_name: builtins.str entry_computation_id: builtins.int + id: builtins.int + """The id of this module.""" + is_dynamic: builtins.bool + """True if the module contains dynamic computation.""" + use_auto_spmd_partitioning: builtins.bool + """Uses AutoSharding pass or not.""" @property def computations(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___HloComputationProto]: """The array of computations is always in a valid dependency order, where callees appear before their callers. """ + @property def host_program_shape(self) -> tensorflow.compiler.xla.xla_data_pb2.ProgramShapeProto: """The host program shape (with layout) of the entry computation.""" - id: builtins.int - """The id of this module.""" + @property def schedule(self) -> global___HloScheduleProto: """The schedule for this module.""" + @property def input_output_alias(self) -> global___HloInputOutputAliasProto: """Describes alias information between inputs and outputs.""" + @property def dynamic_parameter_binding(self) -> global___DynamicParameterBindingProto: ... @property def cross_program_prefetches(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___CrossProgramPrefetch]: ... - is_dynamic: builtins.bool - """True if the module contains dynamic computation.""" @property def spmd_output_sharding(self) -> tensorflow.compiler.xla.xla_data_pb2.OpSharding: ... @property def spmd_parameters_shardings(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[tensorflow.compiler.xla.xla_data_pb2.OpSharding]: ... - use_auto_spmd_partitioning: builtins.bool - """Uses AutoSharding pass or not.""" @property def profile_info(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___HloModuleProto.ProfileInfo]: """Profile information for the HLO module.""" + @property def device_assignment(self) -> tensorflow.compiler.xla.xla_data_pb2.DeviceAssignmentProto: """DeviceAssignment object information.""" + def __init__( self, *, @@ -973,18 +1004,18 @@ class HloModuleProto(google.protobuf.message.Message): profile_info: collections.abc.Iterable[global___HloModuleProto.ProfileInfo] | None = ..., device_assignment: tensorflow.compiler.xla.xla_data_pb2.DeviceAssignmentProto | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["device_assignment", b"device_assignment", "dynamic_parameter_binding", b"dynamic_parameter_binding", "host_program_shape", b"host_program_shape", "input_output_alias", b"input_output_alias", "schedule", b"schedule", "spmd_output_sharding", b"spmd_output_sharding"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["computations", b"computations", "cross_program_prefetches", b"cross_program_prefetches", "device_assignment", b"device_assignment", "dynamic_parameter_binding", b"dynamic_parameter_binding", "entry_computation_id", b"entry_computation_id", "entry_computation_name", b"entry_computation_name", "host_program_shape", b"host_program_shape", "id", b"id", "input_output_alias", b"input_output_alias", "is_dynamic", b"is_dynamic", "name", b"name", "profile_info", b"profile_info", "schedule", b"schedule", "spmd_output_sharding", b"spmd_output_sharding", "spmd_parameters_shardings", b"spmd_parameters_shardings", "use_auto_spmd_partitioning", b"use_auto_spmd_partitioning"]) -> None: ... + def HasField(self, field_name: typing.Literal["device_assignment", b"device_assignment", "dynamic_parameter_binding", b"dynamic_parameter_binding", "host_program_shape", b"host_program_shape", "input_output_alias", b"input_output_alias", "schedule", b"schedule", "spmd_output_sharding", b"spmd_output_sharding"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["computations", b"computations", "cross_program_prefetches", b"cross_program_prefetches", "device_assignment", b"device_assignment", "dynamic_parameter_binding", b"dynamic_parameter_binding", "entry_computation_id", b"entry_computation_id", "entry_computation_name", b"entry_computation_name", "host_program_shape", b"host_program_shape", "id", b"id", "input_output_alias", b"input_output_alias", "is_dynamic", b"is_dynamic", "name", b"name", "profile_info", b"profile_info", "schedule", b"schedule", "spmd_output_sharding", b"spmd_output_sharding", "spmd_parameters_shardings", b"spmd_parameters_shardings", "use_auto_spmd_partitioning", b"use_auto_spmd_partitioning"]) -> None: ... global___HloModuleProto = HloModuleProto -@typing_extensions.final +@typing.final class LogicalBufferProto(google.protobuf.message.Message): """Serialization of LogicalBuffer.""" DESCRIPTOR: google.protobuf.descriptor.Descriptor - @typing_extensions.final + @typing.final class Location(google.protobuf.message.Message): """Location represents an instruction and its shape index, which uniquely identifies a point where a buffer is needed. @@ -1007,7 +1038,7 @@ class LogicalBufferProto(google.protobuf.message.Message): instruction_id: builtins.int | None = ..., shape_index: collections.abc.Iterable[builtins.int] | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["instruction_id", b"instruction_id", "instruction_name", b"instruction_name", "shape_index", b"shape_index"]) -> None: ... + def ClearField(self, field_name: typing.Literal["instruction_id", b"instruction_id", "instruction_name", b"instruction_name", "shape_index", b"shape_index"]) -> None: ... ID_FIELD_NUMBER: builtins.int SIZE_FIELD_NUMBER: builtins.int @@ -1015,10 +1046,11 @@ class LogicalBufferProto(google.protobuf.message.Message): COLOR_FIELD_NUMBER: builtins.int id: builtins.int size: builtins.int + color: builtins.int @property def defined_at(self) -> global___LogicalBufferProto.Location: """The location where the buffer is defined.""" - color: builtins.int + def __init__( self, *, @@ -1027,18 +1059,18 @@ class LogicalBufferProto(google.protobuf.message.Message): defined_at: global___LogicalBufferProto.Location | None = ..., color: builtins.int | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["defined_at", b"defined_at"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["color", b"color", "defined_at", b"defined_at", "id", b"id", "size", b"size"]) -> None: ... + def HasField(self, field_name: typing.Literal["defined_at", b"defined_at"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["color", b"color", "defined_at", b"defined_at", "id", b"id", "size", b"size"]) -> None: ... global___LogicalBufferProto = LogicalBufferProto -@typing_extensions.final +@typing.final class BufferAllocationProto(google.protobuf.message.Message): """Serialization of BufferAllocation.""" DESCRIPTOR: google.protobuf.descriptor.Descriptor - @typing_extensions.final + @typing.final class Assigned(google.protobuf.message.Message): """Assigned represents a single LogicalBuffer that is assigned to this BufferAllocation. @@ -1059,7 +1091,7 @@ class BufferAllocationProto(google.protobuf.message.Message): offset: builtins.int | None = ..., size: builtins.int | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["logical_buffer_id", b"logical_buffer_id", "offset", b"offset", "size", b"size"]) -> None: ... + def ClearField(self, field_name: typing.Literal["logical_buffer_id", b"logical_buffer_id", "offset", b"offset", "size", b"size"]) -> None: ... INDEX_FIELD_NUMBER: builtins.int SIZE_FIELD_NUMBER: builtins.int @@ -1079,11 +1111,11 @@ class BufferAllocationProto(google.protobuf.message.Message): is_entry_computation_parameter: builtins.bool is_constant: builtins.bool parameter_number: builtins.int - @property - def parameter_shape_index(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.int]: ... maybe_live_out: builtins.bool color: builtins.int @property + def parameter_shape_index(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.int]: ... + @property def assigned(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___BufferAllocationProto.Assigned]: ... def __init__( self, @@ -1100,17 +1132,17 @@ class BufferAllocationProto(google.protobuf.message.Message): color: builtins.int | None = ..., assigned: collections.abc.Iterable[global___BufferAllocationProto.Assigned] | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["assigned", b"assigned", "color", b"color", "index", b"index", "is_constant", b"is_constant", "is_entry_computation_parameter", b"is_entry_computation_parameter", "is_thread_local", b"is_thread_local", "is_tuple", b"is_tuple", "maybe_live_out", b"maybe_live_out", "parameter_number", b"parameter_number", "parameter_shape_index", b"parameter_shape_index", "size", b"size"]) -> None: ... + def ClearField(self, field_name: typing.Literal["assigned", b"assigned", "color", b"color", "index", b"index", "is_constant", b"is_constant", "is_entry_computation_parameter", b"is_entry_computation_parameter", "is_thread_local", b"is_thread_local", "is_tuple", b"is_tuple", "maybe_live_out", b"maybe_live_out", "parameter_number", b"parameter_number", "parameter_shape_index", b"parameter_shape_index", "size", b"size"]) -> None: ... global___BufferAllocationProto = BufferAllocationProto -@typing_extensions.final +@typing.final class HeapSimulatorTrace(google.protobuf.message.Message): """A trace of a HeapSimulator run.""" DESCRIPTOR: google.protobuf.descriptor.Descriptor - @typing_extensions.final + @typing.final class Event(google.protobuf.message.Message): """The trace includes a list of events, where each event describes one action performed by the heap simulator. @@ -1176,15 +1208,15 @@ class HeapSimulatorTrace(google.protobuf.message.Message): instruction_name: builtins.str | None = ..., share_with_canonical_id: builtins.int | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["buffer_id", b"buffer_id", "computation_name", b"computation_name", "instruction_name", b"instruction_name", "kind", b"kind", "share_with_canonical_id", b"share_with_canonical_id"]) -> None: ... + def ClearField(self, field_name: typing.Literal["buffer_id", b"buffer_id", "computation_name", b"computation_name", "instruction_name", b"instruction_name", "kind", b"kind", "share_with_canonical_id", b"share_with_canonical_id"]) -> None: ... EVENTS_FIELD_NUMBER: builtins.int WHOLE_MODULE_SIMULATION_FIELD_NUMBER: builtins.int BUFFER_ALLOCATION_INDEX_FIELD_NUMBER: builtins.int - @property - def events(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___HeapSimulatorTrace.Event]: ... whole_module_simulation: builtins.bool buffer_allocation_index: builtins.int + @property + def events(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___HeapSimulatorTrace.Event]: ... def __init__( self, *, @@ -1192,11 +1224,11 @@ class HeapSimulatorTrace(google.protobuf.message.Message): whole_module_simulation: builtins.bool | None = ..., buffer_allocation_index: builtins.int | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["buffer_allocation_index", b"buffer_allocation_index", "events", b"events", "whole_module_simulation", b"whole_module_simulation"]) -> None: ... + def ClearField(self, field_name: typing.Literal["buffer_allocation_index", b"buffer_allocation_index", "events", b"events", "whole_module_simulation", b"whole_module_simulation"]) -> None: ... global___HeapSimulatorTrace = HeapSimulatorTrace -@typing_extensions.final +@typing.final class HloModuleGroupProto(google.protobuf.message.Message): """An abstraction representing a set of HLO module built to run concurrently across different devices. @@ -1215,17 +1247,17 @@ class HloModuleGroupProto(google.protobuf.message.Message): name: builtins.str | None = ..., hlo_modules: collections.abc.Iterable[global___HloModuleProto] | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["hlo_modules", b"hlo_modules", "name", b"name"]) -> None: ... + def ClearField(self, field_name: typing.Literal["hlo_modules", b"hlo_modules", "name", b"name"]) -> None: ... global___HloModuleGroupProto = HloModuleGroupProto -@typing_extensions.final +@typing.final class BufferAssignmentProto(google.protobuf.message.Message): """Serialization of BufferAssignment.""" DESCRIPTOR: google.protobuf.descriptor.Descriptor - @typing_extensions.final + @typing.final class BufferAlias(google.protobuf.message.Message): """Alias represents a source LogicalBuffer, and the buffer location that aliases it. @@ -1244,8 +1276,8 @@ class BufferAssignmentProto(google.protobuf.message.Message): source_buffer_id: builtins.int | None = ..., location: global___LogicalBufferProto.Location | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["location", b"location"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["location", b"location", "source_buffer_id", b"source_buffer_id"]) -> None: ... + def HasField(self, field_name: typing.Literal["location", b"location"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["location", b"location", "source_buffer_id", b"source_buffer_id"]) -> None: ... LOGICAL_BUFFERS_FIELD_NUMBER: builtins.int BUFFER_ALIASES_FIELD_NUMBER: builtins.int @@ -1267,11 +1299,11 @@ class BufferAssignmentProto(google.protobuf.message.Message): buffer_allocations: collections.abc.Iterable[global___BufferAllocationProto] | None = ..., heap_simulator_traces: collections.abc.Iterable[global___HeapSimulatorTrace] | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["buffer_aliases", b"buffer_aliases", "buffer_allocations", b"buffer_allocations", "heap_simulator_traces", b"heap_simulator_traces", "logical_buffers", b"logical_buffers"]) -> None: ... + def ClearField(self, field_name: typing.Literal["buffer_aliases", b"buffer_aliases", "buffer_allocations", b"buffer_allocations", "heap_simulator_traces", b"heap_simulator_traces", "logical_buffers", b"logical_buffers"]) -> None: ... global___BufferAssignmentProto = BufferAssignmentProto -@typing_extensions.final +@typing.final class HloProto(google.protobuf.message.Message): """Grouping message that contains all of the information above.""" @@ -1289,12 +1321,12 @@ class HloProto(google.protobuf.message.Message): hlo_module: global___HloModuleProto | None = ..., buffer_assignment: global___BufferAssignmentProto | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["buffer_assignment", b"buffer_assignment", "hlo_module", b"hlo_module"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["buffer_assignment", b"buffer_assignment", "hlo_module", b"hlo_module"]) -> None: ... + def HasField(self, field_name: typing.Literal["buffer_assignment", b"buffer_assignment", "hlo_module", b"hlo_module"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["buffer_assignment", b"buffer_assignment", "hlo_module", b"hlo_module"]) -> None: ... global___HloProto = HloProto -@typing_extensions.final +@typing.final class HloSnapshot(google.protobuf.message.Message): """Encapsulates HloProto together with the arguments, result, and execution_platform. This message is used for purposes such as @@ -1307,17 +1339,20 @@ class HloSnapshot(google.protobuf.message.Message): ARGUMENTS_FIELD_NUMBER: builtins.int RESULT_FIELD_NUMBER: builtins.int EXECUTION_PLATFORM_FIELD_NUMBER: builtins.int + execution_platform: builtins.str + """The name of the platform used to run the graph.""" @property def hlo(self) -> global___HloProto: """The hlo graph.""" + @property def arguments(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[tensorflow.compiler.xla.xla_data_pb2.LiteralProto]: """The arguments passed to the graph.""" + @property def result(self) -> tensorflow.compiler.xla.xla_data_pb2.LiteralProto: """The result of the graph.""" - execution_platform: builtins.str - """The name of the platform used to run the graph.""" + def __init__( self, *, @@ -1326,12 +1361,12 @@ class HloSnapshot(google.protobuf.message.Message): result: tensorflow.compiler.xla.xla_data_pb2.LiteralProto | None = ..., execution_platform: builtins.str | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["hlo", b"hlo", "result", b"result"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["arguments", b"arguments", "execution_platform", b"execution_platform", "hlo", b"hlo", "result", b"result"]) -> None: ... + def HasField(self, field_name: typing.Literal["hlo", b"hlo", "result", b"result"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["arguments", b"arguments", "execution_platform", b"execution_platform", "hlo", b"hlo", "result", b"result"]) -> None: ... global___HloSnapshot = HloSnapshot -@typing_extensions.final +@typing.final class HloModuleMetadataProto(google.protobuf.message.Message): """Metadata for an HLO module. Dumped after HLO passes and before LLO lowering with filename module_####.metadata.textproto, where #### is @@ -1362,9 +1397,11 @@ class HloModuleMetadataProto(google.protobuf.message.Message): """The canonical module ids of the modules that this one is partitioned into, if applicable. """ + @property def pass_metadata(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___HloPassMetadata]: """Metadata for the HLO passes that are run on the module.""" + def __init__( self, *, @@ -1374,11 +1411,11 @@ class HloModuleMetadataProto(google.protobuf.message.Message): partitioned_module_ids: collections.abc.Iterable[builtins.int] | None = ..., pass_metadata: collections.abc.Iterable[global___HloPassMetadata] | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["canonical_module_id", b"canonical_module_id", "module_group_name", b"module_group_name", "original_module_id", b"original_module_id", "partitioned_module_ids", b"partitioned_module_ids", "pass_metadata", b"pass_metadata"]) -> None: ... + def ClearField(self, field_name: typing.Literal["canonical_module_id", b"canonical_module_id", "module_group_name", b"module_group_name", "original_module_id", b"original_module_id", "partitioned_module_ids", b"partitioned_module_ids", "pass_metadata", b"pass_metadata"]) -> None: ... global___HloModuleMetadataProto = HloModuleMetadataProto -@typing_extensions.final +@typing.final class HloPassMetadata(google.protobuf.message.Message): """Metadata for one run of an HLO pass on a module. Provides more information when processing debug dumps of HloProtos about the order of HLO passes and @@ -1407,12 +1444,6 @@ class HloPassMetadata(google.protobuf.message.Message): """ pass_name: builtins.str pipeline_name: builtins.str - @property - def dump_filenames(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.str]: - """Filenames of the dumps of the module after this pass ran. Module may be - dumped in multiple formats, and the order of formats in this field will - stay consistent across passes. - """ module_changed: builtins.bool """Return value of pass.Run(). True if this pass changed the module, or, in the case where the module was run through this pass as part of a module @@ -1423,14 +1454,22 @@ class HloPassMetadata(google.protobuf.message.Message): the canonical_module_id of the HloModuleMetadata that this HloPassMetadata is inside. """ + start_timestamp_usec: builtins.int + """Timestamp before and after the pass is run. Note they may be equal.""" + end_timestamp_usec: builtins.int + @property + def dump_filenames(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.str]: + """Filenames of the dumps of the module after this pass ran. Module may be + dumped in multiple formats, and the order of formats in this field will + stay consistent across passes. + """ + @property def module_group_module_ids(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.int]: """If the module went through this pass as part of a module group, this is set as the ids of all the modules in the module group. Empty otherwise. """ - start_timestamp_usec: builtins.int - """Timestamp before and after the pass is run. Note they may be equal.""" - end_timestamp_usec: builtins.int + def __init__( self, *, @@ -1444,17 +1483,17 @@ class HloPassMetadata(google.protobuf.message.Message): start_timestamp_usec: builtins.int | None = ..., end_timestamp_usec: builtins.int | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["dump_filenames", b"dump_filenames", "end_timestamp_usec", b"end_timestamp_usec", "module_changed", b"module_changed", "module_group_module_ids", b"module_group_module_ids", "module_id", b"module_id", "pass_id", b"pass_id", "pass_name", b"pass_name", "pipeline_name", b"pipeline_name", "start_timestamp_usec", b"start_timestamp_usec"]) -> None: ... + def ClearField(self, field_name: typing.Literal["dump_filenames", b"dump_filenames", "end_timestamp_usec", b"end_timestamp_usec", "module_changed", b"module_changed", "module_group_module_ids", b"module_group_module_ids", "module_id", b"module_id", "pass_id", b"pass_id", "pass_name", b"pass_name", "pipeline_name", b"pipeline_name", "start_timestamp_usec", b"start_timestamp_usec"]) -> None: ... global___HloPassMetadata = HloPassMetadata -@typing_extensions.final +@typing.final class EntryFunctionAttributes(google.protobuf.message.Message): """Encodes attributes for an entry function.""" DESCRIPTOR: google.protobuf.descriptor.Descriptor - @typing_extensions.final + @typing.final class ShapeIndex(google.protobuf.message.Message): """Acts as the underlying container for an xla::ShapeIndex.""" @@ -1468,9 +1507,9 @@ class EntryFunctionAttributes(google.protobuf.message.Message): *, indices: collections.abc.Iterable[builtins.int] | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["indices", b"indices"]) -> None: ... + def ClearField(self, field_name: typing.Literal["indices", b"indices"]) -> None: ... - @typing_extensions.final + @typing.final class BufferParameterAttributes(google.protobuf.message.Message): """Encodes attributes for a single buffer parameter.""" @@ -1488,16 +1527,18 @@ class EntryFunctionAttributes(google.protobuf.message.Message): """TODO(hanbinyoon): Deprecate when optional fields are available in proto3 (Protocol Buffers v3.15.0). """ - @property - def lmhlo_param_shape_index(self) -> global___EntryFunctionAttributes.ShapeIndex: - """Represents an lmhlo.param_shape_index function argument attribute.""" lmhlo_constant_name: builtins.str """Represents an lmhlo.constant_name function argument attribute.""" lmhlo_must_alias: builtins.bool """Represents an lmhlo.must_alias function argument attribute.""" + @property + def lmhlo_param_shape_index(self) -> global___EntryFunctionAttributes.ShapeIndex: + """Represents an lmhlo.param_shape_index function argument attribute.""" + @property def lmhlo_output_index(self) -> global___EntryFunctionAttributes.ShapeIndex: """Represents an lmhlo.params function argument attribute.""" + def __init__( self, *, @@ -1508,26 +1549,26 @@ class EntryFunctionAttributes(google.protobuf.message.Message): lmhlo_must_alias: builtins.bool | None = ..., lmhlo_output_index: global___EntryFunctionAttributes.ShapeIndex | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["lmhlo_output_index", b"lmhlo_output_index", "lmhlo_param_shape_index", b"lmhlo_param_shape_index"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["lmhlo_constant_name", b"lmhlo_constant_name", "lmhlo_must_alias", b"lmhlo_must_alias", "lmhlo_output_index", b"lmhlo_output_index", "lmhlo_param_shape_index", b"lmhlo_param_shape_index", "lmhlo_params", b"lmhlo_params", "lmhlo_params_present", b"lmhlo_params_present"]) -> None: ... + def HasField(self, field_name: typing.Literal["lmhlo_output_index", b"lmhlo_output_index", "lmhlo_param_shape_index", b"lmhlo_param_shape_index"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["lmhlo_constant_name", b"lmhlo_constant_name", "lmhlo_must_alias", b"lmhlo_must_alias", "lmhlo_output_index", b"lmhlo_output_index", "lmhlo_param_shape_index", b"lmhlo_param_shape_index", "lmhlo_params", b"lmhlo_params", "lmhlo_params_present", b"lmhlo_params_present"]) -> None: ... BUFFERS_FIELD_NUMBER: builtins.int RESULT_XLA_SHAPE_FIELD_NUMBER: builtins.int - @property - def buffers(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___EntryFunctionAttributes.BufferParameterAttributes]: ... result_xla_shape: builtins.str """xla::Shape in string format.""" + @property + def buffers(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___EntryFunctionAttributes.BufferParameterAttributes]: ... def __init__( self, *, buffers: collections.abc.Iterable[global___EntryFunctionAttributes.BufferParameterAttributes] | None = ..., result_xla_shape: builtins.str | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["buffers", b"buffers", "result_xla_shape", b"result_xla_shape"]) -> None: ... + def ClearField(self, field_name: typing.Literal["buffers", b"buffers", "result_xla_shape", b"result_xla_shape"]) -> None: ... global___EntryFunctionAttributes = EntryFunctionAttributes -@typing_extensions.final +@typing.final class XlaRuntimeExecutableProto(google.protobuf.message.Message): """Encodes the underlying Xla runtime executable compiled from the XLA module.""" @@ -1536,8 +1577,6 @@ class XlaRuntimeExecutableProto(google.protobuf.message.Message): HLO_MODULE_PROTO_FIELD_NUMBER: builtins.int OBJ_FILE_FIELD_NUMBER: builtins.int MLIR_MODULE_FIELD_NUMBER: builtins.int - @property - def hlo_module_proto(self) -> global___HloModuleProto: ... obj_file: builtins.bytes """TODO(b/232263665)): Serialized executable has to know what APIs it has to be linked with, including the version. For example Gpu executable must be @@ -1547,6 +1586,8 @@ class XlaRuntimeExecutableProto(google.protobuf.message.Message): """ mlir_module: builtins.str """Serialized MLIR module corresponding to compiled object file.""" + @property + def hlo_module_proto(self) -> global___HloModuleProto: ... def __init__( self, *, @@ -1554,7 +1595,7 @@ class XlaRuntimeExecutableProto(google.protobuf.message.Message): obj_file: builtins.bytes | None = ..., mlir_module: builtins.str | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["hlo_module_proto", b"hlo_module_proto"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["hlo_module_proto", b"hlo_module_proto", "mlir_module", b"mlir_module", "obj_file", b"obj_file"]) -> None: ... + def HasField(self, field_name: typing.Literal["hlo_module_proto", b"hlo_module_proto"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["hlo_module_proto", b"hlo_module_proto", "mlir_module", b"mlir_module", "obj_file", b"obj_file"]) -> None: ... global___XlaRuntimeExecutableProto = XlaRuntimeExecutableProto diff --git a/stubs/tensorflow/tensorflow/compiler/xla/service/metrics_pb2.pyi b/stubs/tensorflow/tensorflow/compiler/xla/service/metrics_pb2.pyi index 39993f67771b..354a1c354f96 100644 --- a/stubs/tensorflow/tensorflow/compiler/xla/service/metrics_pb2.pyi +++ b/stubs/tensorflow/tensorflow/compiler/xla/service/metrics_pb2.pyi @@ -2,6 +2,7 @@ @generated by mypy-protobuf. Do not edit manually! isort:skip_file """ + import builtins import sys import typing @@ -19,7 +20,7 @@ else: DESCRIPTOR: google.protobuf.descriptor.FileDescriptor -@typing_extensions.final +@typing.final class CompilationLogEntry(google.protobuf.message.Message): """Defines XLA compilation metrics.""" @@ -50,16 +51,18 @@ class CompilationLogEntry(google.protobuf.message.Message): STAGE_FIELD_NUMBER: builtins.int DURATION_FIELD_NUMBER: builtins.int TASK_INDEX_FIELD_NUMBER: builtins.int + stage: global___CompilationLogEntry.CompilationStage.ValueType + """Compilation stage recorded by this log entry.""" + task_index: builtins.int + """Task index from which this log entry was recorded.""" @property def timestamp(self) -> google.protobuf.timestamp_pb2.Timestamp: """Time when the event captured by this log entry occurred.""" - stage: global___CompilationLogEntry.CompilationStage.ValueType - """Compilation stage recorded by this log entry.""" + @property def duration(self) -> google.protobuf.duration_pb2.Duration: """Duration of the given compilation stage.""" - task_index: builtins.int - """Task index from which this log entry was recorded.""" + def __init__( self, *, @@ -68,7 +71,7 @@ class CompilationLogEntry(google.protobuf.message.Message): duration: google.protobuf.duration_pb2.Duration | None = ..., task_index: builtins.int | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["duration", b"duration", "timestamp", b"timestamp"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["duration", b"duration", "stage", b"stage", "task_index", b"task_index", "timestamp", b"timestamp"]) -> None: ... + def HasField(self, field_name: typing.Literal["duration", b"duration", "timestamp", b"timestamp"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["duration", b"duration", "stage", b"stage", "task_index", b"task_index", "timestamp", b"timestamp"]) -> None: ... global___CompilationLogEntry = CompilationLogEntry diff --git a/stubs/tensorflow/tensorflow/compiler/xla/xla_data_pb2.pyi b/stubs/tensorflow/tensorflow/compiler/xla/xla_data_pb2.pyi index a283b93afb07..b0979ed099e3 100644 --- a/stubs/tensorflow/tensorflow/compiler/xla/xla_data_pb2.pyi +++ b/stubs/tensorflow/tensorflow/compiler/xla/xla_data_pb2.pyi @@ -16,6 +16,7 @@ See the License for the specific language governing permissions and limitations under the License. ============================================================================== """ + import builtins import collections.abc import sys @@ -377,7 +378,7 @@ RNG_PHILOX: RandomAlgorithm.ValueType # 2 """Next: 2""" global___RandomAlgorithm = RandomAlgorithm -@typing_extensions.final +@typing.final class PaddingConfig(google.protobuf.message.Message): """Describes the padding configuration for Pad operation. The padding amount on both edges as well as between the elements are specified for each dimension. @@ -385,7 +386,7 @@ class PaddingConfig(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor - @typing_extensions.final + @typing.final class PaddingConfigDimension(google.protobuf.message.Message): """Describes the padding configuration for a dimension.""" @@ -409,22 +410,23 @@ class PaddingConfig(google.protobuf.message.Message): edge_padding_high: builtins.int | None = ..., interior_padding: builtins.int | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["edge_padding_high", b"edge_padding_high", "edge_padding_low", b"edge_padding_low", "interior_padding", b"interior_padding"]) -> None: ... + def ClearField(self, field_name: typing.Literal["edge_padding_high", b"edge_padding_high", "edge_padding_low", b"edge_padding_low", "interior_padding", b"interior_padding"]) -> None: ... DIMENSIONS_FIELD_NUMBER: builtins.int @property def dimensions(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___PaddingConfig.PaddingConfigDimension]: """The padding configuration for all dimensions.""" + def __init__( self, *, dimensions: collections.abc.Iterable[global___PaddingConfig.PaddingConfigDimension] | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["dimensions", b"dimensions"]) -> None: ... + def ClearField(self, field_name: typing.Literal["dimensions", b"dimensions"]) -> None: ... global___PaddingConfig = PaddingConfig -@typing_extensions.final +@typing.final class TileProto(google.protobuf.message.Message): """Describes a tile used in tiling-based layout. Refer to g3doc/third_party/tensorflow/compiler/xla/g3doc/tiled_layout.md for @@ -441,16 +443,17 @@ class TileProto(google.protobuf.message.Message): The dimensions correspond to a suffix of the dimensions of the shape being tiled. """ + def __init__( self, *, dimensions: collections.abc.Iterable[builtins.int] | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["dimensions", b"dimensions"]) -> None: ... + def ClearField(self, field_name: typing.Literal["dimensions", b"dimensions"]) -> None: ... global___TileProto = TileProto -@typing_extensions.final +@typing.final class LayoutProto(google.protobuf.message.Message): """A layout describes how the array is placed in (1D) memory space. This includes the minor-to-major ordering of dimensions within a shape. @@ -476,12 +479,31 @@ class LayoutProto(google.protobuf.message.Message): POINTER_PRIMITIVE_TYPE_FIELD_NUMBER: builtins.int PHYSICAL_SHAPE_FIELD_NUMBER: builtins.int DYNAMIC_SHAPE_METADATA_PREFIX_BYTES_FIELD_NUMBER: builtins.int + memory_space: builtins.int + """Memory space where this array resides. The integer field is interpreted in + a backend-specific manner. + """ + index_primitive_type: global___PrimitiveType.ValueType + """The integer types to be used for indices and pointers. These fields must + not be used unless the layout represents a sparse array. The PrimitiveType + must correspond to an unsigned integer (U8, U16, U32, or U64). + If not provided, the compiler will use the largest unsigned integer + that is naturally supported by the target device (U32 or U64 in currently + supported devices). + """ + pointer_primitive_type: global___PrimitiveType.ValueType + dynamic_shape_metadata_prefix_bytes: builtins.int + """The dynamic shape metadata size in bytes in front of the shape data. The + field may be non-zero for a static shape whose associated buffer is for a + dynamic shape, e.g. a result of SliceToDynamic. + """ @property def dim_level_types(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[global___DimLevelType.ValueType]: """The dimension level type list for this array, specifying the way in which each array dimension is represented in memory. If this list is empty, the array is assumed to be dense. """ + @property def dim_unique(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.bool]: """Whether each dimension is unique or ordered. Each of the following lists @@ -490,6 +512,7 @@ class LayoutProto(google.protobuf.message.Message): respectively. Entries in this list may not be false for some DimLevelType values (such as DIM_DENSE in particular). """ + @property def dim_ordered(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.bool]: ... @property @@ -497,6 +520,7 @@ class LayoutProto(google.protobuf.message.Message): """Sequence of dimension numbers, from minor (fastest varying index) to major (slowest varying index). This field is required. """ + @property def tiles(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___TileProto]: """A sequence of tiles, starting from the tile that's applied first to the @@ -505,19 +529,7 @@ class LayoutProto(google.protobuf.message.Message): TODO(b/119839262): implement tiling in each backend or add Unimplemented error. """ - memory_space: builtins.int - """Memory space where this array resides. The integer field is interpreted in - a backend-specific manner. - """ - index_primitive_type: global___PrimitiveType.ValueType - """The integer types to be used for indices and pointers. These fields must - not be used unless the layout represents a sparse array. The PrimitiveType - must correspond to an unsigned integer (U8, U16, U32, or U64). - If not provided, the compiler will use the largest unsigned integer - that is naturally supported by the target device (U32 or U64 in currently - supported devices). - """ - pointer_primitive_type: global___PrimitiveType.ValueType + @property def physical_shape(self) -> global___ShapeProto: """The physical, on-device shape used to represent the shape this layout @@ -525,11 +537,7 @@ class LayoutProto(google.protobuf.message.Message): The layout(s) contained within the physical shape should not also contain a physical shape. """ - dynamic_shape_metadata_prefix_bytes: builtins.int - """The dynamic shape metadata size in bytes in front of the shape data. The - field may be non-zero for a static shape whose associated buffer is for a - dynamic shape, e.g. a result of SliceToDynamic. - """ + def __init__( self, *, @@ -544,12 +552,12 @@ class LayoutProto(google.protobuf.message.Message): physical_shape: global___ShapeProto | None = ..., dynamic_shape_metadata_prefix_bytes: builtins.int | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["physical_shape", b"physical_shape"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["dim_level_types", b"dim_level_types", "dim_ordered", b"dim_ordered", "dim_unique", b"dim_unique", "dynamic_shape_metadata_prefix_bytes", b"dynamic_shape_metadata_prefix_bytes", "index_primitive_type", b"index_primitive_type", "memory_space", b"memory_space", "minor_to_major", b"minor_to_major", "physical_shape", b"physical_shape", "pointer_primitive_type", b"pointer_primitive_type", "tiles", b"tiles"]) -> None: ... + def HasField(self, field_name: typing.Literal["physical_shape", b"physical_shape"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["dim_level_types", b"dim_level_types", "dim_ordered", b"dim_ordered", "dim_unique", b"dim_unique", "dynamic_shape_metadata_prefix_bytes", b"dynamic_shape_metadata_prefix_bytes", "index_primitive_type", b"index_primitive_type", "memory_space", b"memory_space", "minor_to_major", b"minor_to_major", "physical_shape", b"physical_shape", "pointer_primitive_type", b"pointer_primitive_type", "tiles", b"tiles"]) -> None: ... global___LayoutProto = LayoutProto -@typing_extensions.final +@typing.final class ShapeProto(google.protobuf.message.Message): """A shape describes the number of dimensions in the array, the size of each dimension, and the primitive component type. @@ -582,12 +590,15 @@ class ShapeProto(google.protobuf.message.Message): If the respective element in 'is_dimension_dynamic' is true then the value in this field represents an upper bound on the size of the dimension. """ + @property def tuple_shapes(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___ShapeProto]: """For tuples only, the shapes of constituent shapes in the tuple sequence.""" + @property def layout(self) -> global___LayoutProto: """The layout used to back this shape.""" + @property def is_dynamic_dimension(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.bool]: """For arrays, this indicates whether or not each dimension is @@ -595,6 +606,7 @@ class ShapeProto(google.protobuf.message.Message): zero (indicating that no dimensions are dynamic) or equal to the number of elements in the 'dimensions' field. """ + def __init__( self, *, @@ -604,12 +616,12 @@ class ShapeProto(google.protobuf.message.Message): layout: global___LayoutProto | None = ..., is_dynamic_dimension: collections.abc.Iterable[builtins.bool] | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["layout", b"layout"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["dimensions", b"dimensions", "element_type", b"element_type", "is_dynamic_dimension", b"is_dynamic_dimension", "layout", b"layout", "tuple_shapes", b"tuple_shapes"]) -> None: ... + def HasField(self, field_name: typing.Literal["layout", b"layout"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["dimensions", b"dimensions", "element_type", b"element_type", "is_dynamic_dimension", b"is_dynamic_dimension", "layout", b"layout", "tuple_shapes", b"tuple_shapes"]) -> None: ... global___ShapeProto = ShapeProto -@typing_extensions.final +@typing.final class ProgramShapeProto(google.protobuf.message.Message): """Shape of the parameters and output of a computation (like a traditional function signature). @@ -633,12 +645,12 @@ class ProgramShapeProto(google.protobuf.message.Message): result: global___ShapeProto | None = ..., parameter_names: collections.abc.Iterable[builtins.str] | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["result", b"result"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["parameter_names", b"parameter_names", "parameters", b"parameters", "result", b"result"]) -> None: ... + def HasField(self, field_name: typing.Literal["result", b"result"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["parameter_names", b"parameter_names", "parameters", b"parameters", "result", b"result"]) -> None: ... global___ProgramShapeProto = ProgramShapeProto -@typing_extensions.final +@typing.final class ComputationStats(google.protobuf.message.Message): """Statistics of a computation.""" @@ -656,11 +668,11 @@ class ComputationStats(google.protobuf.message.Message): flop_count: builtins.float | None = ..., transcendental_count: builtins.float | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["flop_count", b"flop_count", "transcendental_count", b"transcendental_count"]) -> None: ... + def ClearField(self, field_name: typing.Literal["flop_count", b"flop_count", "transcendental_count", b"transcendental_count"]) -> None: ... global___ComputationStats = ComputationStats -@typing_extensions.final +@typing.final class OpMetadata(google.protobuf.message.Message): """Symbolization metadata for HLO Instructions. @@ -670,7 +682,7 @@ class OpMetadata(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor - @typing_extensions.final + @typing.final class ProfileInfo(google.protobuf.message.Message): """Information about the optimization profile that this operation contains.""" @@ -680,9 +692,6 @@ class OpMetadata(google.protobuf.message.Message): RELATIVE_SPEEDUP_FIELD_NUMBER: builtins.int PROFILE_SOURCE_FIELD_NUMBER: builtins.int COMPILATION_EVENT_FIELD_NUMBER: builtins.int - @property - def profile_type(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[global___ProfileType.ValueType]: - """The type of optimization profiles that this operation contains.""" relative_speedup: builtins.float """Speedup of tuned config compared to default config. TODO(b/203817882) Set the relative_speedup. @@ -691,6 +700,10 @@ class OpMetadata(google.protobuf.message.Message): """The source of the optimization profiles that this operation contains.""" compilation_event: global___CompilationEvent.ValueType """The compilation event that triggered the use of the profiles.""" + @property + def profile_type(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[global___ProfileType.ValueType]: + """The type of optimization profiles that this operation contains.""" + def __init__( self, *, @@ -699,7 +712,7 @@ class OpMetadata(google.protobuf.message.Message): profile_source: global___ProfileSource.ValueType | None = ..., compilation_event: global___CompilationEvent.ValueType | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["compilation_event", b"compilation_event", "profile_source", b"profile_source", "profile_type", b"profile_type", "relative_speedup", b"relative_speedup"]) -> None: ... + def ClearField(self, field_name: typing.Literal["compilation_event", b"compilation_event", "profile_source", b"profile_source", "profile_type", b"profile_type", "relative_speedup", b"relative_speedup"]) -> None: ... OP_TYPE_FIELD_NUMBER: builtins.int OP_NAME_FIELD_NUMBER: builtins.int @@ -732,9 +745,6 @@ class OpMetadata(google.protobuf.message.Message): e.g. it could be the file and line of user code that generated the op. """ source_line: builtins.int - @property - def profile_type(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[global___ProfileType.ValueType]: - """Deprecated, use [ProfileInfo][profile_type] instead.""" creation_pass_id: builtins.int """HloPassMetadata.pass_id of the pass that created this HLO instruction object. Should never be copied between HLO instructions. Zero if unset and @@ -752,9 +762,14 @@ class OpMetadata(google.protobuf.message.Message): """The size of the working set, i.e., the amount of memory, used by the instruction in a compiler-managed fast device memory. """ + @property + def profile_type(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[global___ProfileType.ValueType]: + """Deprecated, use [ProfileInfo][profile_type] instead.""" + @property def profile_info(self) -> global___OpMetadata.ProfileInfo: """Profile information for the Op.""" + def __init__( self, *, @@ -769,12 +784,12 @@ class OpMetadata(google.protobuf.message.Message): size_of_memory_working_set_in_bytes: builtins.int | None = ..., profile_info: global___OpMetadata.ProfileInfo | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["profile_info", b"profile_info"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["creation_pass_id", b"creation_pass_id", "logical_creation_pass_id", b"logical_creation_pass_id", "op_name", b"op_name", "op_type", b"op_type", "profile_info", b"profile_info", "profile_type", b"profile_type", "size_of_generated_code_in_bytes", b"size_of_generated_code_in_bytes", "size_of_memory_working_set_in_bytes", b"size_of_memory_working_set_in_bytes", "source_file", b"source_file", "source_line", b"source_line"]) -> None: ... + def HasField(self, field_name: typing.Literal["profile_info", b"profile_info"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["creation_pass_id", b"creation_pass_id", "logical_creation_pass_id", b"logical_creation_pass_id", "op_name", b"op_name", "op_type", b"op_type", "profile_info", b"profile_info", "profile_type", b"profile_type", "size_of_generated_code_in_bytes", b"size_of_generated_code_in_bytes", "size_of_memory_working_set_in_bytes", b"size_of_memory_working_set_in_bytes", "source_file", b"source_file", "source_line", b"source_line"]) -> None: ... global___OpMetadata = OpMetadata -@typing_extensions.final +@typing.final class ExecutionProfile(google.protobuf.message.Message): """Profile data from the execution of a computation.""" @@ -824,11 +839,11 @@ class ExecutionProfile(google.protobuf.message.Message): executable_size_in_bytes: builtins.int | None = ..., profile_cache_hit: builtins.bool | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["compilation_cache_hit", b"compilation_cache_hit", "compile_time_ms", b"compile_time_ms", "compute_and_transfer_time_ns", b"compute_and_transfer_time_ns", "compute_cycle_count", b"compute_cycle_count", "compute_time_ns", b"compute_time_ns", "executable_size_in_bytes", b"executable_size_in_bytes", "profile_cache_hit", b"profile_cache_hit"]) -> None: ... + def ClearField(self, field_name: typing.Literal["compilation_cache_hit", b"compilation_cache_hit", "compile_time_ms", b"compile_time_ms", "compute_and_transfer_time_ns", b"compute_and_transfer_time_ns", "compute_cycle_count", b"compute_cycle_count", "compute_time_ns", b"compute_time_ns", "executable_size_in_bytes", b"executable_size_in_bytes", "profile_cache_hit", b"profile_cache_hit"]) -> None: ... global___ExecutionProfile = ExecutionProfile -@typing_extensions.final +@typing.final class ExecutionHandle(google.protobuf.message.Message): """Handle given to a user that represents an execution that the user launched asynchronously on the device. @@ -843,11 +858,11 @@ class ExecutionHandle(google.protobuf.message.Message): *, handle: builtins.int | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["handle", b"handle"]) -> None: ... + def ClearField(self, field_name: typing.Literal["handle", b"handle"]) -> None: ... global___ExecutionHandle = ExecutionHandle -@typing_extensions.final +@typing.final class GlobalDataHandle(google.protobuf.message.Message): """Handle given to a user that represents a globally accessible allocation. Contrast this against a ComputationDataHandle, which is not globally @@ -863,11 +878,11 @@ class GlobalDataHandle(google.protobuf.message.Message): *, handle: builtins.int | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["handle", b"handle"]) -> None: ... + def ClearField(self, field_name: typing.Literal["handle", b"handle"]) -> None: ... global___GlobalDataHandle = GlobalDataHandle -@typing_extensions.final +@typing.final class DeviceHandle(google.protobuf.message.Message): """Handle given to a user that represents a replicated virtual device. Each replicated device represents N physical devices for execution where N is the @@ -889,11 +904,11 @@ class DeviceHandle(google.protobuf.message.Message): handle: builtins.int | None = ..., device_count: builtins.int | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["device_count", b"device_count", "handle", b"handle"]) -> None: ... + def ClearField(self, field_name: typing.Literal["device_count", b"device_count", "handle", b"handle"]) -> None: ... global___DeviceHandle = DeviceHandle -@typing_extensions.final +@typing.final class ChannelHandle(google.protobuf.message.Message): """Handle given to a user to represent a channel between two computations via a Send and Recv instruction pair. Channels are unbuffered, so Send @@ -945,11 +960,11 @@ class ChannelHandle(google.protobuf.message.Message): handle: builtins.int | None = ..., type: global___ChannelHandle.ChannelType.ValueType | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["handle", b"handle", "type", b"type"]) -> None: ... + def ClearField(self, field_name: typing.Literal["handle", b"handle", "type", b"type"]) -> None: ... global___ChannelHandle = ChannelHandle -@typing_extensions.final +@typing.final class DeviceAssignmentProto(google.protobuf.message.Message): """DeviceAssignmentProto is a serialized form of DeviceAssignment class, which represents the device ids assigned to a set of replicated computations. @@ -958,7 +973,7 @@ class DeviceAssignmentProto(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor - @typing_extensions.final + @typing.final class ComputationDevice(google.protobuf.message.Message): """Each logical computation runs on replica_count physical devices. ComputationDevice represents the device ids assinged to the replicas. @@ -974,7 +989,7 @@ class DeviceAssignmentProto(google.protobuf.message.Message): *, replica_device_ids: collections.abc.Iterable[builtins.int] | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["replica_device_ids", b"replica_device_ids"]) -> None: ... + def ClearField(self, field_name: typing.Literal["replica_device_ids", b"replica_device_ids"]) -> None: ... REPLICA_COUNT_FIELD_NUMBER: builtins.int COMPUTATION_COUNT_FIELD_NUMBER: builtins.int @@ -990,11 +1005,11 @@ class DeviceAssignmentProto(google.protobuf.message.Message): computation_count: builtins.int | None = ..., computation_devices: collections.abc.Iterable[global___DeviceAssignmentProto.ComputationDevice] | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["computation_count", b"computation_count", "computation_devices", b"computation_devices", "replica_count", b"replica_count"]) -> None: ... + def ClearField(self, field_name: typing.Literal["computation_count", b"computation_count", "computation_devices", b"computation_devices", "replica_count", b"replica_count"]) -> None: ... global___DeviceAssignmentProto = DeviceAssignmentProto -@typing_extensions.final +@typing.final class LiteralProto(google.protobuf.message.Message): """Literals are used when the server and client need to exchange materialized data / results. Literals are also used to describe constants used in @@ -1026,12 +1041,19 @@ class LiteralProto(google.protobuf.message.Message): F8E5M2S_FIELD_NUMBER: builtins.int F8E4M3FNS_FIELD_NUMBER: builtins.int SPARSE_INDICES_FIELD_NUMBER: builtins.int + s8s: builtins.bytes + u8s: builtins.bytes + f16s: builtins.bytes + """The F16s, BF16s, U16s and S16s are encoded in little endian byte order""" + bf16s: builtins.bytes + u16s: builtins.bytes + s16s: builtins.bytes + f8e5m2s: builtins.bytes + f8e4m3fns: builtins.bytes @property def shape(self) -> global___ShapeProto: ... @property def preds(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.bool]: ... - s8s: builtins.bytes - u8s: builtins.bytes @property def s32s(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.int]: ... @property @@ -1047,21 +1069,17 @@ class LiteralProto(google.protobuf.message.Message): @property def c64s(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.float]: """Stored as interleaved real, imag floats.""" + @property def c128s(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.float]: """Stored as interleaved real, imag doubles.""" + @property def tuple_literals(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___LiteralProto]: ... - f16s: builtins.bytes - """The F16s, BF16s, U16s and S16s are encoded in little endian byte order""" - bf16s: builtins.bytes - u16s: builtins.bytes - s16s: builtins.bytes - f8e5m2s: builtins.bytes - f8e4m3fns: builtins.bytes @property def sparse_indices(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.int]: """Next = 21""" + def __init__( self, *, @@ -1086,12 +1104,12 @@ class LiteralProto(google.protobuf.message.Message): f8e4m3fns: builtins.bytes | None = ..., sparse_indices: collections.abc.Iterable[builtins.int] | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["shape", b"shape"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["bf16s", b"bf16s", "c128s", b"c128s", "c64s", b"c64s", "f16s", b"f16s", "f32s", b"f32s", "f64s", b"f64s", "f8e4m3fns", b"f8e4m3fns", "f8e5m2s", b"f8e5m2s", "preds", b"preds", "s16s", b"s16s", "s32s", b"s32s", "s64s", b"s64s", "s8s", b"s8s", "shape", b"shape", "sparse_indices", b"sparse_indices", "tuple_literals", b"tuple_literals", "u16s", b"u16s", "u32s", b"u32s", "u64s", b"u64s", "u8s", b"u8s"]) -> None: ... + def HasField(self, field_name: typing.Literal["shape", b"shape"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["bf16s", b"bf16s", "c128s", b"c128s", "c64s", b"c64s", "f16s", b"f16s", "f32s", b"f32s", "f64s", b"f64s", "f8e4m3fns", b"f8e4m3fns", "f8e5m2s", b"f8e5m2s", "preds", b"preds", "s16s", b"s16s", "s32s", b"s32s", "s64s", b"s64s", "s8s", b"s8s", "shape", b"shape", "sparse_indices", b"sparse_indices", "tuple_literals", b"tuple_literals", "u16s", b"u16s", "u32s", b"u32s", "u64s", b"u64s", "u8s", b"u8s"]) -> None: ... global___LiteralProto = LiteralProto -@typing_extensions.final +@typing.final class WindowDimension(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -1153,11 +1171,11 @@ class WindowDimension(google.protobuf.message.Message): base_dilation: builtins.int | None = ..., window_reversal: builtins.bool | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["base_dilation", b"base_dilation", "padding_high", b"padding_high", "padding_low", b"padding_low", "size", b"size", "stride", b"stride", "window_dilation", b"window_dilation", "window_reversal", b"window_reversal"]) -> None: ... + def ClearField(self, field_name: typing.Literal["base_dilation", b"base_dilation", "padding_high", b"padding_high", "padding_low", b"padding_low", "size", b"size", "stride", b"stride", "window_dilation", b"window_dilation", "window_reversal", b"window_reversal"]) -> None: ... global___WindowDimension = WindowDimension -@typing_extensions.final +@typing.final class Window(google.protobuf.message.Message): """Describes the windowing in an operation such as convolution. @@ -1176,11 +1194,11 @@ class Window(google.protobuf.message.Message): *, dimensions: collections.abc.Iterable[global___WindowDimension] | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["dimensions", b"dimensions"]) -> None: ... + def ClearField(self, field_name: typing.Literal["dimensions", b"dimensions"]) -> None: ... global___Window = Window -@typing_extensions.final +@typing.final class GatherDimensionNumbers(google.protobuf.message.Message): """Describes the dimension numbers for a gather operation. @@ -1194,6 +1212,10 @@ class GatherDimensionNumbers(google.protobuf.message.Message): COLLAPSED_SLICE_DIMS_FIELD_NUMBER: builtins.int START_INDEX_MAP_FIELD_NUMBER: builtins.int INDEX_VECTOR_DIM_FIELD_NUMBER: builtins.int + index_vector_dim: builtins.int + """The dimension in the start_indices input that contains the starting + indices. + """ @property def offset_dims(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.int]: """"Window indices" is a term for a set of indices that index into the @@ -1210,6 +1232,7 @@ class GatherDimensionNumbers(google.protobuf.message.Message): then 0 else Out[offset_dims[i++]] """ + @property def collapsed_slice_dims(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.int]: ... @property @@ -1218,10 +1241,7 @@ class GatherDimensionNumbers(google.protobuf.message.Message): transforms the gather index looked up from the start_indices tensor into the starting index in the input space. """ - index_vector_dim: builtins.int - """The dimension in the start_indices input that contains the starting - indices. - """ + def __init__( self, *, @@ -1230,11 +1250,11 @@ class GatherDimensionNumbers(google.protobuf.message.Message): start_index_map: collections.abc.Iterable[builtins.int] | None = ..., index_vector_dim: builtins.int | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["collapsed_slice_dims", b"collapsed_slice_dims", "index_vector_dim", b"index_vector_dim", "offset_dims", b"offset_dims", "start_index_map", b"start_index_map"]) -> None: ... + def ClearField(self, field_name: typing.Literal["collapsed_slice_dims", b"collapsed_slice_dims", "index_vector_dim", b"index_vector_dim", "offset_dims", b"offset_dims", "start_index_map", b"start_index_map"]) -> None: ... global___GatherDimensionNumbers = GatherDimensionNumbers -@typing_extensions.final +@typing.final class ScatterDimensionNumbers(google.protobuf.message.Message): """Describes the dimension numbers for a scatter operation. @@ -1248,15 +1268,17 @@ class ScatterDimensionNumbers(google.protobuf.message.Message): INSERTED_WINDOW_DIMS_FIELD_NUMBER: builtins.int SCATTER_DIMS_TO_OPERAND_DIMS_FIELD_NUMBER: builtins.int INDEX_VECTOR_DIM_FIELD_NUMBER: builtins.int + index_vector_dim: builtins.int @property def update_window_dims(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.int]: """The set of dimensions in the updates shape that are window dimensions.""" + @property def inserted_window_dims(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.int]: """The set of window dimensions that must be inserted into the updates shape.""" + @property def scatter_dims_to_operand_dims(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.int]: ... - index_vector_dim: builtins.int def __init__( self, *, @@ -1265,11 +1287,11 @@ class ScatterDimensionNumbers(google.protobuf.message.Message): scatter_dims_to_operand_dims: collections.abc.Iterable[builtins.int] | None = ..., index_vector_dim: builtins.int | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["index_vector_dim", b"index_vector_dim", "inserted_window_dims", b"inserted_window_dims", "scatter_dims_to_operand_dims", b"scatter_dims_to_operand_dims", "update_window_dims", b"update_window_dims"]) -> None: ... + def ClearField(self, field_name: typing.Literal["index_vector_dim", b"index_vector_dim", "inserted_window_dims", b"inserted_window_dims", "scatter_dims_to_operand_dims", b"scatter_dims_to_operand_dims", "update_window_dims", b"update_window_dims"]) -> None: ... global___ScatterDimensionNumbers = ScatterDimensionNumbers -@typing_extensions.final +@typing.final class ConvolutionDimensionNumbers(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -1286,11 +1308,6 @@ class ConvolutionDimensionNumbers(google.protobuf.message.Message): """The number of the dimension that represents batch in the input.""" input_feature_dimension: builtins.int """The number of the dimension that represents features in the input.""" - @property - def input_spatial_dimensions(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.int]: - """The dimension numbers for the spatial dimensions that the window - moves through in the input. - """ kernel_input_feature_dimension: builtins.int """The number of the dimension that represents input features in the convolutional kernel (rhs). @@ -1299,21 +1316,29 @@ class ConvolutionDimensionNumbers(google.protobuf.message.Message): """The number of the dimension that represents output features in the convolutional kernel (rhs). """ + output_batch_dimension: builtins.int + """The number of the dimension that represents batch in the output.""" + output_feature_dimension: builtins.int + """The number of the dimension that represents features in the output.""" + @property + def input_spatial_dimensions(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.int]: + """The dimension numbers for the spatial dimensions that the window + moves through in the input. + """ + @property def kernel_spatial_dimensions(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.int]: """The dimension numbers for the spatial dimensions that the window moves through in the kernel (rhs). window.strides(0) is the stride in the kernel_spatial_dimensions(0) dimension. """ - output_batch_dimension: builtins.int - """The number of the dimension that represents batch in the output.""" - output_feature_dimension: builtins.int - """The number of the dimension that represents features in the output.""" + @property def output_spatial_dimensions(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.int]: """The dimension numbers for the spatial dimensions that the window moves through in the output. """ + def __init__( self, *, @@ -1327,11 +1352,11 @@ class ConvolutionDimensionNumbers(google.protobuf.message.Message): output_feature_dimension: builtins.int | None = ..., output_spatial_dimensions: collections.abc.Iterable[builtins.int] | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["input_batch_dimension", b"input_batch_dimension", "input_feature_dimension", b"input_feature_dimension", "input_spatial_dimensions", b"input_spatial_dimensions", "kernel_input_feature_dimension", b"kernel_input_feature_dimension", "kernel_output_feature_dimension", b"kernel_output_feature_dimension", "kernel_spatial_dimensions", b"kernel_spatial_dimensions", "output_batch_dimension", b"output_batch_dimension", "output_feature_dimension", b"output_feature_dimension", "output_spatial_dimensions", b"output_spatial_dimensions"]) -> None: ... + def ClearField(self, field_name: typing.Literal["input_batch_dimension", b"input_batch_dimension", "input_feature_dimension", b"input_feature_dimension", "input_spatial_dimensions", b"input_spatial_dimensions", "kernel_input_feature_dimension", b"kernel_input_feature_dimension", "kernel_output_feature_dimension", b"kernel_output_feature_dimension", "kernel_spatial_dimensions", b"kernel_spatial_dimensions", "output_batch_dimension", b"output_batch_dimension", "output_feature_dimension", b"output_feature_dimension", "output_spatial_dimensions", b"output_spatial_dimensions"]) -> None: ... global___ConvolutionDimensionNumbers = ConvolutionDimensionNumbers -@typing_extensions.final +@typing.final class DotDimensionNumbers(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -1342,15 +1367,19 @@ class DotDimensionNumbers(google.protobuf.message.Message): @property def lhs_contracting_dimensions(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.int]: """The dimension numbers that represent the 'lhs' contracting dimensions.""" + @property def rhs_contracting_dimensions(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.int]: """The dimension numbers that represent the 'rhs' contracting dimensions.""" + @property def lhs_batch_dimensions(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.int]: """The dimension numbers that represent the 'lhs' batch dimensions.""" + @property def rhs_batch_dimensions(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.int]: """The dimension numbers that represent the 'rhs' batch dimensions.""" + def __init__( self, *, @@ -1359,11 +1388,11 @@ class DotDimensionNumbers(google.protobuf.message.Message): lhs_batch_dimensions: collections.abc.Iterable[builtins.int] | None = ..., rhs_batch_dimensions: collections.abc.Iterable[builtins.int] | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["lhs_batch_dimensions", b"lhs_batch_dimensions", "lhs_contracting_dimensions", b"lhs_contracting_dimensions", "rhs_batch_dimensions", b"rhs_batch_dimensions", "rhs_contracting_dimensions", b"rhs_contracting_dimensions"]) -> None: ... + def ClearField(self, field_name: typing.Literal["lhs_batch_dimensions", b"lhs_batch_dimensions", "lhs_contracting_dimensions", b"lhs_contracting_dimensions", "rhs_batch_dimensions", b"rhs_batch_dimensions", "rhs_contracting_dimensions", b"rhs_contracting_dimensions"]) -> None: ... global___DotDimensionNumbers = DotDimensionNumbers -@typing_extensions.final +@typing.final class TriangularSolveOptions(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -1411,11 +1440,11 @@ class TriangularSolveOptions(google.protobuf.message.Message): unit_diagonal: builtins.bool | None = ..., transpose_a: global___TriangularSolveOptions.Transpose.ValueType | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["left_side", b"left_side", "lower", b"lower", "transpose_a", b"transpose_a", "unit_diagonal", b"unit_diagonal"]) -> None: ... + def ClearField(self, field_name: typing.Literal["left_side", b"left_side", "lower", b"lower", "transpose_a", b"transpose_a", "unit_diagonal", b"unit_diagonal"]) -> None: ... global___TriangularSolveOptions = TriangularSolveOptions -@typing_extensions.final +@typing.final class CholeskyOptions(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -1429,11 +1458,11 @@ class CholeskyOptions(google.protobuf.message.Message): *, lower: builtins.bool | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["lower", b"lower"]) -> None: ... + def ClearField(self, field_name: typing.Literal["lower", b"lower"]) -> None: ... global___CholeskyOptions = CholeskyOptions -@typing_extensions.final +@typing.final class FrontendAttributes(google.protobuf.message.Message): """Generic map of attributes used to pass hints / configuration options from the Python frontend to the XLA backend. @@ -1441,7 +1470,7 @@ class FrontendAttributes(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor - @typing_extensions.final + @typing.final class MapEntry(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -1455,7 +1484,7 @@ class FrontendAttributes(google.protobuf.message.Message): key: builtins.str | None = ..., value: builtins.str | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["key", b"key", "value", b"value"]) -> None: ... + def ClearField(self, field_name: typing.Literal["key", b"key", "value", b"value"]) -> None: ... MAP_FIELD_NUMBER: builtins.int @property @@ -1465,11 +1494,11 @@ class FrontendAttributes(google.protobuf.message.Message): *, map: collections.abc.Mapping[builtins.str, builtins.str] | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["map", b"map"]) -> None: ... + def ClearField(self, field_name: typing.Literal["map", b"map"]) -> None: ... global___FrontendAttributes = FrontendAttributes -@typing_extensions.final +@typing.final class OpSharding(google.protobuf.message.Message): """LINT.IfChange""" @@ -1521,20 +1550,28 @@ class OpSharding(google.protobuf.message.Message): METADATA_FIELD_NUMBER: builtins.int LAST_TILE_DIMS_FIELD_NUMBER: builtins.int type: global___OpSharding.Type.ValueType + replicate_on_last_tile_dim: builtins.bool + """Only used for OTHER type. If true, data is sharded according to other + dimensions of tile_assignment(), but replicated across devices along the + last dimension. (Experimental) + """ @property def tile_shape(self) -> global___ShapeProto: """The shape of the sharded tile.""" + @property def tile_assignment_dimensions(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.int]: """The shape of the tile assignment tensor - this must be the same rank as tile_shape and the product of its dimensions must equal tile_assignment_devices.size(). """ + @property def tile_assignment_devices(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.int]: """Flattened list of device IDs. The order of flattening is the same as used by IndexUtil::MultiToLinearIndex(tile_assignment_shape). """ + @property def tuple_shardings(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___OpSharding]: """If type == TUPLE, the sub-shardings, one per leaf node in the tuple shape, @@ -1544,11 +1581,7 @@ class OpSharding(google.protobuf.message.Message): applied, this is inferred from the instruction this sharding gets attached to. """ - replicate_on_last_tile_dim: builtins.bool - """Only used for OTHER type. If true, data is sharded according to other - dimensions of tile_assignment(), but replicated across devices along the - last dimension. (Experimental) - """ + @property def metadata(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___OpMetadata]: """This field is used to track the source of this sharding, usually derived @@ -1557,6 +1590,7 @@ class OpSharding(google.protobuf.message.Message): type == TUPLE and instead metadata should be set on individual tuple elements. """ + @property def last_tile_dims(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[global___OpSharding.Type.ValueType]: """This field is used to represented the sharding type of each subgroup. @@ -1565,6 +1599,7 @@ class OpSharding(google.protobuf.message.Message): in [2,2,2,2] represents a subgrouping in replicate, manual, unreduced sharding type respectively. """ + def __init__( self, *, @@ -1577,12 +1612,12 @@ class OpSharding(google.protobuf.message.Message): metadata: collections.abc.Iterable[global___OpMetadata] | None = ..., last_tile_dims: collections.abc.Iterable[global___OpSharding.Type.ValueType] | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["tile_shape", b"tile_shape"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["last_tile_dims", b"last_tile_dims", "metadata", b"metadata", "replicate_on_last_tile_dim", b"replicate_on_last_tile_dim", "tile_assignment_devices", b"tile_assignment_devices", "tile_assignment_dimensions", b"tile_assignment_dimensions", "tile_shape", b"tile_shape", "tuple_shardings", b"tuple_shardings", "type", b"type"]) -> None: ... + def HasField(self, field_name: typing.Literal["tile_shape", b"tile_shape"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["last_tile_dims", b"last_tile_dims", "metadata", b"metadata", "replicate_on_last_tile_dim", b"replicate_on_last_tile_dim", "tile_assignment_devices", b"tile_assignment_devices", "tile_assignment_dimensions", b"tile_assignment_dimensions", "tile_shape", b"tile_shape", "tuple_shardings", b"tuple_shardings", "type", b"type"]) -> None: ... global___OpSharding = OpSharding -@typing_extensions.final +@typing.final class ReplicaGroup(google.protobuf.message.Message): """Describes the replica groups in a cross replica op (e.g., all-reduce and all-to-all). @@ -1596,16 +1631,17 @@ class ReplicaGroup(google.protobuf.message.Message): """The ids of the replicas that belongs to the same group. The ordering of the ids matters in some ops (e.g., all-to-all). """ + def __init__( self, *, replica_ids: collections.abc.Iterable[builtins.int] | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["replica_ids", b"replica_ids"]) -> None: ... + def ClearField(self, field_name: typing.Literal["replica_ids", b"replica_ids"]) -> None: ... global___ReplicaGroup = ReplicaGroup -@typing_extensions.final +@typing.final class SourceTarget(google.protobuf.message.Message): """Describes the source target pair in the collective permute op.""" @@ -1621,11 +1657,11 @@ class SourceTarget(google.protobuf.message.Message): source: builtins.int | None = ..., target: builtins.int | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["source", b"source", "target", b"target"]) -> None: ... + def ClearField(self, field_name: typing.Literal["source", b"source", "target", b"target"]) -> None: ... global___SourceTarget = SourceTarget -@typing_extensions.final +@typing.final class PrecisionConfig(google.protobuf.message.Message): """Used to indicate the precision configuration. It has backend specific meaning. @@ -1660,11 +1696,11 @@ class PrecisionConfig(google.protobuf.message.Message): *, operand_precision: collections.abc.Iterable[global___PrecisionConfig.Precision.ValueType] | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["operand_precision", b"operand_precision"]) -> None: ... + def ClearField(self, field_name: typing.Literal["operand_precision", b"operand_precision"]) -> None: ... global___PrecisionConfig = PrecisionConfig -@typing_extensions.final +@typing.final class ParameterReplication(google.protobuf.message.Message): """Describes whether all data-parallelism replicas will receive the same parameter data at each buffer. @@ -1682,16 +1718,17 @@ class ParameterReplication(google.protobuf.message.Message): number of elements in this field must match the number of leaf buffers in the HLO instruction's shape. """ + def __init__( self, *, replicated_at_leaf_buffers: collections.abc.Iterable[builtins.bool] | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["replicated_at_leaf_buffers", b"replicated_at_leaf_buffers"]) -> None: ... + def ClearField(self, field_name: typing.Literal["replicated_at_leaf_buffers", b"replicated_at_leaf_buffers"]) -> None: ... global___ParameterReplication = ParameterReplication -@typing_extensions.final +@typing.final class WhileLoopBackendConfig(google.protobuf.message.Message): """A backend-config for kWhile loops that stores the loop's trip count, if it is known. @@ -1705,7 +1742,7 @@ class WhileLoopBackendConfig(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor - @typing_extensions.final + @typing.final class KnownTripCount(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -1716,7 +1753,7 @@ class WhileLoopBackendConfig(google.protobuf.message.Message): *, n: builtins.int | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["n", b"n"]) -> None: ... + def ClearField(self, field_name: typing.Literal["n", b"n"]) -> None: ... KNOWN_TRIP_COUNT_FIELD_NUMBER: builtins.int @property @@ -1724,17 +1761,18 @@ class WhileLoopBackendConfig(google.protobuf.message.Message): """This indirection lets us distinguish between known-trip-count == 0 and unknown-trip-count. """ + def __init__( self, *, known_trip_count: global___WhileLoopBackendConfig.KnownTripCount | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["known_trip_count", b"known_trip_count"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["known_trip_count", b"known_trip_count"]) -> None: ... + def HasField(self, field_name: typing.Literal["known_trip_count", b"known_trip_count"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["known_trip_count", b"known_trip_count"]) -> None: ... global___WhileLoopBackendConfig = WhileLoopBackendConfig -@typing_extensions.final +@typing.final class OutputOperandAliasing(google.protobuf.message.Message): """Specifies a pair of output/operand buffers that alias each other for kCustomCall and kFusion @@ -1745,9 +1783,9 @@ class OutputOperandAliasing(google.protobuf.message.Message): OUTPUT_SHAPE_INDEX_FIELD_NUMBER: builtins.int OPERAND_INDEX_FIELD_NUMBER: builtins.int OPERAND_SHAPE_INDEX_FIELD_NUMBER: builtins.int + operand_index: builtins.int @property def output_shape_index(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.int]: ... - operand_index: builtins.int @property def operand_shape_index(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.int]: ... def __init__( @@ -1757,6 +1795,6 @@ class OutputOperandAliasing(google.protobuf.message.Message): operand_index: builtins.int | None = ..., operand_shape_index: collections.abc.Iterable[builtins.int] | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["operand_index", b"operand_index", "operand_shape_index", b"operand_shape_index", "output_shape_index", b"output_shape_index"]) -> None: ... + def ClearField(self, field_name: typing.Literal["operand_index", b"operand_index", "operand_shape_index", b"operand_shape_index", "output_shape_index", b"output_shape_index"]) -> None: ... global___OutputOperandAliasing = OutputOperandAliasing diff --git a/stubs/tensorflow/tensorflow/core/example/example_parser_configuration_pb2.pyi b/stubs/tensorflow/tensorflow/core/example/example_parser_configuration_pb2.pyi index 9a0ec205c04c..6b5c255da3b4 100644 --- a/stubs/tensorflow/tensorflow/core/example/example_parser_configuration_pb2.pyi +++ b/stubs/tensorflow/tensorflow/core/example/example_parser_configuration_pb2.pyi @@ -2,9 +2,10 @@ @generated by mypy-protobuf. Do not edit manually! isort:skip_file Protocol messages for describing the configuration of the ExampleParserOp.""" + import builtins import collections.abc -import typing as typing_extensions +import typing import google.protobuf.descriptor import google.protobuf.internal.containers @@ -15,7 +16,7 @@ import tensorflow.core.framework.types_pb2 DESCRIPTOR: google.protobuf.descriptor.FileDescriptor -@typing_extensions.final +@typing.final class VarLenFeatureProto(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -35,11 +36,11 @@ class VarLenFeatureProto(google.protobuf.message.Message): indices_output_tensor_name: builtins.str | None = ..., shapes_output_tensor_name: builtins.str | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["dtype", b"dtype", "indices_output_tensor_name", b"indices_output_tensor_name", "shapes_output_tensor_name", b"shapes_output_tensor_name", "values_output_tensor_name", b"values_output_tensor_name"]) -> None: ... + def ClearField(self, field_name: typing.Literal["dtype", b"dtype", "indices_output_tensor_name", b"indices_output_tensor_name", "shapes_output_tensor_name", b"shapes_output_tensor_name", "values_output_tensor_name", b"values_output_tensor_name"]) -> None: ... global___VarLenFeatureProto = VarLenFeatureProto -@typing_extensions.final +@typing.final class FixedLenFeatureProto(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -48,11 +49,11 @@ class FixedLenFeatureProto(google.protobuf.message.Message): DEFAULT_VALUE_FIELD_NUMBER: builtins.int VALUES_OUTPUT_TENSOR_NAME_FIELD_NUMBER: builtins.int dtype: tensorflow.core.framework.types_pb2.DataType.ValueType + values_output_tensor_name: builtins.str @property def shape(self) -> tensorflow.core.framework.tensor_shape_pb2.TensorShapeProto: ... @property def default_value(self) -> tensorflow.core.framework.tensor_pb2.TensorProto: ... - values_output_tensor_name: builtins.str def __init__( self, *, @@ -61,12 +62,12 @@ class FixedLenFeatureProto(google.protobuf.message.Message): default_value: tensorflow.core.framework.tensor_pb2.TensorProto | None = ..., values_output_tensor_name: builtins.str | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["default_value", b"default_value", "shape", b"shape"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["default_value", b"default_value", "dtype", b"dtype", "shape", b"shape", "values_output_tensor_name", b"values_output_tensor_name"]) -> None: ... + def HasField(self, field_name: typing.Literal["default_value", b"default_value", "shape", b"shape"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["default_value", b"default_value", "dtype", b"dtype", "shape", b"shape", "values_output_tensor_name", b"values_output_tensor_name"]) -> None: ... global___FixedLenFeatureProto = FixedLenFeatureProto -@typing_extensions.final +@typing.final class FeatureConfiguration(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -82,17 +83,17 @@ class FeatureConfiguration(google.protobuf.message.Message): fixed_len_feature: global___FixedLenFeatureProto | None = ..., var_len_feature: global___VarLenFeatureProto | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["config", b"config", "fixed_len_feature", b"fixed_len_feature", "var_len_feature", b"var_len_feature"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["config", b"config", "fixed_len_feature", b"fixed_len_feature", "var_len_feature", b"var_len_feature"]) -> None: ... - def WhichOneof(self, oneof_group: typing_extensions.Literal["config", b"config"]) -> typing_extensions.Literal["fixed_len_feature", "var_len_feature"] | None: ... + def HasField(self, field_name: typing.Literal["config", b"config", "fixed_len_feature", b"fixed_len_feature", "var_len_feature", b"var_len_feature"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["config", b"config", "fixed_len_feature", b"fixed_len_feature", "var_len_feature", b"var_len_feature"]) -> None: ... + def WhichOneof(self, oneof_group: typing.Literal["config", b"config"]) -> typing.Literal["fixed_len_feature", "var_len_feature"] | None: ... global___FeatureConfiguration = FeatureConfiguration -@typing_extensions.final +@typing.final class ExampleParserConfiguration(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor - @typing_extensions.final + @typing.final class FeatureMapEntry(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -107,8 +108,8 @@ class ExampleParserConfiguration(google.protobuf.message.Message): key: builtins.str | None = ..., value: global___FeatureConfiguration | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["value", b"value"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["key", b"key", "value", b"value"]) -> None: ... + def HasField(self, field_name: typing.Literal["value", b"value"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["key", b"key", "value", b"value"]) -> None: ... FEATURE_MAP_FIELD_NUMBER: builtins.int @property @@ -118,6 +119,6 @@ class ExampleParserConfiguration(google.protobuf.message.Message): *, feature_map: collections.abc.Mapping[builtins.str, global___FeatureConfiguration] | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["feature_map", b"feature_map"]) -> None: ... + def ClearField(self, field_name: typing.Literal["feature_map", b"feature_map"]) -> None: ... global___ExampleParserConfiguration = ExampleParserConfiguration diff --git a/stubs/tensorflow/tensorflow/core/example/example_pb2.pyi b/stubs/tensorflow/tensorflow/core/example/example_pb2.pyi index c123b10085e7..562a6c44cf55 100644 --- a/stubs/tensorflow/tensorflow/core/example/example_pb2.pyi +++ b/stubs/tensorflow/tensorflow/core/example/example_pb2.pyi @@ -4,8 +4,9 @@ isort:skip_file Protocol messages for describing input data Examples for machine learning model training or inference. """ + import builtins -import typing as typing_extensions +import typing import google.protobuf.descriptor import google.protobuf.message @@ -13,7 +14,7 @@ import tensorflow.core.example.feature_pb2 DESCRIPTOR: google.protobuf.descriptor.FileDescriptor -@typing_extensions.final +@typing.final class Example(google.protobuf.message.Message): """An Example is a mostly-normalized data format for storing data for training and inference. It contains a key-value store (features); where @@ -99,12 +100,12 @@ class Example(google.protobuf.message.Message): *, features: tensorflow.core.example.feature_pb2.Features | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["features", b"features"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["features", b"features"]) -> None: ... + def HasField(self, field_name: typing.Literal["features", b"features"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["features", b"features"]) -> None: ... global___Example = Example -@typing_extensions.final +@typing.final class SequenceExample(google.protobuf.message.Message): """A SequenceExample is an Example representing one or more sequences, and some context. The context contains features which apply to the entire @@ -327,7 +328,7 @@ class SequenceExample(google.protobuf.message.Message): context: tensorflow.core.example.feature_pb2.Features | None = ..., feature_lists: tensorflow.core.example.feature_pb2.FeatureLists | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["context", b"context", "feature_lists", b"feature_lists"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["context", b"context", "feature_lists", b"feature_lists"]) -> None: ... + def HasField(self, field_name: typing.Literal["context", b"context", "feature_lists", b"feature_lists"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["context", b"context", "feature_lists", b"feature_lists"]) -> None: ... global___SequenceExample = SequenceExample diff --git a/stubs/tensorflow/tensorflow/core/example/feature_pb2.pyi b/stubs/tensorflow/tensorflow/core/example/feature_pb2.pyi index 9f087bfbc559..3fbc881cbaa2 100644 --- a/stubs/tensorflow/tensorflow/core/example/feature_pb2.pyi +++ b/stubs/tensorflow/tensorflow/core/example/feature_pb2.pyi @@ -55,9 +55,10 @@ Example Features for a movie recommendation application: }} } """ + import builtins import collections.abc -import typing as typing_extensions +import typing import google.protobuf.descriptor import google.protobuf.internal.containers @@ -65,7 +66,7 @@ import google.protobuf.message DESCRIPTOR: google.protobuf.descriptor.FileDescriptor -@typing_extensions.final +@typing.final class BytesList(google.protobuf.message.Message): """LINT.IfChange Containers to hold repeated fundamental values. @@ -81,11 +82,11 @@ class BytesList(google.protobuf.message.Message): *, value: collections.abc.Iterable[builtins.bytes] | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["value", b"value"]) -> None: ... + def ClearField(self, field_name: typing.Literal["value", b"value"]) -> None: ... global___BytesList = BytesList -@typing_extensions.final +@typing.final class FloatList(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -97,11 +98,11 @@ class FloatList(google.protobuf.message.Message): *, value: collections.abc.Iterable[builtins.float] | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["value", b"value"]) -> None: ... + def ClearField(self, field_name: typing.Literal["value", b"value"]) -> None: ... global___FloatList = FloatList -@typing_extensions.final +@typing.final class Int64List(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -113,11 +114,11 @@ class Int64List(google.protobuf.message.Message): *, value: collections.abc.Iterable[builtins.int] | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["value", b"value"]) -> None: ... + def ClearField(self, field_name: typing.Literal["value", b"value"]) -> None: ... global___Int64List = Int64List -@typing_extensions.final +@typing.final class Feature(google.protobuf.message.Message): """Containers for non-sequential data.""" @@ -139,17 +140,17 @@ class Feature(google.protobuf.message.Message): float_list: global___FloatList | None = ..., int64_list: global___Int64List | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["bytes_list", b"bytes_list", "float_list", b"float_list", "int64_list", b"int64_list", "kind", b"kind"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["bytes_list", b"bytes_list", "float_list", b"float_list", "int64_list", b"int64_list", "kind", b"kind"]) -> None: ... - def WhichOneof(self, oneof_group: typing_extensions.Literal["kind", b"kind"]) -> typing_extensions.Literal["bytes_list", "float_list", "int64_list"] | None: ... + def HasField(self, field_name: typing.Literal["bytes_list", b"bytes_list", "float_list", b"float_list", "int64_list", b"int64_list", "kind", b"kind"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["bytes_list", b"bytes_list", "float_list", b"float_list", "int64_list", b"int64_list", "kind", b"kind"]) -> None: ... + def WhichOneof(self, oneof_group: typing.Literal["kind", b"kind"]) -> typing.Literal["bytes_list", "float_list", "int64_list"] | None: ... global___Feature = Feature -@typing_extensions.final +@typing.final class Features(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor - @typing_extensions.final + @typing.final class FeatureEntry(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -164,23 +165,24 @@ class Features(google.protobuf.message.Message): key: builtins.str | None = ..., value: global___Feature | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["value", b"value"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["key", b"key", "value", b"value"]) -> None: ... + def HasField(self, field_name: typing.Literal["value", b"value"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["key", b"key", "value", b"value"]) -> None: ... FEATURE_FIELD_NUMBER: builtins.int @property def feature(self) -> google.protobuf.internal.containers.MessageMap[builtins.str, global___Feature]: """Map from feature name to feature.""" + def __init__( self, *, feature: collections.abc.Mapping[builtins.str, global___Feature] | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["feature", b"feature"]) -> None: ... + def ClearField(self, field_name: typing.Literal["feature", b"feature"]) -> None: ... global___Features = Features -@typing_extensions.final +@typing.final class FeatureList(google.protobuf.message.Message): """Containers for sequential data. @@ -201,15 +203,15 @@ class FeatureList(google.protobuf.message.Message): *, feature: collections.abc.Iterable[global___Feature] | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["feature", b"feature"]) -> None: ... + def ClearField(self, field_name: typing.Literal["feature", b"feature"]) -> None: ... global___FeatureList = FeatureList -@typing_extensions.final +@typing.final class FeatureLists(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor - @typing_extensions.final + @typing.final class FeatureListEntry(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -224,18 +226,19 @@ class FeatureLists(google.protobuf.message.Message): key: builtins.str | None = ..., value: global___FeatureList | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["value", b"value"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["key", b"key", "value", b"value"]) -> None: ... + def HasField(self, field_name: typing.Literal["value", b"value"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["key", b"key", "value", b"value"]) -> None: ... FEATURE_LIST_FIELD_NUMBER: builtins.int @property def feature_list(self) -> google.protobuf.internal.containers.MessageMap[builtins.str, global___FeatureList]: """Map from feature name to feature list.""" + def __init__( self, *, feature_list: collections.abc.Mapping[builtins.str, global___FeatureList] | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["feature_list", b"feature_list"]) -> None: ... + def ClearField(self, field_name: typing.Literal["feature_list", b"feature_list"]) -> None: ... global___FeatureLists = FeatureLists diff --git a/stubs/tensorflow/tensorflow/core/framework/allocation_description_pb2.pyi b/stubs/tensorflow/tensorflow/core/framework/allocation_description_pb2.pyi index 72810915bb86..6e0f0cb22534 100644 --- a/stubs/tensorflow/tensorflow/core/framework/allocation_description_pb2.pyi +++ b/stubs/tensorflow/tensorflow/core/framework/allocation_description_pb2.pyi @@ -2,15 +2,16 @@ @generated by mypy-protobuf. Do not edit manually! isort:skip_file """ + import builtins -import typing as typing_extensions +import typing import google.protobuf.descriptor import google.protobuf.message DESCRIPTOR: google.protobuf.descriptor.FileDescriptor -@typing_extensions.final +@typing.final class AllocationDescription(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -42,6 +43,6 @@ class AllocationDescription(google.protobuf.message.Message): has_single_reference: builtins.bool | None = ..., ptr: builtins.int | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["allocated_bytes", b"allocated_bytes", "allocation_id", b"allocation_id", "allocator_name", b"allocator_name", "has_single_reference", b"has_single_reference", "ptr", b"ptr", "requested_bytes", b"requested_bytes"]) -> None: ... + def ClearField(self, field_name: typing.Literal["allocated_bytes", b"allocated_bytes", "allocation_id", b"allocation_id", "allocator_name", b"allocator_name", "has_single_reference", b"has_single_reference", "ptr", b"ptr", "requested_bytes", b"requested_bytes"]) -> None: ... global___AllocationDescription = AllocationDescription diff --git a/stubs/tensorflow/tensorflow/core/framework/api_def_pb2.pyi b/stubs/tensorflow/tensorflow/core/framework/api_def_pb2.pyi index b2f1a514a69e..30f81032a88d 100644 --- a/stubs/tensorflow/tensorflow/core/framework/api_def_pb2.pyi +++ b/stubs/tensorflow/tensorflow/core/framework/api_def_pb2.pyi @@ -4,6 +4,7 @@ isort:skip_file Defines the text format for including per-op API definition and overrides for client language op code generators. """ + import builtins import collections.abc import sys @@ -22,7 +23,7 @@ else: DESCRIPTOR: google.protobuf.descriptor.FileDescriptor -@typing_extensions.final +@typing.final class ApiDef(google.protobuf.message.Message): """Used to specify and override the default API & behavior in the generated code for client languages, from what you would get from @@ -81,7 +82,7 @@ class ApiDef(google.protobuf.message.Message): is appropriate in the target language). """ - @typing_extensions.final + @typing.final class Endpoint(google.protobuf.message.Message): """If you specify any endpoint, this will replace all of the inherited endpoints. The first endpoint should be the @@ -116,9 +117,9 @@ class ApiDef(google.protobuf.message.Message): deprecated: builtins.bool | None = ..., deprecation_version: builtins.int | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["deprecated", b"deprecated", "deprecation_version", b"deprecation_version", "name", b"name"]) -> None: ... + def ClearField(self, field_name: typing.Literal["deprecated", b"deprecated", "deprecation_version", b"deprecation_version", "name", b"name"]) -> None: ... - @typing_extensions.final + @typing.final class Arg(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -143,9 +144,9 @@ class ApiDef(google.protobuf.message.Message): rename_to: builtins.str | None = ..., description: builtins.str | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["description", b"description", "name", b"name", "rename_to", b"rename_to"]) -> None: ... + def ClearField(self, field_name: typing.Literal["description", b"description", "name", b"name", "rename_to", b"rename_to"]) -> None: ... - @typing_extensions.final + @typing.final class Attr(google.protobuf.message.Message): """Description of the graph-construction-time configuration of this Op. That is to say, this describes the attr fields that will @@ -164,6 +165,10 @@ class ApiDef(google.protobuf.message.Message): is used in the GraphDef. Note that these names in `backticks` will also be replaced in the summary & description fields. """ + description: builtins.str + """Note: this will replace any inherited attr doc, there is no current + way of modifying attr descriptions as can be done with op descriptions. + """ @property def default_value(self) -> tensorflow.core.framework.attr_value_pb2.AttrValue: """Specify a new default value to use for this attr. This default @@ -171,10 +176,7 @@ class ApiDef(google.protobuf.message.Message): default in the OpDef, which will be used when interpreting old GraphDefs. """ - description: builtins.str - """Note: this will replace any inherited attr doc, there is no current - way of modifying attr descriptions as can be done with op descriptions. - """ + def __init__( self, *, @@ -183,8 +185,8 @@ class ApiDef(google.protobuf.message.Message): default_value: tensorflow.core.framework.attr_value_pb2.AttrValue | None = ..., description: builtins.str | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["default_value", b"default_value"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["default_value", b"default_value", "description", b"description", "name", b"name", "rename_to", b"rename_to"]) -> None: ... + def HasField(self, field_name: typing.Literal["default_value", b"default_value"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["default_value", b"default_value", "description", b"description", "name", b"name", "rename_to", b"rename_to"]) -> None: ... GRAPH_OP_NAME_FIELD_NUMBER: builtins.int DEPRECATION_MESSAGE_FIELD_NUMBER: builtins.int @@ -212,6 +214,15 @@ class ApiDef(google.protobuf.message.Message): deprecated in versions before that. """ visibility: global___ApiDef.Visibility.ValueType + summary: builtins.str + """One-line human-readable description of what the Op does.""" + description: builtins.str + """Additional, longer human-readable description of what the Op does.""" + description_prefix: builtins.str + """Modify an existing/inherited description by adding text to the beginning + or end. + """ + description_suffix: builtins.str @property def endpoint(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___ApiDef.Endpoint]: ... @property @@ -224,17 +235,9 @@ class ApiDef(google.protobuf.message.Message): Length of arg_order should be either empty to keep current order or match size of in_arg. """ + @property def attr(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___ApiDef.Attr]: ... - summary: builtins.str - """One-line human-readable description of what the Op does.""" - description: builtins.str - """Additional, longer human-readable description of what the Op does.""" - description_prefix: builtins.str - """Modify an existing/inherited description by adding text to the beginning - or end. - """ - description_suffix: builtins.str def __init__( self, *, @@ -252,11 +255,11 @@ class ApiDef(google.protobuf.message.Message): description_prefix: builtins.str | None = ..., description_suffix: builtins.str | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["arg_order", b"arg_order", "attr", b"attr", "deprecation_message", b"deprecation_message", "deprecation_version", b"deprecation_version", "description", b"description", "description_prefix", b"description_prefix", "description_suffix", b"description_suffix", "endpoint", b"endpoint", "graph_op_name", b"graph_op_name", "in_arg", b"in_arg", "out_arg", b"out_arg", "summary", b"summary", "visibility", b"visibility"]) -> None: ... + def ClearField(self, field_name: typing.Literal["arg_order", b"arg_order", "attr", b"attr", "deprecation_message", b"deprecation_message", "deprecation_version", b"deprecation_version", "description", b"description", "description_prefix", b"description_prefix", "description_suffix", b"description_suffix", "endpoint", b"endpoint", "graph_op_name", b"graph_op_name", "in_arg", b"in_arg", "out_arg", b"out_arg", "summary", b"summary", "visibility", b"visibility"]) -> None: ... global___ApiDef = ApiDef -@typing_extensions.final +@typing.final class ApiDefs(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -268,6 +271,6 @@ class ApiDefs(google.protobuf.message.Message): *, op: collections.abc.Iterable[global___ApiDef] | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["op", b"op"]) -> None: ... + def ClearField(self, field_name: typing.Literal["op", b"op"]) -> None: ... global___ApiDefs = ApiDefs diff --git a/stubs/tensorflow/tensorflow/core/framework/attr_value_pb2.pyi b/stubs/tensorflow/tensorflow/core/framework/attr_value_pb2.pyi index 3e42d11f5fe2..80bdde459e0f 100644 --- a/stubs/tensorflow/tensorflow/core/framework/attr_value_pb2.pyi +++ b/stubs/tensorflow/tensorflow/core/framework/attr_value_pb2.pyi @@ -2,9 +2,10 @@ @generated by mypy-protobuf. Do not edit manually! isort:skip_file """ + import builtins import collections.abc -import typing as typing_extensions +import typing import google.protobuf.descriptor import google.protobuf.internal.containers @@ -15,7 +16,7 @@ import tensorflow.core.framework.types_pb2 DESCRIPTOR: google.protobuf.descriptor.FileDescriptor -@typing_extensions.final +@typing.final class AttrValue(google.protobuf.message.Message): """Protocol buffer representing the value for an attr used to configure an Op. Comment indicates the corresponding attr type. Only the field matching the @@ -24,7 +25,7 @@ class AttrValue(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor - @typing_extensions.final + @typing.final class ListValue(google.protobuf.message.Message): """LINT.IfChange""" @@ -41,27 +42,35 @@ class AttrValue(google.protobuf.message.Message): @property def s(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.bytes]: """"list(string)" """ + @property def i(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.int]: """"list(int)" """ + @property def f(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.float]: """"list(float)" """ + @property def b(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.bool]: """"list(bool)" """ + @property def type(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[tensorflow.core.framework.types_pb2.DataType.ValueType]: """"list(type)" """ + @property def shape(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[tensorflow.core.framework.tensor_shape_pb2.TensorShapeProto]: """"list(shape)" """ + @property def tensor(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[tensorflow.core.framework.tensor_pb2.TensorProto]: """"list(tensor)" """ + @property def func(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___NameAttrList]: """"list(attr)" """ + def __init__( self, *, @@ -74,7 +83,7 @@ class AttrValue(google.protobuf.message.Message): tensor: collections.abc.Iterable[tensorflow.core.framework.tensor_pb2.TensorProto] | None = ..., func: collections.abc.Iterable[global___NameAttrList] | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["b", b"b", "f", b"f", "func", b"func", "i", b"i", "s", b"s", "shape", b"shape", "tensor", b"tensor", "type", b"type"]) -> None: ... + def ClearField(self, field_name: typing.Literal["b", b"b", "f", b"f", "func", b"func", "i", b"i", "s", b"s", "shape", b"shape", "tensor", b"tensor", "type", b"type"]) -> None: ... S_FIELD_NUMBER: builtins.int I_FIELD_NUMBER: builtins.int @@ -96,15 +105,27 @@ class AttrValue(google.protobuf.message.Message): """"bool" """ type: tensorflow.core.framework.types_pb2.DataType.ValueType """"type" """ + placeholder: builtins.str + """This is a placeholder only used in nodes defined inside a + function. It indicates the attr value will be supplied when + the function is instantiated. For example, let us suppose a + node "N" in function "FN". "N" has an attr "A" with value + placeholder = "foo". When FN is instantiated with attr "foo" + set to "bar", the instantiated node N's attr A will have been + given the value "bar". + """ @property def shape(self) -> tensorflow.core.framework.tensor_shape_pb2.TensorShapeProto: """"shape" """ + @property def tensor(self) -> tensorflow.core.framework.tensor_pb2.TensorProto: """"tensor" """ + @property def list(self) -> global___AttrValue.ListValue: """any "list(...)" """ + @property def func(self) -> global___NameAttrList: """"func" represents a function. func.name is a function's name or @@ -112,15 +133,7 @@ class AttrValue(google.protobuf.message.Message): defined for that function. func.attr.second is the value for that attr in the instantiation. """ - placeholder: builtins.str - """This is a placeholder only used in nodes defined inside a - function. It indicates the attr value will be supplied when - the function is instantiated. For example, let us suppose a - node "N" in function "FN". "N" has an attr "A" with value - placeholder = "foo". When FN is instantiated with attr "foo" - set to "bar", the instantiated node N's attr A will have been - given the value "bar". - """ + def __init__( self, *, @@ -135,13 +148,13 @@ class AttrValue(google.protobuf.message.Message): func: global___NameAttrList | None = ..., placeholder: builtins.str | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["b", b"b", "f", b"f", "func", b"func", "i", b"i", "list", b"list", "placeholder", b"placeholder", "s", b"s", "shape", b"shape", "tensor", b"tensor", "type", b"type", "value", b"value"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["b", b"b", "f", b"f", "func", b"func", "i", b"i", "list", b"list", "placeholder", b"placeholder", "s", b"s", "shape", b"shape", "tensor", b"tensor", "type", b"type", "value", b"value"]) -> None: ... - def WhichOneof(self, oneof_group: typing_extensions.Literal["value", b"value"]) -> typing_extensions.Literal["s", "i", "f", "b", "type", "shape", "tensor", "list", "func", "placeholder"] | None: ... + def HasField(self, field_name: typing.Literal["b", b"b", "f", b"f", "func", b"func", "i", b"i", "list", b"list", "placeholder", b"placeholder", "s", b"s", "shape", b"shape", "tensor", b"tensor", "type", b"type", "value", b"value"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["b", b"b", "f", b"f", "func", b"func", "i", b"i", "list", b"list", "placeholder", b"placeholder", "s", b"s", "shape", b"shape", "tensor", b"tensor", "type", b"type", "value", b"value"]) -> None: ... + def WhichOneof(self, oneof_group: typing.Literal["value", b"value"]) -> typing.Literal["s", "i", "f", "b", "type", "shape", "tensor", "list", "func", "placeholder"] | None: ... global___AttrValue = AttrValue -@typing_extensions.final +@typing.final class NameAttrList(google.protobuf.message.Message): """A list of attr names and their values. The whole list is attached with a string name. E.g., MatMul[T=float]. @@ -149,7 +162,7 @@ class NameAttrList(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor - @typing_extensions.final + @typing.final class AttrEntry(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -164,8 +177,8 @@ class NameAttrList(google.protobuf.message.Message): key: builtins.str | None = ..., value: global___AttrValue | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["value", b"value"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["key", b"key", "value", b"value"]) -> None: ... + def HasField(self, field_name: typing.Literal["value", b"value"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["key", b"key", "value", b"value"]) -> None: ... NAME_FIELD_NUMBER: builtins.int ATTR_FIELD_NUMBER: builtins.int @@ -178,6 +191,6 @@ class NameAttrList(google.protobuf.message.Message): name: builtins.str | None = ..., attr: collections.abc.Mapping[builtins.str, global___AttrValue] | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["attr", b"attr", "name", b"name"]) -> None: ... + def ClearField(self, field_name: typing.Literal["attr", b"attr", "name", b"name"]) -> None: ... global___NameAttrList = NameAttrList diff --git a/stubs/tensorflow/tensorflow/core/framework/cost_graph_pb2.pyi b/stubs/tensorflow/tensorflow/core/framework/cost_graph_pb2.pyi index 92cab2446fc2..d54c0196320a 100644 --- a/stubs/tensorflow/tensorflow/core/framework/cost_graph_pb2.pyi +++ b/stubs/tensorflow/tensorflow/core/framework/cost_graph_pb2.pyi @@ -2,9 +2,10 @@ @generated by mypy-protobuf. Do not edit manually! isort:skip_file """ + import builtins import collections.abc -import typing as typing_extensions +import typing import google.protobuf.descriptor import google.protobuf.internal.containers @@ -14,15 +15,15 @@ import tensorflow.core.framework.types_pb2 DESCRIPTOR: google.protobuf.descriptor.FileDescriptor -@typing_extensions.final +@typing.final class CostGraphDef(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor - @typing_extensions.final + @typing.final class Node(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor - @typing_extensions.final + @typing.final class InputInfo(google.protobuf.message.Message): """Inputs of this node. They must be executed before this node can be executed. An input is a particular output of another node, specified @@ -41,9 +42,9 @@ class CostGraphDef(google.protobuf.message.Message): preceding_node: builtins.int | None = ..., preceding_port: builtins.int | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["preceding_node", b"preceding_node", "preceding_port", b"preceding_port"]) -> None: ... + def ClearField(self, field_name: typing.Literal["preceding_node", b"preceding_node", "preceding_port", b"preceding_port"]) -> None: ... - @typing_extensions.final + @typing.final class OutputInfo(google.protobuf.message.Message): """Outputs of this node.""" @@ -59,9 +60,9 @@ class CostGraphDef(google.protobuf.message.Message): may itself be an alias. The algorithm will therefore need to follow those pointers. """ + dtype: tensorflow.core.framework.types_pb2.DataType.ValueType @property def shape(self) -> tensorflow.core.framework.tensor_shape_pb2.TensorShapeProto: ... - dtype: tensorflow.core.framework.types_pb2.DataType.ValueType def __init__( self, *, @@ -70,8 +71,8 @@ class CostGraphDef(google.protobuf.message.Message): shape: tensorflow.core.framework.tensor_shape_pb2.TensorShapeProto | None = ..., dtype: tensorflow.core.framework.types_pb2.DataType.ValueType | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["shape", b"shape"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["alias_input_port", b"alias_input_port", "dtype", b"dtype", "shape", b"shape", "size", b"size"]) -> None: ... + def HasField(self, field_name: typing.Literal["shape", b"shape"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["alias_input_port", b"alias_input_port", "dtype", b"dtype", "shape", b"shape", "size", b"size"]) -> None: ... NAME_FIELD_NUMBER: builtins.int DEVICE_FIELD_NUMBER: builtins.int @@ -97,10 +98,6 @@ class CostGraphDef(google.protobuf.message.Message): """ id: builtins.int """The id of the node. Node ids are only unique inside a partition.""" - @property - def input_info(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___CostGraphDef.Node.InputInfo]: ... - @property - def output_info(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___CostGraphDef.Node.OutputInfo]: ... temporary_memory_size: builtins.int """Temporary memory used by this node.""" persistent_memory_size: builtins.int @@ -122,11 +119,16 @@ class CostGraphDef(google.protobuf.message.Message): """If true, the output is permanent: it can't be discarded, because this node is part of the "final output". Nodes may depend on final nodes. """ + inaccurate: builtins.bool + """Are the costs inaccurate?""" + @property + def input_info(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___CostGraphDef.Node.InputInfo]: ... + @property + def output_info(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___CostGraphDef.Node.OutputInfo]: ... @property def control_input(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.int]: """Ids of the control inputs for this node.""" - inaccurate: builtins.bool - """Are the costs inaccurate?""" + def __init__( self, *, @@ -147,9 +149,9 @@ class CostGraphDef(google.protobuf.message.Message): control_input: collections.abc.Iterable[builtins.int] | None = ..., inaccurate: builtins.bool | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["compute_cost", b"compute_cost", "compute_time", b"compute_time", "control_input", b"control_input", "device", b"device", "device_persistent_memory_size", b"device_persistent_memory_size", "device_temp_memory_size", b"device_temp_memory_size", "host_temp_memory_size", b"host_temp_memory_size", "id", b"id", "inaccurate", b"inaccurate", "input_info", b"input_info", "is_final", b"is_final", "memory_time", b"memory_time", "name", b"name", "output_info", b"output_info", "persistent_memory_size", b"persistent_memory_size", "temporary_memory_size", b"temporary_memory_size"]) -> None: ... + def ClearField(self, field_name: typing.Literal["compute_cost", b"compute_cost", "compute_time", b"compute_time", "control_input", b"control_input", "device", b"device", "device_persistent_memory_size", b"device_persistent_memory_size", "device_temp_memory_size", b"device_temp_memory_size", "host_temp_memory_size", b"host_temp_memory_size", "id", b"id", "inaccurate", b"inaccurate", "input_info", b"input_info", "is_final", b"is_final", "memory_time", b"memory_time", "name", b"name", "output_info", b"output_info", "persistent_memory_size", b"persistent_memory_size", "temporary_memory_size", b"temporary_memory_size"]) -> None: ... - @typing_extensions.final + @typing.final class AggregatedCost(google.protobuf.message.Message): """Total cost of this graph, typically used for balancing decisions.""" @@ -167,7 +169,7 @@ class CostGraphDef(google.protobuf.message.Message): cost: builtins.float | None = ..., dimension: builtins.str | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["cost", b"cost", "dimension", b"dimension"]) -> None: ... + def ClearField(self, field_name: typing.Literal["cost", b"cost", "dimension", b"dimension"]) -> None: ... NODE_FIELD_NUMBER: builtins.int COST_FIELD_NUMBER: builtins.int @@ -181,6 +183,6 @@ class CostGraphDef(google.protobuf.message.Message): node: collections.abc.Iterable[global___CostGraphDef.Node] | None = ..., cost: collections.abc.Iterable[global___CostGraphDef.AggregatedCost] | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["cost", b"cost", "node", b"node"]) -> None: ... + def ClearField(self, field_name: typing.Literal["cost", b"cost", "node", b"node"]) -> None: ... global___CostGraphDef = CostGraphDef diff --git a/stubs/tensorflow/tensorflow/core/framework/dataset_metadata_pb2.pyi b/stubs/tensorflow/tensorflow/core/framework/dataset_metadata_pb2.pyi index be0a6828bf1a..a1c7b19143c5 100644 --- a/stubs/tensorflow/tensorflow/core/framework/dataset_metadata_pb2.pyi +++ b/stubs/tensorflow/tensorflow/core/framework/dataset_metadata_pb2.pyi @@ -2,15 +2,16 @@ @generated by mypy-protobuf. Do not edit manually! isort:skip_file """ + import builtins -import typing as typing_extensions +import typing import google.protobuf.descriptor import google.protobuf.message DESCRIPTOR: google.protobuf.descriptor.FileDescriptor -@typing_extensions.final +@typing.final class Metadata(google.protobuf.message.Message): """next: 2""" @@ -23,6 +24,6 @@ class Metadata(google.protobuf.message.Message): *, name: builtins.bytes | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["name", b"name"]) -> None: ... + def ClearField(self, field_name: typing.Literal["name", b"name"]) -> None: ... global___Metadata = Metadata diff --git a/stubs/tensorflow/tensorflow/core/framework/dataset_options_pb2.pyi b/stubs/tensorflow/tensorflow/core/framework/dataset_options_pb2.pyi index d31d1d267f9e..d41c5772c96a 100644 --- a/stubs/tensorflow/tensorflow/core/framework/dataset_options_pb2.pyi +++ b/stubs/tensorflow/tensorflow/core/framework/dataset_options_pb2.pyi @@ -2,6 +2,7 @@ @generated by mypy-protobuf. Do not edit manually! isort:skip_file """ + import builtins import sys import typing @@ -88,7 +89,7 @@ POLICY_IGNORE: ExternalStatePolicy.ValueType # 1 POLICY_FAIL: ExternalStatePolicy.ValueType # 2 global___ExternalStatePolicy = ExternalStatePolicy -@typing_extensions.final +@typing.final class AutotuneOptions(google.protobuf.message.Message): """next: 5""" @@ -110,20 +111,20 @@ class AutotuneOptions(google.protobuf.message.Message): ram_budget: builtins.int | None = ..., autotune_algorithm: tensorflow.core.framework.model_pb2.AutotuneAlgorithm.ValueType | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["autotune_algorithm", b"autotune_algorithm", "cpu_budget", b"cpu_budget", "enabled", b"enabled", "optional_autotune_algorithm", b"optional_autotune_algorithm", "optional_cpu_budget", b"optional_cpu_budget", "optional_enabled", b"optional_enabled", "optional_ram_budget", b"optional_ram_budget", "ram_budget", b"ram_budget"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["autotune_algorithm", b"autotune_algorithm", "cpu_budget", b"cpu_budget", "enabled", b"enabled", "optional_autotune_algorithm", b"optional_autotune_algorithm", "optional_cpu_budget", b"optional_cpu_budget", "optional_enabled", b"optional_enabled", "optional_ram_budget", b"optional_ram_budget", "ram_budget", b"ram_budget"]) -> None: ... + def HasField(self, field_name: typing.Literal["autotune_algorithm", b"autotune_algorithm", "cpu_budget", b"cpu_budget", "enabled", b"enabled", "optional_autotune_algorithm", b"optional_autotune_algorithm", "optional_cpu_budget", b"optional_cpu_budget", "optional_enabled", b"optional_enabled", "optional_ram_budget", b"optional_ram_budget", "ram_budget", b"ram_budget"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["autotune_algorithm", b"autotune_algorithm", "cpu_budget", b"cpu_budget", "enabled", b"enabled", "optional_autotune_algorithm", b"optional_autotune_algorithm", "optional_cpu_budget", b"optional_cpu_budget", "optional_enabled", b"optional_enabled", "optional_ram_budget", b"optional_ram_budget", "ram_budget", b"ram_budget"]) -> None: ... @typing.overload - def WhichOneof(self, oneof_group: typing_extensions.Literal["optional_autotune_algorithm", b"optional_autotune_algorithm"]) -> typing_extensions.Literal["autotune_algorithm"] | None: ... + def WhichOneof(self, oneof_group: typing.Literal["optional_autotune_algorithm", b"optional_autotune_algorithm"]) -> typing.Literal["autotune_algorithm"] | None: ... @typing.overload - def WhichOneof(self, oneof_group: typing_extensions.Literal["optional_cpu_budget", b"optional_cpu_budget"]) -> typing_extensions.Literal["cpu_budget"] | None: ... + def WhichOneof(self, oneof_group: typing.Literal["optional_cpu_budget", b"optional_cpu_budget"]) -> typing.Literal["cpu_budget"] | None: ... @typing.overload - def WhichOneof(self, oneof_group: typing_extensions.Literal["optional_enabled", b"optional_enabled"]) -> typing_extensions.Literal["enabled"] | None: ... + def WhichOneof(self, oneof_group: typing.Literal["optional_enabled", b"optional_enabled"]) -> typing.Literal["enabled"] | None: ... @typing.overload - def WhichOneof(self, oneof_group: typing_extensions.Literal["optional_ram_budget", b"optional_ram_budget"]) -> typing_extensions.Literal["ram_budget"] | None: ... + def WhichOneof(self, oneof_group: typing.Literal["optional_ram_budget", b"optional_ram_budget"]) -> typing.Literal["ram_budget"] | None: ... global___AutotuneOptions = AutotuneOptions -@typing_extensions.final +@typing.final class CardinalityOptions(google.protobuf.message.Message): """next: 2""" @@ -169,11 +170,11 @@ class CardinalityOptions(google.protobuf.message.Message): *, compute_level: global___CardinalityOptions.ComputeLevel.ValueType | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["compute_level", b"compute_level"]) -> None: ... + def ClearField(self, field_name: typing.Literal["compute_level", b"compute_level"]) -> None: ... global___CardinalityOptions = CardinalityOptions -@typing_extensions.final +@typing.final class DistributeOptions(google.protobuf.message.Message): """next: 3""" @@ -189,13 +190,13 @@ class DistributeOptions(google.protobuf.message.Message): auto_shard_policy: global___AutoShardPolicy.ValueType | None = ..., num_devices: builtins.int | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["num_devices", b"num_devices", "optional_num_devices", b"optional_num_devices"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["auto_shard_policy", b"auto_shard_policy", "num_devices", b"num_devices", "optional_num_devices", b"optional_num_devices"]) -> None: ... - def WhichOneof(self, oneof_group: typing_extensions.Literal["optional_num_devices", b"optional_num_devices"]) -> typing_extensions.Literal["num_devices"] | None: ... + def HasField(self, field_name: typing.Literal["num_devices", b"num_devices", "optional_num_devices", b"optional_num_devices"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["auto_shard_policy", b"auto_shard_policy", "num_devices", b"num_devices", "optional_num_devices", b"optional_num_devices"]) -> None: ... + def WhichOneof(self, oneof_group: typing.Literal["optional_num_devices", b"optional_num_devices"]) -> typing.Literal["num_devices"] | None: ... global___DistributeOptions = DistributeOptions -@typing_extensions.final +@typing.final class OptimizationOptions(google.protobuf.message.Message): """next: 20""" @@ -238,34 +239,34 @@ class OptimizationOptions(google.protobuf.message.Message): filter_parallelization: builtins.bool | None = ..., inject_prefetch: builtins.bool | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["apply_default_optimizations", b"apply_default_optimizations", "filter_fusion", b"filter_fusion", "filter_parallelization", b"filter_parallelization", "inject_prefetch", b"inject_prefetch", "map_and_batch_fusion", b"map_and_batch_fusion", "map_and_filter_fusion", b"map_and_filter_fusion", "map_fusion", b"map_fusion", "map_parallelization", b"map_parallelization", "noop_elimination", b"noop_elimination", "optional_apply_default_optimizations", b"optional_apply_default_optimizations", "optional_filter_fusion", b"optional_filter_fusion", "optional_filter_parallelization", b"optional_filter_parallelization", "optional_inject_prefetch", b"optional_inject_prefetch", "optional_map_and_batch_fusion", b"optional_map_and_batch_fusion", "optional_map_and_filter_fusion", b"optional_map_and_filter_fusion", "optional_map_fusion", b"optional_map_fusion", "optional_map_parallelization", b"optional_map_parallelization", "optional_noop_elimination", b"optional_noop_elimination", "optional_parallel_batch", b"optional_parallel_batch", "optional_shuffle_and_repeat_fusion", b"optional_shuffle_and_repeat_fusion", "parallel_batch", b"parallel_batch", "shuffle_and_repeat_fusion", b"shuffle_and_repeat_fusion"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["apply_default_optimizations", b"apply_default_optimizations", "filter_fusion", b"filter_fusion", "filter_parallelization", b"filter_parallelization", "inject_prefetch", b"inject_prefetch", "map_and_batch_fusion", b"map_and_batch_fusion", "map_and_filter_fusion", b"map_and_filter_fusion", "map_fusion", b"map_fusion", "map_parallelization", b"map_parallelization", "noop_elimination", b"noop_elimination", "optional_apply_default_optimizations", b"optional_apply_default_optimizations", "optional_filter_fusion", b"optional_filter_fusion", "optional_filter_parallelization", b"optional_filter_parallelization", "optional_inject_prefetch", b"optional_inject_prefetch", "optional_map_and_batch_fusion", b"optional_map_and_batch_fusion", "optional_map_and_filter_fusion", b"optional_map_and_filter_fusion", "optional_map_fusion", b"optional_map_fusion", "optional_map_parallelization", b"optional_map_parallelization", "optional_noop_elimination", b"optional_noop_elimination", "optional_parallel_batch", b"optional_parallel_batch", "optional_shuffle_and_repeat_fusion", b"optional_shuffle_and_repeat_fusion", "parallel_batch", b"parallel_batch", "shuffle_and_repeat_fusion", b"shuffle_and_repeat_fusion"]) -> None: ... + def HasField(self, field_name: typing.Literal["apply_default_optimizations", b"apply_default_optimizations", "filter_fusion", b"filter_fusion", "filter_parallelization", b"filter_parallelization", "inject_prefetch", b"inject_prefetch", "map_and_batch_fusion", b"map_and_batch_fusion", "map_and_filter_fusion", b"map_and_filter_fusion", "map_fusion", b"map_fusion", "map_parallelization", b"map_parallelization", "noop_elimination", b"noop_elimination", "optional_apply_default_optimizations", b"optional_apply_default_optimizations", "optional_filter_fusion", b"optional_filter_fusion", "optional_filter_parallelization", b"optional_filter_parallelization", "optional_inject_prefetch", b"optional_inject_prefetch", "optional_map_and_batch_fusion", b"optional_map_and_batch_fusion", "optional_map_and_filter_fusion", b"optional_map_and_filter_fusion", "optional_map_fusion", b"optional_map_fusion", "optional_map_parallelization", b"optional_map_parallelization", "optional_noop_elimination", b"optional_noop_elimination", "optional_parallel_batch", b"optional_parallel_batch", "optional_shuffle_and_repeat_fusion", b"optional_shuffle_and_repeat_fusion", "parallel_batch", b"parallel_batch", "shuffle_and_repeat_fusion", b"shuffle_and_repeat_fusion"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["apply_default_optimizations", b"apply_default_optimizations", "filter_fusion", b"filter_fusion", "filter_parallelization", b"filter_parallelization", "inject_prefetch", b"inject_prefetch", "map_and_batch_fusion", b"map_and_batch_fusion", "map_and_filter_fusion", b"map_and_filter_fusion", "map_fusion", b"map_fusion", "map_parallelization", b"map_parallelization", "noop_elimination", b"noop_elimination", "optional_apply_default_optimizations", b"optional_apply_default_optimizations", "optional_filter_fusion", b"optional_filter_fusion", "optional_filter_parallelization", b"optional_filter_parallelization", "optional_inject_prefetch", b"optional_inject_prefetch", "optional_map_and_batch_fusion", b"optional_map_and_batch_fusion", "optional_map_and_filter_fusion", b"optional_map_and_filter_fusion", "optional_map_fusion", b"optional_map_fusion", "optional_map_parallelization", b"optional_map_parallelization", "optional_noop_elimination", b"optional_noop_elimination", "optional_parallel_batch", b"optional_parallel_batch", "optional_shuffle_and_repeat_fusion", b"optional_shuffle_and_repeat_fusion", "parallel_batch", b"parallel_batch", "shuffle_and_repeat_fusion", b"shuffle_and_repeat_fusion"]) -> None: ... @typing.overload - def WhichOneof(self, oneof_group: typing_extensions.Literal["optional_apply_default_optimizations", b"optional_apply_default_optimizations"]) -> typing_extensions.Literal["apply_default_optimizations"] | None: ... + def WhichOneof(self, oneof_group: typing.Literal["optional_apply_default_optimizations", b"optional_apply_default_optimizations"]) -> typing.Literal["apply_default_optimizations"] | None: ... @typing.overload - def WhichOneof(self, oneof_group: typing_extensions.Literal["optional_filter_fusion", b"optional_filter_fusion"]) -> typing_extensions.Literal["filter_fusion"] | None: ... + def WhichOneof(self, oneof_group: typing.Literal["optional_filter_fusion", b"optional_filter_fusion"]) -> typing.Literal["filter_fusion"] | None: ... @typing.overload - def WhichOneof(self, oneof_group: typing_extensions.Literal["optional_filter_parallelization", b"optional_filter_parallelization"]) -> typing_extensions.Literal["filter_parallelization"] | None: ... + def WhichOneof(self, oneof_group: typing.Literal["optional_filter_parallelization", b"optional_filter_parallelization"]) -> typing.Literal["filter_parallelization"] | None: ... @typing.overload - def WhichOneof(self, oneof_group: typing_extensions.Literal["optional_inject_prefetch", b"optional_inject_prefetch"]) -> typing_extensions.Literal["inject_prefetch"] | None: ... + def WhichOneof(self, oneof_group: typing.Literal["optional_inject_prefetch", b"optional_inject_prefetch"]) -> typing.Literal["inject_prefetch"] | None: ... @typing.overload - def WhichOneof(self, oneof_group: typing_extensions.Literal["optional_map_and_batch_fusion", b"optional_map_and_batch_fusion"]) -> typing_extensions.Literal["map_and_batch_fusion"] | None: ... + def WhichOneof(self, oneof_group: typing.Literal["optional_map_and_batch_fusion", b"optional_map_and_batch_fusion"]) -> typing.Literal["map_and_batch_fusion"] | None: ... @typing.overload - def WhichOneof(self, oneof_group: typing_extensions.Literal["optional_map_and_filter_fusion", b"optional_map_and_filter_fusion"]) -> typing_extensions.Literal["map_and_filter_fusion"] | None: ... + def WhichOneof(self, oneof_group: typing.Literal["optional_map_and_filter_fusion", b"optional_map_and_filter_fusion"]) -> typing.Literal["map_and_filter_fusion"] | None: ... @typing.overload - def WhichOneof(self, oneof_group: typing_extensions.Literal["optional_map_fusion", b"optional_map_fusion"]) -> typing_extensions.Literal["map_fusion"] | None: ... + def WhichOneof(self, oneof_group: typing.Literal["optional_map_fusion", b"optional_map_fusion"]) -> typing.Literal["map_fusion"] | None: ... @typing.overload - def WhichOneof(self, oneof_group: typing_extensions.Literal["optional_map_parallelization", b"optional_map_parallelization"]) -> typing_extensions.Literal["map_parallelization"] | None: ... + def WhichOneof(self, oneof_group: typing.Literal["optional_map_parallelization", b"optional_map_parallelization"]) -> typing.Literal["map_parallelization"] | None: ... @typing.overload - def WhichOneof(self, oneof_group: typing_extensions.Literal["optional_noop_elimination", b"optional_noop_elimination"]) -> typing_extensions.Literal["noop_elimination"] | None: ... + def WhichOneof(self, oneof_group: typing.Literal["optional_noop_elimination", b"optional_noop_elimination"]) -> typing.Literal["noop_elimination"] | None: ... @typing.overload - def WhichOneof(self, oneof_group: typing_extensions.Literal["optional_parallel_batch", b"optional_parallel_batch"]) -> typing_extensions.Literal["parallel_batch"] | None: ... + def WhichOneof(self, oneof_group: typing.Literal["optional_parallel_batch", b"optional_parallel_batch"]) -> typing.Literal["parallel_batch"] | None: ... @typing.overload - def WhichOneof(self, oneof_group: typing_extensions.Literal["optional_shuffle_and_repeat_fusion", b"optional_shuffle_and_repeat_fusion"]) -> typing_extensions.Literal["shuffle_and_repeat_fusion"] | None: ... + def WhichOneof(self, oneof_group: typing.Literal["optional_shuffle_and_repeat_fusion", b"optional_shuffle_and_repeat_fusion"]) -> typing.Literal["shuffle_and_repeat_fusion"] | None: ... global___OptimizationOptions = OptimizationOptions -@typing_extensions.final +@typing.final class ThreadingOptions(google.protobuf.message.Message): """next: 3""" @@ -281,16 +282,16 @@ class ThreadingOptions(google.protobuf.message.Message): max_intra_op_parallelism: builtins.int | None = ..., private_threadpool_size: builtins.int | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["max_intra_op_parallelism", b"max_intra_op_parallelism", "optional_max_intra_op_parallelism", b"optional_max_intra_op_parallelism", "optional_private_threadpool_size", b"optional_private_threadpool_size", "private_threadpool_size", b"private_threadpool_size"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["max_intra_op_parallelism", b"max_intra_op_parallelism", "optional_max_intra_op_parallelism", b"optional_max_intra_op_parallelism", "optional_private_threadpool_size", b"optional_private_threadpool_size", "private_threadpool_size", b"private_threadpool_size"]) -> None: ... + def HasField(self, field_name: typing.Literal["max_intra_op_parallelism", b"max_intra_op_parallelism", "optional_max_intra_op_parallelism", b"optional_max_intra_op_parallelism", "optional_private_threadpool_size", b"optional_private_threadpool_size", "private_threadpool_size", b"private_threadpool_size"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["max_intra_op_parallelism", b"max_intra_op_parallelism", "optional_max_intra_op_parallelism", b"optional_max_intra_op_parallelism", "optional_private_threadpool_size", b"optional_private_threadpool_size", "private_threadpool_size", b"private_threadpool_size"]) -> None: ... @typing.overload - def WhichOneof(self, oneof_group: typing_extensions.Literal["optional_max_intra_op_parallelism", b"optional_max_intra_op_parallelism"]) -> typing_extensions.Literal["max_intra_op_parallelism"] | None: ... + def WhichOneof(self, oneof_group: typing.Literal["optional_max_intra_op_parallelism", b"optional_max_intra_op_parallelism"]) -> typing.Literal["max_intra_op_parallelism"] | None: ... @typing.overload - def WhichOneof(self, oneof_group: typing_extensions.Literal["optional_private_threadpool_size", b"optional_private_threadpool_size"]) -> typing_extensions.Literal["private_threadpool_size"] | None: ... + def WhichOneof(self, oneof_group: typing.Literal["optional_private_threadpool_size", b"optional_private_threadpool_size"]) -> typing.Literal["private_threadpool_size"] | None: ... global___ThreadingOptions = ThreadingOptions -@typing_extensions.final +@typing.final class Options(google.protobuf.message.Message): """Message stored with Dataset objects to control how datasets are processed and optimized. @@ -309,21 +310,25 @@ class Options(google.protobuf.message.Message): EXTERNAL_STATE_POLICY_FIELD_NUMBER: builtins.int SYMBOLIC_CHECKPOINT_FIELD_NUMBER: builtins.int deterministic: builtins.bool + slack: builtins.bool + external_state_policy: global___ExternalStatePolicy.ValueType + symbolic_checkpoint: builtins.bool @property def autotune_options(self) -> global___AutotuneOptions: """The distribution strategy options associated with the dataset.""" + @property def distribute_options(self) -> global___DistributeOptions: """The distribution strategy options associated with the dataset.""" + @property def optimization_options(self) -> global___OptimizationOptions: """The optimization options associated with the dataset.""" - slack: builtins.bool + @property def threading_options(self) -> global___ThreadingOptions: """The threading options associated with the dataset.""" - external_state_policy: global___ExternalStatePolicy.ValueType - symbolic_checkpoint: builtins.bool + def __init__( self, *, @@ -336,15 +341,15 @@ class Options(google.protobuf.message.Message): external_state_policy: global___ExternalStatePolicy.ValueType | None = ..., symbolic_checkpoint: builtins.bool | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["autotune_options", b"autotune_options", "deterministic", b"deterministic", "distribute_options", b"distribute_options", "external_state_policy", b"external_state_policy", "optimization_options", b"optimization_options", "optional_deterministic", b"optional_deterministic", "optional_external_state_policy", b"optional_external_state_policy", "optional_slack", b"optional_slack", "optional_symbolic_checkpoint", b"optional_symbolic_checkpoint", "slack", b"slack", "symbolic_checkpoint", b"symbolic_checkpoint", "threading_options", b"threading_options"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["autotune_options", b"autotune_options", "deterministic", b"deterministic", "distribute_options", b"distribute_options", "external_state_policy", b"external_state_policy", "optimization_options", b"optimization_options", "optional_deterministic", b"optional_deterministic", "optional_external_state_policy", b"optional_external_state_policy", "optional_slack", b"optional_slack", "optional_symbolic_checkpoint", b"optional_symbolic_checkpoint", "slack", b"slack", "symbolic_checkpoint", b"symbolic_checkpoint", "threading_options", b"threading_options"]) -> None: ... + def HasField(self, field_name: typing.Literal["autotune_options", b"autotune_options", "deterministic", b"deterministic", "distribute_options", b"distribute_options", "external_state_policy", b"external_state_policy", "optimization_options", b"optimization_options", "optional_deterministic", b"optional_deterministic", "optional_external_state_policy", b"optional_external_state_policy", "optional_slack", b"optional_slack", "optional_symbolic_checkpoint", b"optional_symbolic_checkpoint", "slack", b"slack", "symbolic_checkpoint", b"symbolic_checkpoint", "threading_options", b"threading_options"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["autotune_options", b"autotune_options", "deterministic", b"deterministic", "distribute_options", b"distribute_options", "external_state_policy", b"external_state_policy", "optimization_options", b"optimization_options", "optional_deterministic", b"optional_deterministic", "optional_external_state_policy", b"optional_external_state_policy", "optional_slack", b"optional_slack", "optional_symbolic_checkpoint", b"optional_symbolic_checkpoint", "slack", b"slack", "symbolic_checkpoint", b"symbolic_checkpoint", "threading_options", b"threading_options"]) -> None: ... @typing.overload - def WhichOneof(self, oneof_group: typing_extensions.Literal["optional_deterministic", b"optional_deterministic"]) -> typing_extensions.Literal["deterministic"] | None: ... + def WhichOneof(self, oneof_group: typing.Literal["optional_deterministic", b"optional_deterministic"]) -> typing.Literal["deterministic"] | None: ... @typing.overload - def WhichOneof(self, oneof_group: typing_extensions.Literal["optional_external_state_policy", b"optional_external_state_policy"]) -> typing_extensions.Literal["external_state_policy"] | None: ... + def WhichOneof(self, oneof_group: typing.Literal["optional_external_state_policy", b"optional_external_state_policy"]) -> typing.Literal["external_state_policy"] | None: ... @typing.overload - def WhichOneof(self, oneof_group: typing_extensions.Literal["optional_slack", b"optional_slack"]) -> typing_extensions.Literal["slack"] | None: ... + def WhichOneof(self, oneof_group: typing.Literal["optional_slack", b"optional_slack"]) -> typing.Literal["slack"] | None: ... @typing.overload - def WhichOneof(self, oneof_group: typing_extensions.Literal["optional_symbolic_checkpoint", b"optional_symbolic_checkpoint"]) -> typing_extensions.Literal["symbolic_checkpoint"] | None: ... + def WhichOneof(self, oneof_group: typing.Literal["optional_symbolic_checkpoint", b"optional_symbolic_checkpoint"]) -> typing.Literal["symbolic_checkpoint"] | None: ... global___Options = Options diff --git a/stubs/tensorflow/tensorflow/core/framework/dataset_pb2.pyi b/stubs/tensorflow/tensorflow/core/framework/dataset_pb2.pyi index 993b0a25c984..72392b2b7698 100644 --- a/stubs/tensorflow/tensorflow/core/framework/dataset_pb2.pyi +++ b/stubs/tensorflow/tensorflow/core/framework/dataset_pb2.pyi @@ -2,9 +2,10 @@ @generated by mypy-protobuf. Do not edit manually! isort:skip_file """ + import builtins import collections.abc -import typing as typing_extensions +import typing import google.protobuf.descriptor import google.protobuf.internal.containers @@ -15,7 +16,7 @@ import tensorflow.core.framework.types_pb2 DESCRIPTOR: google.protobuf.descriptor.FileDescriptor -@typing_extensions.final +@typing.final class CompressedComponentMetadata(google.protobuf.message.Message): """This file contains protocol buffers for working with tf.data Datasets. @@ -32,6 +33,7 @@ class CompressedComponentMetadata(google.protobuf.message.Message): @property def tensor_shape(self) -> tensorflow.core.framework.tensor_shape_pb2.TensorShapeProto: """The shape of the component tensor.""" + @property def uncompressed_bytes(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.int]: """The amount of uncompressed tensor data. @@ -40,6 +42,7 @@ class CompressedComponentMetadata(google.protobuf.message.Message): - For all other tensors, there is a single element indicating the size of the tensor. """ + def __init__( self, *, @@ -47,12 +50,12 @@ class CompressedComponentMetadata(google.protobuf.message.Message): tensor_shape: tensorflow.core.framework.tensor_shape_pb2.TensorShapeProto | None = ..., uncompressed_bytes: collections.abc.Iterable[builtins.int] | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["tensor_shape", b"tensor_shape"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["dtype", b"dtype", "tensor_shape", b"tensor_shape", "uncompressed_bytes", b"uncompressed_bytes"]) -> None: ... + def HasField(self, field_name: typing.Literal["tensor_shape", b"tensor_shape"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["dtype", b"dtype", "tensor_shape", b"tensor_shape", "uncompressed_bytes", b"uncompressed_bytes"]) -> None: ... global___CompressedComponentMetadata = CompressedComponentMetadata -@typing_extensions.final +@typing.final class CompressedElement(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -61,9 +64,6 @@ class CompressedElement(google.protobuf.message.Message): VERSION_FIELD_NUMBER: builtins.int data: builtins.bytes """Compressed tensor bytes for all components of the element.""" - @property - def component_metadata(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___CompressedComponentMetadata]: - """Metadata for the components of the element.""" version: builtins.int """Version of the CompressedElement. CompressedElements may be stored on disk and read back by later versions of code, so we store a version number to @@ -71,6 +71,10 @@ class CompressedElement(google.protobuf.message.Message): field to this proto, you need to increment kCompressedElementVersion in tensorflow/core/data/compression_utils.cc. """ + @property + def component_metadata(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___CompressedComponentMetadata]: + """Metadata for the components of the element.""" + def __init__( self, *, @@ -78,11 +82,11 @@ class CompressedElement(google.protobuf.message.Message): component_metadata: collections.abc.Iterable[global___CompressedComponentMetadata] | None = ..., version: builtins.int | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["component_metadata", b"component_metadata", "data", b"data", "version", b"version"]) -> None: ... + def ClearField(self, field_name: typing.Literal["component_metadata", b"component_metadata", "data", b"data", "version", b"version"]) -> None: ... global___CompressedElement = CompressedElement -@typing_extensions.final +@typing.final class UncompressedElement(google.protobuf.message.Message): """An uncompressed dataset element.""" @@ -96,6 +100,6 @@ class UncompressedElement(google.protobuf.message.Message): *, components: collections.abc.Iterable[tensorflow.core.framework.tensor_pb2.TensorProto] | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["components", b"components"]) -> None: ... + def ClearField(self, field_name: typing.Literal["components", b"components"]) -> None: ... global___UncompressedElement = UncompressedElement diff --git a/stubs/tensorflow/tensorflow/core/framework/device_attributes_pb2.pyi b/stubs/tensorflow/tensorflow/core/framework/device_attributes_pb2.pyi index 0c9279720f8c..aafdc2c8a51e 100644 --- a/stubs/tensorflow/tensorflow/core/framework/device_attributes_pb2.pyi +++ b/stubs/tensorflow/tensorflow/core/framework/device_attributes_pb2.pyi @@ -2,9 +2,10 @@ @generated by mypy-protobuf. Do not edit manually! isort:skip_file """ + import builtins import collections.abc -import typing as typing_extensions +import typing import google.protobuf.descriptor import google.protobuf.internal.containers @@ -12,7 +13,7 @@ import google.protobuf.message DESCRIPTOR: google.protobuf.descriptor.FileDescriptor -@typing_extensions.final +@typing.final class InterconnectLink(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -29,11 +30,11 @@ class InterconnectLink(google.protobuf.message.Message): type: builtins.str | None = ..., strength: builtins.int | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["device_id", b"device_id", "strength", b"strength", "type", b"type"]) -> None: ... + def ClearField(self, field_name: typing.Literal["device_id", b"device_id", "strength", b"strength", "type", b"type"]) -> None: ... global___InterconnectLink = InterconnectLink -@typing_extensions.final +@typing.final class LocalLinks(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -45,11 +46,11 @@ class LocalLinks(google.protobuf.message.Message): *, link: collections.abc.Iterable[global___InterconnectLink] | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["link", b"link"]) -> None: ... + def ClearField(self, field_name: typing.Literal["link", b"link"]) -> None: ... global___LocalLinks = LocalLinks -@typing_extensions.final +@typing.final class DeviceLocality(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -65,6 +66,7 @@ class DeviceLocality(google.protobuf.message.Message): @property def links(self) -> global___LocalLinks: """Optional local interconnect links to other devices.""" + def __init__( self, *, @@ -72,12 +74,12 @@ class DeviceLocality(google.protobuf.message.Message): numa_node: builtins.int | None = ..., links: global___LocalLinks | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["links", b"links"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["bus_id", b"bus_id", "links", b"links", "numa_node", b"numa_node"]) -> None: ... + def HasField(self, field_name: typing.Literal["links", b"links"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["bus_id", b"bus_id", "links", b"links", "numa_node", b"numa_node"]) -> None: ... global___DeviceLocality = DeviceLocality -@typing_extensions.final +@typing.final class DeviceAttributes(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -94,11 +96,6 @@ class DeviceAttributes(google.protobuf.message.Message): """String representation of device_type.""" memory_limit: builtins.int """Memory capacity of device in bytes.""" - @property - def locality(self) -> global___DeviceLocality: - """Platform-specific data about device that may be useful - for supporting efficient data transfers. - """ incarnation: builtins.int """A device is assigned a global unique number each time it is initialized. "incarnation" should never be 0. @@ -110,6 +107,12 @@ class DeviceAttributes(google.protobuf.message.Message): clients in a multi-client setup. Set to -1 if unavailable, non-negative otherwise. """ + @property + def locality(self) -> global___DeviceLocality: + """Platform-specific data about device that may be useful + for supporting efficient data transfers. + """ + def __init__( self, *, @@ -121,7 +124,7 @@ class DeviceAttributes(google.protobuf.message.Message): physical_device_desc: builtins.str | None = ..., xla_global_id: builtins.int | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["locality", b"locality"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["device_type", b"device_type", "incarnation", b"incarnation", "locality", b"locality", "memory_limit", b"memory_limit", "name", b"name", "physical_device_desc", b"physical_device_desc", "xla_global_id", b"xla_global_id"]) -> None: ... + def HasField(self, field_name: typing.Literal["locality", b"locality"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["device_type", b"device_type", "incarnation", b"incarnation", "locality", b"locality", "memory_limit", b"memory_limit", "name", b"name", "physical_device_desc", b"physical_device_desc", "xla_global_id", b"xla_global_id"]) -> None: ... global___DeviceAttributes = DeviceAttributes diff --git a/stubs/tensorflow/tensorflow/core/framework/full_type_pb2.pyi b/stubs/tensorflow/tensorflow/core/framework/full_type_pb2.pyi index 0c5e1e9d955a..e37ac0ff0495 100644 --- a/stubs/tensorflow/tensorflow/core/framework/full_type_pb2.pyi +++ b/stubs/tensorflow/tensorflow/core/framework/full_type_pb2.pyi @@ -2,6 +2,7 @@ @generated by mypy-protobuf. Do not edit manually! isort:skip_file """ + import builtins import collections.abc import sys @@ -573,7 +574,7 @@ not a subtype of LEGACY_VARIANT. """ global___FullTypeId = FullTypeId -@typing_extensions.final +@typing.final class FullTypeDef(google.protobuf.message.Message): """Highly experimental and very likely to change. This encoding uses tags instead of dedicated messages for regularity. In @@ -592,11 +593,11 @@ class FullTypeDef(google.protobuf.message.Message): (Tensor, Dataset) a type variable (used for dependent types) a type symbol (Any, Union). See FullTypeId for details. """ - @property - def args(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___FullTypeDef]: ... s: builtins.str i: builtins.int """TODO(mdan): list/tensor, map? Need to reconcile with TFT_RECORD, etc.""" + @property + def args(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___FullTypeDef]: ... def __init__( self, *, @@ -605,8 +606,8 @@ class FullTypeDef(google.protobuf.message.Message): s: builtins.str | None = ..., i: builtins.int | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["attr", b"attr", "i", b"i", "s", b"s"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["args", b"args", "attr", b"attr", "i", b"i", "s", b"s", "type_id", b"type_id"]) -> None: ... - def WhichOneof(self, oneof_group: typing_extensions.Literal["attr", b"attr"]) -> typing_extensions.Literal["s", "i"] | None: ... + def HasField(self, field_name: typing.Literal["attr", b"attr", "i", b"i", "s", b"s"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["args", b"args", "attr", b"attr", "i", b"i", "s", b"s", "type_id", b"type_id"]) -> None: ... + def WhichOneof(self, oneof_group: typing.Literal["attr", b"attr"]) -> typing.Literal["s", "i"] | None: ... global___FullTypeDef = FullTypeDef diff --git a/stubs/tensorflow/tensorflow/core/framework/function_pb2.pyi b/stubs/tensorflow/tensorflow/core/framework/function_pb2.pyi index a4f7ee17cc4c..c0908173a958 100644 --- a/stubs/tensorflow/tensorflow/core/framework/function_pb2.pyi +++ b/stubs/tensorflow/tensorflow/core/framework/function_pb2.pyi @@ -2,9 +2,10 @@ @generated by mypy-protobuf. Do not edit manually! isort:skip_file """ + import builtins import collections.abc -import typing as typing_extensions +import typing import google.protobuf.descriptor import google.protobuf.internal.containers @@ -15,7 +16,7 @@ import tensorflow.core.framework.op_def_pb2 DESCRIPTOR: google.protobuf.descriptor.FileDescriptor -@typing_extensions.final +@typing.final class FunctionDefLibrary(google.protobuf.message.Message): """A library is a set of named functions.""" @@ -37,11 +38,11 @@ class FunctionDefLibrary(google.protobuf.message.Message): gradient: collections.abc.Iterable[global___GradientDef] | None = ..., registered_gradients: collections.abc.Iterable[global___RegisteredGradient] | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["function", b"function", "gradient", b"gradient", "registered_gradients", b"registered_gradients"]) -> None: ... + def ClearField(self, field_name: typing.Literal["function", b"function", "gradient", b"gradient", "registered_gradients", b"registered_gradients"]) -> None: ... global___FunctionDefLibrary = FunctionDefLibrary -@typing_extensions.final +@typing.final class FunctionDef(google.protobuf.message.Message): """A function can be instantiated when the runtime can bind every attr with a value. When a GraphDef has a call to a function, it must @@ -53,7 +54,7 @@ class FunctionDef(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor - @typing_extensions.final + @typing.final class AttrEntry(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -68,10 +69,10 @@ class FunctionDef(google.protobuf.message.Message): key: builtins.str | None = ..., value: tensorflow.core.framework.attr_value_pb2.AttrValue | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["value", b"value"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["key", b"key", "value", b"value"]) -> None: ... + def HasField(self, field_name: typing.Literal["value", b"value"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["key", b"key", "value", b"value"]) -> None: ... - @typing_extensions.final + @typing.final class ArgAttrs(google.protobuf.message.Message): """Attributes for function arguments. These attributes are the same set of valid attributes as to _Arg nodes. @@ -79,7 +80,7 @@ class FunctionDef(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor - @typing_extensions.final + @typing.final class AttrEntry(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -94,8 +95,8 @@ class FunctionDef(google.protobuf.message.Message): key: builtins.str | None = ..., value: tensorflow.core.framework.attr_value_pb2.AttrValue | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["value", b"value"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["key", b"key", "value", b"value"]) -> None: ... + def HasField(self, field_name: typing.Literal["value", b"value"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["key", b"key", "value", b"value"]) -> None: ... ATTR_FIELD_NUMBER: builtins.int @property @@ -105,9 +106,9 @@ class FunctionDef(google.protobuf.message.Message): *, attr: collections.abc.Mapping[builtins.str, tensorflow.core.framework.attr_value_pb2.AttrValue] | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["attr", b"attr"]) -> None: ... + def ClearField(self, field_name: typing.Literal["attr", b"attr"]) -> None: ... - @typing_extensions.final + @typing.final class ArgAttrEntry(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -122,10 +123,10 @@ class FunctionDef(google.protobuf.message.Message): key: builtins.int | None = ..., value: global___FunctionDef.ArgAttrs | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["value", b"value"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["key", b"key", "value", b"value"]) -> None: ... + def HasField(self, field_name: typing.Literal["value", b"value"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["key", b"key", "value", b"value"]) -> None: ... - @typing_extensions.final + @typing.final class ResourceArgUniqueIdEntry(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -139,9 +140,9 @@ class FunctionDef(google.protobuf.message.Message): key: builtins.int | None = ..., value: builtins.int | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["key", b"key", "value", b"value"]) -> None: ... + def ClearField(self, field_name: typing.Literal["key", b"key", "value", b"value"]) -> None: ... - @typing_extensions.final + @typing.final class RetEntry(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -155,9 +156,9 @@ class FunctionDef(google.protobuf.message.Message): key: builtins.str | None = ..., value: builtins.str | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["key", b"key", "value", b"value"]) -> None: ... + def ClearField(self, field_name: typing.Literal["key", b"key", "value", b"value"]) -> None: ... - @typing_extensions.final + @typing.final class ControlRetEntry(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -171,7 +172,7 @@ class FunctionDef(google.protobuf.message.Message): key: builtins.str | None = ..., value: builtins.str | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["key", b"key", "value", b"value"]) -> None: ... + def ClearField(self, field_name: typing.Literal["key", b"key", "value", b"value"]) -> None: ... SIGNATURE_FIELD_NUMBER: builtins.int ATTR_FIELD_NUMBER: builtins.int @@ -185,9 +186,11 @@ class FunctionDef(google.protobuf.message.Message): """The definition of the function's name, arguments, return values, attrs etc. """ + @property def attr(self) -> google.protobuf.internal.containers.MessageMap[builtins.str, tensorflow.core.framework.attr_value_pb2.AttrValue]: """Attributes specific to this function definition.""" + @property def arg_attr(self) -> google.protobuf.internal.containers.MessageMap[builtins.int, global___FunctionDef.ArgAttrs]: ... @property @@ -202,6 +205,7 @@ class FunctionDef(google.protobuf.message.Message): When instantiated, the unique IDs will be attached to the _Arg nodes' "_resource_arg_unique_id" attribute. """ + @property def node_def(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[tensorflow.core.framework.node_def_pb2.NodeDef]: """The body of the function. Unlike the NodeDefs in a GraphDef, attrs @@ -212,16 +216,19 @@ class FunctionDef(google.protobuf.message.Message): user-defined library first. If not resolved, "func" is assumed to be a builtin op. """ + @property def ret(self) -> google.protobuf.internal.containers.ScalarMap[builtins.str, builtins.str]: """A mapping from the output arg names from `signature` to the outputs from `node_def` that should be returned by the function. """ + @property def control_ret(self) -> google.protobuf.internal.containers.ScalarMap[builtins.str, builtins.str]: """A mapping from control output names from `signature` to node names in `node_def` which should be control outputs of this function. """ + def __init__( self, *, @@ -233,12 +240,12 @@ class FunctionDef(google.protobuf.message.Message): ret: collections.abc.Mapping[builtins.str, builtins.str] | None = ..., control_ret: collections.abc.Mapping[builtins.str, builtins.str] | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["signature", b"signature"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["arg_attr", b"arg_attr", "attr", b"attr", "control_ret", b"control_ret", "node_def", b"node_def", "resource_arg_unique_id", b"resource_arg_unique_id", "ret", b"ret", "signature", b"signature"]) -> None: ... + def HasField(self, field_name: typing.Literal["signature", b"signature"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["arg_attr", b"arg_attr", "attr", b"attr", "control_ret", b"control_ret", "node_def", b"node_def", "resource_arg_unique_id", b"resource_arg_unique_id", "ret", b"ret", "signature", b"signature"]) -> None: ... global___FunctionDef = FunctionDef -@typing_extensions.final +@typing.final class GradientDef(google.protobuf.message.Message): """GradientDef defines the gradient function of a function defined in a function library. @@ -274,11 +281,11 @@ class GradientDef(google.protobuf.message.Message): function_name: builtins.str | None = ..., gradient_func: builtins.str | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["function_name", b"function_name", "gradient_func", b"gradient_func"]) -> None: ... + def ClearField(self, field_name: typing.Literal["function_name", b"function_name", "gradient_func", b"gradient_func"]) -> None: ... global___GradientDef = GradientDef -@typing_extensions.final +@typing.final class RegisteredGradient(google.protobuf.message.Message): """RegisteredGradient stores a gradient function that is registered in the gradients library and used in the ops of a function in the function library. @@ -300,6 +307,6 @@ class RegisteredGradient(google.protobuf.message.Message): gradient_func: builtins.str | None = ..., registered_op_type: builtins.str | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["gradient_func", b"gradient_func", "registered_op_type", b"registered_op_type"]) -> None: ... + def ClearField(self, field_name: typing.Literal["gradient_func", b"gradient_func", "registered_op_type", b"registered_op_type"]) -> None: ... global___RegisteredGradient = RegisteredGradient diff --git a/stubs/tensorflow/tensorflow/core/framework/graph_pb2.pyi b/stubs/tensorflow/tensorflow/core/framework/graph_pb2.pyi index bc5acf98eb04..b0e5b81e4123 100644 --- a/stubs/tensorflow/tensorflow/core/framework/graph_pb2.pyi +++ b/stubs/tensorflow/tensorflow/core/framework/graph_pb2.pyi @@ -2,9 +2,10 @@ @generated by mypy-protobuf. Do not edit manually! isort:skip_file """ + import builtins import collections.abc -import typing as typing_extensions +import typing import google.protobuf.descriptor import google.protobuf.internal.containers @@ -15,7 +16,7 @@ import tensorflow.core.framework.versions_pb2 DESCRIPTOR: google.protobuf.descriptor.FileDescriptor -@typing_extensions.final +@typing.final class GraphDef(google.protobuf.message.Message): """Represents the graph of operations""" @@ -25,6 +26,11 @@ class GraphDef(google.protobuf.message.Message): VERSIONS_FIELD_NUMBER: builtins.int VERSION_FIELD_NUMBER: builtins.int LIBRARY_FIELD_NUMBER: builtins.int + version: builtins.int + """Deprecated single version field; use versions above instead. Since all + GraphDef changes before "versions" was introduced were forward + compatible, this field is entirely ignored. + """ @property def node(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[tensorflow.core.framework.node_def_pb2.NodeDef]: ... @property @@ -33,11 +39,7 @@ class GraphDef(google.protobuf.message.Message): history. The GraphDef version is distinct from the TensorFlow version, and each release of TensorFlow will support a range of GraphDef versions. """ - version: builtins.int - """Deprecated single version field; use versions above instead. Since all - GraphDef changes before "versions" was introduced were forward - compatible, this field is entirely ignored. - """ + @property def library(self) -> tensorflow.core.framework.function_pb2.FunctionDefLibrary: """"library" provides user-defined functions. @@ -67,6 +69,7 @@ class GraphDef(google.protobuf.message.Message): consumer does not start until all return values of the callee function are ready. """ + def __init__( self, *, @@ -75,7 +78,7 @@ class GraphDef(google.protobuf.message.Message): version: builtins.int | None = ..., library: tensorflow.core.framework.function_pb2.FunctionDefLibrary | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["library", b"library", "versions", b"versions"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["library", b"library", "node", b"node", "version", b"version", "versions", b"versions"]) -> None: ... + def HasField(self, field_name: typing.Literal["library", b"library", "versions", b"versions"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["library", b"library", "node", b"node", "version", b"version", "versions", b"versions"]) -> None: ... global___GraphDef = GraphDef diff --git a/stubs/tensorflow/tensorflow/core/framework/graph_transfer_info_pb2.pyi b/stubs/tensorflow/tensorflow/core/framework/graph_transfer_info_pb2.pyi index 88b587cf2434..ab4dd51228cd 100644 --- a/stubs/tensorflow/tensorflow/core/framework/graph_transfer_info_pb2.pyi +++ b/stubs/tensorflow/tensorflow/core/framework/graph_transfer_info_pb2.pyi @@ -2,6 +2,7 @@ @generated by mypy-protobuf. Do not edit manually! isort:skip_file """ + import builtins import collections.abc import sys @@ -20,7 +21,7 @@ else: DESCRIPTOR: google.protobuf.descriptor.FileDescriptor -@typing_extensions.final +@typing.final class GraphTransferNodeInput(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -34,11 +35,11 @@ class GraphTransferNodeInput(google.protobuf.message.Message): node_id: builtins.int | None = ..., output_port: builtins.int | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["node_id", b"node_id", "output_port", b"output_port"]) -> None: ... + def ClearField(self, field_name: typing.Literal["node_id", b"node_id", "output_port", b"output_port"]) -> None: ... global___GraphTransferNodeInput = GraphTransferNodeInput -@typing_extensions.final +@typing.final class GraphTransferNodeInfo(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -67,11 +68,11 @@ class GraphTransferNodeInfo(google.protobuf.message.Message): input_count: builtins.int | None = ..., output_count: builtins.int | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["input_count", b"input_count", "name", b"name", "node_id", b"node_id", "output_count", b"output_count", "padding_id", b"padding_id", "soc_op_id", b"soc_op_id", "type_name", b"type_name"]) -> None: ... + def ClearField(self, field_name: typing.Literal["input_count", b"input_count", "name", b"name", "node_id", b"node_id", "output_count", b"output_count", "padding_id", b"padding_id", "soc_op_id", b"soc_op_id", "type_name", b"type_name"]) -> None: ... global___GraphTransferNodeInfo = GraphTransferNodeInfo -@typing_extensions.final +@typing.final class GraphTransferConstNodeInfo(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -82,10 +83,10 @@ class GraphTransferConstNodeInfo(google.protobuf.message.Message): DTYPE_FIELD_NUMBER: builtins.int name: builtins.str node_id: builtins.int - @property - def shape(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.int]: ... data: builtins.bytes dtype: tensorflow.core.framework.types_pb2.DataType.ValueType + @property + def shape(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.int]: ... def __init__( self, *, @@ -95,11 +96,11 @@ class GraphTransferConstNodeInfo(google.protobuf.message.Message): data: builtins.bytes | None = ..., dtype: tensorflow.core.framework.types_pb2.DataType.ValueType | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["data", b"data", "dtype", b"dtype", "name", b"name", "node_id", b"node_id", "shape", b"shape"]) -> None: ... + def ClearField(self, field_name: typing.Literal["data", b"data", "dtype", b"dtype", "name", b"name", "node_id", b"node_id", "shape", b"shape"]) -> None: ... global___GraphTransferConstNodeInfo = GraphTransferConstNodeInfo -@typing_extensions.final +@typing.final class GraphTransferNodeInputInfo(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -114,11 +115,11 @@ class GraphTransferNodeInputInfo(google.protobuf.message.Message): node_id: builtins.int | None = ..., node_input: collections.abc.Iterable[global___GraphTransferNodeInput] | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["node_id", b"node_id", "node_input", b"node_input"]) -> None: ... + def ClearField(self, field_name: typing.Literal["node_id", b"node_id", "node_input", b"node_input"]) -> None: ... global___GraphTransferNodeInputInfo = GraphTransferNodeInputInfo -@typing_extensions.final +@typing.final class GraphTransferNodeOutputInfo(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -133,11 +134,11 @@ class GraphTransferNodeOutputInfo(google.protobuf.message.Message): node_id: builtins.int | None = ..., max_byte_size: collections.abc.Iterable[builtins.int] | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["max_byte_size", b"max_byte_size", "node_id", b"node_id"]) -> None: ... + def ClearField(self, field_name: typing.Literal["max_byte_size", b"max_byte_size", "node_id", b"node_id"]) -> None: ... global___GraphTransferNodeOutputInfo = GraphTransferNodeOutputInfo -@typing_extensions.final +@typing.final class GraphTransferGraphInputNodeInfo(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -145,9 +146,9 @@ class GraphTransferGraphInputNodeInfo(google.protobuf.message.Message): SHAPE_FIELD_NUMBER: builtins.int DTYPE_FIELD_NUMBER: builtins.int name: builtins.str + dtype: tensorflow.core.framework.types_pb2.DataType.ValueType @property def shape(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.int]: ... - dtype: tensorflow.core.framework.types_pb2.DataType.ValueType def __init__( self, *, @@ -155,11 +156,11 @@ class GraphTransferGraphInputNodeInfo(google.protobuf.message.Message): shape: collections.abc.Iterable[builtins.int] | None = ..., dtype: tensorflow.core.framework.types_pb2.DataType.ValueType | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["dtype", b"dtype", "name", b"name", "shape", b"shape"]) -> None: ... + def ClearField(self, field_name: typing.Literal["dtype", b"dtype", "name", b"name", "shape", b"shape"]) -> None: ... global___GraphTransferGraphInputNodeInfo = GraphTransferGraphInputNodeInfo -@typing_extensions.final +@typing.final class GraphTransferGraphOutputNodeInfo(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -167,9 +168,9 @@ class GraphTransferGraphOutputNodeInfo(google.protobuf.message.Message): SHAPE_FIELD_NUMBER: builtins.int DTYPE_FIELD_NUMBER: builtins.int name: builtins.str + dtype: tensorflow.core.framework.types_pb2.DataType.ValueType @property def shape(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.int]: ... - dtype: tensorflow.core.framework.types_pb2.DataType.ValueType def __init__( self, *, @@ -177,11 +178,11 @@ class GraphTransferGraphOutputNodeInfo(google.protobuf.message.Message): shape: collections.abc.Iterable[builtins.int] | None = ..., dtype: tensorflow.core.framework.types_pb2.DataType.ValueType | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["dtype", b"dtype", "name", b"name", "shape", b"shape"]) -> None: ... + def ClearField(self, field_name: typing.Literal["dtype", b"dtype", "name", b"name", "shape", b"shape"]) -> None: ... global___GraphTransferGraphOutputNodeInfo = GraphTransferGraphOutputNodeInfo -@typing_extensions.final +@typing.final class GraphTransferInfo(google.protobuf.message.Message): """Protocol buffer representing a handle to a tensorflow resource. Handles are not valid across executions, but can be serialized back and forth from within @@ -210,6 +211,8 @@ class GraphTransferInfo(google.protobuf.message.Message): GRAPH_INPUT_NODE_INFO_FIELD_NUMBER: builtins.int GRAPH_OUTPUT_NODE_INFO_FIELD_NUMBER: builtins.int DESTINATION_FIELD_NUMBER: builtins.int + destination: global___GraphTransferInfo.Destination.ValueType + """Destination of graph transfer""" @property def node_info(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___GraphTransferNodeInfo]: ... @property @@ -221,10 +224,9 @@ class GraphTransferInfo(google.protobuf.message.Message): @property def graph_input_node_info(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___GraphTransferGraphInputNodeInfo]: """Input Node parameters of transferred graph""" + @property def graph_output_node_info(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___GraphTransferGraphOutputNodeInfo]: ... - destination: global___GraphTransferInfo.Destination.ValueType - """Destination of graph transfer""" def __init__( self, *, @@ -236,6 +238,6 @@ class GraphTransferInfo(google.protobuf.message.Message): graph_output_node_info: collections.abc.Iterable[global___GraphTransferGraphOutputNodeInfo] | None = ..., destination: global___GraphTransferInfo.Destination.ValueType | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["const_node_info", b"const_node_info", "destination", b"destination", "graph_input_node_info", b"graph_input_node_info", "graph_output_node_info", b"graph_output_node_info", "node_info", b"node_info", "node_input_info", b"node_input_info", "node_output_info", b"node_output_info"]) -> None: ... + def ClearField(self, field_name: typing.Literal["const_node_info", b"const_node_info", "destination", b"destination", "graph_input_node_info", b"graph_input_node_info", "graph_output_node_info", b"graph_output_node_info", "node_info", b"node_info", "node_input_info", b"node_input_info", "node_output_info", b"node_output_info"]) -> None: ... global___GraphTransferInfo = GraphTransferInfo diff --git a/stubs/tensorflow/tensorflow/core/framework/kernel_def_pb2.pyi b/stubs/tensorflow/tensorflow/core/framework/kernel_def_pb2.pyi index 3e3e93d8be80..ea1844b41fbc 100644 --- a/stubs/tensorflow/tensorflow/core/framework/kernel_def_pb2.pyi +++ b/stubs/tensorflow/tensorflow/core/framework/kernel_def_pb2.pyi @@ -2,9 +2,10 @@ @generated by mypy-protobuf. Do not edit manually! isort:skip_file """ + import builtins import collections.abc -import typing as typing_extensions +import typing import google.protobuf.descriptor import google.protobuf.internal.containers @@ -13,11 +14,11 @@ import tensorflow.core.framework.attr_value_pb2 DESCRIPTOR: google.protobuf.descriptor.FileDescriptor -@typing_extensions.final +@typing.final class KernelDef(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor - @typing_extensions.final + @typing.final class AttrConstraint(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -30,14 +31,15 @@ class KernelDef(google.protobuf.message.Message): """A list of values that this kernel supports for this attr. Like OpDef.AttrDef.allowed_values, except for kernels instead of Ops. """ + def __init__( self, *, name: builtins.str | None = ..., allowed_values: tensorflow.core.framework.attr_value_pb2.AttrValue | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["allowed_values", b"allowed_values"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["allowed_values", b"allowed_values", "name", b"name"]) -> None: ... + def HasField(self, field_name: typing.Literal["allowed_values", b"allowed_values"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["allowed_values", b"allowed_values", "name", b"name"]) -> None: ... OP_FIELD_NUMBER: builtins.int DEVICE_TYPE_FIELD_NUMBER: builtins.int @@ -49,13 +51,6 @@ class KernelDef(google.protobuf.message.Message): """Must match the name of an Op.""" device_type: builtins.str """Type of device this kernel runs on.""" - @property - def constraint(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___KernelDef.AttrConstraint]: ... - @property - def host_memory_arg(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.str]: - """Names of the Op's input_/output_args that reside in host memory - instead of device memory. - """ label: builtins.str """This allows experimental kernels to be registered for an op that won't be used unless the user specifies a "_kernel" attr with @@ -66,6 +61,14 @@ class KernelDef(google.protobuf.message.Message): priority is 0. The higher the priority the better. By default (i.e. if this is not set), we prefer GPU kernels over CPU. """ + @property + def constraint(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___KernelDef.AttrConstraint]: ... + @property + def host_memory_arg(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.str]: + """Names of the Op's input_/output_args that reside in host memory + instead of device memory. + """ + def __init__( self, *, @@ -76,11 +79,11 @@ class KernelDef(google.protobuf.message.Message): label: builtins.str | None = ..., priority: builtins.int | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["constraint", b"constraint", "device_type", b"device_type", "host_memory_arg", b"host_memory_arg", "label", b"label", "op", b"op", "priority", b"priority"]) -> None: ... + def ClearField(self, field_name: typing.Literal["constraint", b"constraint", "device_type", b"device_type", "host_memory_arg", b"host_memory_arg", "label", b"label", "op", b"op", "priority", b"priority"]) -> None: ... global___KernelDef = KernelDef -@typing_extensions.final +@typing.final class KernelList(google.protobuf.message.Message): """A collection of KernelDefs""" @@ -94,6 +97,6 @@ class KernelList(google.protobuf.message.Message): *, kernel: collections.abc.Iterable[global___KernelDef] | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["kernel", b"kernel"]) -> None: ... + def ClearField(self, field_name: typing.Literal["kernel", b"kernel"]) -> None: ... global___KernelList = KernelList diff --git a/stubs/tensorflow/tensorflow/core/framework/log_memory_pb2.pyi b/stubs/tensorflow/tensorflow/core/framework/log_memory_pb2.pyi index 8ed5e51e41d6..ba0e1700fc9f 100644 --- a/stubs/tensorflow/tensorflow/core/framework/log_memory_pb2.pyi +++ b/stubs/tensorflow/tensorflow/core/framework/log_memory_pb2.pyi @@ -2,8 +2,9 @@ @generated by mypy-protobuf. Do not edit manually! isort:skip_file """ + import builtins -import typing as typing_extensions +import typing import google.protobuf.descriptor import google.protobuf.message @@ -11,7 +12,7 @@ import tensorflow.core.framework.tensor_description_pb2 DESCRIPTOR: google.protobuf.descriptor.FileDescriptor -@typing_extensions.final +@typing.final class MemoryLogStep(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -27,11 +28,11 @@ class MemoryLogStep(google.protobuf.message.Message): step_id: builtins.int | None = ..., handle: builtins.str | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["handle", b"handle", "step_id", b"step_id"]) -> None: ... + def ClearField(self, field_name: typing.Literal["handle", b"handle", "step_id", b"step_id"]) -> None: ... global___MemoryLogStep = MemoryLogStep -@typing_extensions.final +@typing.final class MemoryLogTensorAllocation(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -47,6 +48,7 @@ class MemoryLogTensorAllocation(google.protobuf.message.Message): @property def tensor(self) -> tensorflow.core.framework.tensor_description_pb2.TensorDescription: """Allocated tensor details.""" + def __init__( self, *, @@ -54,12 +56,12 @@ class MemoryLogTensorAllocation(google.protobuf.message.Message): kernel_name: builtins.str | None = ..., tensor: tensorflow.core.framework.tensor_description_pb2.TensorDescription | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["tensor", b"tensor"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["kernel_name", b"kernel_name", "step_id", b"step_id", "tensor", b"tensor"]) -> None: ... + def HasField(self, field_name: typing.Literal["tensor", b"tensor"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["kernel_name", b"kernel_name", "step_id", b"step_id", "tensor", b"tensor"]) -> None: ... global___MemoryLogTensorAllocation = MemoryLogTensorAllocation -@typing_extensions.final +@typing.final class MemoryLogTensorDeallocation(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -77,11 +79,11 @@ class MemoryLogTensorDeallocation(google.protobuf.message.Message): allocation_id: builtins.int | None = ..., allocator_name: builtins.str | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["allocation_id", b"allocation_id", "allocator_name", b"allocator_name"]) -> None: ... + def ClearField(self, field_name: typing.Literal["allocation_id", b"allocation_id", "allocator_name", b"allocator_name"]) -> None: ... global___MemoryLogTensorDeallocation = MemoryLogTensorDeallocation -@typing_extensions.final +@typing.final class MemoryLogTensorOutput(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -100,6 +102,7 @@ class MemoryLogTensorOutput(google.protobuf.message.Message): @property def tensor(self) -> tensorflow.core.framework.tensor_description_pb2.TensorDescription: """Output tensor details.""" + def __init__( self, *, @@ -108,12 +111,12 @@ class MemoryLogTensorOutput(google.protobuf.message.Message): index: builtins.int | None = ..., tensor: tensorflow.core.framework.tensor_description_pb2.TensorDescription | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["tensor", b"tensor"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["index", b"index", "kernel_name", b"kernel_name", "step_id", b"step_id", "tensor", b"tensor"]) -> None: ... + def HasField(self, field_name: typing.Literal["tensor", b"tensor"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["index", b"index", "kernel_name", b"kernel_name", "step_id", b"step_id", "tensor", b"tensor"]) -> None: ... global___MemoryLogTensorOutput = MemoryLogTensorOutput -@typing_extensions.final +@typing.final class MemoryLogRawAllocation(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -147,11 +150,11 @@ class MemoryLogRawAllocation(google.protobuf.message.Message): allocation_id: builtins.int | None = ..., allocator_name: builtins.str | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["allocation_id", b"allocation_id", "allocator_name", b"allocator_name", "num_bytes", b"num_bytes", "operation", b"operation", "ptr", b"ptr", "step_id", b"step_id"]) -> None: ... + def ClearField(self, field_name: typing.Literal["allocation_id", b"allocation_id", "allocator_name", b"allocator_name", "num_bytes", b"num_bytes", "operation", b"operation", "ptr", b"ptr", "step_id", b"step_id"]) -> None: ... global___MemoryLogRawAllocation = MemoryLogRawAllocation -@typing_extensions.final +@typing.final class MemoryLogRawDeallocation(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -183,6 +186,6 @@ class MemoryLogRawDeallocation(google.protobuf.message.Message): allocator_name: builtins.str | None = ..., deferred: builtins.bool | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["allocation_id", b"allocation_id", "allocator_name", b"allocator_name", "deferred", b"deferred", "operation", b"operation", "step_id", b"step_id"]) -> None: ... + def ClearField(self, field_name: typing.Literal["allocation_id", b"allocation_id", "allocator_name", b"allocator_name", "deferred", b"deferred", "operation", b"operation", "step_id", b"step_id"]) -> None: ... global___MemoryLogRawDeallocation = MemoryLogRawDeallocation diff --git a/stubs/tensorflow/tensorflow/core/framework/model_pb2.pyi b/stubs/tensorflow/tensorflow/core/framework/model_pb2.pyi index 8c4fdf2af8e0..90646c76eec1 100644 --- a/stubs/tensorflow/tensorflow/core/framework/model_pb2.pyi +++ b/stubs/tensorflow/tensorflow/core/framework/model_pb2.pyi @@ -2,6 +2,7 @@ @generated by mypy-protobuf. Do not edit manually! isort:skip_file """ + import builtins import collections.abc import sys @@ -67,7 +68,7 @@ MAX_PARALLELISM: AutotuneAlgorithm.ValueType # 3 STAGE_BASED: AutotuneAlgorithm.ValueType # 4 global___AutotuneAlgorithm = AutotuneAlgorithm -@typing_extensions.final +@typing.final class ModelProto(google.protobuf.message.Message): """Protocol buffer representing the data used by the autotuning modeling framework. @@ -75,13 +76,13 @@ class ModelProto(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor - @typing_extensions.final + @typing.final class Node(google.protobuf.message.Message): """General representation of a node in the model.""" DESCRIPTOR: google.protobuf.descriptor.Descriptor - @typing_extensions.final + @typing.final class Parameter(google.protobuf.message.Message): """Represents a node parameter.""" @@ -117,7 +118,7 @@ class ModelProto(google.protobuf.message.Message): max: builtins.float | None = ..., tunable: builtins.bool | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["max", b"max", "min", b"min", "name", b"name", "state_value", b"state_value", "tunable", b"tunable", "value", b"value"]) -> None: ... + def ClearField(self, field_name: typing.Literal["max", b"max", "min", b"min", "name", b"name", "state_value", b"state_value", "tunable", b"tunable", "value", b"value"]) -> None: ... ID_FIELD_NUMBER: builtins.int NAME_FIELD_NUMBER: builtins.int @@ -158,15 +159,9 @@ class ModelProto(google.protobuf.message.Message): """An indication whether this node records metrics about produced and consumed elements. """ - @property - def parameters(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___ModelProto.Node.Parameter]: - """Parameters of this node.""" input_processing_time_sum: builtins.float """Statistic of inputs processing time history.""" input_processing_time_count: builtins.int - @property - def inputs(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.int]: - """IDs of inputs of this node.""" node_class: global___NodeClass.ValueType """Class of this node.""" ratio: builtins.float @@ -177,6 +172,14 @@ class ModelProto(google.protobuf.message.Message): """Ratio identifies how many parallelism calls are introduced by one buffered element. This is only used by ASYNC_KNOWN_RATIO nodes. """ + @property + def parameters(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___ModelProto.Node.Parameter]: + """Parameters of this node.""" + + @property + def inputs(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.int]: + """IDs of inputs of this node.""" + def __init__( self, *, @@ -198,9 +201,9 @@ class ModelProto(google.protobuf.message.Message): ratio: builtins.float | None = ..., memory_ratio: builtins.float | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["autotune", b"autotune", "buffered_bytes", b"buffered_bytes", "buffered_elements", b"buffered_elements", "bytes_consumed", b"bytes_consumed", "bytes_produced", b"bytes_produced", "id", b"id", "input_processing_time_count", b"input_processing_time_count", "input_processing_time_sum", b"input_processing_time_sum", "inputs", b"inputs", "memory_ratio", b"memory_ratio", "name", b"name", "node_class", b"node_class", "num_elements", b"num_elements", "parameters", b"parameters", "processing_time", b"processing_time", "ratio", b"ratio", "record_metrics", b"record_metrics"]) -> None: ... + def ClearField(self, field_name: typing.Literal["autotune", b"autotune", "buffered_bytes", b"buffered_bytes", "buffered_elements", b"buffered_elements", "bytes_consumed", b"bytes_consumed", "bytes_produced", b"bytes_produced", "id", b"id", "input_processing_time_count", b"input_processing_time_count", "input_processing_time_sum", b"input_processing_time_sum", "inputs", b"inputs", "memory_ratio", b"memory_ratio", "name", b"name", "node_class", b"node_class", "num_elements", b"num_elements", "parameters", b"parameters", "processing_time", b"processing_time", "ratio", b"ratio", "record_metrics", b"record_metrics"]) -> None: ... - @typing_extensions.final + @typing.final class NodesEntry(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -215,10 +218,10 @@ class ModelProto(google.protobuf.message.Message): key: builtins.int | None = ..., value: global___ModelProto.Node | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["value", b"value"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["key", b"key", "value", b"value"]) -> None: ... + def HasField(self, field_name: typing.Literal["value", b"value"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["key", b"key", "value", b"value"]) -> None: ... - @typing_extensions.final + @typing.final class OptimizationParams(google.protobuf.message.Message): """Contains parameters of the model autotuning optimization.""" @@ -246,19 +249,20 @@ class ModelProto(google.protobuf.message.Message): ram_budget: builtins.int | None = ..., model_input_time: builtins.float | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["algorithm", b"algorithm", "cpu_budget", b"cpu_budget", "model_input_time", b"model_input_time", "ram_budget", b"ram_budget"]) -> None: ... + def ClearField(self, field_name: typing.Literal["algorithm", b"algorithm", "cpu_budget", b"cpu_budget", "model_input_time", b"model_input_time", "ram_budget", b"ram_budget"]) -> None: ... NODES_FIELD_NUMBER: builtins.int OUTPUT_FIELD_NUMBER: builtins.int ID_COUNTER_FIELD_NUMBER: builtins.int OPTIMIZATION_PARAMS_FIELD_NUMBER: builtins.int - @property - def nodes(self) -> google.protobuf.internal.containers.MessageMap[builtins.int, global___ModelProto.Node]: - """Map of node IDs to nodes of this model.""" output: builtins.int """ID of the output node of this model.""" id_counter: builtins.int """Counter for node IDs of this model.""" + @property + def nodes(self) -> google.protobuf.internal.containers.MessageMap[builtins.int, global___ModelProto.Node]: + """Map of node IDs to nodes of this model.""" + @property def optimization_params(self) -> global___ModelProto.OptimizationParams: ... def __init__( @@ -269,7 +273,7 @@ class ModelProto(google.protobuf.message.Message): id_counter: builtins.int | None = ..., optimization_params: global___ModelProto.OptimizationParams | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["optimization_params", b"optimization_params"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["id_counter", b"id_counter", "nodes", b"nodes", "optimization_params", b"optimization_params", "output", b"output"]) -> None: ... + def HasField(self, field_name: typing.Literal["optimization_params", b"optimization_params"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["id_counter", b"id_counter", "nodes", b"nodes", "optimization_params", b"optimization_params", "output", b"output"]) -> None: ... global___ModelProto = ModelProto diff --git a/stubs/tensorflow/tensorflow/core/framework/node_def_pb2.pyi b/stubs/tensorflow/tensorflow/core/framework/node_def_pb2.pyi index 70fd99f66056..663e4d216ec9 100644 --- a/stubs/tensorflow/tensorflow/core/framework/node_def_pb2.pyi +++ b/stubs/tensorflow/tensorflow/core/framework/node_def_pb2.pyi @@ -2,9 +2,10 @@ @generated by mypy-protobuf. Do not edit manually! isort:skip_file """ + import builtins import collections.abc -import typing as typing_extensions +import typing import google.protobuf.descriptor import google.protobuf.internal.containers @@ -14,11 +15,11 @@ import tensorflow.core.framework.full_type_pb2 DESCRIPTOR: google.protobuf.descriptor.FileDescriptor -@typing_extensions.final +@typing.final class NodeDef(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor - @typing_extensions.final + @typing.final class AttrEntry(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -33,10 +34,10 @@ class NodeDef(google.protobuf.message.Message): key: builtins.str | None = ..., value: tensorflow.core.framework.attr_value_pb2.AttrValue | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["value", b"value"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["key", b"key", "value", b"value"]) -> None: ... + def HasField(self, field_name: typing.Literal["value", b"value"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["key", b"key", "value", b"value"]) -> None: ... - @typing_extensions.final + @typing.final class ExperimentalDebugInfo(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -52,6 +53,7 @@ class NodeDef(google.protobuf.message.Message): be {A, B}. This information can be used to map errors originating at the current node to some top level source code. """ + @property def original_func_names(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.str]: """This is intended to store the list of names of the functions from the @@ -62,13 +64,14 @@ class NodeDef(google.protobuf.message.Message): `original_node_names` can be used to map errors originating at the current ndoe to some top level source code. """ + def __init__( self, *, original_node_names: collections.abc.Iterable[builtins.str] | None = ..., original_func_names: collections.abc.Iterable[builtins.str] | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["original_func_names", b"original_func_names", "original_node_names", b"original_node_names"]) -> None: ... + def ClearField(self, field_name: typing.Literal["original_func_names", b"original_func_names", "original_node_names", b"original_node_names"]) -> None: ... NAME_FIELD_NUMBER: builtins.int OP_FIELD_NUMBER: builtins.int @@ -86,14 +89,6 @@ class NodeDef(google.protobuf.message.Message): """The operation name. There may be custom parameters in attrs. Op names starting with an underscore are reserved for internal use. """ - @property - def input(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.str]: - """Each input is "node:src_output" with "node" being a string name and - "src_output" indicating which output tensor to use from "node". If - "src_output" is 0 the ":0" suffix can be omitted. Regular inputs - may optionally be followed by control inputs that have the format - "^node". - """ device: builtins.str """A (possibly partial) specification for the device on which this node should be placed. @@ -116,6 +111,15 @@ class NodeDef(google.protobuf.message.Message): field is empty or not present), the runtime will attempt to choose a device automatically. """ + @property + def input(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.str]: + """Each input is "node:src_output" with "node" being a string name and + "src_output" indicating which output tensor to use from "node". If + "src_output" is 0 the ":0" suffix can be omitted. Regular inputs + may optionally be followed by control inputs that have the format + "^node". + """ + @property def attr(self) -> google.protobuf.internal.containers.MessageMap[builtins.str, tensorflow.core.framework.attr_value_pb2.AttrValue]: """Operation-specific graph-construction-time configuration. @@ -131,9 +135,11 @@ class NodeDef(google.protobuf.message.Message): attr's type field. TODO(josh11b): Add some examples here showing best practices. """ + @property def experimental_debug_info(self) -> global___NodeDef.ExperimentalDebugInfo: """This stores debug information associated with the node.""" + @property def experimental_type(self) -> tensorflow.core.framework.full_type_pb2.FullTypeDef: """The complete type of this node. Experimental and subject to change. @@ -141,6 +147,7 @@ class NodeDef(google.protobuf.message.Message): extend in the future to contain the entire signature of the node, as a function type. """ + def __init__( self, *, @@ -152,7 +159,7 @@ class NodeDef(google.protobuf.message.Message): experimental_debug_info: global___NodeDef.ExperimentalDebugInfo | None = ..., experimental_type: tensorflow.core.framework.full_type_pb2.FullTypeDef | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["experimental_debug_info", b"experimental_debug_info", "experimental_type", b"experimental_type"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["attr", b"attr", "device", b"device", "experimental_debug_info", b"experimental_debug_info", "experimental_type", b"experimental_type", "input", b"input", "name", b"name", "op", b"op"]) -> None: ... + def HasField(self, field_name: typing.Literal["experimental_debug_info", b"experimental_debug_info", "experimental_type", b"experimental_type"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["attr", b"attr", "device", b"device", "experimental_debug_info", b"experimental_debug_info", "experimental_type", b"experimental_type", "input", b"input", "name", b"name", "op", b"op"]) -> None: ... global___NodeDef = NodeDef diff --git a/stubs/tensorflow/tensorflow/core/framework/op_def_pb2.pyi b/stubs/tensorflow/tensorflow/core/framework/op_def_pb2.pyi index 37ff910d3f27..6656ddcadf3f 100644 --- a/stubs/tensorflow/tensorflow/core/framework/op_def_pb2.pyi +++ b/stubs/tensorflow/tensorflow/core/framework/op_def_pb2.pyi @@ -2,9 +2,10 @@ @generated by mypy-protobuf. Do not edit manually! isort:skip_file """ + import builtins import collections.abc -import typing as typing_extensions +import typing import google.protobuf.descriptor import google.protobuf.internal.containers @@ -16,7 +17,7 @@ import tensorflow.core.framework.types_pb2 DESCRIPTOR: google.protobuf.descriptor.FileDescriptor -@typing_extensions.final +@typing.final class OpDef(google.protobuf.message.Message): """Defines an operation. A NodeDef in a GraphDef specifies an Op by using the "op" field which should match the name of a OpDef. @@ -25,7 +26,7 @@ class OpDef(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor - @typing_extensions.final + @typing.final class ArgDef(google.protobuf.message.Message): """For describing inputs and outputs.""" @@ -64,14 +65,15 @@ class OpDef(google.protobuf.message.Message): """If specified, attr must have type "list(type)", and none of type, type_attr, and number_attr may be specified. """ - @property - def handle_data(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[tensorflow.core.framework.resource_handle_pb2.ResourceHandleProto.DtypeAndShape]: - """The handle data for resource inputs.""" is_ref: builtins.bool """For inputs: if true, the inputs are required to be refs. By default, inputs can be either refs or non-refs. For outputs: if true, outputs are refs, otherwise they are not. """ + @property + def handle_data(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[tensorflow.core.framework.resource_handle_pb2.ResourceHandleProto.DtypeAndShape]: + """The handle data for resource inputs.""" + @property def experimental_full_type(self) -> tensorflow.core.framework.full_type_pb2.FullTypeDef: """Experimental. Full type declaration for this argument. @@ -84,6 +86,7 @@ class OpDef(google.protobuf.message.Message): entire OpDef as a single type: a callable. In that context, this field is just the type of a single argument. """ + def __init__( self, *, @@ -97,10 +100,10 @@ class OpDef(google.protobuf.message.Message): is_ref: builtins.bool | None = ..., experimental_full_type: tensorflow.core.framework.full_type_pb2.FullTypeDef | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["experimental_full_type", b"experimental_full_type"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["description", b"description", "experimental_full_type", b"experimental_full_type", "handle_data", b"handle_data", "is_ref", b"is_ref", "name", b"name", "number_attr", b"number_attr", "type", b"type", "type_attr", b"type_attr", "type_list_attr", b"type_list_attr"]) -> None: ... + def HasField(self, field_name: typing.Literal["experimental_full_type", b"experimental_full_type"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["description", b"description", "experimental_full_type", b"experimental_full_type", "handle_data", b"handle_data", "is_ref", b"is_ref", "name", b"name", "number_attr", b"number_attr", "type", b"type", "type_attr", b"type_attr", "type_list_attr", b"type_list_attr"]) -> None: ... - @typing_extensions.final + @typing.final class AttrDef(google.protobuf.message.Message): """Description of the graph-construction-time configuration of this Op. That is to say, this describes the attr fields that will @@ -125,11 +128,6 @@ class OpDef(google.protobuf.message.Message): """One of the type names from attr_value.proto ("string", "list(string)", "int", etc.). """ - @property - def default_value(self) -> tensorflow.core.framework.attr_value_pb2.AttrValue: - """A reasonable default for this attribute if the user does not supply - a value. If not specified, the user must supply a value. - """ description: builtins.str """Human-readable description.""" has_minimum: builtins.bool @@ -141,6 +139,12 @@ class OpDef(google.protobuf.message.Message): types, this is the minimum length. """ minimum: builtins.int + @property + def default_value(self) -> tensorflow.core.framework.attr_value_pb2.AttrValue: + """A reasonable default for this attribute if the user does not supply + a value. If not specified, the user must supply a value. + """ + @property def allowed_values(self) -> tensorflow.core.framework.attr_value_pb2.AttrValue: """The set of allowed values. Has type that is the "list" version @@ -150,6 +154,7 @@ class OpDef(google.protobuf.message.Message): If type == "string" or "list(string)", then the "s" field of "allowed_values.list" has the set of allowed strings. """ + def __init__( self, *, @@ -161,8 +166,8 @@ class OpDef(google.protobuf.message.Message): minimum: builtins.int | None = ..., allowed_values: tensorflow.core.framework.attr_value_pb2.AttrValue | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["allowed_values", b"allowed_values", "default_value", b"default_value"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["allowed_values", b"allowed_values", "default_value", b"default_value", "description", b"description", "has_minimum", b"has_minimum", "minimum", b"minimum", "name", b"name", "type", b"type"]) -> None: ... + def HasField(self, field_name: typing.Literal["allowed_values", b"allowed_values", "default_value", b"default_value"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["allowed_values", b"allowed_values", "default_value", b"default_value", "description", b"description", "has_minimum", b"has_minimum", "minimum", b"minimum", "name", b"name", "type", b"type"]) -> None: ... NAME_FIELD_NUMBER: builtins.int INPUT_ARG_FIELD_NUMBER: builtins.int @@ -181,22 +186,6 @@ class OpDef(google.protobuf.message.Message): """Op names starting with an underscore are reserved for internal use. Names should be CamelCase and match the regexp "[A-Z][a-zA-Z0-9>_]*". """ - @property - def input_arg(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___OpDef.ArgDef]: - """Description of the input(s).""" - @property - def output_arg(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___OpDef.ArgDef]: - """Description of the output(s).""" - @property - def control_output(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.str]: - """Named control outputs for this operation. Useful only for composite - operations (i.e. functions) which want to name different control outputs. - """ - @property - def attr(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___OpDef.AttrDef]: ... - @property - def deprecation(self) -> global___OpDeprecation: - """Optional deprecation based on GraphDef versions.""" summary: builtins.str """One-line human-readable description of what the Op does.""" description: builtins.str @@ -250,6 +239,26 @@ class OpDef(google.protobuf.message.Message): If True, the op is allowed to return errors for network disconnection and trigger TF network failure handling logics. """ + @property + def input_arg(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___OpDef.ArgDef]: + """Description of the input(s).""" + + @property + def output_arg(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___OpDef.ArgDef]: + """Description of the output(s).""" + + @property + def control_output(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.str]: + """Named control outputs for this operation. Useful only for composite + operations (i.e. functions) which want to name different control outputs. + """ + + @property + def attr(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___OpDef.AttrDef]: ... + @property + def deprecation(self) -> global___OpDeprecation: + """Optional deprecation based on GraphDef versions.""" + def __init__( self, *, @@ -267,12 +276,12 @@ class OpDef(google.protobuf.message.Message): allows_uninitialized_input: builtins.bool | None = ..., is_distributed_communication: builtins.bool | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["deprecation", b"deprecation"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["allows_uninitialized_input", b"allows_uninitialized_input", "attr", b"attr", "control_output", b"control_output", "deprecation", b"deprecation", "description", b"description", "input_arg", b"input_arg", "is_aggregate", b"is_aggregate", "is_commutative", b"is_commutative", "is_distributed_communication", b"is_distributed_communication", "is_stateful", b"is_stateful", "name", b"name", "output_arg", b"output_arg", "summary", b"summary"]) -> None: ... + def HasField(self, field_name: typing.Literal["deprecation", b"deprecation"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["allows_uninitialized_input", b"allows_uninitialized_input", "attr", b"attr", "control_output", b"control_output", "deprecation", b"deprecation", "description", b"description", "input_arg", b"input_arg", "is_aggregate", b"is_aggregate", "is_commutative", b"is_commutative", "is_distributed_communication", b"is_distributed_communication", "is_stateful", b"is_stateful", "name", b"name", "output_arg", b"output_arg", "summary", b"summary"]) -> None: ... global___OpDef = OpDef -@typing_extensions.final +@typing.final class OpDeprecation(google.protobuf.message.Message): """Information about version-dependent deprecation of an op""" @@ -290,11 +299,11 @@ class OpDeprecation(google.protobuf.message.Message): version: builtins.int | None = ..., explanation: builtins.str | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["explanation", b"explanation", "version", b"version"]) -> None: ... + def ClearField(self, field_name: typing.Literal["explanation", b"explanation", "version", b"version"]) -> None: ... global___OpDeprecation = OpDeprecation -@typing_extensions.final +@typing.final class OpList(google.protobuf.message.Message): """A collection of OpDefs""" @@ -308,6 +317,6 @@ class OpList(google.protobuf.message.Message): *, op: collections.abc.Iterable[global___OpDef] | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["op", b"op"]) -> None: ... + def ClearField(self, field_name: typing.Literal["op", b"op"]) -> None: ... global___OpList = OpList diff --git a/stubs/tensorflow/tensorflow/core/framework/optimized_function_graph_pb2.pyi b/stubs/tensorflow/tensorflow/core/framework/optimized_function_graph_pb2.pyi index 967a5a1de385..7d142553d95b 100644 --- a/stubs/tensorflow/tensorflow/core/framework/optimized_function_graph_pb2.pyi +++ b/stubs/tensorflow/tensorflow/core/framework/optimized_function_graph_pb2.pyi @@ -2,9 +2,10 @@ @generated by mypy-protobuf. Do not edit manually! isort:skip_file """ + import builtins import collections.abc -import typing as typing_extensions +import typing import google.protobuf.descriptor import google.protobuf.internal.containers @@ -14,7 +15,7 @@ import tensorflow.core.framework.types_pb2 DESCRIPTOR: google.protobuf.descriptor.FileDescriptor -@typing_extensions.final +@typing.final class OptimizedFunctionGraph(google.protobuf.message.Message): """Optimized function graph after instantiation-related graph optimization passes (up till before graph partitioning). The first half of the proto is @@ -24,7 +25,7 @@ class OptimizedFunctionGraph(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor - @typing_extensions.final + @typing.final class NodeNameToControlRetEntry(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -38,7 +39,7 @@ class OptimizedFunctionGraph(google.protobuf.message.Message): key: builtins.str | None = ..., value: builtins.str | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["key", b"key", "value", b"value"]) -> None: ... + def ClearField(self, field_name: typing.Literal["key", b"key", "value", b"value"]) -> None: ... NAME_FIELD_NUMBER: builtins.int FUNCTION_GRAPH_FIELD_NUMBER: builtins.int @@ -49,21 +50,24 @@ class OptimizedFunctionGraph(google.protobuf.message.Message): """Function name. It can be a human-readable SignatureDef's method name, or a FunctionDef name. """ + num_return_nodes: builtins.int + """Number of return nodes. This is an output of graph preprocessing.""" @property def function_graph(self) -> tensorflow.core.framework.graph_pb2.GraphDef: """Optimized function graph.""" + @property def node_name_to_control_ret(self) -> google.protobuf.internal.containers.ScalarMap[builtins.str, builtins.str]: """Maps from node name to control ret. This is an output from running TF/XLA bridge. """ + @property def ret_types(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[tensorflow.core.framework.types_pb2.DataType.ValueType]: """Return node types of the function. This is an output of graph preprocessing. """ - num_return_nodes: builtins.int - """Number of return nodes. This is an output of graph preprocessing.""" + def __init__( self, *, @@ -73,7 +77,7 @@ class OptimizedFunctionGraph(google.protobuf.message.Message): ret_types: collections.abc.Iterable[tensorflow.core.framework.types_pb2.DataType.ValueType] | None = ..., num_return_nodes: builtins.int | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["function_graph", b"function_graph"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["function_graph", b"function_graph", "name", b"name", "node_name_to_control_ret", b"node_name_to_control_ret", "num_return_nodes", b"num_return_nodes", "ret_types", b"ret_types"]) -> None: ... + def HasField(self, field_name: typing.Literal["function_graph", b"function_graph"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["function_graph", b"function_graph", "name", b"name", "node_name_to_control_ret", b"node_name_to_control_ret", "num_return_nodes", b"num_return_nodes", "ret_types", b"ret_types"]) -> None: ... global___OptimizedFunctionGraph = OptimizedFunctionGraph diff --git a/stubs/tensorflow/tensorflow/core/framework/reader_base_pb2.pyi b/stubs/tensorflow/tensorflow/core/framework/reader_base_pb2.pyi index 2bc0aafe35a9..7e6e6ea31932 100644 --- a/stubs/tensorflow/tensorflow/core/framework/reader_base_pb2.pyi +++ b/stubs/tensorflow/tensorflow/core/framework/reader_base_pb2.pyi @@ -2,15 +2,16 @@ @generated by mypy-protobuf. Do not edit manually! isort:skip_file """ + import builtins -import typing as typing_extensions +import typing import google.protobuf.descriptor import google.protobuf.message DESCRIPTOR: google.protobuf.descriptor.FileDescriptor -@typing_extensions.final +@typing.final class ReaderBaseState(google.protobuf.message.Message): """For serializing and restoring the state of ReaderBase, see reader_base.h for details. @@ -34,6 +35,6 @@ class ReaderBaseState(google.protobuf.message.Message): num_records_produced: builtins.int | None = ..., current_work: builtins.bytes | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["current_work", b"current_work", "num_records_produced", b"num_records_produced", "work_finished", b"work_finished", "work_started", b"work_started"]) -> None: ... + def ClearField(self, field_name: typing.Literal["current_work", b"current_work", "num_records_produced", b"num_records_produced", "work_finished", b"work_finished", "work_started", b"work_started"]) -> None: ... global___ReaderBaseState = ReaderBaseState diff --git a/stubs/tensorflow/tensorflow/core/framework/resource_handle_pb2.pyi b/stubs/tensorflow/tensorflow/core/framework/resource_handle_pb2.pyi index c2f282c80d62..693e93d05f54 100644 --- a/stubs/tensorflow/tensorflow/core/framework/resource_handle_pb2.pyi +++ b/stubs/tensorflow/tensorflow/core/framework/resource_handle_pb2.pyi @@ -2,9 +2,10 @@ @generated by mypy-protobuf. Do not edit manually! isort:skip_file """ + import builtins import collections.abc -import typing as typing_extensions +import typing import google.protobuf.descriptor import google.protobuf.internal.containers @@ -14,7 +15,7 @@ import tensorflow.core.framework.types_pb2 DESCRIPTOR: google.protobuf.descriptor.FileDescriptor -@typing_extensions.final +@typing.final class ResourceHandleProto(google.protobuf.message.Message): """Protocol buffer representing a handle to a tensorflow resource. Handles are not valid across executions, but can be serialized back and forth from within @@ -23,7 +24,7 @@ class ResourceHandleProto(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor - @typing_extensions.final + @typing.final class DtypeAndShape(google.protobuf.message.Message): """Protocol buffer representing a pair of (data type, tensor shape).""" @@ -40,8 +41,8 @@ class ResourceHandleProto(google.protobuf.message.Message): dtype: tensorflow.core.framework.types_pb2.DataType.ValueType | None = ..., shape: tensorflow.core.framework.tensor_shape_pb2.TensorShapeProto | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["shape", b"shape"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["dtype", b"dtype", "shape", b"shape"]) -> None: ... + def HasField(self, field_name: typing.Literal["shape", b"shape"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["dtype", b"dtype", "shape", b"shape"]) -> None: ... DEVICE_FIELD_NUMBER: builtins.int CONTAINER_FIELD_NUMBER: builtins.int @@ -66,6 +67,7 @@ class ResourceHandleProto(google.protobuf.message.Message): @property def dtypes_and_shapes(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___ResourceHandleProto.DtypeAndShape]: """Data types and shapes for the underlying resource.""" + def __init__( self, *, @@ -76,6 +78,6 @@ class ResourceHandleProto(google.protobuf.message.Message): maybe_type_name: builtins.str | None = ..., dtypes_and_shapes: collections.abc.Iterable[global___ResourceHandleProto.DtypeAndShape] | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["container", b"container", "device", b"device", "dtypes_and_shapes", b"dtypes_and_shapes", "hash_code", b"hash_code", "maybe_type_name", b"maybe_type_name", "name", b"name"]) -> None: ... + def ClearField(self, field_name: typing.Literal["container", b"container", "device", b"device", "dtypes_and_shapes", b"dtypes_and_shapes", "hash_code", b"hash_code", "maybe_type_name", b"maybe_type_name", "name", b"name"]) -> None: ... global___ResourceHandleProto = ResourceHandleProto diff --git a/stubs/tensorflow/tensorflow/core/framework/step_stats_pb2.pyi b/stubs/tensorflow/tensorflow/core/framework/step_stats_pb2.pyi index 85375199ae39..947cbdb41683 100644 --- a/stubs/tensorflow/tensorflow/core/framework/step_stats_pb2.pyi +++ b/stubs/tensorflow/tensorflow/core/framework/step_stats_pb2.pyi @@ -2,9 +2,10 @@ @generated by mypy-protobuf. Do not edit manually! isort:skip_file """ + import builtins import collections.abc -import typing as typing_extensions +import typing import google.protobuf.descriptor import google.protobuf.internal.containers @@ -14,7 +15,7 @@ import tensorflow.core.framework.tensor_description_pb2 DESCRIPTOR: google.protobuf.descriptor.FileDescriptor -@typing_extensions.final +@typing.final class AllocationRecord(google.protobuf.message.Message): """An allocation/de-allocation operation performed by the allocator.""" @@ -32,11 +33,11 @@ class AllocationRecord(google.protobuf.message.Message): alloc_micros: builtins.int | None = ..., alloc_bytes: builtins.int | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["alloc_bytes", b"alloc_bytes", "alloc_micros", b"alloc_micros"]) -> None: ... + def ClearField(self, field_name: typing.Literal["alloc_bytes", b"alloc_bytes", "alloc_micros", b"alloc_micros"]) -> None: ... global___AllocationRecord = AllocationRecord -@typing_extensions.final +@typing.final class AllocatorMemoryUsed(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -52,13 +53,14 @@ class AllocatorMemoryUsed(google.protobuf.message.Message): peak_bytes: builtins.int live_bytes: builtins.int """The bytes that are not deallocated.""" - @property - def allocation_records(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___AllocationRecord]: - """The allocation and deallocation timeline.""" allocator_bytes_in_use: builtins.int """These are snapshots of the overall allocator memory stats. The number of live bytes currently allocated by the allocator. """ + @property + def allocation_records(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___AllocationRecord]: + """The allocation and deallocation timeline.""" + def __init__( self, *, @@ -69,11 +71,11 @@ class AllocatorMemoryUsed(google.protobuf.message.Message): allocation_records: collections.abc.Iterable[global___AllocationRecord] | None = ..., allocator_bytes_in_use: builtins.int | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["allocation_records", b"allocation_records", "allocator_bytes_in_use", b"allocator_bytes_in_use", "allocator_name", b"allocator_name", "live_bytes", b"live_bytes", "peak_bytes", b"peak_bytes", "total_bytes", b"total_bytes"]) -> None: ... + def ClearField(self, field_name: typing.Literal["allocation_records", b"allocation_records", "allocator_bytes_in_use", b"allocator_bytes_in_use", "allocator_name", b"allocator_name", "live_bytes", b"live_bytes", "peak_bytes", b"peak_bytes", "total_bytes", b"total_bytes"]) -> None: ... global___AllocatorMemoryUsed = AllocatorMemoryUsed -@typing_extensions.final +@typing.final class NodeOutput(google.protobuf.message.Message): """Output sizes recorded for a single execution of a graph node.""" @@ -90,12 +92,12 @@ class NodeOutput(google.protobuf.message.Message): slot: builtins.int | None = ..., tensor_description: tensorflow.core.framework.tensor_description_pb2.TensorDescription | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["tensor_description", b"tensor_description"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["slot", b"slot", "tensor_description", b"tensor_description"]) -> None: ... + def HasField(self, field_name: typing.Literal["tensor_description", b"tensor_description"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["slot", b"slot", "tensor_description", b"tensor_description"]) -> None: ... global___NodeOutput = NodeOutput -@typing_extensions.final +@typing.final class MemoryStats(google.protobuf.message.Message): """For memory tracking.""" @@ -109,11 +111,11 @@ class MemoryStats(google.protobuf.message.Message): DEVICE_PERSISTENT_TENSOR_ALLOC_IDS_FIELD_NUMBER: builtins.int temp_memory_size: builtins.int persistent_memory_size: builtins.int - @property - def persistent_tensor_alloc_ids(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.int]: ... device_temp_memory_size: builtins.int device_persistent_memory_size: builtins.int @property + def persistent_tensor_alloc_ids(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.int]: ... + @property def device_persistent_tensor_alloc_ids(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.int]: ... def __init__( self, @@ -125,11 +127,11 @@ class MemoryStats(google.protobuf.message.Message): device_persistent_memory_size: builtins.int | None = ..., device_persistent_tensor_alloc_ids: collections.abc.Iterable[builtins.int] | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["device_persistent_memory_size", b"device_persistent_memory_size", "device_persistent_tensor_alloc_ids", b"device_persistent_tensor_alloc_ids", "device_temp_memory_size", b"device_temp_memory_size", "persistent_memory_size", b"persistent_memory_size", "persistent_tensor_alloc_ids", b"persistent_tensor_alloc_ids", "temp_memory_size", b"temp_memory_size"]) -> None: ... + def ClearField(self, field_name: typing.Literal["device_persistent_memory_size", b"device_persistent_memory_size", "device_persistent_tensor_alloc_ids", b"device_persistent_tensor_alloc_ids", "device_temp_memory_size", b"device_temp_memory_size", "persistent_memory_size", b"persistent_memory_size", "persistent_tensor_alloc_ids", b"persistent_tensor_alloc_ids", "temp_memory_size", b"temp_memory_size"]) -> None: ... global___MemoryStats = MemoryStats -@typing_extensions.final +@typing.final class NodeExecStats(google.protobuf.message.Message): """Time/size stats recorded for a single execution of a graph node.""" @@ -162,22 +164,22 @@ class NodeExecStats(google.protobuf.message.Message): op_start_rel_micros: builtins.int op_end_rel_micros: builtins.int all_end_rel_micros: builtins.int - @property - def memory(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___AllocatorMemoryUsed]: ... - @property - def output(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___NodeOutput]: ... timeline_label: builtins.str scheduled_micros: builtins.int thread_id: builtins.int - @property - def referenced_tensor(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[tensorflow.core.framework.allocation_description_pb2.AllocationDescription]: ... - @property - def memory_stats(self) -> global___MemoryStats: ... all_start_nanos: builtins.int op_start_rel_nanos: builtins.int op_end_rel_nanos: builtins.int all_end_rel_nanos: builtins.int scheduled_nanos: builtins.int + @property + def memory(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___AllocatorMemoryUsed]: ... + @property + def output(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___NodeOutput]: ... + @property + def referenced_tensor(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[tensorflow.core.framework.allocation_description_pb2.AllocationDescription]: ... + @property + def memory_stats(self) -> global___MemoryStats: ... def __init__( self, *, @@ -199,16 +201,16 @@ class NodeExecStats(google.protobuf.message.Message): all_end_rel_nanos: builtins.int | None = ..., scheduled_nanos: builtins.int | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["memory_stats", b"memory_stats"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["all_end_rel_micros", b"all_end_rel_micros", "all_end_rel_nanos", b"all_end_rel_nanos", "all_start_micros", b"all_start_micros", "all_start_nanos", b"all_start_nanos", "memory", b"memory", "memory_stats", b"memory_stats", "node_name", b"node_name", "op_end_rel_micros", b"op_end_rel_micros", "op_end_rel_nanos", b"op_end_rel_nanos", "op_start_rel_micros", b"op_start_rel_micros", "op_start_rel_nanos", b"op_start_rel_nanos", "output", b"output", "referenced_tensor", b"referenced_tensor", "scheduled_micros", b"scheduled_micros", "scheduled_nanos", b"scheduled_nanos", "thread_id", b"thread_id", "timeline_label", b"timeline_label"]) -> None: ... + def HasField(self, field_name: typing.Literal["memory_stats", b"memory_stats"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["all_end_rel_micros", b"all_end_rel_micros", "all_end_rel_nanos", b"all_end_rel_nanos", "all_start_micros", b"all_start_micros", "all_start_nanos", b"all_start_nanos", "memory", b"memory", "memory_stats", b"memory_stats", "node_name", b"node_name", "op_end_rel_micros", b"op_end_rel_micros", "op_end_rel_nanos", b"op_end_rel_nanos", "op_start_rel_micros", b"op_start_rel_micros", "op_start_rel_nanos", b"op_start_rel_nanos", "output", b"output", "referenced_tensor", b"referenced_tensor", "scheduled_micros", b"scheduled_micros", "scheduled_nanos", b"scheduled_nanos", "thread_id", b"thread_id", "timeline_label", b"timeline_label"]) -> None: ... global___NodeExecStats = NodeExecStats -@typing_extensions.final +@typing.final class DeviceStepStats(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor - @typing_extensions.final + @typing.final class ThreadNamesEntry(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -222,7 +224,7 @@ class DeviceStepStats(google.protobuf.message.Message): key: builtins.int | None = ..., value: builtins.str | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["key", b"key", "value", b"value"]) -> None: ... + def ClearField(self, field_name: typing.Literal["key", b"key", "value", b"value"]) -> None: ... DEVICE_FIELD_NUMBER: builtins.int NODE_STATS_FIELD_NUMBER: builtins.int @@ -233,6 +235,7 @@ class DeviceStepStats(google.protobuf.message.Message): @property def thread_names(self) -> google.protobuf.internal.containers.ScalarMap[builtins.int, builtins.str]: """Its key is thread id.""" + def __init__( self, *, @@ -240,11 +243,11 @@ class DeviceStepStats(google.protobuf.message.Message): node_stats: collections.abc.Iterable[global___NodeExecStats] | None = ..., thread_names: collections.abc.Mapping[builtins.int, builtins.str] | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["device", b"device", "node_stats", b"node_stats", "thread_names", b"thread_names"]) -> None: ... + def ClearField(self, field_name: typing.Literal["device", b"device", "node_stats", b"node_stats", "thread_names", b"thread_names"]) -> None: ... global___DeviceStepStats = DeviceStepStats -@typing_extensions.final +@typing.final class StepStats(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -256,6 +259,6 @@ class StepStats(google.protobuf.message.Message): *, dev_stats: collections.abc.Iterable[global___DeviceStepStats] | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["dev_stats", b"dev_stats"]) -> None: ... + def ClearField(self, field_name: typing.Literal["dev_stats", b"dev_stats"]) -> None: ... global___StepStats = StepStats diff --git a/stubs/tensorflow/tensorflow/core/framework/summary_pb2.pyi b/stubs/tensorflow/tensorflow/core/framework/summary_pb2.pyi index 609abbe28650..5df66b7e7978 100644 --- a/stubs/tensorflow/tensorflow/core/framework/summary_pb2.pyi +++ b/stubs/tensorflow/tensorflow/core/framework/summary_pb2.pyi @@ -2,6 +2,7 @@ @generated by mypy-protobuf. Do not edit manually! isort:skip_file """ + import builtins import collections.abc import sys @@ -69,7 +70,7 @@ have `tensor` set to a rank-1 tensor of bytestring dtype. """ global___DataClass = DataClass -@typing_extensions.final +@typing.final class SummaryDescription(google.protobuf.message.Message): """Metadata associated with a series of Summary data""" @@ -85,11 +86,11 @@ class SummaryDescription(google.protobuf.message.Message): *, type_hint: builtins.str | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["type_hint", b"type_hint"]) -> None: ... + def ClearField(self, field_name: typing.Literal["type_hint", b"type_hint"]) -> None: ... global___SummaryDescription = SummaryDescription -@typing_extensions.final +@typing.final class SummaryMetadata(google.protobuf.message.Message): """A SummaryMetadata encapsulates information on which plugins are able to make use of a certain summary value. @@ -97,7 +98,7 @@ class SummaryMetadata(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor - @typing_extensions.final + @typing.final class PluginData(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -115,15 +116,12 @@ class SummaryMetadata(google.protobuf.message.Message): plugin_name: builtins.str | None = ..., content: builtins.bytes | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["content", b"content", "plugin_name", b"plugin_name"]) -> None: ... + def ClearField(self, field_name: typing.Literal["content", b"content", "plugin_name", b"plugin_name"]) -> None: ... PLUGIN_DATA_FIELD_NUMBER: builtins.int DISPLAY_NAME_FIELD_NUMBER: builtins.int SUMMARY_DESCRIPTION_FIELD_NUMBER: builtins.int DATA_CLASS_FIELD_NUMBER: builtins.int - @property - def plugin_data(self) -> global___SummaryMetadata.PluginData: - """Data that associates a summary with a certain plugin.""" display_name: builtins.str """Display name for viewing in TensorBoard.""" summary_description: builtins.str @@ -134,6 +132,10 @@ class SummaryMetadata(google.protobuf.message.Message): imposes constraints on the dtype and shape of the corresponding tensor values. See `DataClass` docs for details. """ + @property + def plugin_data(self) -> global___SummaryMetadata.PluginData: + """Data that associates a summary with a certain plugin.""" + def __init__( self, *, @@ -142,12 +144,12 @@ class SummaryMetadata(google.protobuf.message.Message): summary_description: builtins.str | None = ..., data_class: global___DataClass.ValueType | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["plugin_data", b"plugin_data"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["data_class", b"data_class", "display_name", b"display_name", "plugin_data", b"plugin_data", "summary_description", b"summary_description"]) -> None: ... + def HasField(self, field_name: typing.Literal["plugin_data", b"plugin_data"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["data_class", b"data_class", "display_name", b"display_name", "plugin_data", b"plugin_data", "summary_description", b"summary_description"]) -> None: ... global___SummaryMetadata = SummaryMetadata -@typing_extensions.final +@typing.final class Summary(google.protobuf.message.Message): """A Summary is a set of named values to be displayed by the visualizer. @@ -159,7 +161,7 @@ class Summary(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor - @typing_extensions.final + @typing.final class Image(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -191,9 +193,9 @@ class Summary(google.protobuf.message.Message): colorspace: builtins.int | None = ..., encoded_image_string: builtins.bytes | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["colorspace", b"colorspace", "encoded_image_string", b"encoded_image_string", "height", b"height", "width", b"width"]) -> None: ... + def ClearField(self, field_name: typing.Literal["colorspace", b"colorspace", "encoded_image_string", b"encoded_image_string", "height", b"height", "width", b"width"]) -> None: ... - @typing_extensions.final + @typing.final class Audio(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -222,9 +224,9 @@ class Summary(google.protobuf.message.Message): encoded_audio_string: builtins.bytes | None = ..., content_type: builtins.str | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["content_type", b"content_type", "encoded_audio_string", b"encoded_audio_string", "length_frames", b"length_frames", "num_channels", b"num_channels", "sample_rate", b"sample_rate"]) -> None: ... + def ClearField(self, field_name: typing.Literal["content_type", b"content_type", "encoded_audio_string", b"encoded_audio_string", "length_frames", b"length_frames", "num_channels", b"num_channels", "sample_rate", b"sample_rate"]) -> None: ... - @typing_extensions.final + @typing.final class Value(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -244,6 +246,8 @@ class Summary(google.protobuf.message.Message): are often organized by scope (which contains slashes to convey hierarchy). For example: foo/bar/0 """ + simple_value: builtins.float + obsolete_old_style_histogram: builtins.bytes @property def metadata(self) -> global___SummaryMetadata: """Contains metadata on the summary value such as which plugins may use it. @@ -252,8 +256,7 @@ class Summary(google.protobuf.message.Message): value with a certain tag for each tag. TensorBoard then remembers which tags are associated with which plugins. This saves space. """ - simple_value: builtins.float - obsolete_old_style_histogram: builtins.bytes + @property def image(self) -> global___Summary.Image: ... @property @@ -275,19 +278,20 @@ class Summary(google.protobuf.message.Message): audio: global___Summary.Audio | None = ..., tensor: tensorflow.core.framework.tensor_pb2.TensorProto | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["audio", b"audio", "histo", b"histo", "image", b"image", "metadata", b"metadata", "obsolete_old_style_histogram", b"obsolete_old_style_histogram", "simple_value", b"simple_value", "tensor", b"tensor", "value", b"value"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["audio", b"audio", "histo", b"histo", "image", b"image", "metadata", b"metadata", "node_name", b"node_name", "obsolete_old_style_histogram", b"obsolete_old_style_histogram", "simple_value", b"simple_value", "tag", b"tag", "tensor", b"tensor", "value", b"value"]) -> None: ... - def WhichOneof(self, oneof_group: typing_extensions.Literal["value", b"value"]) -> typing_extensions.Literal["simple_value", "obsolete_old_style_histogram", "image", "histo", "audio", "tensor"] | None: ... + def HasField(self, field_name: typing.Literal["audio", b"audio", "histo", b"histo", "image", b"image", "metadata", b"metadata", "obsolete_old_style_histogram", b"obsolete_old_style_histogram", "simple_value", b"simple_value", "tensor", b"tensor", "value", b"value"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["audio", b"audio", "histo", b"histo", "image", b"image", "metadata", b"metadata", "node_name", b"node_name", "obsolete_old_style_histogram", b"obsolete_old_style_histogram", "simple_value", b"simple_value", "tag", b"tag", "tensor", b"tensor", "value", b"value"]) -> None: ... + def WhichOneof(self, oneof_group: typing.Literal["value", b"value"]) -> typing.Literal["simple_value", "obsolete_old_style_histogram", "image", "histo", "audio", "tensor"] | None: ... VALUE_FIELD_NUMBER: builtins.int @property def value(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___Summary.Value]: """Set of values for the summary.""" + def __init__( self, *, value: collections.abc.Iterable[global___Summary.Value] | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["value", b"value"]) -> None: ... + def ClearField(self, field_name: typing.Literal["value", b"value"]) -> None: ... global___Summary = Summary diff --git a/stubs/tensorflow/tensorflow/core/framework/tensor_description_pb2.pyi b/stubs/tensorflow/tensorflow/core/framework/tensor_description_pb2.pyi index 3fb9b3ea3737..71a5df5340a2 100644 --- a/stubs/tensorflow/tensorflow/core/framework/tensor_description_pb2.pyi +++ b/stubs/tensorflow/tensorflow/core/framework/tensor_description_pb2.pyi @@ -2,8 +2,9 @@ @generated by mypy-protobuf. Do not edit manually! isort:skip_file """ + import builtins -import typing as typing_extensions +import typing import google.protobuf.descriptor import google.protobuf.message @@ -13,7 +14,7 @@ import tensorflow.core.framework.types_pb2 DESCRIPTOR: google.protobuf.descriptor.FileDescriptor -@typing_extensions.final +@typing.final class TensorDescription(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -25,9 +26,11 @@ class TensorDescription(google.protobuf.message.Message): @property def shape(self) -> tensorflow.core.framework.tensor_shape_pb2.TensorShapeProto: """Shape of the tensor.""" + @property def allocation_description(self) -> tensorflow.core.framework.allocation_description_pb2.AllocationDescription: """Information about the size and allocator used for the data""" + def __init__( self, *, @@ -35,7 +38,7 @@ class TensorDescription(google.protobuf.message.Message): shape: tensorflow.core.framework.tensor_shape_pb2.TensorShapeProto | None = ..., allocation_description: tensorflow.core.framework.allocation_description_pb2.AllocationDescription | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["allocation_description", b"allocation_description", "shape", b"shape"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["allocation_description", b"allocation_description", "dtype", b"dtype", "shape", b"shape"]) -> None: ... + def HasField(self, field_name: typing.Literal["allocation_description", b"allocation_description", "shape", b"shape"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["allocation_description", b"allocation_description", "dtype", b"dtype", "shape", b"shape"]) -> None: ... global___TensorDescription = TensorDescription diff --git a/stubs/tensorflow/tensorflow/core/framework/tensor_pb2.pyi b/stubs/tensorflow/tensorflow/core/framework/tensor_pb2.pyi index db6b81b6ae3b..59e3ad20f7d4 100644 --- a/stubs/tensorflow/tensorflow/core/framework/tensor_pb2.pyi +++ b/stubs/tensorflow/tensorflow/core/framework/tensor_pb2.pyi @@ -2,9 +2,10 @@ @generated by mypy-protobuf. Do not edit manually! isort:skip_file """ + import builtins import collections.abc -import typing as typing_extensions +import typing import google.protobuf.descriptor import google.protobuf.internal.containers @@ -15,7 +16,7 @@ import tensorflow.core.framework.types_pb2 DESCRIPTOR: google.protobuf.descriptor.FileDescriptor -@typing_extensions.final +@typing.final class TensorProto(google.protobuf.message.Message): """Protocol buffer representing a tensor.""" @@ -40,9 +41,6 @@ class TensorProto(google.protobuf.message.Message): UINT64_VAL_FIELD_NUMBER: builtins.int FLOAT8_VAL_FIELD_NUMBER: builtins.int dtype: tensorflow.core.framework.types_pb2.DataType.ValueType - @property - def tensor_shape(self) -> tensorflow.core.framework.tensor_shape_pb2.TensorShapeProto: - """Shape of the tensor. TODO(touts): sort out the 0-rank issues.""" version_number: builtins.int """Only one of the representations below is set, one of "tensor_contents" and the "xxx_val" attributes. We are not using oneof because as oneofs cannot @@ -61,6 +59,14 @@ class TensorProto(google.protobuf.message.Message): reduce serialization overhead during RPC call by avoiding serialization of many repeated small items. """ + float8_val: builtins.bytes + """DT_FLOAT8_*, use variable-sized set of bytes + (i.e. the equivalent of repeated uint8, if such a thing existed). + """ + @property + def tensor_shape(self) -> tensorflow.core.framework.tensor_shape_pb2.TensorShapeProto: + """Shape of the tensor. TODO(touts): sort out the 0-rank issues.""" + @property def half_val(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.int]: """Type specific representations that make it easy to create tensor protos in @@ -71,50 +77,59 @@ class TensorProto(google.protobuf.message.Message): DT_HALF, DT_BFLOAT16. Note that since protobuf has no int16 type, we'll have some pointless zero padding for each value here. """ + @property def float_val(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.float]: """DT_FLOAT.""" + @property def double_val(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.float]: """DT_DOUBLE.""" + @property def int_val(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.int]: """DT_INT32, DT_INT16, DT_UINT16, DT_INT8, DT_UINT8.""" + @property def string_val(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.bytes]: """DT_STRING""" + @property def scomplex_val(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.float]: """DT_COMPLEX64. scomplex_val(2*i) and scomplex_val(2*i+1) are real and imaginary parts of i-th single precision complex. """ + @property def int64_val(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.int]: """DT_INT64""" + @property def bool_val(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.bool]: """DT_BOOL""" + @property def dcomplex_val(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.float]: """DT_COMPLEX128. dcomplex_val(2*i) and dcomplex_val(2*i+1) are real and imaginary parts of i-th double precision complex. """ + @property def resource_handle_val(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[tensorflow.core.framework.resource_handle_pb2.ResourceHandleProto]: """DT_RESOURCE""" + @property def variant_val(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___VariantTensorDataProto]: """DT_VARIANT""" + @property def uint32_val(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.int]: """DT_UINT32""" + @property def uint64_val(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.int]: """DT_UINT64""" - float8_val: builtins.bytes - """DT_FLOAT8_*, use variable-sized set of bytes - (i.e. the equivalent of repeated uint8, if such a thing existed). - """ + def __init__( self, *, @@ -137,12 +152,12 @@ class TensorProto(google.protobuf.message.Message): uint64_val: collections.abc.Iterable[builtins.int] | None = ..., float8_val: builtins.bytes | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["tensor_shape", b"tensor_shape"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["bool_val", b"bool_val", "dcomplex_val", b"dcomplex_val", "double_val", b"double_val", "dtype", b"dtype", "float8_val", b"float8_val", "float_val", b"float_val", "half_val", b"half_val", "int64_val", b"int64_val", "int_val", b"int_val", "resource_handle_val", b"resource_handle_val", "scomplex_val", b"scomplex_val", "string_val", b"string_val", "tensor_content", b"tensor_content", "tensor_shape", b"tensor_shape", "uint32_val", b"uint32_val", "uint64_val", b"uint64_val", "variant_val", b"variant_val", "version_number", b"version_number"]) -> None: ... + def HasField(self, field_name: typing.Literal["tensor_shape", b"tensor_shape"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["bool_val", b"bool_val", "dcomplex_val", b"dcomplex_val", "double_val", b"double_val", "dtype", b"dtype", "float8_val", b"float8_val", "float_val", b"float_val", "half_val", b"half_val", "int64_val", b"int64_val", "int_val", b"int_val", "resource_handle_val", b"resource_handle_val", "scomplex_val", b"scomplex_val", "string_val", b"string_val", "tensor_content", b"tensor_content", "tensor_shape", b"tensor_shape", "uint32_val", b"uint32_val", "uint64_val", b"uint64_val", "variant_val", b"variant_val", "version_number", b"version_number"]) -> None: ... global___TensorProto = TensorProto -@typing_extensions.final +@typing.final class VariantTensorDataProto(google.protobuf.message.Message): """Protocol buffer representing the serialization format of DT_VARIANT tensors.""" @@ -158,6 +173,7 @@ class VariantTensorDataProto(google.protobuf.message.Message): @property def tensors(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___TensorProto]: """Tensors contained within objects being serialized.""" + def __init__( self, *, @@ -165,6 +181,6 @@ class VariantTensorDataProto(google.protobuf.message.Message): metadata: builtins.bytes | None = ..., tensors: collections.abc.Iterable[global___TensorProto] | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["metadata", b"metadata", "tensors", b"tensors", "type_name", b"type_name"]) -> None: ... + def ClearField(self, field_name: typing.Literal["metadata", b"metadata", "tensors", b"tensors", "type_name", b"type_name"]) -> None: ... global___VariantTensorDataProto = VariantTensorDataProto diff --git a/stubs/tensorflow/tensorflow/core/framework/tensor_shape_pb2.pyi b/stubs/tensorflow/tensorflow/core/framework/tensor_shape_pb2.pyi index 04c31cdeeffe..2d852a920271 100644 --- a/stubs/tensorflow/tensorflow/core/framework/tensor_shape_pb2.pyi +++ b/stubs/tensorflow/tensorflow/core/framework/tensor_shape_pb2.pyi @@ -2,9 +2,10 @@ @generated by mypy-protobuf. Do not edit manually! isort:skip_file Protocol buffer representing the shape of tensors.""" + import builtins import collections.abc -import typing as typing_extensions +import typing import google.protobuf.descriptor import google.protobuf.internal.containers @@ -12,13 +13,13 @@ import google.protobuf.message DESCRIPTOR: google.protobuf.descriptor.FileDescriptor -@typing_extensions.final +@typing.final class TensorShapeProto(google.protobuf.message.Message): """Dimensions of a tensor.""" DESCRIPTOR: google.protobuf.descriptor.Descriptor - @typing_extensions.final + @typing.final class Dim(google.protobuf.message.Message): """One dimension of the tensor.""" @@ -41,10 +42,15 @@ class TensorShapeProto(google.protobuf.message.Message): size: builtins.int | None = ..., name: builtins.str | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["name", b"name", "size", b"size"]) -> None: ... + def ClearField(self, field_name: typing.Literal["name", b"name", "size", b"size"]) -> None: ... DIM_FIELD_NUMBER: builtins.int UNKNOWN_RANK_FIELD_NUMBER: builtins.int + unknown_rank: builtins.bool + """If true, the number of dimensions in the shape is unknown. + + If true, "dim.size()" must be 0. + """ @property def dim(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___TensorShapeProto.Dim]: """Dimensions of the tensor, such as {"input", 30}, {"output", 40} @@ -61,17 +67,13 @@ class TensorShapeProto(google.protobuf.message.Message): If "dim.size()" > 0, "unknown_rank" must be false. """ - unknown_rank: builtins.bool - """If true, the number of dimensions in the shape is unknown. - If true, "dim.size()" must be 0. - """ def __init__( self, *, dim: collections.abc.Iterable[global___TensorShapeProto.Dim] | None = ..., unknown_rank: builtins.bool | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["dim", b"dim", "unknown_rank", b"unknown_rank"]) -> None: ... + def ClearField(self, field_name: typing.Literal["dim", b"dim", "unknown_rank", b"unknown_rank"]) -> None: ... global___TensorShapeProto = TensorShapeProto diff --git a/stubs/tensorflow/tensorflow/core/framework/tensor_slice_pb2.pyi b/stubs/tensorflow/tensorflow/core/framework/tensor_slice_pb2.pyi index 640fa1c6f47b..949fd0f1d6a3 100644 --- a/stubs/tensorflow/tensorflow/core/framework/tensor_slice_pb2.pyi +++ b/stubs/tensorflow/tensorflow/core/framework/tensor_slice_pb2.pyi @@ -2,9 +2,10 @@ @generated by mypy-protobuf. Do not edit manually! isort:skip_file Protocol buffer representing slices of a tensor""" + import builtins import collections.abc -import typing as typing_extensions +import typing import google.protobuf.descriptor import google.protobuf.internal.containers @@ -12,13 +13,13 @@ import google.protobuf.message DESCRIPTOR: google.protobuf.descriptor.FileDescriptor -@typing_extensions.final +@typing.final class TensorSliceProto(google.protobuf.message.Message): """Can only be interpreted if you know the corresponding TensorShape.""" DESCRIPTOR: google.protobuf.descriptor.Descriptor - @typing_extensions.final + @typing.final class Extent(google.protobuf.message.Message): """Extent of the slice in one dimension. Either both or no attributes must be set. When no attribute is set @@ -38,9 +39,9 @@ class TensorSliceProto(google.protobuf.message.Message): start: builtins.int | None = ..., length: builtins.int | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["has_length", b"has_length", "length", b"length"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["has_length", b"has_length", "length", b"length", "start", b"start"]) -> None: ... - def WhichOneof(self, oneof_group: typing_extensions.Literal["has_length", b"has_length"]) -> typing_extensions.Literal["length"] | None: ... + def HasField(self, field_name: typing.Literal["has_length", b"has_length", "length", b"length"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["has_length", b"has_length", "length", b"length", "start", b"start"]) -> None: ... + def WhichOneof(self, oneof_group: typing.Literal["has_length", b"has_length"]) -> typing.Literal["length"] | None: ... EXTENT_FIELD_NUMBER: builtins.int @property @@ -51,11 +52,12 @@ class TensorSliceProto(google.protobuf.message.Message): slice belongs to. The order of sizes is the same as the order of dimensions in the TensorShape. """ + def __init__( self, *, extent: collections.abc.Iterable[global___TensorSliceProto.Extent] | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["extent", b"extent"]) -> None: ... + def ClearField(self, field_name: typing.Literal["extent", b"extent"]) -> None: ... global___TensorSliceProto = TensorSliceProto diff --git a/stubs/tensorflow/tensorflow/core/framework/types_pb2.pyi b/stubs/tensorflow/tensorflow/core/framework/types_pb2.pyi index 9f4d4fea804f..22ff38234dd2 100644 --- a/stubs/tensorflow/tensorflow/core/framework/types_pb2.pyi +++ b/stubs/tensorflow/tensorflow/core/framework/types_pb2.pyi @@ -2,6 +2,7 @@ @generated by mypy-protobuf. Do not edit manually! isort:skip_file """ + import builtins import sys import typing @@ -177,7 +178,7 @@ DT_FLOAT8_E5M2_REF: DataType.ValueType # 124 DT_FLOAT8_E4M3FN_REF: DataType.ValueType # 125 global___DataType = DataType -@typing_extensions.final +@typing.final class SerializedDType(google.protobuf.message.Message): """Represents a serialized tf.dtypes.Dtype""" @@ -190,6 +191,6 @@ class SerializedDType(google.protobuf.message.Message): *, datatype: global___DataType.ValueType | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["datatype", b"datatype"]) -> None: ... + def ClearField(self, field_name: typing.Literal["datatype", b"datatype"]) -> None: ... global___SerializedDType = SerializedDType diff --git a/stubs/tensorflow/tensorflow/core/framework/variable_pb2.pyi b/stubs/tensorflow/tensorflow/core/framework/variable_pb2.pyi index 2c7796d2f573..2d2320096e66 100644 --- a/stubs/tensorflow/tensorflow/core/framework/variable_pb2.pyi +++ b/stubs/tensorflow/tensorflow/core/framework/variable_pb2.pyi @@ -2,6 +2,7 @@ @generated by mypy-protobuf. Do not edit manually! isort:skip_file """ + import builtins import collections.abc import sys @@ -109,7 +110,7 @@ global step counter. """ global___VariableAggregation = VariableAggregation -@typing_extensions.final +@typing.final class VariableDef(google.protobuf.message.Message): """Protocol buffer representing a Variable.""" @@ -132,9 +133,6 @@ class VariableDef(google.protobuf.message.Message): """Name of the initializer op.""" snapshot_name: builtins.str """Name of the snapshot tensor.""" - @property - def save_slice_info_def(self) -> global___SaveSliceInfoDef: - """Support for saving variables as slices of a larger variable.""" is_resource: builtins.bool """Whether to represent this as a ResourceVariable.""" trainable: builtins.bool @@ -143,6 +141,10 @@ class VariableDef(google.protobuf.message.Message): """Indicates when a distributed variable will be synced.""" aggregation: global___VariableAggregation.ValueType """Indicates how a distributed variable will be aggregated.""" + @property + def save_slice_info_def(self) -> global___SaveSliceInfoDef: + """Support for saving variables as slices of a larger variable.""" + def __init__( self, *, @@ -156,12 +158,12 @@ class VariableDef(google.protobuf.message.Message): synchronization: global___VariableSynchronization.ValueType | None = ..., aggregation: global___VariableAggregation.ValueType | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["save_slice_info_def", b"save_slice_info_def"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["aggregation", b"aggregation", "initial_value_name", b"initial_value_name", "initializer_name", b"initializer_name", "is_resource", b"is_resource", "save_slice_info_def", b"save_slice_info_def", "snapshot_name", b"snapshot_name", "synchronization", b"synchronization", "trainable", b"trainable", "variable_name", b"variable_name"]) -> None: ... + def HasField(self, field_name: typing.Literal["save_slice_info_def", b"save_slice_info_def"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["aggregation", b"aggregation", "initial_value_name", b"initial_value_name", "initializer_name", b"initializer_name", "is_resource", b"is_resource", "save_slice_info_def", b"save_slice_info_def", "snapshot_name", b"snapshot_name", "synchronization", b"synchronization", "trainable", b"trainable", "variable_name", b"variable_name"]) -> None: ... global___VariableDef = VariableDef -@typing_extensions.final +@typing.final class SaveSliceInfoDef(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -174,12 +176,15 @@ class SaveSliceInfoDef(google.protobuf.message.Message): @property def full_shape(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.int]: """Shape of the full variable.""" + @property def var_offset(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.int]: """Offset of this variable into the full variable.""" + @property def var_shape(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.int]: """Shape of this variable.""" + def __init__( self, *, @@ -188,6 +193,6 @@ class SaveSliceInfoDef(google.protobuf.message.Message): var_offset: collections.abc.Iterable[builtins.int] | None = ..., var_shape: collections.abc.Iterable[builtins.int] | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["full_name", b"full_name", "full_shape", b"full_shape", "var_offset", b"var_offset", "var_shape", b"var_shape"]) -> None: ... + def ClearField(self, field_name: typing.Literal["full_name", b"full_name", "full_shape", b"full_shape", "var_offset", b"var_offset", "var_shape", b"var_shape"]) -> None: ... global___SaveSliceInfoDef = SaveSliceInfoDef diff --git a/stubs/tensorflow/tensorflow/core/framework/versions_pb2.pyi b/stubs/tensorflow/tensorflow/core/framework/versions_pb2.pyi index ec22a6f1d778..7ca17c36bdfd 100644 --- a/stubs/tensorflow/tensorflow/core/framework/versions_pb2.pyi +++ b/stubs/tensorflow/tensorflow/core/framework/versions_pb2.pyi @@ -2,9 +2,10 @@ @generated by mypy-protobuf. Do not edit manually! isort:skip_file """ + import builtins import collections.abc -import typing as typing_extensions +import typing import google.protobuf.descriptor import google.protobuf.internal.containers @@ -12,7 +13,7 @@ import google.protobuf.message DESCRIPTOR: google.protobuf.descriptor.FileDescriptor -@typing_extensions.final +@typing.final class VersionDef(google.protobuf.message.Message): """Version information for a piece of serialized data @@ -40,6 +41,7 @@ class VersionDef(google.protobuf.message.Message): @property def bad_consumers(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.int]: """Specific consumer versions which are disallowed (e.g. due to bugs).""" + def __init__( self, *, @@ -47,6 +49,6 @@ class VersionDef(google.protobuf.message.Message): min_consumer: builtins.int | None = ..., bad_consumers: collections.abc.Iterable[builtins.int] | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["bad_consumers", b"bad_consumers", "min_consumer", b"min_consumer", "producer", b"producer"]) -> None: ... + def ClearField(self, field_name: typing.Literal["bad_consumers", b"bad_consumers", "min_consumer", b"min_consumer", "producer", b"producer"]) -> None: ... global___VersionDef = VersionDef diff --git a/stubs/tensorflow/tensorflow/core/protobuf/bfc_memory_map_pb2.pyi b/stubs/tensorflow/tensorflow/core/protobuf/bfc_memory_map_pb2.pyi index 6733cfe87ee3..81bdbd56d9f7 100644 --- a/stubs/tensorflow/tensorflow/core/protobuf/bfc_memory_map_pb2.pyi +++ b/stubs/tensorflow/tensorflow/core/protobuf/bfc_memory_map_pb2.pyi @@ -2,6 +2,7 @@ @generated by mypy-protobuf. Do not edit manually! isort:skip_file """ + import google.protobuf.descriptor from tensorflow.tsl.protobuf.bfc_memory_map_pb2 import ( BinSummary as BinSummary, diff --git a/stubs/tensorflow/tensorflow/core/protobuf/cluster_pb2.pyi b/stubs/tensorflow/tensorflow/core/protobuf/cluster_pb2.pyi index 8fb3dd48bde8..de831c2eb9c0 100644 --- a/stubs/tensorflow/tensorflow/core/protobuf/cluster_pb2.pyi +++ b/stubs/tensorflow/tensorflow/core/protobuf/cluster_pb2.pyi @@ -16,9 +16,10 @@ See the License for the specific language governing permissions and limitations under the License. ============================================================================== """ + import builtins import collections.abc -import typing as typing_extensions +import typing import google.protobuf.descriptor import google.protobuf.internal.containers @@ -26,7 +27,7 @@ import google.protobuf.message DESCRIPTOR: google.protobuf.descriptor.FileDescriptor -@typing_extensions.final +@typing.final class JobDef(google.protobuf.message.Message): """This file contains protos to be used when defining a TensorFlow cluster. @@ -74,7 +75,7 @@ class JobDef(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor - @typing_extensions.final + @typing.final class TasksEntry(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -88,7 +89,7 @@ class JobDef(google.protobuf.message.Message): key: builtins.int | None = ..., value: builtins.str | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["key", b"key", "value", b"value"]) -> None: ... + def ClearField(self, field_name: typing.Literal["key", b"key", "value", b"value"]) -> None: ... NAME_FIELD_NUMBER: builtins.int TASKS_FIELD_NUMBER: builtins.int @@ -102,17 +103,18 @@ class JobDef(google.protobuf.message.Message): mapping from 7 to "example.org:2222", then the device prefix "/job:worker/task:7" will be assigned to "example.org:2222". """ + def __init__( self, *, name: builtins.str | None = ..., tasks: collections.abc.Mapping[builtins.int, builtins.str] | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["name", b"name", "tasks", b"tasks"]) -> None: ... + def ClearField(self, field_name: typing.Literal["name", b"name", "tasks", b"tasks"]) -> None: ... global___JobDef = JobDef -@typing_extensions.final +@typing.final class ClusterDef(google.protobuf.message.Message): """Defines a TensorFlow cluster as a set of jobs.""" @@ -122,11 +124,12 @@ class ClusterDef(google.protobuf.message.Message): @property def job(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___JobDef]: """The jobs that comprise the cluster.""" + def __init__( self, *, job: collections.abc.Iterable[global___JobDef] | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["job", b"job"]) -> None: ... + def ClearField(self, field_name: typing.Literal["job", b"job"]) -> None: ... global___ClusterDef = ClusterDef diff --git a/stubs/tensorflow/tensorflow/core/protobuf/composite_tensor_variant_pb2.pyi b/stubs/tensorflow/tensorflow/core/protobuf/composite_tensor_variant_pb2.pyi index 3fe68dfe4262..1dbe6e5573b5 100644 --- a/stubs/tensorflow/tensorflow/core/protobuf/composite_tensor_variant_pb2.pyi +++ b/stubs/tensorflow/tensorflow/core/protobuf/composite_tensor_variant_pb2.pyi @@ -2,8 +2,9 @@ @generated by mypy-protobuf. Do not edit manually! isort:skip_file """ + import builtins -import typing as typing_extensions +import typing import google.protobuf.descriptor import google.protobuf.message @@ -11,7 +12,7 @@ import tensorflow.core.protobuf.struct_pb2 DESCRIPTOR: google.protobuf.descriptor.FileDescriptor -@typing_extensions.final +@typing.final class CompositeTensorVariantMetadata(google.protobuf.message.Message): """Metadata for CompositeTensorVariant, used when serializing as Variant. @@ -30,7 +31,7 @@ class CompositeTensorVariantMetadata(google.protobuf.message.Message): *, type_spec_proto: tensorflow.core.protobuf.struct_pb2.TypeSpecProto | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["type_spec_proto", b"type_spec_proto"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["type_spec_proto", b"type_spec_proto"]) -> None: ... + def HasField(self, field_name: typing.Literal["type_spec_proto", b"type_spec_proto"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["type_spec_proto", b"type_spec_proto"]) -> None: ... global___CompositeTensorVariantMetadata = CompositeTensorVariantMetadata diff --git a/stubs/tensorflow/tensorflow/core/protobuf/config_pb2.pyi b/stubs/tensorflow/tensorflow/core/protobuf/config_pb2.pyi index d45828cd305c..27d4e9798274 100644 --- a/stubs/tensorflow/tensorflow/core/protobuf/config_pb2.pyi +++ b/stubs/tensorflow/tensorflow/core/protobuf/config_pb2.pyi @@ -2,6 +2,7 @@ @generated by mypy-protobuf. Do not edit manually! isort:skip_file """ + import builtins import collections.abc import sys @@ -27,15 +28,15 @@ else: DESCRIPTOR: google.protobuf.descriptor.FileDescriptor -@typing_extensions.final +@typing.final class GPUOptions(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor - @typing_extensions.final + @typing.final class Experimental(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor - @typing_extensions.final + @typing.final class VirtualDevices(google.protobuf.message.Message): """Configuration for breaking down a visible GPU into multiple "virtual" devices. @@ -57,6 +58,7 @@ class GPUOptions(google.protobuf.message.Message): For the concept of "visible" and "virtual" GPU, see the comments for "visible_device_list" above for more information. """ + @property def priority(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.int]: """Priority values to use with the virtual devices. Use the cuda function @@ -70,6 +72,7 @@ class GPUOptions(google.protobuf.message.Message): created with the default. If this field has values set, then the size of this must match with the above memory_limit_mb. """ + @property def device_ordinal(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.int]: """Virtual Device ordinal number determines the device ID of the device. @@ -77,6 +80,7 @@ class GPUOptions(google.protobuf.message.Message): smaller device id. The phyiscal device id and location in the virtual device list is used to break ties. """ + def __init__( self, *, @@ -84,7 +88,7 @@ class GPUOptions(google.protobuf.message.Message): priority: collections.abc.Iterable[builtins.int] | None = ..., device_ordinal: collections.abc.Iterable[builtins.int] | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["device_ordinal", b"device_ordinal", "memory_limit_mb", b"memory_limit_mb", "priority", b"priority"]) -> None: ... + def ClearField(self, field_name: typing.Literal["device_ordinal", b"device_ordinal", "memory_limit_mb", b"memory_limit_mb", "priority", b"priority"]) -> None: ... VIRTUAL_DEVICES_FIELD_NUMBER: builtins.int USE_UNIFIED_MEMORY_FIELD_NUMBER: builtins.int @@ -99,47 +103,6 @@ class GPUOptions(google.protobuf.message.Message): DISALLOW_RETRY_ON_ALLOCATION_FAILURE_FIELD_NUMBER: builtins.int GPU_HOST_MEM_LIMIT_IN_MB_FIELD_NUMBER: builtins.int GPU_HOST_MEM_DISALLOW_GROWTH_FIELD_NUMBER: builtins.int - @property - def virtual_devices(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___GPUOptions.Experimental.VirtualDevices]: - """The multi virtual device settings. If empty (not set), it will create - single virtual device on each visible GPU, according to the settings - in "visible_device_list" above. Otherwise, the number of elements in the - list must be the same as the number of visible GPUs (after - "visible_device_list" filtering if it is set), and the string represented - device names (e.g. /device:GPU:) will refer to the virtual - devices and have the field assigned sequentially starting from 0, - according to the order of the virtual devices determined by - device_ordinal and the location in the virtual device list. - - For example, - visible_device_list = "1,0" - virtual_devices { memory_limit: 1GB memory_limit: 2GB } - virtual_devices { memory_limit: 3GB memory_limit: 4GB } - will create 4 virtual devices as: - /device:GPU:0 -> visible GPU 1 with 1GB memory - /device:GPU:1 -> visible GPU 1 with 2GB memory - /device:GPU:2 -> visible GPU 0 with 3GB memory - /device:GPU:3 -> visible GPU 0 with 4GB memory - - but - visible_device_list = "1,0" - virtual_devices { memory_limit: 1GB memory_limit: 2GB - device_ordinal: 10 device_ordinal: 20} - virtual_devices { memory_limit: 3GB memory_limit: 4GB - device_ordinal: 10 device_ordinal: 20} - will create 4 virtual devices as: - /device:GPU:0 -> visible GPU 1 with 1GB memory (ordinal 10) - /device:GPU:1 -> visible GPU 0 with 3GB memory (ordinal 10) - /device:GPU:2 -> visible GPU 1 with 2GB memory (ordinal 20) - /device:GPU:3 -> visible GPU 0 with 4GB memory (ordinal 20) - - NOTE: - 1. It's invalid to set both this and "per_process_gpu_memory_fraction" - at the same time. - 2. Currently this setting is per-process, not per-session. Using - different settings in different sessions within same process will - result in undefined behavior. - """ use_unified_memory: builtins.bool """If true, uses CUDA unified memory for memory allocations. If per_process_gpu_memory_fraction option is greater than 1.0, then unified @@ -222,6 +185,48 @@ class GPUOptions(google.protobuf.message.Message): gpu_host_mem_limit_in_mb, because the default GPU host memory limit is quite high. """ + @property + def virtual_devices(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___GPUOptions.Experimental.VirtualDevices]: + """The multi virtual device settings. If empty (not set), it will create + single virtual device on each visible GPU, according to the settings + in "visible_device_list" above. Otherwise, the number of elements in the + list must be the same as the number of visible GPUs (after + "visible_device_list" filtering if it is set), and the string represented + device names (e.g. /device:GPU:) will refer to the virtual + devices and have the field assigned sequentially starting from 0, + according to the order of the virtual devices determined by + device_ordinal and the location in the virtual device list. + + For example, + visible_device_list = "1,0" + virtual_devices { memory_limit: 1GB memory_limit: 2GB } + virtual_devices { memory_limit: 3GB memory_limit: 4GB } + will create 4 virtual devices as: + /device:GPU:0 -> visible GPU 1 with 1GB memory + /device:GPU:1 -> visible GPU 1 with 2GB memory + /device:GPU:2 -> visible GPU 0 with 3GB memory + /device:GPU:3 -> visible GPU 0 with 4GB memory + + but + visible_device_list = "1,0" + virtual_devices { memory_limit: 1GB memory_limit: 2GB + device_ordinal: 10 device_ordinal: 20} + virtual_devices { memory_limit: 3GB memory_limit: 4GB + device_ordinal: 10 device_ordinal: 20} + will create 4 virtual devices as: + /device:GPU:0 -> visible GPU 1 with 1GB memory (ordinal 10) + /device:GPU:1 -> visible GPU 0 with 3GB memory (ordinal 10) + /device:GPU:2 -> visible GPU 1 with 2GB memory (ordinal 20) + /device:GPU:3 -> visible GPU 0 with 4GB memory (ordinal 20) + + NOTE: + 1. It's invalid to set both this and "per_process_gpu_memory_fraction" + at the same time. + 2. Currently this setting is per-process, not per-session. Using + different settings in different sessions within same process will + result in undefined behavior. + """ + def __init__( self, *, @@ -239,7 +244,7 @@ class GPUOptions(google.protobuf.message.Message): gpu_host_mem_limit_in_mb: builtins.float | None = ..., gpu_host_mem_disallow_growth: builtins.bool | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["collective_ring_order", b"collective_ring_order", "disallow_retry_on_allocation_failure", b"disallow_retry_on_allocation_failure", "gpu_host_mem_disallow_growth", b"gpu_host_mem_disallow_growth", "gpu_host_mem_limit_in_mb", b"gpu_host_mem_limit_in_mb", "internal_fragmentation_fraction", b"internal_fragmentation_fraction", "kernel_tracker_max_bytes", b"kernel_tracker_max_bytes", "kernel_tracker_max_interval", b"kernel_tracker_max_interval", "kernel_tracker_max_pending", b"kernel_tracker_max_pending", "num_dev_to_dev_copy_streams", b"num_dev_to_dev_copy_streams", "timestamped_allocator", b"timestamped_allocator", "use_cuda_malloc_async", b"use_cuda_malloc_async", "use_unified_memory", b"use_unified_memory", "virtual_devices", b"virtual_devices"]) -> None: ... + def ClearField(self, field_name: typing.Literal["collective_ring_order", b"collective_ring_order", "disallow_retry_on_allocation_failure", b"disallow_retry_on_allocation_failure", "gpu_host_mem_disallow_growth", b"gpu_host_mem_disallow_growth", "gpu_host_mem_limit_in_mb", b"gpu_host_mem_limit_in_mb", "internal_fragmentation_fraction", b"internal_fragmentation_fraction", "kernel_tracker_max_bytes", b"kernel_tracker_max_bytes", "kernel_tracker_max_interval", b"kernel_tracker_max_interval", "kernel_tracker_max_pending", b"kernel_tracker_max_pending", "num_dev_to_dev_copy_streams", b"num_dev_to_dev_copy_streams", "timestamped_allocator", b"timestamped_allocator", "use_cuda_malloc_async", b"use_cuda_malloc_async", "use_unified_memory", b"use_unified_memory", "virtual_devices", b"virtual_devices"]) -> None: ... PER_PROCESS_GPU_MEMORY_FRACTION_FIELD_NUMBER: builtins.int ALLOW_GROWTH_FIELD_NUMBER: builtins.int @@ -336,6 +341,7 @@ class GPUOptions(google.protobuf.message.Message): to API stability guarantees in https://www.tensorflow.org/guide/version_compat. """ + def __init__( self, *, @@ -349,12 +355,12 @@ class GPUOptions(google.protobuf.message.Message): force_gpu_compatible: builtins.bool | None = ..., experimental: global___GPUOptions.Experimental | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["experimental", b"experimental"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["allocator_type", b"allocator_type", "allow_growth", b"allow_growth", "deferred_deletion_bytes", b"deferred_deletion_bytes", "experimental", b"experimental", "force_gpu_compatible", b"force_gpu_compatible", "per_process_gpu_memory_fraction", b"per_process_gpu_memory_fraction", "polling_active_delay_usecs", b"polling_active_delay_usecs", "polling_inactive_delay_msecs", b"polling_inactive_delay_msecs", "visible_device_list", b"visible_device_list"]) -> None: ... + def HasField(self, field_name: typing.Literal["experimental", b"experimental"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["allocator_type", b"allocator_type", "allow_growth", b"allow_growth", "deferred_deletion_bytes", b"deferred_deletion_bytes", "experimental", b"experimental", "force_gpu_compatible", b"force_gpu_compatible", "per_process_gpu_memory_fraction", b"per_process_gpu_memory_fraction", "polling_active_delay_usecs", b"polling_active_delay_usecs", "polling_inactive_delay_msecs", b"polling_inactive_delay_msecs", "visible_device_list", b"visible_device_list"]) -> None: ... global___GPUOptions = GPUOptions -@typing_extensions.final +@typing.final class OptimizerOptions(google.protobuf.message.Message): """Options passed to the graph optimizer""" @@ -466,11 +472,11 @@ class OptimizerOptions(google.protobuf.message.Message): global_jit_level: global___OptimizerOptions.GlobalJitLevel.ValueType | None = ..., cpu_global_jit: builtins.bool | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["cpu_global_jit", b"cpu_global_jit", "do_common_subexpression_elimination", b"do_common_subexpression_elimination", "do_constant_folding", b"do_constant_folding", "do_function_inlining", b"do_function_inlining", "global_jit_level", b"global_jit_level", "max_folded_constant_in_bytes", b"max_folded_constant_in_bytes", "opt_level", b"opt_level"]) -> None: ... + def ClearField(self, field_name: typing.Literal["cpu_global_jit", b"cpu_global_jit", "do_common_subexpression_elimination", b"do_common_subexpression_elimination", "do_constant_folding", b"do_constant_folding", "do_function_inlining", b"do_function_inlining", "global_jit_level", b"global_jit_level", "max_folded_constant_in_bytes", b"max_folded_constant_in_bytes", "opt_level", b"opt_level"]) -> None: ... global___OptimizerOptions = OptimizerOptions -@typing_extensions.final +@typing.final class GraphOptions(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -487,9 +493,6 @@ class GraphOptions(google.protobuf.message.Message): """If true, use control flow to schedule the activation of Recv nodes. (Currently ignored.) """ - @property - def optimizer_options(self) -> global___OptimizerOptions: - """Options controlling how graph is optimized.""" build_cost_model: builtins.int """The number of steps to run before returning a cost model detailing the memory usage and performance of each node of the graph. 0 means @@ -518,12 +521,17 @@ class GraphOptions(google.protobuf.message.Message): """If > 0, record a timeline every this many steps. EXPERIMENTAL: This currently has no effect in MasterSession. """ + @property + def optimizer_options(self) -> global___OptimizerOptions: + """Options controlling how graph is optimized.""" + @property def rewrite_options(self) -> tensorflow.core.protobuf.rewriter_config_pb2.RewriterConfig: """Options that control the type and amount of graph rewriting. Not currently configurable via the public Python API (i.e. there is no API stability guarantee if you import RewriterConfig explicitly). """ + def __init__( self, *, @@ -537,12 +545,12 @@ class GraphOptions(google.protobuf.message.Message): timeline_step: builtins.int | None = ..., rewrite_options: tensorflow.core.protobuf.rewriter_config_pb2.RewriterConfig | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["optimizer_options", b"optimizer_options", "rewrite_options", b"rewrite_options"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["build_cost_model", b"build_cost_model", "build_cost_model_after", b"build_cost_model_after", "enable_bfloat16_sendrecv", b"enable_bfloat16_sendrecv", "enable_recv_scheduling", b"enable_recv_scheduling", "infer_shapes", b"infer_shapes", "optimizer_options", b"optimizer_options", "place_pruned_graph", b"place_pruned_graph", "rewrite_options", b"rewrite_options", "timeline_step", b"timeline_step"]) -> None: ... + def HasField(self, field_name: typing.Literal["optimizer_options", b"optimizer_options", "rewrite_options", b"rewrite_options"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["build_cost_model", b"build_cost_model", "build_cost_model_after", b"build_cost_model_after", "enable_bfloat16_sendrecv", b"enable_bfloat16_sendrecv", "enable_recv_scheduling", b"enable_recv_scheduling", "infer_shapes", b"infer_shapes", "optimizer_options", b"optimizer_options", "place_pruned_graph", b"place_pruned_graph", "rewrite_options", b"rewrite_options", "timeline_step", b"timeline_step"]) -> None: ... global___GraphOptions = GraphOptions -@typing_extensions.final +@typing.final class ThreadPoolOptionProto(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -577,11 +585,11 @@ class ThreadPoolOptionProto(google.protobuf.message.Message): num_threads: builtins.int | None = ..., global_name: builtins.str | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["global_name", b"global_name", "num_threads", b"num_threads"]) -> None: ... + def ClearField(self, field_name: typing.Literal["global_name", b"global_name", "num_threads", b"num_threads"]) -> None: ... global___ThreadPoolOptionProto = ThreadPoolOptionProto -@typing_extensions.final +@typing.final class SessionMetadata(google.protobuf.message.Message): """Metadata about the session. @@ -606,11 +614,11 @@ class SessionMetadata(google.protobuf.message.Message): name: builtins.str | None = ..., version: builtins.int | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["name", b"name", "version", b"version"]) -> None: ... + def ClearField(self, field_name: typing.Literal["name", b"name", "version", b"version"]) -> None: ... global___SessionMetadata = SessionMetadata -@typing_extensions.final +@typing.final class ConfigProto(google.protobuf.message.Message): """Session configuration parameters. The system picks appropriate values for fields that are not set. @@ -618,7 +626,7 @@ class ConfigProto(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor - @typing_extensions.final + @typing.final class DeviceCountEntry(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -632,9 +640,9 @@ class ConfigProto(google.protobuf.message.Message): key: builtins.str | None = ..., value: builtins.int | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["key", b"key", "value", b"value"]) -> None: ... + def ClearField(self, field_name: typing.Literal["key", b"key", "value", b"value"]) -> None: ... - @typing_extensions.final + @typing.final class Experimental(google.protobuf.message.Message): """Everything inside Experimental is subject to change and is not subject to API stability guarantees in @@ -747,16 +755,6 @@ class ConfigProto(google.protobuf.message.Message): """This was promoted to a non-experimental API. Please use ConfigProto.share_cluster_devices_in_session instead. """ - @property - def session_metadata(self) -> global___SessionMetadata: - """Metadata about the session. - - If set, this can be used by the runtime and the Ops for debugging, - monitoring, etc. - - NOTE: This is currently used and propagated only by the direct session - and EagerContext. - """ optimize_for_static_graph: builtins.bool """If true, the session may treat the graph as being static for optimization purposes. @@ -812,9 +810,6 @@ class ConfigProto(google.protobuf.message.Message): """Provides a hint to XLA auto clustering to prefer forming a single large cluster that encompases most of the graph. """ - @property - def coordination_config(self) -> tensorflow.tsl.protobuf.coordination_config_pb2.CoordinationServiceConfig: - """Distributed coordination service configurations.""" disable_optimize_for_static_graph: builtins.bool """If true, the session will treat the graph as being non-static for optimization purposes. @@ -826,6 +821,21 @@ class ConfigProto(google.protobuf.message.Message): This option is meant to replace `optimize_for_static_graph` and it aims to negate its value. """ + @property + def session_metadata(self) -> global___SessionMetadata: + """Metadata about the session. + + If set, this can be used by the runtime and the Ops for debugging, + monitoring, etc. + + NOTE: This is currently used and propagated only by the direct session + and EagerContext. + """ + + @property + def coordination_config(self) -> tensorflow.tsl.protobuf.coordination_config_pb2.CoordinationServiceConfig: + """Distributed coordination service configurations.""" + def __init__( self, *, @@ -851,8 +861,8 @@ class ConfigProto(google.protobuf.message.Message): coordination_config: tensorflow.tsl.protobuf.coordination_config_pb2.CoordinationServiceConfig | None = ..., disable_optimize_for_static_graph: builtins.bool | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["coordination_config", b"coordination_config", "session_metadata", b"session_metadata"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["collective_deterministic_sequential_execution", b"collective_deterministic_sequential_execution", "collective_group_leader", b"collective_group_leader", "collective_nccl", b"collective_nccl", "coordination_config", b"coordination_config", "disable_functional_ops_lowering", b"disable_functional_ops_lowering", "disable_optimize_for_static_graph", b"disable_optimize_for_static_graph", "disable_output_partition_graphs", b"disable_output_partition_graphs", "disable_thread_spinning", b"disable_thread_spinning", "enable_mlir_bridge", b"enable_mlir_bridge", "enable_mlir_graph_optimization", b"enable_mlir_graph_optimization", "executor_type", b"executor_type", "mlir_bridge_rollout", b"mlir_bridge_rollout", "optimize_for_static_graph", b"optimize_for_static_graph", "recv_buf_max_chunk", b"recv_buf_max_chunk", "session_metadata", b"session_metadata", "share_cluster_devices_in_session", b"share_cluster_devices_in_session", "share_session_state_in_clusterspec_propagation", b"share_session_state_in_clusterspec_propagation", "use_numa_affinity", b"use_numa_affinity", "use_tfrt", b"use_tfrt", "xla_fusion_autotuner_thresh", b"xla_fusion_autotuner_thresh", "xla_prefer_single_graph_cluster", b"xla_prefer_single_graph_cluster"]) -> None: ... + def HasField(self, field_name: typing.Literal["coordination_config", b"coordination_config", "session_metadata", b"session_metadata"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["collective_deterministic_sequential_execution", b"collective_deterministic_sequential_execution", "collective_group_leader", b"collective_group_leader", "collective_nccl", b"collective_nccl", "coordination_config", b"coordination_config", "disable_functional_ops_lowering", b"disable_functional_ops_lowering", "disable_optimize_for_static_graph", b"disable_optimize_for_static_graph", "disable_output_partition_graphs", b"disable_output_partition_graphs", "disable_thread_spinning", b"disable_thread_spinning", "enable_mlir_bridge", b"enable_mlir_bridge", "enable_mlir_graph_optimization", b"enable_mlir_graph_optimization", "executor_type", b"executor_type", "mlir_bridge_rollout", b"mlir_bridge_rollout", "optimize_for_static_graph", b"optimize_for_static_graph", "recv_buf_max_chunk", b"recv_buf_max_chunk", "session_metadata", b"session_metadata", "share_cluster_devices_in_session", b"share_cluster_devices_in_session", "share_session_state_in_clusterspec_propagation", b"share_session_state_in_clusterspec_propagation", "use_numa_affinity", b"use_numa_affinity", "use_tfrt", b"use_tfrt", "xla_fusion_autotuner_thresh", b"xla_fusion_autotuner_thresh", "xla_prefer_single_graph_cluster", b"xla_prefer_single_graph_cluster"]) -> None: ... DEVICE_COUNT_FIELD_NUMBER: builtins.int INTRA_OP_PARALLELISM_THREADS_FIELD_NUMBER: builtins.int @@ -871,13 +881,6 @@ class ConfigProto(google.protobuf.message.Message): ISOLATE_SESSION_STATE_FIELD_NUMBER: builtins.int SHARE_CLUSTER_DEVICES_IN_SESSION_FIELD_NUMBER: builtins.int EXPERIMENTAL_FIELD_NUMBER: builtins.int - @property - def device_count(self) -> google.protobuf.internal.containers.ScalarMap[builtins.str, builtins.int]: - """Map from device type name (e.g., "CPU" or "GPU" ) to maximum - number of devices of that type to use. If a particular device - type is not found in the map, the system picks an appropriate - number. - """ intra_op_parallelism_threads: builtins.int """The execution of an individual op (for some op types) can be parallelized on a pool of intra_op_parallelism_threads. @@ -916,6 +919,46 @@ class ConfigProto(google.protobuf.message.Message): session_inter_op_thread_pool to have one element, whose num_threads equals inter_op_parallelism_threads. """ + placement_period: builtins.int + """Assignment of Nodes to Devices is recomputed every placement_period + steps until the system warms up (at which point the recomputation + typically slows down automatically). + """ + allow_soft_placement: builtins.bool + """Whether soft placement is allowed. If allow_soft_placement is true, + an op will be placed on CPU if + 1. there's no GPU implementation for the OP + or + 2. no GPU devices are known or registered + or + 3. need to co-locate with reftype input(s) which are from CPU. + """ + log_device_placement: builtins.bool + """Whether device placements should be logged.""" + operation_timeout_in_ms: builtins.int + """Global timeout for all blocking operations in this session. If non-zero, + and not overridden on a per-operation basis, this value will be used as the + deadline for all blocking operations. + """ + isolate_session_state: builtins.bool + """If true, any resources such as Variables used in the session will not be + shared with other sessions. However, when clusterspec propagation is + enabled, this field is ignored and sessions are always isolated. + """ + share_cluster_devices_in_session: builtins.bool + """When true, WorkerSessions are created with device attributes from the + full cluster. + This is helpful when a worker wants to partition a graph + (for example during a PartitionedCallOp). + """ + @property + def device_count(self) -> google.protobuf.internal.containers.ScalarMap[builtins.str, builtins.int]: + """Map from device type name (e.g., "CPU" or "GPU" ) to maximum + number of devices of that type to use. If a particular device + type is not found in the map, the system picks an appropriate + number. + """ + @property def session_inter_op_thread_pool(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___ThreadPoolOptionProto]: """This option is experimental - it may be replaced with a different mechanism @@ -938,56 +981,30 @@ class ConfigProto(google.protobuf.message.Message): run the non-low-priority work, even across sessions, in a single large pool. """ - placement_period: builtins.int - """Assignment of Nodes to Devices is recomputed every placement_period - steps until the system warms up (at which point the recomputation - typically slows down automatically). - """ + @property def device_filters(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.str]: """When any filters are present sessions will ignore all devices which do not match the filters. Each filter can be partially specified, e.g. "/job:ps" "/job:worker/replica:3", etc. """ + @property def gpu_options(self) -> global___GPUOptions: """Options that apply to all GPUs.""" - allow_soft_placement: builtins.bool - """Whether soft placement is allowed. If allow_soft_placement is true, - an op will be placed on CPU if - 1. there's no GPU implementation for the OP - or - 2. no GPU devices are known or registered - or - 3. need to co-locate with reftype input(s) which are from CPU. - """ - log_device_placement: builtins.bool - """Whether device placements should be logged.""" + @property def graph_options(self) -> global___GraphOptions: """Options that apply to all graphs.""" - operation_timeout_in_ms: builtins.int - """Global timeout for all blocking operations in this session. If non-zero, - and not overridden on a per-operation basis, this value will be used as the - deadline for all blocking operations. - """ + @property def rpc_options(self) -> tensorflow.tsl.protobuf.rpc_options_pb2.RPCOptions: """Options that apply when this session uses the distributed runtime.""" + @property def cluster_def(self) -> tensorflow.core.protobuf.cluster_pb2.ClusterDef: """Optional list of all workers to use in this session.""" - isolate_session_state: builtins.bool - """If true, any resources such as Variables used in the session will not be - shared with other sessions. However, when clusterspec propagation is - enabled, this field is ignored and sessions are always isolated. - """ - share_cluster_devices_in_session: builtins.bool - """When true, WorkerSessions are created with device attributes from the - full cluster. - This is helpful when a worker wants to partition a graph - (for example during a PartitionedCallOp). - """ + @property def experimental(self) -> global___ConfigProto.Experimental: ... def __init__( @@ -1011,12 +1028,12 @@ class ConfigProto(google.protobuf.message.Message): share_cluster_devices_in_session: builtins.bool | None = ..., experimental: global___ConfigProto.Experimental | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["cluster_def", b"cluster_def", "experimental", b"experimental", "gpu_options", b"gpu_options", "graph_options", b"graph_options", "rpc_options", b"rpc_options"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["allow_soft_placement", b"allow_soft_placement", "cluster_def", b"cluster_def", "device_count", b"device_count", "device_filters", b"device_filters", "experimental", b"experimental", "gpu_options", b"gpu_options", "graph_options", b"graph_options", "inter_op_parallelism_threads", b"inter_op_parallelism_threads", "intra_op_parallelism_threads", b"intra_op_parallelism_threads", "isolate_session_state", b"isolate_session_state", "log_device_placement", b"log_device_placement", "operation_timeout_in_ms", b"operation_timeout_in_ms", "placement_period", b"placement_period", "rpc_options", b"rpc_options", "session_inter_op_thread_pool", b"session_inter_op_thread_pool", "share_cluster_devices_in_session", b"share_cluster_devices_in_session", "use_per_session_threads", b"use_per_session_threads"]) -> None: ... + def HasField(self, field_name: typing.Literal["cluster_def", b"cluster_def", "experimental", b"experimental", "gpu_options", b"gpu_options", "graph_options", b"graph_options", "rpc_options", b"rpc_options"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["allow_soft_placement", b"allow_soft_placement", "cluster_def", b"cluster_def", "device_count", b"device_count", "device_filters", b"device_filters", "experimental", b"experimental", "gpu_options", b"gpu_options", "graph_options", b"graph_options", "inter_op_parallelism_threads", b"inter_op_parallelism_threads", "intra_op_parallelism_threads", b"intra_op_parallelism_threads", "isolate_session_state", b"isolate_session_state", "log_device_placement", b"log_device_placement", "operation_timeout_in_ms", b"operation_timeout_in_ms", "placement_period", b"placement_period", "rpc_options", b"rpc_options", "session_inter_op_thread_pool", b"session_inter_op_thread_pool", "share_cluster_devices_in_session", b"share_cluster_devices_in_session", "use_per_session_threads", b"use_per_session_threads"]) -> None: ... global___ConfigProto = ConfigProto -@typing_extensions.final +@typing.final class RunOptions(google.protobuf.message.Message): """Options for a single Run() call.""" @@ -1043,7 +1060,7 @@ class RunOptions(google.protobuf.message.Message): HARDWARE_TRACE: RunOptions.TraceLevel.ValueType # 2 FULL_TRACE: RunOptions.TraceLevel.ValueType # 3 - @typing_extensions.final + @typing.final class Experimental(google.protobuf.message.Message): """Everything inside Experimental is subject to change and is not subject to API stability guarantees in @@ -1052,7 +1069,7 @@ class RunOptions(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor - @typing_extensions.final + @typing.final class RunHandlerPoolOptions(google.protobuf.message.Message): """Options for run handler thread pool.""" @@ -1068,7 +1085,7 @@ class RunOptions(google.protobuf.message.Message): *, priority: builtins.int | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["priority", b"priority"]) -> None: ... + def ClearField(self, field_name: typing.Literal["priority", b"priority"]) -> None: ... COLLECTIVE_GRAPH_KEY_FIELD_NUMBER: builtins.int USE_RUN_HANDLER_POOL_FIELD_NUMBER: builtins.int @@ -1094,8 +1111,8 @@ class RunOptions(google.protobuf.message.Message): use_run_handler_pool: builtins.bool | None = ..., run_handler_pool_options: global___RunOptions.Experimental.RunHandlerPoolOptions | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["run_handler_pool_options", b"run_handler_pool_options"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["collective_graph_key", b"collective_graph_key", "run_handler_pool_options", b"run_handler_pool_options", "use_run_handler_pool", b"use_run_handler_pool"]) -> None: ... + def HasField(self, field_name: typing.Literal["run_handler_pool_options", b"run_handler_pool_options"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["collective_graph_key", b"collective_graph_key", "run_handler_pool_options", b"run_handler_pool_options", "use_run_handler_pool", b"use_run_handler_pool"]) -> None: ... TRACE_LEVEL_FIELD_NUMBER: builtins.int TIMEOUT_IN_MS_FIELD_NUMBER: builtins.int @@ -1119,9 +1136,6 @@ class RunOptions(google.protobuf.message.Message): """Whether the partition graph(s) executed by the executor(s) should be outputted via RunMetadata. """ - @property - def debug_options(self) -> tensorflow.core.protobuf.debug_pb2.DebugOptions: - """EXPERIMENTAL. Options used to initialize DebuggerState, if enabled.""" report_tensor_allocations_upon_oom: builtins.bool """When enabled, causes tensor allocation information to be included in the error message when the Run() call fails because the allocator ran @@ -1129,6 +1143,10 @@ class RunOptions(google.protobuf.message.Message): Enabling this option can slow down the Run() call. """ + @property + def debug_options(self) -> tensorflow.core.protobuf.debug_pb2.DebugOptions: + """EXPERIMENTAL. Options used to initialize DebuggerState, if enabled.""" + @property def experimental(self) -> global___RunOptions.Experimental: ... def __init__( @@ -1142,18 +1160,18 @@ class RunOptions(google.protobuf.message.Message): report_tensor_allocations_upon_oom: builtins.bool | None = ..., experimental: global___RunOptions.Experimental | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["debug_options", b"debug_options", "experimental", b"experimental"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["debug_options", b"debug_options", "experimental", b"experimental", "inter_op_thread_pool", b"inter_op_thread_pool", "output_partition_graphs", b"output_partition_graphs", "report_tensor_allocations_upon_oom", b"report_tensor_allocations_upon_oom", "timeout_in_ms", b"timeout_in_ms", "trace_level", b"trace_level"]) -> None: ... + def HasField(self, field_name: typing.Literal["debug_options", b"debug_options", "experimental", b"experimental"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["debug_options", b"debug_options", "experimental", b"experimental", "inter_op_thread_pool", b"inter_op_thread_pool", "output_partition_graphs", b"output_partition_graphs", "report_tensor_allocations_upon_oom", b"report_tensor_allocations_upon_oom", "timeout_in_ms", b"timeout_in_ms", "trace_level", b"trace_level"]) -> None: ... global___RunOptions = RunOptions -@typing_extensions.final +@typing.final class RunMetadata(google.protobuf.message.Message): """Metadata output (i.e., non-Tensor) for a single Run() call.""" DESCRIPTOR: google.protobuf.descriptor.Descriptor - @typing_extensions.final + @typing.final class FunctionGraphs(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -1163,6 +1181,7 @@ class RunMetadata(google.protobuf.message.Message): @property def partition_graphs(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[tensorflow.core.framework.graph_pb2.GraphDef]: """TODO(nareshmodi): Include some sort of function/cache-key identifier?""" + @property def pre_optimization_graph(self) -> tensorflow.core.framework.graph_pb2.GraphDef: ... @property @@ -1174,8 +1193,8 @@ class RunMetadata(google.protobuf.message.Message): pre_optimization_graph: tensorflow.core.framework.graph_pb2.GraphDef | None = ..., post_optimization_graph: tensorflow.core.framework.graph_pb2.GraphDef | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["post_optimization_graph", b"post_optimization_graph", "pre_optimization_graph", b"pre_optimization_graph"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["partition_graphs", b"partition_graphs", "post_optimization_graph", b"post_optimization_graph", "pre_optimization_graph", b"pre_optimization_graph"]) -> None: ... + def HasField(self, field_name: typing.Literal["post_optimization_graph", b"post_optimization_graph", "pre_optimization_graph", b"pre_optimization_graph"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["partition_graphs", b"partition_graphs", "post_optimization_graph", b"post_optimization_graph", "pre_optimization_graph", b"pre_optimization_graph"]) -> None: ... STEP_STATS_FIELD_NUMBER: builtins.int COST_GRAPH_FIELD_NUMBER: builtins.int @@ -1188,12 +1207,15 @@ class RunMetadata(google.protobuf.message.Message): "RunOptions" proto. EXPERIMENTAL: The format and set of events may change in future versions. """ + @property def cost_graph(self) -> tensorflow.core.framework.cost_graph_pb2.CostGraphDef: """The cost graph for the computation defined by the run call.""" + @property def partition_graphs(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[tensorflow.core.framework.graph_pb2.GraphDef]: """Graphs of the partitions executed by executors.""" + @property def function_graphs(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___RunMetadata.FunctionGraphs]: """This is only populated for graphs that are run as functions in TensorFlow @@ -1207,9 +1229,11 @@ class RunMetadata(google.protobuf.message.Message): level idea of what the built graph looks like (since the various graph optimization passes might change the structure of the graph significantly). """ + @property def session_metadata(self) -> global___SessionMetadata: """Metadata about the session.""" + def __init__( self, *, @@ -1219,12 +1243,12 @@ class RunMetadata(google.protobuf.message.Message): function_graphs: collections.abc.Iterable[global___RunMetadata.FunctionGraphs] | None = ..., session_metadata: global___SessionMetadata | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["cost_graph", b"cost_graph", "session_metadata", b"session_metadata", "step_stats", b"step_stats"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["cost_graph", b"cost_graph", "function_graphs", b"function_graphs", "partition_graphs", b"partition_graphs", "session_metadata", b"session_metadata", "step_stats", b"step_stats"]) -> None: ... + def HasField(self, field_name: typing.Literal["cost_graph", b"cost_graph", "session_metadata", b"session_metadata", "step_stats", b"step_stats"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["cost_graph", b"cost_graph", "function_graphs", b"function_graphs", "partition_graphs", b"partition_graphs", "session_metadata", b"session_metadata", "step_stats", b"step_stats"]) -> None: ... global___RunMetadata = RunMetadata -@typing_extensions.final +@typing.final class TensorConnection(google.protobuf.message.Message): """Defines a connection between two tensors in a `GraphDef`.""" @@ -1246,11 +1270,11 @@ class TensorConnection(google.protobuf.message.Message): from_tensor: builtins.str | None = ..., to_tensor: builtins.str | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["from_tensor", b"from_tensor", "to_tensor", b"to_tensor"]) -> None: ... + def ClearField(self, field_name: typing.Literal["from_tensor", b"from_tensor", "to_tensor", b"to_tensor"]) -> None: ... global___TensorConnection = TensorConnection -@typing_extensions.final +@typing.final class CallableOptions(google.protobuf.message.Message): """Defines a subgraph in another `GraphDef` as a set of feed points and nodes to be fetched or executed. @@ -1260,7 +1284,7 @@ class CallableOptions(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor - @typing_extensions.final + @typing.final class FeedDevicesEntry(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -1274,9 +1298,9 @@ class CallableOptions(google.protobuf.message.Message): key: builtins.str | None = ..., value: builtins.str | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["key", b"key", "value", b"value"]) -> None: ... + def ClearField(self, field_name: typing.Literal["key", b"key", "value", b"value"]) -> None: ... - @typing_extensions.final + @typing.final class FetchDevicesEntry(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -1290,7 +1314,7 @@ class CallableOptions(google.protobuf.message.Message): key: builtins.str | None = ..., value: builtins.str | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["key", b"key", "value", b"value"]) -> None: ... + def ClearField(self, field_name: typing.Literal["key", b"key", "value", b"value"]) -> None: ... FEED_FIELD_NUMBER: builtins.int FETCH_FIELD_NUMBER: builtins.int @@ -1300,29 +1324,46 @@ class CallableOptions(google.protobuf.message.Message): FEED_DEVICES_FIELD_NUMBER: builtins.int FETCH_DEVICES_FIELD_NUMBER: builtins.int FETCH_SKIP_SYNC_FIELD_NUMBER: builtins.int + fetch_skip_sync: builtins.bool + """By default, RunCallable() will synchronize the GPU stream before returning + fetched tensors on a GPU device, to ensure that the values in those tensors + have been produced. This simplifies interacting with the tensors, but + potentially incurs a performance hit. + + If this options is set to true, the caller is responsible for ensuring + that the values in the fetched tensors have been produced before they are + used. The caller can do this by invoking `Device::Sync()` on the underlying + device(s), or by feeding the tensors back to the same Session using + `feed_devices` with the same corresponding device name. + """ @property def feed(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.str]: """Tensors to be fed in the callable. Each feed is the name of a tensor.""" + @property def fetch(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.str]: """Fetches. A list of tensor names. The caller of the callable expects a tensor to be returned for each fetch[i] (see RunStepResponse.tensor). The order of specified fetches does not change the execution order. """ + @property def target(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.str]: """Target Nodes. A list of node names. The named nodes will be run by the callable but their outputs will not be returned. """ + @property def run_options(self) -> global___RunOptions: """Options that will be applied to each run.""" + @property def tensor_connection(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___TensorConnection]: """Tensors to be connected in the callable. Each TensorConnection denotes a pair of tensors in the graph, between which an edge will be created in the callable. """ + @property def feed_devices(self) -> google.protobuf.internal.containers.ScalarMap[builtins.str, builtins.str]: """The Tensor objects fed in the callable and fetched from the callable @@ -1373,20 +1414,9 @@ class CallableOptions(google.protobuf.message.Message): CUDA stream has been synchronized (e.g., via cuCtxSynchronize() or cuStreamSynchronize()). """ + @property def fetch_devices(self) -> google.protobuf.internal.containers.ScalarMap[builtins.str, builtins.str]: ... - fetch_skip_sync: builtins.bool - """By default, RunCallable() will synchronize the GPU stream before returning - fetched tensors on a GPU device, to ensure that the values in those tensors - have been produced. This simplifies interacting with the tensors, but - potentially incurs a performance hit. - - If this options is set to true, the caller is responsible for ensuring - that the values in the fetched tensors have been produced before they are - used. The caller can do this by invoking `Device::Sync()` on the underlying - device(s), or by feeding the tensors back to the same Session using - `feed_devices` with the same corresponding device name. - """ def __init__( self, *, @@ -1399,7 +1429,7 @@ class CallableOptions(google.protobuf.message.Message): fetch_devices: collections.abc.Mapping[builtins.str, builtins.str] | None = ..., fetch_skip_sync: builtins.bool | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["run_options", b"run_options"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["feed", b"feed", "feed_devices", b"feed_devices", "fetch", b"fetch", "fetch_devices", b"fetch_devices", "fetch_skip_sync", b"fetch_skip_sync", "run_options", b"run_options", "target", b"target", "tensor_connection", b"tensor_connection"]) -> None: ... + def HasField(self, field_name: typing.Literal["run_options", b"run_options"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["feed", b"feed", "feed_devices", b"feed_devices", "fetch", b"fetch", "fetch_devices", b"fetch_devices", "fetch_skip_sync", b"fetch_skip_sync", "run_options", b"run_options", "target", b"target", "tensor_connection", b"tensor_connection"]) -> None: ... global___CallableOptions = CallableOptions diff --git a/stubs/tensorflow/tensorflow/core/protobuf/control_flow_pb2.pyi b/stubs/tensorflow/tensorflow/core/protobuf/control_flow_pb2.pyi index dd8044f8add8..713544819ed5 100644 --- a/stubs/tensorflow/tensorflow/core/protobuf/control_flow_pb2.pyi +++ b/stubs/tensorflow/tensorflow/core/protobuf/control_flow_pb2.pyi @@ -2,9 +2,10 @@ @generated by mypy-protobuf. Do not edit manually! isort:skip_file """ + import builtins import collections.abc -import typing as typing_extensions +import typing import google.protobuf.descriptor import google.protobuf.internal.containers @@ -12,7 +13,7 @@ import google.protobuf.message DESCRIPTOR: google.protobuf.descriptor.FileDescriptor -@typing_extensions.final +@typing.final class ValuesDef(google.protobuf.message.Message): """Control flow context related protocol buffers. @@ -21,7 +22,7 @@ class ValuesDef(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor - @typing_extensions.final + @typing.final class ExternalValuesEntry(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -35,27 +36,29 @@ class ValuesDef(google.protobuf.message.Message): key: builtins.str | None = ..., value: builtins.str | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["key", b"key", "value", b"value"]) -> None: ... + def ClearField(self, field_name: typing.Literal["key", b"key", "value", b"value"]) -> None: ... VALUES_FIELD_NUMBER: builtins.int EXTERNAL_VALUES_FIELD_NUMBER: builtins.int @property def values(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.str]: """Value names that have been seen in this context.""" + @property def external_values(self) -> google.protobuf.internal.containers.ScalarMap[builtins.str, builtins.str]: """Value names referenced by but external to this context.""" + def __init__( self, *, values: collections.abc.Iterable[builtins.str] | None = ..., external_values: collections.abc.Mapping[builtins.str, builtins.str] | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["external_values", b"external_values", "values", b"values"]) -> None: ... + def ClearField(self, field_name: typing.Literal["external_values", b"external_values", "values", b"values"]) -> None: ... global___ValuesDef = ValuesDef -@typing_extensions.final +@typing.final class ControlFlowContextDef(google.protobuf.message.Message): """Container for any kind of control flow context. Any other control flow contexts that are added below should also be added here. @@ -75,13 +78,13 @@ class ControlFlowContextDef(google.protobuf.message.Message): cond_ctxt: global___CondContextDef | None = ..., while_ctxt: global___WhileContextDef | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["cond_ctxt", b"cond_ctxt", "ctxt", b"ctxt", "while_ctxt", b"while_ctxt"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["cond_ctxt", b"cond_ctxt", "ctxt", b"ctxt", "while_ctxt", b"while_ctxt"]) -> None: ... - def WhichOneof(self, oneof_group: typing_extensions.Literal["ctxt", b"ctxt"]) -> typing_extensions.Literal["cond_ctxt", "while_ctxt"] | None: ... + def HasField(self, field_name: typing.Literal["cond_ctxt", b"cond_ctxt", "ctxt", b"ctxt", "while_ctxt", b"while_ctxt"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["cond_ctxt", b"cond_ctxt", "ctxt", b"ctxt", "while_ctxt", b"while_ctxt"]) -> None: ... + def WhichOneof(self, oneof_group: typing.Literal["ctxt", b"ctxt"]) -> typing.Literal["cond_ctxt", "while_ctxt"] | None: ... global___ControlFlowContextDef = ControlFlowContextDef -@typing_extensions.final +@typing.final class CondContextDef(google.protobuf.message.Message): """Protocol buffer representing a CondContext object.""" @@ -104,9 +107,11 @@ class CondContextDef(google.protobuf.message.Message): @property def values_def(self) -> global___ValuesDef: """Values and external values in control flow context.""" + @property def nested_contexts(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___ControlFlowContextDef]: """Contexts contained inside this context (e.g. nested conds).""" + def __init__( self, *, @@ -117,12 +122,12 @@ class CondContextDef(google.protobuf.message.Message): values_def: global___ValuesDef | None = ..., nested_contexts: collections.abc.Iterable[global___ControlFlowContextDef] | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["values_def", b"values_def"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["branch", b"branch", "context_name", b"context_name", "nested_contexts", b"nested_contexts", "pivot_name", b"pivot_name", "pred_name", b"pred_name", "values_def", b"values_def"]) -> None: ... + def HasField(self, field_name: typing.Literal["values_def", b"values_def"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["branch", b"branch", "context_name", b"context_name", "nested_contexts", b"nested_contexts", "pivot_name", b"pivot_name", "pred_name", b"pred_name", "values_def", b"values_def"]) -> None: ... global___CondContextDef = CondContextDef -@typing_extensions.final +@typing.final class WhileContextDef(google.protobuf.message.Message): """Protocol buffer representing a WhileContext object.""" @@ -154,20 +159,24 @@ class WhileContextDef(google.protobuf.message.Message): """Name of the pivot_for_pred tensor.""" pivot_for_body_name: builtins.str """Name of the pivot_for_body tensor.""" + maximum_iterations_name: builtins.str + """Optional name of the maximum_iterations tensor.""" @property def loop_exit_names(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.str]: """List of names for exit tensors.""" + @property def loop_enter_names(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.str]: """List of names for enter tensors.""" + @property def values_def(self) -> global___ValuesDef: """Values and external values in control flow context.""" - maximum_iterations_name: builtins.str - """Optional name of the maximum_iterations tensor.""" + @property def nested_contexts(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___ControlFlowContextDef]: """Contexts contained inside this context (e.g. nested whiles).""" + def __init__( self, *, @@ -184,7 +193,7 @@ class WhileContextDef(google.protobuf.message.Message): maximum_iterations_name: builtins.str | None = ..., nested_contexts: collections.abc.Iterable[global___ControlFlowContextDef] | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["values_def", b"values_def"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["back_prop", b"back_prop", "context_name", b"context_name", "loop_enter_names", b"loop_enter_names", "loop_exit_names", b"loop_exit_names", "maximum_iterations_name", b"maximum_iterations_name", "nested_contexts", b"nested_contexts", "parallel_iterations", b"parallel_iterations", "pivot_for_body_name", b"pivot_for_body_name", "pivot_for_pred_name", b"pivot_for_pred_name", "pivot_name", b"pivot_name", "swap_memory", b"swap_memory", "values_def", b"values_def"]) -> None: ... + def HasField(self, field_name: typing.Literal["values_def", b"values_def"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["back_prop", b"back_prop", "context_name", b"context_name", "loop_enter_names", b"loop_enter_names", "loop_exit_names", b"loop_exit_names", "maximum_iterations_name", b"maximum_iterations_name", "nested_contexts", b"nested_contexts", "parallel_iterations", b"parallel_iterations", "pivot_for_body_name", b"pivot_for_body_name", "pivot_for_pred_name", b"pivot_for_pred_name", "pivot_name", b"pivot_name", "swap_memory", b"swap_memory", "values_def", b"values_def"]) -> None: ... global___WhileContextDef = WhileContextDef diff --git a/stubs/tensorflow/tensorflow/core/protobuf/coordination_config_pb2.pyi b/stubs/tensorflow/tensorflow/core/protobuf/coordination_config_pb2.pyi deleted file mode 100644 index c4855fe17c53..000000000000 --- a/stubs/tensorflow/tensorflow/core/protobuf/coordination_config_pb2.pyi +++ /dev/null @@ -1,108 +0,0 @@ -""" -@generated by mypy-protobuf. Do not edit manually! -isort:skip_file -""" -import builtins -import collections.abc -import typing as typing_extensions - -import google.protobuf.descriptor -import google.protobuf.internal.containers -import google.protobuf.message - -DESCRIPTOR: google.protobuf.descriptor.FileDescriptor - -@typing_extensions.final -class CoordinatedJob(google.protobuf.message.Message): - """Represents a job type and the number of tasks under this job. - For example, ("worker", 20) implies that there will be 20 worker tasks. - """ - - DESCRIPTOR: google.protobuf.descriptor.Descriptor - - NAME_FIELD_NUMBER: builtins.int - NUM_TASKS_FIELD_NUMBER: builtins.int - name: builtins.str - num_tasks: builtins.int - def __init__( - self, - *, - name: builtins.str | None = ..., - num_tasks: builtins.int | None = ..., - ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["name", b"name", "num_tasks", b"num_tasks"]) -> None: ... - -global___CoordinatedJob = CoordinatedJob - -@typing_extensions.final -class CoordinationServiceConfig(google.protobuf.message.Message): - """Coordination service configuration parameters. - The system picks appropriate values for fields that are not set. - """ - - DESCRIPTOR: google.protobuf.descriptor.Descriptor - - SERVICE_TYPE_FIELD_NUMBER: builtins.int - SERVICE_LEADER_FIELD_NUMBER: builtins.int - ENABLE_HEALTH_CHECK_FIELD_NUMBER: builtins.int - CLUSTER_REGISTER_TIMEOUT_IN_MS_FIELD_NUMBER: builtins.int - HEARTBEAT_TIMEOUT_IN_MS_FIELD_NUMBER: builtins.int - COORDINATED_JOB_LIST_FIELD_NUMBER: builtins.int - SHUTDOWN_BARRIER_TIMEOUT_IN_MS_FIELD_NUMBER: builtins.int - AGENT_DESTRUCTION_WITHOUT_SHUTDOWN_FIELD_NUMBER: builtins.int - RECOVERABLE_JOBS_FIELD_NUMBER: builtins.int - service_type: builtins.str - """Type of coordination service implementation to enable. - For example, setting the service type as "standalone" starts a service - instance on the leader task to provide the coordination services such as - heartbeats and consistent key-value store. - """ - service_leader: builtins.str - """Address where the coordination service instance is hosted.""" - enable_health_check: builtins.bool - """Whether to enable the health check mechanism.""" - cluster_register_timeout_in_ms: builtins.int - """Maximum wait time for all members in the cluster to be registered.""" - heartbeat_timeout_in_ms: builtins.int - """Heartbeat timeout, if a task does not record heartbeat in this time - window, it will be considered disconnected. - Note: This is also used as a grace period to accept any heartbeats after - the agent has disconnected, to account for the lag time between the service - recording the state change and the agent stopping heartbeats. - """ - @property - def coordinated_job_list(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___CoordinatedJob]: ... - shutdown_barrier_timeout_in_ms: builtins.int - """Denotes how long to wait for all coordination agents to reach the barriers - (after the first shutdown request) before disconnecting together. If - set to 0, no barrier is imposed upon shutdown and each worker can - disconnect individually. - """ - agent_destruction_without_shutdown: builtins.bool - """If set, agents do not make an explicit Shutdown() call. Service will only - find out about the disconnecte agent via stale heartbeats. Used for - testing. - """ - @property - def recoverable_jobs(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.str]: - """The list of jobs which are recoverable. If a task in this list fails, - it will not propagate error to other tasks. - If empty, no jobs will be recoverable and every task failure will cause - error propagation to other tasks. - """ - def __init__( - self, - *, - service_type: builtins.str | None = ..., - service_leader: builtins.str | None = ..., - enable_health_check: builtins.bool | None = ..., - cluster_register_timeout_in_ms: builtins.int | None = ..., - heartbeat_timeout_in_ms: builtins.int | None = ..., - coordinated_job_list: collections.abc.Iterable[global___CoordinatedJob] | None = ..., - shutdown_barrier_timeout_in_ms: builtins.int | None = ..., - agent_destruction_without_shutdown: builtins.bool | None = ..., - recoverable_jobs: collections.abc.Iterable[builtins.str] | None = ..., - ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["agent_destruction_without_shutdown", b"agent_destruction_without_shutdown", "cluster_register_timeout_in_ms", b"cluster_register_timeout_in_ms", "coordinated_job_list", b"coordinated_job_list", "enable_health_check", b"enable_health_check", "heartbeat_timeout_in_ms", b"heartbeat_timeout_in_ms", "recoverable_jobs", b"recoverable_jobs", "service_leader", b"service_leader", "service_type", b"service_type", "shutdown_barrier_timeout_in_ms", b"shutdown_barrier_timeout_in_ms"]) -> None: ... - -global___CoordinationServiceConfig = CoordinationServiceConfig diff --git a/stubs/tensorflow/tensorflow/core/protobuf/core_platform_payloads_pb2.pyi b/stubs/tensorflow/tensorflow/core/protobuf/core_platform_payloads_pb2.pyi index f06c008c37ba..44eea2b74e65 100644 --- a/stubs/tensorflow/tensorflow/core/protobuf/core_platform_payloads_pb2.pyi +++ b/stubs/tensorflow/tensorflow/core/protobuf/core_platform_payloads_pb2.pyi @@ -2,6 +2,7 @@ @generated by mypy-protobuf. Do not edit manually! isort:skip_file """ + import builtins import sys import typing @@ -17,7 +18,7 @@ else: DESCRIPTOR: google.protobuf.descriptor.FileDescriptor -@typing_extensions.final +@typing.final class ErrorSourceProto(google.protobuf.message.Message): """If included as a payload, this message contains the error source information where the error was raised. @@ -62,6 +63,6 @@ class ErrorSourceProto(google.protobuf.message.Message): *, error_source: global___ErrorSourceProto.ErrorSource.ValueType | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["error_source", b"error_source"]) -> None: ... + def ClearField(self, field_name: typing.Literal["error_source", b"error_source"]) -> None: ... global___ErrorSourceProto = ErrorSourceProto diff --git a/stubs/tensorflow/tensorflow/core/protobuf/data_service_pb2.pyi b/stubs/tensorflow/tensorflow/core/protobuf/data_service_pb2.pyi index 151a3d18ec47..3c149e5ee5ac 100644 --- a/stubs/tensorflow/tensorflow/core/protobuf/data_service_pb2.pyi +++ b/stubs/tensorflow/tensorflow/core/protobuf/data_service_pb2.pyi @@ -2,6 +2,7 @@ @generated by mypy-protobuf. Do not edit manually! isort:skip_file """ + import builtins import sys import typing @@ -47,7 +48,7 @@ hosts. """ global___DeploymentMode = DeploymentMode -@typing_extensions.final +@typing.final class ProcessingModeDef(google.protobuf.message.Message): """Next tag: 2""" @@ -145,11 +146,11 @@ class ProcessingModeDef(google.protobuf.message.Message): *, sharding_policy: global___ProcessingModeDef.ShardingPolicy.ValueType | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["sharding_policy", b"sharding_policy"]) -> None: ... + def ClearField(self, field_name: typing.Literal["sharding_policy", b"sharding_policy"]) -> None: ... global___ProcessingModeDef = ProcessingModeDef -@typing_extensions.final +@typing.final class DataServiceMetadata(google.protobuf.message.Message): """Metadata related to tf.data service datasets. Next tag: 4 @@ -191,13 +192,13 @@ class DataServiceMetadata(google.protobuf.message.Message): compression: global___DataServiceMetadata.Compression.ValueType | None = ..., cardinality: builtins.int | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["element_spec", b"element_spec", "optional_element_spec", b"optional_element_spec"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["cardinality", b"cardinality", "compression", b"compression", "element_spec", b"element_spec", "optional_element_spec", b"optional_element_spec"]) -> None: ... - def WhichOneof(self, oneof_group: typing_extensions.Literal["optional_element_spec", b"optional_element_spec"]) -> typing_extensions.Literal["element_spec"] | None: ... + def HasField(self, field_name: typing.Literal["element_spec", b"element_spec", "optional_element_spec", b"optional_element_spec"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["cardinality", b"cardinality", "compression", b"compression", "element_spec", b"element_spec", "optional_element_spec", b"optional_element_spec"]) -> None: ... + def WhichOneof(self, oneof_group: typing.Literal["optional_element_spec", b"optional_element_spec"]) -> typing.Literal["element_spec"] | None: ... global___DataServiceMetadata = DataServiceMetadata -@typing_extensions.final +@typing.final class CrossTrainerCacheOptions(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -208,11 +209,11 @@ class CrossTrainerCacheOptions(google.protobuf.message.Message): *, trainer_id: builtins.str | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["trainer_id", b"trainer_id"]) -> None: ... + def ClearField(self, field_name: typing.Literal["trainer_id", b"trainer_id"]) -> None: ... global___CrossTrainerCacheOptions = CrossTrainerCacheOptions -@typing_extensions.final +@typing.final class DataServiceConfig(google.protobuf.message.Message): """Data service config available to the client through GetDataServiceConfig RPC. Next tag: 2 @@ -227,6 +228,6 @@ class DataServiceConfig(google.protobuf.message.Message): *, deployment_mode: global___DeploymentMode.ValueType | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["deployment_mode", b"deployment_mode"]) -> None: ... + def ClearField(self, field_name: typing.Literal["deployment_mode", b"deployment_mode"]) -> None: ... global___DataServiceConfig = DataServiceConfig diff --git a/stubs/tensorflow/tensorflow/core/protobuf/debug_event_pb2.pyi b/stubs/tensorflow/tensorflow/core/protobuf/debug_event_pb2.pyi index 89570d7cef77..e97a92cad7c6 100644 --- a/stubs/tensorflow/tensorflow/core/protobuf/debug_event_pb2.pyi +++ b/stubs/tensorflow/tensorflow/core/protobuf/debug_event_pb2.pyi @@ -2,6 +2,7 @@ @generated by mypy-protobuf. Do not edit manually! isort:skip_file """ + import builtins import collections.abc import sys @@ -130,7 +131,7 @@ REDUCE_INF_NAN_THREE_SLOTS: TensorDebugMode.ValueType # 8 """ global___TensorDebugMode = TensorDebugMode -@typing_extensions.final +@typing.final class DebugEvent(google.protobuf.message.Message): """An Event related to the debugging of a TensorFlow program.""" @@ -151,40 +152,48 @@ class DebugEvent(google.protobuf.message.Message): """Timestamp in seconds (with microsecond precision).""" step: builtins.int """Step of training (if available).""" + graph_id: builtins.str + """The ID of the graph (i.e., FuncGraph) executed here: applicable only + to the execution of a FuncGraph. + """ @property def debug_metadata(self) -> global___DebugMetadata: """Metadata related to this debugging data.""" + @property def source_file(self) -> global___SourceFile: """The content of a source file.""" + @property def stack_frame_with_id(self) -> global___StackFrameWithId: """A stack frame (filename, line number and column number, function name and code string) with ID. """ + @property def graph_op_creation(self) -> global___GraphOpCreation: """The creation of an op within a graph (e.g., a FuncGraph compiled from a Python function). """ + @property def debugged_graph(self) -> global___DebuggedGraph: """Information about a debugged graph.""" + @property def execution(self) -> global___Execution: """Execution of an op or a Graph (e.g., a tf.function).""" + @property def graph_execution_trace(self) -> global___GraphExecutionTrace: """A graph execution trace: Contains information about the intermediate tensors computed during the graph execution. """ - graph_id: builtins.str - """The ID of the graph (i.e., FuncGraph) executed here: applicable only - to the execution of a FuncGraph. - """ + @property def debugged_device(self) -> global___DebuggedDevice: """A device on which debugger-instrumented ops and/or tensors reside.""" + def __init__( self, *, @@ -200,13 +209,13 @@ class DebugEvent(google.protobuf.message.Message): graph_id: builtins.str | None = ..., debugged_device: global___DebuggedDevice | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["debug_metadata", b"debug_metadata", "debugged_device", b"debugged_device", "debugged_graph", b"debugged_graph", "execution", b"execution", "graph_execution_trace", b"graph_execution_trace", "graph_id", b"graph_id", "graph_op_creation", b"graph_op_creation", "source_file", b"source_file", "stack_frame_with_id", b"stack_frame_with_id", "what", b"what"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["debug_metadata", b"debug_metadata", "debugged_device", b"debugged_device", "debugged_graph", b"debugged_graph", "execution", b"execution", "graph_execution_trace", b"graph_execution_trace", "graph_id", b"graph_id", "graph_op_creation", b"graph_op_creation", "source_file", b"source_file", "stack_frame_with_id", b"stack_frame_with_id", "step", b"step", "wall_time", b"wall_time", "what", b"what"]) -> None: ... - def WhichOneof(self, oneof_group: typing_extensions.Literal["what", b"what"]) -> typing_extensions.Literal["debug_metadata", "source_file", "stack_frame_with_id", "graph_op_creation", "debugged_graph", "execution", "graph_execution_trace", "graph_id", "debugged_device"] | None: ... + def HasField(self, field_name: typing.Literal["debug_metadata", b"debug_metadata", "debugged_device", b"debugged_device", "debugged_graph", b"debugged_graph", "execution", b"execution", "graph_execution_trace", b"graph_execution_trace", "graph_id", b"graph_id", "graph_op_creation", b"graph_op_creation", "source_file", b"source_file", "stack_frame_with_id", b"stack_frame_with_id", "what", b"what"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["debug_metadata", b"debug_metadata", "debugged_device", b"debugged_device", "debugged_graph", b"debugged_graph", "execution", b"execution", "graph_execution_trace", b"graph_execution_trace", "graph_id", b"graph_id", "graph_op_creation", b"graph_op_creation", "source_file", b"source_file", "stack_frame_with_id", b"stack_frame_with_id", "step", b"step", "wall_time", b"wall_time", "what", b"what"]) -> None: ... + def WhichOneof(self, oneof_group: typing.Literal["what", b"what"]) -> typing.Literal["debug_metadata", "source_file", "stack_frame_with_id", "graph_op_creation", "debugged_graph", "execution", "graph_execution_trace", "graph_id", "debugged_device"] | None: ... global___DebugEvent = DebugEvent -@typing_extensions.final +@typing.final class DebugMetadata(google.protobuf.message.Message): """Metadata about the debugger and the debugged TensorFlow program.""" @@ -234,11 +243,11 @@ class DebugMetadata(google.protobuf.message.Message): file_version: builtins.str | None = ..., tfdbg_run_id: builtins.str | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["file_version", b"file_version", "tensorflow_version", b"tensorflow_version", "tfdbg_run_id", b"tfdbg_run_id"]) -> None: ... + def ClearField(self, field_name: typing.Literal["file_version", b"file_version", "tensorflow_version", b"tensorflow_version", "tfdbg_run_id", b"tfdbg_run_id"]) -> None: ... global___DebugMetadata = DebugMetadata -@typing_extensions.final +@typing.final class SourceFile(google.protobuf.message.Message): """Content of a source file involved in the execution of the debugged TensorFlow program. @@ -256,6 +265,7 @@ class SourceFile(google.protobuf.message.Message): @property def lines(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.str]: """Line-by-line content of the file.""" + def __init__( self, *, @@ -263,11 +273,11 @@ class SourceFile(google.protobuf.message.Message): host_name: builtins.str | None = ..., lines: collections.abc.Iterable[builtins.str] | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["file_path", b"file_path", "host_name", b"host_name", "lines", b"lines"]) -> None: ... + def ClearField(self, field_name: typing.Literal["file_path", b"file_path", "host_name", b"host_name", "lines", b"lines"]) -> None: ... global___SourceFile = SourceFile -@typing_extensions.final +@typing.final class StackFrameWithId(google.protobuf.message.Message): """A stack frame with ID.""" @@ -283,18 +293,19 @@ class StackFrameWithId(google.protobuf.message.Message): regarding the file name, line number, function name, code content of the line, and column number (if available). """ + def __init__( self, *, id: builtins.str | None = ..., file_line_col: tensorflow.core.protobuf.graph_debug_info_pb2.GraphDebugInfo.FileLineCol | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["file_line_col", b"file_line_col"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["file_line_col", b"file_line_col", "id", b"id"]) -> None: ... + def HasField(self, field_name: typing.Literal["file_line_col", b"file_line_col"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["file_line_col", b"file_line_col", "id", b"id"]) -> None: ... global___StackFrameWithId = StackFrameWithId -@typing_extensions.final +@typing.final class CodeLocation(google.protobuf.message.Message): """Code location information: A stack trace with host-name information. Instead of encoding the detailed stack trace, this proto refers to IDs of @@ -313,17 +324,18 @@ class CodeLocation(google.protobuf.message.Message): by a unique ID. The ordering of the frames is consistent with Python's `traceback.extract_tb()`. """ + def __init__( self, *, host_name: builtins.str | None = ..., stack_frame_ids: collections.abc.Iterable[builtins.str] | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["host_name", b"host_name", "stack_frame_ids", b"stack_frame_ids"]) -> None: ... + def ClearField(self, field_name: typing.Literal["host_name", b"host_name", "stack_frame_ids", b"stack_frame_ids"]) -> None: ... global___CodeLocation = CodeLocation -@typing_extensions.final +@typing.final class GraphOpCreation(google.protobuf.message.Message): """The creation of an op in a TensorFlow Graph (e.g., FuncGraph in TF2).""" @@ -350,17 +362,20 @@ class GraphOpCreation(google.protobuf.message.Message): """ device_name: builtins.str """Name of the device that the op is assigned to (if available).""" + num_outputs: builtins.int + """Number of output tensors emitted by the op.""" @property def input_names(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.str]: """Names of the input tensors to the op.""" - num_outputs: builtins.int - """Number of output tensors emitted by the op.""" + @property def code_location(self) -> global___CodeLocation: """The unique ID for code location (stack trace) of the op's creation.""" + @property def output_tensor_ids(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.int]: """Unique IDs for the output tensors of this op.""" + def __init__( self, *, @@ -374,12 +389,12 @@ class GraphOpCreation(google.protobuf.message.Message): code_location: global___CodeLocation | None = ..., output_tensor_ids: collections.abc.Iterable[builtins.int] | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["code_location", b"code_location"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["code_location", b"code_location", "device_name", b"device_name", "graph_id", b"graph_id", "graph_name", b"graph_name", "input_names", b"input_names", "num_outputs", b"num_outputs", "op_name", b"op_name", "op_type", b"op_type", "output_tensor_ids", b"output_tensor_ids"]) -> None: ... + def HasField(self, field_name: typing.Literal["code_location", b"code_location"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["code_location", b"code_location", "device_name", b"device_name", "graph_id", b"graph_id", "graph_name", b"graph_name", "input_names", b"input_names", "num_outputs", b"num_outputs", "op_name", b"op_name", "op_type", b"op_type", "output_tensor_ids", b"output_tensor_ids"]) -> None: ... global___GraphOpCreation = GraphOpCreation -@typing_extensions.final +@typing.final class DebuggedGraph(google.protobuf.message.Message): """A debugger-instrumented graph.""" @@ -397,11 +412,6 @@ class DebuggedGraph(google.protobuf.message.Message): """ graph_name: builtins.str """Name of the graph (if available).""" - @property - def instrumented_ops(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.str]: - """Names of the instrumented ops. This can be used to look up op name - based on the numeric-summary tensors (2nd column). - """ original_graph_def: builtins.bytes """Original (uninstrumented) GraphDef (if available).""" instrumented_graph_def: builtins.bytes @@ -410,6 +420,12 @@ class DebuggedGraph(google.protobuf.message.Message): """ outer_context_id: builtins.str """IDs of the immediate enclosing context (graph), if any.""" + @property + def instrumented_ops(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.str]: + """Names of the instrumented ops. This can be used to look up op name + based on the numeric-summary tensors (2nd column). + """ + def __init__( self, *, @@ -420,11 +436,11 @@ class DebuggedGraph(google.protobuf.message.Message): instrumented_graph_def: builtins.bytes | None = ..., outer_context_id: builtins.str | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["graph_id", b"graph_id", "graph_name", b"graph_name", "instrumented_graph_def", b"instrumented_graph_def", "instrumented_ops", b"instrumented_ops", "original_graph_def", b"original_graph_def", "outer_context_id", b"outer_context_id"]) -> None: ... + def ClearField(self, field_name: typing.Literal["graph_id", b"graph_id", "graph_name", b"graph_name", "instrumented_graph_def", b"instrumented_graph_def", "instrumented_ops", b"instrumented_ops", "original_graph_def", b"original_graph_def", "outer_context_id", b"outer_context_id"]) -> None: ... global___DebuggedGraph = DebuggedGraph -@typing_extensions.final +@typing.final class DebuggedDevice(google.protobuf.message.Message): """A device on which ops and/or tensors are instrumented by the debugger.""" @@ -446,11 +462,11 @@ class DebuggedDevice(google.protobuf.message.Message): device_name: builtins.str | None = ..., device_id: builtins.int | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["device_id", b"device_id", "device_name", b"device_name"]) -> None: ... + def ClearField(self, field_name: typing.Literal["device_id", b"device_id", "device_name", b"device_name"]) -> None: ... global___DebuggedDevice = DebuggedDevice -@typing_extensions.final +@typing.final class Execution(google.protobuf.message.Message): """Data relating to the eager execution of an op or a Graph. For a op that generates N output tensors (N >= 0), only one @@ -478,30 +494,35 @@ class Execution(google.protobuf.message.Message): """The graph that's executed: applicable only to the eager execution of a FuncGraph. """ + tensor_debug_mode: global___TensorDebugMode.ValueType + """Type of the tensor value encapsulated in this proto.""" @property def input_tensor_ids(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.int]: """IDs of the input tensors (if available).""" + @property def output_tensor_ids(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.int]: """IDs of the output tensors (if availbable). If specified, must have the same length as tensor_protos. """ - tensor_debug_mode: global___TensorDebugMode.ValueType - """Type of the tensor value encapsulated in this proto.""" + @property def tensor_protos(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[tensorflow.core.framework.tensor_pb2.TensorProto]: """Output Tensor values in the type described by `tensor_value_type`. The length of this should match `num_outputs`. """ + @property def code_location(self) -> global___CodeLocation: """Stack trace of the eager execution.""" + @property def output_tensor_device_ids(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.int]: """Debugged-generated IDs of the devices on which the output tensors reside. To look up details about the device (e.g., name), cross-reference this field with the DebuggedDevice messages. """ + def __init__( self, *, @@ -515,12 +536,12 @@ class Execution(google.protobuf.message.Message): code_location: global___CodeLocation | None = ..., output_tensor_device_ids: collections.abc.Iterable[builtins.int] | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["code_location", b"code_location"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["code_location", b"code_location", "graph_id", b"graph_id", "input_tensor_ids", b"input_tensor_ids", "num_outputs", b"num_outputs", "op_type", b"op_type", "output_tensor_device_ids", b"output_tensor_device_ids", "output_tensor_ids", b"output_tensor_ids", "tensor_debug_mode", b"tensor_debug_mode", "tensor_protos", b"tensor_protos"]) -> None: ... + def HasField(self, field_name: typing.Literal["code_location", b"code_location"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["code_location", b"code_location", "graph_id", b"graph_id", "input_tensor_ids", b"input_tensor_ids", "num_outputs", b"num_outputs", "op_type", b"op_type", "output_tensor_device_ids", b"output_tensor_device_ids", "output_tensor_ids", b"output_tensor_ids", "tensor_debug_mode", b"tensor_debug_mode", "tensor_protos", b"tensor_protos"]) -> None: ... global___Execution = Execution -@typing_extensions.final +@typing.final class GraphExecutionTrace(google.protobuf.message.Message): """Data relating to an execution of a Graph (e.g., an eager execution of a FuncGraph). @@ -552,14 +573,15 @@ class GraphExecutionTrace(google.protobuf.message.Message): """ tensor_debug_mode: global___TensorDebugMode.ValueType """Type of the tensor value encapsulated in this proto.""" + device_name: builtins.str + """Name of the device that the op belongs to.""" @property def tensor_proto(self) -> tensorflow.core.framework.tensor_pb2.TensorProto: """Tensor value in the type described by `tensor_value_type`. This tensor may summarize the value of a single intermediate op of the graph, or those of multiple intermediate tensors. """ - device_name: builtins.str - """Name of the device that the op belongs to.""" + def __init__( self, *, @@ -570,7 +592,7 @@ class GraphExecutionTrace(google.protobuf.message.Message): tensor_proto: tensorflow.core.framework.tensor_pb2.TensorProto | None = ..., device_name: builtins.str | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["tensor_proto", b"tensor_proto"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["device_name", b"device_name", "op_name", b"op_name", "output_slot", b"output_slot", "tensor_debug_mode", b"tensor_debug_mode", "tensor_proto", b"tensor_proto", "tfdbg_context_id", b"tfdbg_context_id"]) -> None: ... + def HasField(self, field_name: typing.Literal["tensor_proto", b"tensor_proto"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["device_name", b"device_name", "op_name", b"op_name", "output_slot", b"output_slot", "tensor_debug_mode", b"tensor_debug_mode", "tensor_proto", b"tensor_proto", "tfdbg_context_id", b"tfdbg_context_id"]) -> None: ... global___GraphExecutionTrace = GraphExecutionTrace diff --git a/stubs/tensorflow/tensorflow/core/protobuf/debug_pb2.pyi b/stubs/tensorflow/tensorflow/core/protobuf/debug_pb2.pyi index 0280d3bbe3f9..5ee6b532d850 100644 --- a/stubs/tensorflow/tensorflow/core/protobuf/debug_pb2.pyi +++ b/stubs/tensorflow/tensorflow/core/protobuf/debug_pb2.pyi @@ -2,9 +2,10 @@ @generated by mypy-protobuf. Do not edit manually! isort:skip_file """ + import builtins import collections.abc -import typing as typing_extensions +import typing import google.protobuf.descriptor import google.protobuf.internal.containers @@ -12,7 +13,7 @@ import google.protobuf.message DESCRIPTOR: google.protobuf.descriptor.FileDescriptor -@typing_extensions.final +@typing.final class DebugTensorWatch(google.protobuf.message.Message): """Option for watching a node in TensorFlow Debugger (tfdbg).""" @@ -35,12 +36,17 @@ class DebugTensorWatch(google.protobuf.message.Message): Other negative values of output_slot are invalid and will lead to errors currently. """ + tolerate_debug_op_creation_failures: builtins.bool + """Do not error out if debug op creation fails (e.g., due to dtype + incompatibility). Instead, just log the failure. + """ @property def debug_ops(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.str]: """Name(s) of the debugging op(s). One or more than one probes on a tensor. e.g., {"DebugIdentity", "DebugNanCount"} """ + @property def debug_urls(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.str]: """URL(s) for debug targets(s). @@ -64,10 +70,7 @@ class DebugTensorWatch(google.protobuf.message.Message): among the invocations. TODO(cais): More visible documentation of this in g3docs. """ - tolerate_debug_op_creation_failures: builtins.bool - """Do not error out if debug op creation fails (e.g., due to dtype - incompatibility). Instead, just log the failure. - """ + def __init__( self, *, @@ -77,11 +80,11 @@ class DebugTensorWatch(google.protobuf.message.Message): debug_urls: collections.abc.Iterable[builtins.str] | None = ..., tolerate_debug_op_creation_failures: builtins.bool | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["debug_ops", b"debug_ops", "debug_urls", b"debug_urls", "node_name", b"node_name", "output_slot", b"output_slot", "tolerate_debug_op_creation_failures", b"tolerate_debug_op_creation_failures"]) -> None: ... + def ClearField(self, field_name: typing.Literal["debug_ops", b"debug_ops", "debug_urls", b"debug_urls", "node_name", b"node_name", "output_slot", b"output_slot", "tolerate_debug_op_creation_failures", b"tolerate_debug_op_creation_failures"]) -> None: ... global___DebugTensorWatch = DebugTensorWatch -@typing_extensions.final +@typing.final class DebugOptions(google.protobuf.message.Message): """Options for initializing DebuggerState in TensorFlow Debugger (tfdbg).""" @@ -90,9 +93,6 @@ class DebugOptions(google.protobuf.message.Message): DEBUG_TENSOR_WATCH_OPTS_FIELD_NUMBER: builtins.int GLOBAL_STEP_FIELD_NUMBER: builtins.int RESET_DISK_BYTE_USAGE_FIELD_NUMBER: builtins.int - @property - def debug_tensor_watch_opts(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___DebugTensorWatch]: - """Debugging options""" global_step: builtins.int """Caller-specified global step count. Note that this is distinct from the session run count and the executor @@ -104,6 +104,10 @@ class DebugOptions(google.protobuf.message.Message): such as the local CLI ones to indicate that the dumped tensors are cleaned up from the disk after each Session.run. """ + @property + def debug_tensor_watch_opts(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___DebugTensorWatch]: + """Debugging options""" + def __init__( self, *, @@ -111,11 +115,11 @@ class DebugOptions(google.protobuf.message.Message): global_step: builtins.int | None = ..., reset_disk_byte_usage: builtins.bool | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["debug_tensor_watch_opts", b"debug_tensor_watch_opts", "global_step", b"global_step", "reset_disk_byte_usage", b"reset_disk_byte_usage"]) -> None: ... + def ClearField(self, field_name: typing.Literal["debug_tensor_watch_opts", b"debug_tensor_watch_opts", "global_step", b"global_step", "reset_disk_byte_usage", b"reset_disk_byte_usage"]) -> None: ... global___DebugOptions = DebugOptions -@typing_extensions.final +@typing.final class DebuggedSourceFile(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -135,6 +139,7 @@ class DebuggedSourceFile(google.protobuf.message.Message): @property def lines(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.str]: """Line-by-line content of the source code file.""" + def __init__( self, *, @@ -144,11 +149,11 @@ class DebuggedSourceFile(google.protobuf.message.Message): bytes: builtins.int | None = ..., lines: collections.abc.Iterable[builtins.str] | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["bytes", b"bytes", "file_path", b"file_path", "host", b"host", "last_modified", b"last_modified", "lines", b"lines"]) -> None: ... + def ClearField(self, field_name: typing.Literal["bytes", b"bytes", "file_path", b"file_path", "host", b"host", "last_modified", b"last_modified", "lines", b"lines"]) -> None: ... global___DebuggedSourceFile = DebuggedSourceFile -@typing_extensions.final +@typing.final class DebuggedSourceFiles(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -156,11 +161,12 @@ class DebuggedSourceFiles(google.protobuf.message.Message): @property def source_files(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___DebuggedSourceFile]: """A collection of source code files.""" + def __init__( self, *, source_files: collections.abc.Iterable[global___DebuggedSourceFile] | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["source_files", b"source_files"]) -> None: ... + def ClearField(self, field_name: typing.Literal["source_files", b"source_files"]) -> None: ... global___DebuggedSourceFiles = DebuggedSourceFiles diff --git a/stubs/tensorflow/tensorflow/core/protobuf/device_filters_pb2.pyi b/stubs/tensorflow/tensorflow/core/protobuf/device_filters_pb2.pyi index 5d480d0fb6e0..f4e0c8efe920 100644 --- a/stubs/tensorflow/tensorflow/core/protobuf/device_filters_pb2.pyi +++ b/stubs/tensorflow/tensorflow/core/protobuf/device_filters_pb2.pyi @@ -16,9 +16,10 @@ See the License for the specific language governing permissions and limitations under the License. ============================================================================== """ + import builtins import collections.abc -import typing as typing_extensions +import typing import google.protobuf.descriptor import google.protobuf.internal.containers @@ -26,7 +27,7 @@ import google.protobuf.message DESCRIPTOR: google.protobuf.descriptor.FileDescriptor -@typing_extensions.final +@typing.final class TaskDeviceFilters(google.protobuf.message.Message): """This file contains protos to be used when defining a TensorFlow cluster. @@ -71,17 +72,17 @@ class TaskDeviceFilters(google.protobuf.message.Message): *, device_filters: collections.abc.Iterable[builtins.str] | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["device_filters", b"device_filters"]) -> None: ... + def ClearField(self, field_name: typing.Literal["device_filters", b"device_filters"]) -> None: ... global___TaskDeviceFilters = TaskDeviceFilters -@typing_extensions.final +@typing.final class JobDeviceFilters(google.protobuf.message.Message): """Defines the device filters for tasks in a job.""" DESCRIPTOR: google.protobuf.descriptor.Descriptor - @typing_extensions.final + @typing.final class TasksEntry(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -96,8 +97,8 @@ class JobDeviceFilters(google.protobuf.message.Message): key: builtins.int | None = ..., value: global___TaskDeviceFilters | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["value", b"value"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["key", b"key", "value", b"value"]) -> None: ... + def HasField(self, field_name: typing.Literal["value", b"value"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["key", b"key", "value", b"value"]) -> None: ... NAME_FIELD_NUMBER: builtins.int TASKS_FIELD_NUMBER: builtins.int @@ -106,17 +107,18 @@ class JobDeviceFilters(google.protobuf.message.Message): @property def tasks(self) -> google.protobuf.internal.containers.MessageMap[builtins.int, global___TaskDeviceFilters]: """Mapping from task ID to task device filters.""" + def __init__( self, *, name: builtins.str | None = ..., tasks: collections.abc.Mapping[builtins.int, global___TaskDeviceFilters] | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["name", b"name", "tasks", b"tasks"]) -> None: ... + def ClearField(self, field_name: typing.Literal["name", b"name", "tasks", b"tasks"]) -> None: ... global___JobDeviceFilters = JobDeviceFilters -@typing_extensions.final +@typing.final class ClusterDeviceFilters(google.protobuf.message.Message): """Defines the device filters for jobs in a cluster.""" @@ -130,6 +132,6 @@ class ClusterDeviceFilters(google.protobuf.message.Message): *, jobs: collections.abc.Iterable[global___JobDeviceFilters] | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["jobs", b"jobs"]) -> None: ... + def ClearField(self, field_name: typing.Literal["jobs", b"jobs"]) -> None: ... global___ClusterDeviceFilters = ClusterDeviceFilters diff --git a/stubs/tensorflow/tensorflow/core/protobuf/device_properties_pb2.pyi b/stubs/tensorflow/tensorflow/core/protobuf/device_properties_pb2.pyi index c2b892f12a64..af4bdd7a1f88 100644 --- a/stubs/tensorflow/tensorflow/core/protobuf/device_properties_pb2.pyi +++ b/stubs/tensorflow/tensorflow/core/protobuf/device_properties_pb2.pyi @@ -16,9 +16,10 @@ See the License for the specific language governing permissions and limitations under the License. ============================================================================== """ + import builtins import collections.abc -import typing as typing_extensions +import typing import google.protobuf.descriptor import google.protobuf.internal.containers @@ -26,11 +27,11 @@ import google.protobuf.message DESCRIPTOR: google.protobuf.descriptor.FileDescriptor -@typing_extensions.final +@typing.final class DeviceProperties(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor - @typing_extensions.final + @typing.final class EnvironmentEntry(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -44,7 +45,7 @@ class DeviceProperties(google.protobuf.message.Message): key: builtins.str | None = ..., value: builtins.str | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["key", b"key", "value", b"value"]) -> None: ... + def ClearField(self, field_name: typing.Literal["key", b"key", "value", b"value"]) -> None: ... TYPE_FIELD_NUMBER: builtins.int VENDOR_FIELD_NUMBER: builtins.int @@ -69,11 +70,6 @@ class DeviceProperties(google.protobuf.message.Message): """Core Frequency in Mhz""" num_cores: builtins.int """Number of cores""" - @property - def environment(self) -> google.protobuf.internal.containers.ScalarMap[builtins.str, builtins.str]: - """Version of the tools and libraries used with this device (e.g. gcc 4.9, - cudnn 5.1) - """ num_registers: builtins.int """Number of registers per core.""" l1_cache_size: builtins.int @@ -90,6 +86,12 @@ class DeviceProperties(google.protobuf.message.Message): """Memory size in bytes""" bandwidth: builtins.int """Memory bandwidth in KB/s""" + @property + def environment(self) -> google.protobuf.internal.containers.ScalarMap[builtins.str, builtins.str]: + """Version of the tools and libraries used with this device (e.g. gcc 4.9, + cudnn 5.1) + """ + def __init__( self, *, @@ -107,11 +109,11 @@ class DeviceProperties(google.protobuf.message.Message): memory_size: builtins.int | None = ..., bandwidth: builtins.int | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["bandwidth", b"bandwidth", "environment", b"environment", "frequency", b"frequency", "l1_cache_size", b"l1_cache_size", "l2_cache_size", b"l2_cache_size", "l3_cache_size", b"l3_cache_size", "memory_size", b"memory_size", "model", b"model", "num_cores", b"num_cores", "num_registers", b"num_registers", "shared_memory_size_per_multiprocessor", b"shared_memory_size_per_multiprocessor", "type", b"type", "vendor", b"vendor"]) -> None: ... + def ClearField(self, field_name: typing.Literal["bandwidth", b"bandwidth", "environment", b"environment", "frequency", b"frequency", "l1_cache_size", b"l1_cache_size", "l2_cache_size", b"l2_cache_size", "l3_cache_size", b"l3_cache_size", "memory_size", b"memory_size", "model", b"model", "num_cores", b"num_cores", "num_registers", b"num_registers", "shared_memory_size_per_multiprocessor", b"shared_memory_size_per_multiprocessor", "type", b"type", "vendor", b"vendor"]) -> None: ... global___DeviceProperties = DeviceProperties -@typing_extensions.final +@typing.final class NamedDevice(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -126,7 +128,7 @@ class NamedDevice(google.protobuf.message.Message): name: builtins.str | None = ..., properties: global___DeviceProperties | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["properties", b"properties"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["name", b"name", "properties", b"properties"]) -> None: ... + def HasField(self, field_name: typing.Literal["properties", b"properties"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["name", b"name", "properties", b"properties"]) -> None: ... global___NamedDevice = NamedDevice diff --git a/stubs/tensorflow/tensorflow/core/protobuf/distributed_runtime_payloads_pb2.pyi b/stubs/tensorflow/tensorflow/core/protobuf/distributed_runtime_payloads_pb2.pyi deleted file mode 100644 index b27a37c32cc3..000000000000 --- a/stubs/tensorflow/tensorflow/core/protobuf/distributed_runtime_payloads_pb2.pyi +++ /dev/null @@ -1,81 +0,0 @@ -""" -@generated by mypy-protobuf. Do not edit manually! -isort:skip_file -""" -import builtins -import collections.abc -import typing as typing_extensions - -import google.protobuf.descriptor -import google.protobuf.internal.containers -import google.protobuf.message - -DESCRIPTOR: google.protobuf.descriptor.FileDescriptor - -@typing_extensions.final -class GrpcPayloadContainer(google.protobuf.message.Message): - """Used to serialize and transmit tensorflow::Status payloads through - grpc::Status `error_details` since grpc::Status lacks payload API. - TODO(b/204231601): Use GRPC API once supported. - """ - - DESCRIPTOR: google.protobuf.descriptor.Descriptor - - @typing_extensions.final - class PayloadsEntry(google.protobuf.message.Message): - DESCRIPTOR: google.protobuf.descriptor.Descriptor - - KEY_FIELD_NUMBER: builtins.int - VALUE_FIELD_NUMBER: builtins.int - key: builtins.str - value: builtins.bytes - def __init__( - self, - *, - key: builtins.str | None = ..., - value: builtins.bytes | None = ..., - ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["key", b"key", "value", b"value"]) -> None: ... - - PAYLOADS_FIELD_NUMBER: builtins.int - @property - def payloads(self) -> google.protobuf.internal.containers.ScalarMap[builtins.str, builtins.bytes]: ... - def __init__( - self, - *, - payloads: collections.abc.Mapping[builtins.str, builtins.bytes] | None = ..., - ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["payloads", b"payloads"]) -> None: ... - -global___GrpcPayloadContainer = GrpcPayloadContainer - -@typing_extensions.final -class GrpcPayloadsLost(google.protobuf.message.Message): - """If included as a payload, this message flags the Status to have lost payloads - during the GRPC transmission. - URI: "type.googleapis.com/tensorflow.distributed_runtime.GrpcPayloadsLost" - """ - - DESCRIPTOR: google.protobuf.descriptor.Descriptor - - def __init__( - self, - ) -> None: ... - -global___GrpcPayloadsLost = GrpcPayloadsLost - -@typing_extensions.final -class WorkerPossiblyRestarted(google.protobuf.message.Message): - """If included as a payload, this message flags the Status to be a possible - outcome of a worker restart. - URI: - "type.googleapis.com/tensorflow.distributed_runtime.WorkerPossiblyRestarted" - """ - - DESCRIPTOR: google.protobuf.descriptor.Descriptor - - def __init__( - self, - ) -> None: ... - -global___WorkerPossiblyRestarted = WorkerPossiblyRestarted diff --git a/stubs/tensorflow/tensorflow/core/protobuf/error_codes_pb2.pyi b/stubs/tensorflow/tensorflow/core/protobuf/error_codes_pb2.pyi index 093797947d01..10cb20051e70 100644 --- a/stubs/tensorflow/tensorflow/core/protobuf/error_codes_pb2.pyi +++ b/stubs/tensorflow/tensorflow/core/protobuf/error_codes_pb2.pyi @@ -6,6 +6,7 @@ core/lib/core/error_codes.proto, or having tensorflow.error, like tsl/protobuf/error_codes.proto, results in name collision errors in generated code for some users that use JS through J2CL. """ + import google.protobuf.descriptor from tensorflow.tsl.protobuf.error_codes_pb2 import ( ABORTED as ABORTED, diff --git a/stubs/tensorflow/tensorflow/core/protobuf/fingerprint_pb2.pyi b/stubs/tensorflow/tensorflow/core/protobuf/fingerprint_pb2.pyi index fc486666a960..8f403526b8ff 100644 --- a/stubs/tensorflow/tensorflow/core/protobuf/fingerprint_pb2.pyi +++ b/stubs/tensorflow/tensorflow/core/protobuf/fingerprint_pb2.pyi @@ -2,8 +2,9 @@ @generated by mypy-protobuf. Do not edit manually! isort:skip_file """ + import builtins -import typing as typing_extensions +import typing import google.protobuf.descriptor import google.protobuf.message @@ -11,7 +12,7 @@ import tensorflow.core.framework.versions_pb2 DESCRIPTOR: google.protobuf.descriptor.FileDescriptor -@typing_extensions.final +@typing.final class FingerprintDef(google.protobuf.message.Message): """Protocol buffer representing a SavedModel Fingerprint. @@ -40,6 +41,7 @@ class FingerprintDef(google.protobuf.message.Message): @property def version(self) -> tensorflow.core.framework.versions_pb2.VersionDef: """Version specification of the fingerprint.""" + def __init__( self, *, @@ -50,7 +52,7 @@ class FingerprintDef(google.protobuf.message.Message): checkpoint_hash: builtins.int | None = ..., version: tensorflow.core.framework.versions_pb2.VersionDef | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["version", b"version"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["checkpoint_hash", b"checkpoint_hash", "graph_def_program_hash", b"graph_def_program_hash", "saved_model_checksum", b"saved_model_checksum", "saved_object_graph_hash", b"saved_object_graph_hash", "signature_def_hash", b"signature_def_hash", "version", b"version"]) -> None: ... + def HasField(self, field_name: typing.Literal["version", b"version"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["checkpoint_hash", b"checkpoint_hash", "graph_def_program_hash", b"graph_def_program_hash", "saved_model_checksum", b"saved_model_checksum", "saved_object_graph_hash", b"saved_object_graph_hash", "signature_def_hash", b"signature_def_hash", "version", b"version"]) -> None: ... global___FingerprintDef = FingerprintDef diff --git a/stubs/tensorflow/tensorflow/core/protobuf/graph_debug_info_pb2.pyi b/stubs/tensorflow/tensorflow/core/protobuf/graph_debug_info_pb2.pyi index 182aa9a42819..4792d32a18e0 100644 --- a/stubs/tensorflow/tensorflow/core/protobuf/graph_debug_info_pb2.pyi +++ b/stubs/tensorflow/tensorflow/core/protobuf/graph_debug_info_pb2.pyi @@ -2,9 +2,10 @@ @generated by mypy-protobuf. Do not edit manually! isort:skip_file """ + import builtins import collections.abc -import typing as typing_extensions +import typing import google.protobuf.descriptor import google.protobuf.internal.containers @@ -12,11 +13,11 @@ import google.protobuf.message DESCRIPTOR: google.protobuf.descriptor.FileDescriptor -@typing_extensions.final +@typing.final class GraphDebugInfo(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor - @typing_extensions.final + @typing.final class FileLineCol(google.protobuf.message.Message): """This represents a file/line location in the source code.""" @@ -48,9 +49,9 @@ class GraphDebugInfo(google.protobuf.message.Message): func: builtins.str | None = ..., code: builtins.str | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["code", b"code", "col", b"col", "file_index", b"file_index", "func", b"func", "line", b"line"]) -> None: ... + def ClearField(self, field_name: typing.Literal["code", b"code", "col", b"col", "file_index", b"file_index", "func", b"func", "line", b"line"]) -> None: ... - @typing_extensions.final + @typing.final class StackTrace(google.protobuf.message.Message): """This represents a stack trace which is a ordered list of `FileLineCol`.""" @@ -60,14 +61,15 @@ class GraphDebugInfo(google.protobuf.message.Message): @property def file_line_cols(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___GraphDebugInfo.FileLineCol]: """Each line in the stack trace.""" + def __init__( self, *, file_line_cols: collections.abc.Iterable[global___GraphDebugInfo.FileLineCol] | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["file_line_cols", b"file_line_cols"]) -> None: ... + def ClearField(self, field_name: typing.Literal["file_line_cols", b"file_line_cols"]) -> None: ... - @typing_extensions.final + @typing.final class TracesEntry(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -82,8 +84,8 @@ class GraphDebugInfo(google.protobuf.message.Message): key: builtins.str | None = ..., value: global___GraphDebugInfo.StackTrace | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["value", b"value"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["key", b"key", "value", b"value"]) -> None: ... + def HasField(self, field_name: typing.Literal["value", b"value"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["key", b"key", "value", b"value"]) -> None: ... FILES_FIELD_NUMBER: builtins.int TRACES_FIELD_NUMBER: builtins.int @@ -92,6 +94,7 @@ class GraphDebugInfo(google.protobuf.message.Message): """This stores all the source code file names and can be indexed by the `file_index`. """ + @property def traces(self) -> google.protobuf.internal.containers.MessageMap[builtins.str, global___GraphDebugInfo.StackTrace]: """This maps a node name to a stack trace in the source code. @@ -105,12 +108,13 @@ class GraphDebugInfo(google.protobuf.message.Message): It would be preferable to avoid mangling and use a tuple key of (op.name, func_name), but this is not supported with protocol buffers. """ + def __init__( self, *, files: collections.abc.Iterable[builtins.str] | None = ..., traces: collections.abc.Mapping[builtins.str, global___GraphDebugInfo.StackTrace] | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["files", b"files", "traces", b"traces"]) -> None: ... + def ClearField(self, field_name: typing.Literal["files", b"files", "traces", b"traces"]) -> None: ... global___GraphDebugInfo = GraphDebugInfo diff --git a/stubs/tensorflow/tensorflow/core/protobuf/meta_graph_pb2.pyi b/stubs/tensorflow/tensorflow/core/protobuf/meta_graph_pb2.pyi index cb5eee1183af..7a2192b62640 100644 --- a/stubs/tensorflow/tensorflow/core/protobuf/meta_graph_pb2.pyi +++ b/stubs/tensorflow/tensorflow/core/protobuf/meta_graph_pb2.pyi @@ -2,9 +2,10 @@ @generated by mypy-protobuf. Do not edit manually! isort:skip_file """ + import builtins import collections.abc -import typing as typing_extensions +import typing import google.protobuf.any_pb2 import google.protobuf.descriptor @@ -20,7 +21,7 @@ import tensorflow.core.protobuf.struct_pb2 DESCRIPTOR: google.protobuf.descriptor.FileDescriptor -@typing_extensions.final +@typing.final class MetaGraphDef(google.protobuf.message.Message): """Protocol buffer containing the following which are necessary to restart training, run inference. It can be used to serialize/de-serialize memory @@ -37,7 +38,7 @@ class MetaGraphDef(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor - @typing_extensions.final + @typing.final class MetaInfoDef(google.protobuf.message.Message): """Meta information regarding the graph to be exported. To be used by users of this protocol buffer to encode information regarding their meta graph. @@ -45,7 +46,7 @@ class MetaGraphDef(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor - @typing_extensions.final + @typing.final class FunctionAliasesEntry(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -59,7 +60,7 @@ class MetaGraphDef(google.protobuf.message.Message): key: builtins.str | None = ..., value: builtins.str | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["key", b"key", "value", b"value"]) -> None: ... + def ClearField(self, field_name: typing.Literal["key", b"key", "value", b"value"]) -> None: ... META_GRAPH_VERSION_FIELD_NUMBER: builtins.int STRIPPED_OP_LIST_FIELD_NUMBER: builtins.int @@ -73,16 +74,32 @@ class MetaGraphDef(google.protobuf.message.Message): """User specified Version string. Can be the name of the model and revision, steps this model has been trained to, etc. """ + tensorflow_version: builtins.str + """The __version__ string of the tensorflow build used to write this graph. + This will be populated by the framework, which will overwrite any user + supplied value. + """ + tensorflow_git_version: builtins.str + """The __git_version__ string of the tensorflow build used to write this + graph. This will be populated by the framework, which will overwrite any + user supplied value. + """ + stripped_default_attrs: builtins.bool + """A flag to denote whether default-valued attrs have been stripped from + the nodes in this graph_def. + """ @property def stripped_op_list(self) -> tensorflow.core.framework.op_def_pb2.OpList: """A copy of the OpDefs used by the producer of this graph_def. Descriptions and Ops not used in graph_def are stripped out. """ + @property def any_info(self) -> google.protobuf.any_pb2.Any: """A serialized protobuf. Can be the time this meta graph is created, or modified, or name of the model. """ + @property def tags(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.str]: """User supplied tag(s) on the meta_graph and included graph_def. @@ -92,23 +109,11 @@ class MetaGraphDef(google.protobuf.message.Message): These tags enable loaders to access the MetaGraph(s) appropriate for a specific use-case or runtime environment. """ - tensorflow_version: builtins.str - """The __version__ string of the tensorflow build used to write this graph. - This will be populated by the framework, which will overwrite any user - supplied value. - """ - tensorflow_git_version: builtins.str - """The __git_version__ string of the tensorflow build used to write this - graph. This will be populated by the framework, which will overwrite any - user supplied value. - """ - stripped_default_attrs: builtins.bool - """A flag to denote whether default-valued attrs have been stripped from - the nodes in this graph_def. - """ + @property def function_aliases(self) -> google.protobuf.internal.containers.ScalarMap[builtins.str, builtins.str]: """FunctionDef name to aliases mapping.""" + def __init__( self, *, @@ -121,10 +126,10 @@ class MetaGraphDef(google.protobuf.message.Message): stripped_default_attrs: builtins.bool | None = ..., function_aliases: collections.abc.Mapping[builtins.str, builtins.str] | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["any_info", b"any_info", "stripped_op_list", b"stripped_op_list"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["any_info", b"any_info", "function_aliases", b"function_aliases", "meta_graph_version", b"meta_graph_version", "stripped_default_attrs", b"stripped_default_attrs", "stripped_op_list", b"stripped_op_list", "tags", b"tags", "tensorflow_git_version", b"tensorflow_git_version", "tensorflow_version", b"tensorflow_version"]) -> None: ... + def HasField(self, field_name: typing.Literal["any_info", b"any_info", "stripped_op_list", b"stripped_op_list"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["any_info", b"any_info", "function_aliases", b"function_aliases", "meta_graph_version", b"meta_graph_version", "stripped_default_attrs", b"stripped_default_attrs", "stripped_op_list", b"stripped_op_list", "tags", b"tags", "tensorflow_git_version", b"tensorflow_git_version", "tensorflow_version", b"tensorflow_version"]) -> None: ... - @typing_extensions.final + @typing.final class CollectionDefEntry(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -139,10 +144,10 @@ class MetaGraphDef(google.protobuf.message.Message): key: builtins.str | None = ..., value: global___CollectionDef | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["value", b"value"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["key", b"key", "value", b"value"]) -> None: ... + def HasField(self, field_name: typing.Literal["value", b"value"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["key", b"key", "value", b"value"]) -> None: ... - @typing_extensions.final + @typing.final class SignatureDefEntry(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -157,8 +162,8 @@ class MetaGraphDef(google.protobuf.message.Message): key: builtins.str | None = ..., value: global___SignatureDef | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["value", b"value"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["key", b"key", "value", b"value"]) -> None: ... + def HasField(self, field_name: typing.Literal["value", b"value"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["key", b"key", "value", b"value"]) -> None: ... META_INFO_DEF_FIELD_NUMBER: builtins.int GRAPH_DEF_FIELD_NUMBER: builtins.int @@ -172,25 +177,31 @@ class MetaGraphDef(google.protobuf.message.Message): @property def graph_def(self) -> tensorflow.core.framework.graph_pb2.GraphDef: """GraphDef.""" + @property def saver_def(self) -> tensorflow.core.protobuf.saver_pb2.SaverDef: """SaverDef.""" + @property def collection_def(self) -> google.protobuf.internal.containers.MessageMap[builtins.str, global___CollectionDef]: """collection_def: Map from collection name to collections. See CollectionDef section for details. """ + @property def signature_def(self) -> google.protobuf.internal.containers.MessageMap[builtins.str, global___SignatureDef]: """signature_def: Map from user supplied key for a signature to a single SignatureDef. """ + @property def asset_file_def(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___AssetFileDef]: """Asset file def to be used with the defined graph.""" + @property def object_graph_def(self) -> tensorflow.core.protobuf.saved_object_graph_pb2.SavedObjectGraph: """Extra information about the structure of functions and stateful objects.""" + def __init__( self, *, @@ -202,12 +213,12 @@ class MetaGraphDef(google.protobuf.message.Message): asset_file_def: collections.abc.Iterable[global___AssetFileDef] | None = ..., object_graph_def: tensorflow.core.protobuf.saved_object_graph_pb2.SavedObjectGraph | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["graph_def", b"graph_def", "meta_info_def", b"meta_info_def", "object_graph_def", b"object_graph_def", "saver_def", b"saver_def"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["asset_file_def", b"asset_file_def", "collection_def", b"collection_def", "graph_def", b"graph_def", "meta_info_def", b"meta_info_def", "object_graph_def", b"object_graph_def", "saver_def", b"saver_def", "signature_def", b"signature_def"]) -> None: ... + def HasField(self, field_name: typing.Literal["graph_def", b"graph_def", "meta_info_def", b"meta_info_def", "object_graph_def", b"object_graph_def", "saver_def", b"saver_def"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["asset_file_def", b"asset_file_def", "collection_def", b"collection_def", "graph_def", b"graph_def", "meta_info_def", b"meta_info_def", "object_graph_def", b"object_graph_def", "saver_def", b"saver_def", "signature_def", b"signature_def"]) -> None: ... global___MetaGraphDef = MetaGraphDef -@typing_extensions.final +@typing.final class CollectionDef(google.protobuf.message.Message): """CollectionDef should cover most collections. To add a user-defined collection, do one of the following: @@ -275,7 +286,7 @@ class CollectionDef(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor - @typing_extensions.final + @typing.final class NodeList(google.protobuf.message.Message): """NodeList is used for collecting nodes in graph. For example collection_def { @@ -299,9 +310,9 @@ class CollectionDef(google.protobuf.message.Message): *, value: collections.abc.Iterable[builtins.str] | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["value", b"value"]) -> None: ... + def ClearField(self, field_name: typing.Literal["value", b"value"]) -> None: ... - @typing_extensions.final + @typing.final class BytesList(google.protobuf.message.Message): """BytesList is used for collecting strings and serialized protobufs. For example: @@ -328,9 +339,9 @@ class CollectionDef(google.protobuf.message.Message): *, value: collections.abc.Iterable[builtins.bytes] | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["value", b"value"]) -> None: ... + def ClearField(self, field_name: typing.Literal["value", b"value"]) -> None: ... - @typing_extensions.final + @typing.final class Int64List(google.protobuf.message.Message): """Int64List is used for collecting int, int64 and long values.""" @@ -344,9 +355,9 @@ class CollectionDef(google.protobuf.message.Message): *, value: collections.abc.Iterable[builtins.int] | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["value", b"value"]) -> None: ... + def ClearField(self, field_name: typing.Literal["value", b"value"]) -> None: ... - @typing_extensions.final + @typing.final class FloatList(google.protobuf.message.Message): """FloatList is used for collecting float values.""" @@ -360,9 +371,9 @@ class CollectionDef(google.protobuf.message.Message): *, value: collections.abc.Iterable[builtins.float] | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["value", b"value"]) -> None: ... + def ClearField(self, field_name: typing.Literal["value", b"value"]) -> None: ... - @typing_extensions.final + @typing.final class AnyList(google.protobuf.message.Message): """AnyList is used for collecting Any protos.""" @@ -376,7 +387,7 @@ class CollectionDef(google.protobuf.message.Message): *, value: collections.abc.Iterable[google.protobuf.any_pb2.Any] | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["value", b"value"]) -> None: ... + def ClearField(self, field_name: typing.Literal["value", b"value"]) -> None: ... NODE_LIST_FIELD_NUMBER: builtins.int BYTES_LIST_FIELD_NUMBER: builtins.int @@ -402,19 +413,19 @@ class CollectionDef(google.protobuf.message.Message): float_list: global___CollectionDef.FloatList | None = ..., any_list: global___CollectionDef.AnyList | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["any_list", b"any_list", "bytes_list", b"bytes_list", "float_list", b"float_list", "int64_list", b"int64_list", "kind", b"kind", "node_list", b"node_list"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["any_list", b"any_list", "bytes_list", b"bytes_list", "float_list", b"float_list", "int64_list", b"int64_list", "kind", b"kind", "node_list", b"node_list"]) -> None: ... - def WhichOneof(self, oneof_group: typing_extensions.Literal["kind", b"kind"]) -> typing_extensions.Literal["node_list", "bytes_list", "int64_list", "float_list", "any_list"] | None: ... + def HasField(self, field_name: typing.Literal["any_list", b"any_list", "bytes_list", b"bytes_list", "float_list", b"float_list", "int64_list", b"int64_list", "kind", b"kind", "node_list", b"node_list"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["any_list", b"any_list", "bytes_list", b"bytes_list", "float_list", b"float_list", "int64_list", b"int64_list", "kind", b"kind", "node_list", b"node_list"]) -> None: ... + def WhichOneof(self, oneof_group: typing.Literal["kind", b"kind"]) -> typing.Literal["node_list", "bytes_list", "int64_list", "float_list", "any_list"] | None: ... global___CollectionDef = CollectionDef -@typing_extensions.final +@typing.final class TensorInfo(google.protobuf.message.Message): """Information about a Tensor necessary for feeding or retrieval.""" DESCRIPTOR: google.protobuf.descriptor.Descriptor - @typing_extensions.final + @typing.final class CooSparse(google.protobuf.message.Message): """For sparse tensors, The COO encoding stores a triple of values, indices, and shape. @@ -442,9 +453,9 @@ class TensorInfo(google.protobuf.message.Message): indices_tensor_name: builtins.str | None = ..., dense_shape_tensor_name: builtins.str | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["dense_shape_tensor_name", b"dense_shape_tensor_name", "indices_tensor_name", b"indices_tensor_name", "values_tensor_name", b"values_tensor_name"]) -> None: ... + def ClearField(self, field_name: typing.Literal["dense_shape_tensor_name", b"dense_shape_tensor_name", "indices_tensor_name", b"indices_tensor_name", "values_tensor_name", b"values_tensor_name"]) -> None: ... - @typing_extensions.final + @typing.final class CompositeTensor(google.protobuf.message.Message): """Generic encoding for composite tensors.""" @@ -455,17 +466,19 @@ class TensorInfo(google.protobuf.message.Message): @property def type_spec(self) -> tensorflow.core.protobuf.struct_pb2.TypeSpecProto: """The serialized TypeSpec for the composite tensor.""" + @property def components(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___TensorInfo]: """A TensorInfo for each flattened component tensor.""" + def __init__( self, *, type_spec: tensorflow.core.protobuf.struct_pb2.TypeSpecProto | None = ..., components: collections.abc.Iterable[global___TensorInfo] | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["type_spec", b"type_spec"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["components", b"components", "type_spec", b"type_spec"]) -> None: ... + def HasField(self, field_name: typing.Literal["type_spec", b"type_spec"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["components", b"components", "type_spec", b"type_spec"]) -> None: ... NAME_FIELD_NUMBER: builtins.int COO_SPARSE_FIELD_NUMBER: builtins.int @@ -474,6 +487,7 @@ class TensorInfo(google.protobuf.message.Message): TENSOR_SHAPE_FIELD_NUMBER: builtins.int name: builtins.str """For dense `Tensor`s, the name of the tensor in the graph.""" + dtype: tensorflow.core.framework.types_pb2.DataType.ValueType @property def coo_sparse(self) -> global___TensorInfo.CooSparse: """There are many possible encodings of sparse matrices @@ -481,16 +495,18 @@ class TensorInfo(google.protobuf.message.Message): uses only the COO encoding. This is supported and documented in the SparseTensor Python class. """ + @property def composite_tensor(self) -> global___TensorInfo.CompositeTensor: """Generic encoding for CompositeTensors.""" - dtype: tensorflow.core.framework.types_pb2.DataType.ValueType + @property def tensor_shape(self) -> tensorflow.core.framework.tensor_shape_pb2.TensorShapeProto: """The static shape should be recorded here, to the extent that it can be known in advance. In the case of a SparseTensor, this field describes the logical shape of the represented tensor (aka dense_shape). """ + def __init__( self, *, @@ -500,13 +516,13 @@ class TensorInfo(google.protobuf.message.Message): dtype: tensorflow.core.framework.types_pb2.DataType.ValueType | None = ..., tensor_shape: tensorflow.core.framework.tensor_shape_pb2.TensorShapeProto | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["composite_tensor", b"composite_tensor", "coo_sparse", b"coo_sparse", "encoding", b"encoding", "name", b"name", "tensor_shape", b"tensor_shape"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["composite_tensor", b"composite_tensor", "coo_sparse", b"coo_sparse", "dtype", b"dtype", "encoding", b"encoding", "name", b"name", "tensor_shape", b"tensor_shape"]) -> None: ... - def WhichOneof(self, oneof_group: typing_extensions.Literal["encoding", b"encoding"]) -> typing_extensions.Literal["name", "coo_sparse", "composite_tensor"] | None: ... + def HasField(self, field_name: typing.Literal["composite_tensor", b"composite_tensor", "coo_sparse", b"coo_sparse", "encoding", b"encoding", "name", b"name", "tensor_shape", b"tensor_shape"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["composite_tensor", b"composite_tensor", "coo_sparse", b"coo_sparse", "dtype", b"dtype", "encoding", b"encoding", "name", b"name", "tensor_shape", b"tensor_shape"]) -> None: ... + def WhichOneof(self, oneof_group: typing.Literal["encoding", b"encoding"]) -> typing.Literal["name", "coo_sparse", "composite_tensor"] | None: ... global___TensorInfo = TensorInfo -@typing_extensions.final +@typing.final class SignatureDef(google.protobuf.message.Message): """SignatureDef defines the signature of a computation supported by a TensorFlow graph. @@ -569,7 +585,7 @@ class SignatureDef(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor - @typing_extensions.final + @typing.final class InputsEntry(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -584,10 +600,10 @@ class SignatureDef(google.protobuf.message.Message): key: builtins.str | None = ..., value: global___TensorInfo | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["value", b"value"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["key", b"key", "value", b"value"]) -> None: ... + def HasField(self, field_name: typing.Literal["value", b"value"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["key", b"key", "value", b"value"]) -> None: ... - @typing_extensions.final + @typing.final class OutputsEntry(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -602,18 +618,12 @@ class SignatureDef(google.protobuf.message.Message): key: builtins.str | None = ..., value: global___TensorInfo | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["value", b"value"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["key", b"key", "value", b"value"]) -> None: ... + def HasField(self, field_name: typing.Literal["value", b"value"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["key", b"key", "value", b"value"]) -> None: ... INPUTS_FIELD_NUMBER: builtins.int OUTPUTS_FIELD_NUMBER: builtins.int METHOD_NAME_FIELD_NUMBER: builtins.int - @property - def inputs(self) -> google.protobuf.internal.containers.MessageMap[builtins.str, global___TensorInfo]: - """Named input parameters.""" - @property - def outputs(self) -> google.protobuf.internal.containers.MessageMap[builtins.str, global___TensorInfo]: - """Named output parameters.""" method_name: builtins.str """Extensible method_name information enabling third-party users to mark a SignatureDef as supporting a particular method. This enables producers and @@ -624,6 +634,14 @@ class SignatureDef(google.protobuf.message.Message): method_name. This is commonly used to support multi-headed computation, where a single graph computation may return multiple results. """ + @property + def inputs(self) -> google.protobuf.internal.containers.MessageMap[builtins.str, global___TensorInfo]: + """Named input parameters.""" + + @property + def outputs(self) -> google.protobuf.internal.containers.MessageMap[builtins.str, global___TensorInfo]: + """Named output parameters.""" + def __init__( self, *, @@ -631,11 +649,11 @@ class SignatureDef(google.protobuf.message.Message): outputs: collections.abc.Mapping[builtins.str, global___TensorInfo] | None = ..., method_name: builtins.str | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["inputs", b"inputs", "method_name", b"method_name", "outputs", b"outputs"]) -> None: ... + def ClearField(self, field_name: typing.Literal["inputs", b"inputs", "method_name", b"method_name", "outputs", b"outputs"]) -> None: ... global___SignatureDef = SignatureDef -@typing_extensions.final +@typing.final class AssetFileDef(google.protobuf.message.Message): """An asset file def for a single file or a set of sharded files with the same name. @@ -645,21 +663,22 @@ class AssetFileDef(google.protobuf.message.Message): TENSOR_INFO_FIELD_NUMBER: builtins.int FILENAME_FIELD_NUMBER: builtins.int - @property - def tensor_info(self) -> global___TensorInfo: - """The tensor to bind the asset filename to.""" filename: builtins.str """The filename within an assets directory. Note: does not include the path prefix, i.e. directories. For an asset at /tmp/path/vocab.txt, the filename would be "vocab.txt". """ + @property + def tensor_info(self) -> global___TensorInfo: + """The tensor to bind the asset filename to.""" + def __init__( self, *, tensor_info: global___TensorInfo | None = ..., filename: builtins.str | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["tensor_info", b"tensor_info"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["filename", b"filename", "tensor_info", b"tensor_info"]) -> None: ... + def HasField(self, field_name: typing.Literal["tensor_info", b"tensor_info"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["filename", b"filename", "tensor_info", b"tensor_info"]) -> None: ... global___AssetFileDef = AssetFileDef diff --git a/stubs/tensorflow/tensorflow/core/protobuf/named_tensor_pb2.pyi b/stubs/tensorflow/tensorflow/core/protobuf/named_tensor_pb2.pyi index 6c9841e14653..c1c17417d31c 100644 --- a/stubs/tensorflow/tensorflow/core/protobuf/named_tensor_pb2.pyi +++ b/stubs/tensorflow/tensorflow/core/protobuf/named_tensor_pb2.pyi @@ -2,8 +2,9 @@ @generated by mypy-protobuf. Do not edit manually! isort:skip_file """ + import builtins -import typing as typing_extensions +import typing import google.protobuf.descriptor import google.protobuf.message @@ -11,7 +12,7 @@ import tensorflow.core.framework.tensor_pb2 DESCRIPTOR: google.protobuf.descriptor.FileDescriptor -@typing_extensions.final +@typing.final class NamedTensorProto(google.protobuf.message.Message): """A pair of tensor name and tensor values.""" @@ -30,13 +31,14 @@ class NamedTensorProto(google.protobuf.message.Message): filled tensor fields (float_val, int_val, etc.) or encoded in a compact form in tensor.tensor_content. """ + def __init__( self, *, name: builtins.str | None = ..., tensor: tensorflow.core.framework.tensor_pb2.TensorProto | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["tensor", b"tensor"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["name", b"name", "tensor", b"tensor"]) -> None: ... + def HasField(self, field_name: typing.Literal["tensor", b"tensor"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["name", b"name", "tensor", b"tensor"]) -> None: ... global___NamedTensorProto = NamedTensorProto diff --git a/stubs/tensorflow/tensorflow/core/protobuf/queue_runner_pb2.pyi b/stubs/tensorflow/tensorflow/core/protobuf/queue_runner_pb2.pyi index f362ad0d0ca8..f93fe61c3752 100644 --- a/stubs/tensorflow/tensorflow/core/protobuf/queue_runner_pb2.pyi +++ b/stubs/tensorflow/tensorflow/core/protobuf/queue_runner_pb2.pyi @@ -2,9 +2,10 @@ @generated by mypy-protobuf. Do not edit manually! isort:skip_file """ + import builtins import collections.abc -import typing as typing_extensions +import typing import google.protobuf.descriptor import google.protobuf.internal.containers @@ -13,7 +14,7 @@ import tensorflow.tsl.protobuf.error_codes_pb2 DESCRIPTOR: google.protobuf.descriptor.FileDescriptor -@typing_extensions.final +@typing.final class QueueRunnerDef(google.protobuf.message.Message): """Protocol buffer representing a QueueRunner.""" @@ -26,18 +27,20 @@ class QueueRunnerDef(google.protobuf.message.Message): QUEUE_CLOSED_EXCEPTION_TYPES_FIELD_NUMBER: builtins.int queue_name: builtins.str """Queue name.""" - @property - def enqueue_op_name(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.str]: - """A list of enqueue operations.""" close_op_name: builtins.str """The operation to run to close the queue.""" cancel_op_name: builtins.str """The operation to run to cancel the queue.""" + @property + def enqueue_op_name(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.str]: + """A list of enqueue operations.""" + @property def queue_closed_exception_types(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[tensorflow.tsl.protobuf.error_codes_pb2.Code.ValueType]: """A list of exception types considered to signal a safely closed queue if raised during enqueue operations. """ + def __init__( self, *, @@ -47,6 +50,6 @@ class QueueRunnerDef(google.protobuf.message.Message): cancel_op_name: builtins.str | None = ..., queue_closed_exception_types: collections.abc.Iterable[tensorflow.tsl.protobuf.error_codes_pb2.Code.ValueType] | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["cancel_op_name", b"cancel_op_name", "close_op_name", b"close_op_name", "enqueue_op_name", b"enqueue_op_name", "queue_closed_exception_types", b"queue_closed_exception_types", "queue_name", b"queue_name"]) -> None: ... + def ClearField(self, field_name: typing.Literal["cancel_op_name", b"cancel_op_name", "close_op_name", b"close_op_name", "enqueue_op_name", b"enqueue_op_name", "queue_closed_exception_types", b"queue_closed_exception_types", "queue_name", b"queue_name"]) -> None: ... global___QueueRunnerDef = QueueRunnerDef diff --git a/stubs/tensorflow/tensorflow/core/protobuf/remote_tensor_handle_pb2.pyi b/stubs/tensorflow/tensorflow/core/protobuf/remote_tensor_handle_pb2.pyi index a394c73a80b7..6558122b328b 100644 --- a/stubs/tensorflow/tensorflow/core/protobuf/remote_tensor_handle_pb2.pyi +++ b/stubs/tensorflow/tensorflow/core/protobuf/remote_tensor_handle_pb2.pyi @@ -2,9 +2,10 @@ @generated by mypy-protobuf. Do not edit manually! isort:skip_file """ + import builtins import collections.abc -import typing as typing_extensions +import typing import google.protobuf.descriptor import google.protobuf.internal.containers @@ -14,7 +15,7 @@ import tensorflow.core.framework.types_pb2 DESCRIPTOR: google.protobuf.descriptor.FileDescriptor -@typing_extensions.final +@typing.final class ResourceDtypeAndShape(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -29,12 +30,12 @@ class ResourceDtypeAndShape(google.protobuf.message.Message): dtype: tensorflow.core.framework.types_pb2.DataType.ValueType | None = ..., shape: tensorflow.core.framework.tensor_shape_pb2.TensorShapeProto | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["shape", b"shape"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["dtype", b"dtype", "shape", b"shape"]) -> None: ... + def HasField(self, field_name: typing.Literal["shape", b"shape"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["dtype", b"dtype", "shape", b"shape"]) -> None: ... global___ResourceDtypeAndShape = ResourceDtypeAndShape -@typing_extensions.final +@typing.final class RemoteTensorHandle(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -61,6 +62,7 @@ class RemoteTensorHandle(google.protobuf.message.Message): @property def resource_dtypes_and_shapes(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___ResourceDtypeAndShape]: """Optional data types and shapes of a remote resource variable.""" + def __init__( self, *, @@ -71,6 +73,6 @@ class RemoteTensorHandle(google.protobuf.message.Message): dtype: tensorflow.core.framework.types_pb2.DataType.ValueType | None = ..., resource_dtypes_and_shapes: collections.abc.Iterable[global___ResourceDtypeAndShape] | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["device", b"device", "dtype", b"dtype", "op_device", b"op_device", "op_id", b"op_id", "output_num", b"output_num", "resource_dtypes_and_shapes", b"resource_dtypes_and_shapes"]) -> None: ... + def ClearField(self, field_name: typing.Literal["device", b"device", "dtype", b"dtype", "op_device", b"op_device", "op_id", b"op_id", "output_num", b"output_num", "resource_dtypes_and_shapes", b"resource_dtypes_and_shapes"]) -> None: ... global___RemoteTensorHandle = RemoteTensorHandle diff --git a/stubs/tensorflow/tensorflow/core/protobuf/rewriter_config_pb2.pyi b/stubs/tensorflow/tensorflow/core/protobuf/rewriter_config_pb2.pyi index 9bf638aa42bd..5b151fcc702c 100644 --- a/stubs/tensorflow/tensorflow/core/protobuf/rewriter_config_pb2.pyi +++ b/stubs/tensorflow/tensorflow/core/protobuf/rewriter_config_pb2.pyi @@ -2,6 +2,7 @@ @generated by mypy-protobuf. Do not edit manually! isort:skip_file """ + import builtins import collections.abc import sys @@ -21,7 +22,7 @@ else: DESCRIPTOR: google.protobuf.descriptor.FileDescriptor -@typing_extensions.final +@typing.final class AutoParallelOptions(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -35,11 +36,11 @@ class AutoParallelOptions(google.protobuf.message.Message): enable: builtins.bool | None = ..., num_replicas: builtins.int | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["enable", b"enable", "num_replicas", b"num_replicas"]) -> None: ... + def ClearField(self, field_name: typing.Literal["enable", b"enable", "num_replicas", b"num_replicas"]) -> None: ... global___AutoParallelOptions = AutoParallelOptions -@typing_extensions.final +@typing.final class ScopedAllocatorOptions(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -47,16 +48,17 @@ class ScopedAllocatorOptions(google.protobuf.message.Message): @property def enable_op(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.str]: """If present, only perform optimization for these ops.""" + def __init__( self, *, enable_op: collections.abc.Iterable[builtins.str] | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["enable_op", b"enable_op"]) -> None: ... + def ClearField(self, field_name: typing.Literal["enable_op", b"enable_op"]) -> None: ... global___ScopedAllocatorOptions = ScopedAllocatorOptions -@typing_extensions.final +@typing.final class RewriterConfig(google.protobuf.message.Message): """Graph rewriting is experimental and subject to change, not covered by any API stability guarantees. @@ -207,13 +209,13 @@ class RewriterConfig(google.protobuf.message.Message): HEURISTICS: RewriterConfig.MemOptType.ValueType # 3 """Use any combination of swapping and recomputation heuristics.""" - @typing_extensions.final + @typing.final class CustomGraphOptimizer(google.protobuf.message.Message): """Message to describe custom graph optimizer and its parameters""" DESCRIPTOR: google.protobuf.descriptor.Descriptor - @typing_extensions.final + @typing.final class ParameterMapEntry(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -228,8 +230,8 @@ class RewriterConfig(google.protobuf.message.Message): key: builtins.str | None = ..., value: tensorflow.core.framework.attr_value_pb2.AttrValue | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["value", b"value"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["key", b"key", "value", b"value"]) -> None: ... + def HasField(self, field_name: typing.Literal["value", b"value"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["key", b"key", "value", b"value"]) -> None: ... NAME_FIELD_NUMBER: builtins.int PARAMETER_MAP_FIELD_NUMBER: builtins.int @@ -242,7 +244,7 @@ class RewriterConfig(google.protobuf.message.Message): name: builtins.str | None = ..., parameter_map: collections.abc.Mapping[builtins.str, tensorflow.core.framework.attr_value_pb2.AttrValue] | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["name", b"name", "parameter_map", b"parameter_map"]) -> None: ... + def ClearField(self, field_name: typing.Literal["name", b"name", "parameter_map", b"parameter_map"]) -> None: ... CPU_LAYOUT_CONVERSION_FIELD_NUMBER: builtins.int LAYOUT_OPTIMIZER_FIELD_NUMBER: builtins.int @@ -403,16 +405,17 @@ class RewriterConfig(google.protobuf.message.Message): timing out. If less than or equal to 0 (default value) the optimizer will never time out. """ - @property - def auto_parallel(self) -> global___AutoParallelOptions: - """Configures AutoParallel optimization passes either through the - meta-optimizer or when manually specified through the optimizers field. - """ fail_on_optimizer_errors: builtins.bool """If true, any optimization pass failing will cause the MetaOptimizer to stop with an error. By default - or when set to false, failing passes are skipped silently. """ + @property + def auto_parallel(self) -> global___AutoParallelOptions: + """Configures AutoParallel optimization passes either through the + meta-optimizer or when manually specified through the optimizers field. + """ + @property def scoped_allocator_opts(self) -> global___ScopedAllocatorOptions: ... @property @@ -430,17 +433,21 @@ class RewriterConfig(google.protobuf.message.Message): Custom optimizers (see custom_optimizers) that are not part of this schedule will be run after - in the order that they were specified. """ + @property def custom_optimizers(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___RewriterConfig.CustomGraphOptimizer]: """list of CustomGraphOptimizers to apply.""" + @property def inter_optimizer_verifier_config(self) -> tensorflow.core.protobuf.verifier_config_pb2.VerifierConfig: """VerifierConfig specifying the verifiers to be run after every optimizer.""" + @property def post_optimization_verifier_config(self) -> tensorflow.core.protobuf.verifier_config_pb2.VerifierConfig: """VerifierConfig specifying the verifiers to be run at the end, after all optimizers have run. """ + def __init__( self, *, @@ -481,7 +488,7 @@ class RewriterConfig(google.protobuf.message.Message): inter_optimizer_verifier_config: tensorflow.core.protobuf.verifier_config_pb2.VerifierConfig | None = ..., post_optimization_verifier_config: tensorflow.core.protobuf.verifier_config_pb2.VerifierConfig | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["auto_parallel", b"auto_parallel", "inter_optimizer_verifier_config", b"inter_optimizer_verifier_config", "post_optimization_verifier_config", b"post_optimization_verifier_config", "scoped_allocator_opts", b"scoped_allocator_opts"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["arithmetic_optimization", b"arithmetic_optimization", "auto_mixed_precision", b"auto_mixed_precision", "auto_mixed_precision_cpu", b"auto_mixed_precision_cpu", "auto_mixed_precision_mkl", b"auto_mixed_precision_mkl", "auto_mixed_precision_onednn_bfloat16", b"auto_mixed_precision_onednn_bfloat16", "auto_parallel", b"auto_parallel", "common_subgraph_elimination", b"common_subgraph_elimination", "constant_folding", b"constant_folding", "cpu_layout_conversion", b"cpu_layout_conversion", "custom_optimizers", b"custom_optimizers", "debug_stripper", b"debug_stripper", "dependency_optimization", b"dependency_optimization", "disable_meta_optimizer", b"disable_meta_optimizer", "disable_model_pruning", b"disable_model_pruning", "experimental_conditional_code_motion", b"experimental_conditional_code_motion", "experimental_disable_compressed_tensor_optimization", b"experimental_disable_compressed_tensor_optimization", "experimental_disable_folding_quantization_emulation", b"experimental_disable_folding_quantization_emulation", "fail_on_optimizer_errors", b"fail_on_optimizer_errors", "function_optimization", b"function_optimization", "implementation_selector", b"implementation_selector", "inter_optimizer_verifier_config", b"inter_optimizer_verifier_config", "layout_optimizer", b"layout_optimizer", "loop_optimization", b"loop_optimization", "memory_optimization", b"memory_optimization", "memory_optimizer_target_node_name_scope", b"memory_optimizer_target_node_name_scope", "meta_optimizer_iterations", b"meta_optimizer_iterations", "meta_optimizer_timeout_ms", b"meta_optimizer_timeout_ms", "min_graph_nodes", b"min_graph_nodes", "optimizers", b"optimizers", "pin_to_host_optimization", b"pin_to_host_optimization", "post_optimization_verifier_config", b"post_optimization_verifier_config", "remapping", b"remapping", "scoped_allocator_optimization", b"scoped_allocator_optimization", "scoped_allocator_opts", b"scoped_allocator_opts", "shape_optimization", b"shape_optimization", "use_plugin_optimizers", b"use_plugin_optimizers"]) -> None: ... + def HasField(self, field_name: typing.Literal["auto_parallel", b"auto_parallel", "inter_optimizer_verifier_config", b"inter_optimizer_verifier_config", "post_optimization_verifier_config", b"post_optimization_verifier_config", "scoped_allocator_opts", b"scoped_allocator_opts"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["arithmetic_optimization", b"arithmetic_optimization", "auto_mixed_precision", b"auto_mixed_precision", "auto_mixed_precision_cpu", b"auto_mixed_precision_cpu", "auto_mixed_precision_mkl", b"auto_mixed_precision_mkl", "auto_mixed_precision_onednn_bfloat16", b"auto_mixed_precision_onednn_bfloat16", "auto_parallel", b"auto_parallel", "common_subgraph_elimination", b"common_subgraph_elimination", "constant_folding", b"constant_folding", "cpu_layout_conversion", b"cpu_layout_conversion", "custom_optimizers", b"custom_optimizers", "debug_stripper", b"debug_stripper", "dependency_optimization", b"dependency_optimization", "disable_meta_optimizer", b"disable_meta_optimizer", "disable_model_pruning", b"disable_model_pruning", "experimental_conditional_code_motion", b"experimental_conditional_code_motion", "experimental_disable_compressed_tensor_optimization", b"experimental_disable_compressed_tensor_optimization", "experimental_disable_folding_quantization_emulation", b"experimental_disable_folding_quantization_emulation", "fail_on_optimizer_errors", b"fail_on_optimizer_errors", "function_optimization", b"function_optimization", "implementation_selector", b"implementation_selector", "inter_optimizer_verifier_config", b"inter_optimizer_verifier_config", "layout_optimizer", b"layout_optimizer", "loop_optimization", b"loop_optimization", "memory_optimization", b"memory_optimization", "memory_optimizer_target_node_name_scope", b"memory_optimizer_target_node_name_scope", "meta_optimizer_iterations", b"meta_optimizer_iterations", "meta_optimizer_timeout_ms", b"meta_optimizer_timeout_ms", "min_graph_nodes", b"min_graph_nodes", "optimizers", b"optimizers", "pin_to_host_optimization", b"pin_to_host_optimization", "post_optimization_verifier_config", b"post_optimization_verifier_config", "remapping", b"remapping", "scoped_allocator_optimization", b"scoped_allocator_optimization", "scoped_allocator_opts", b"scoped_allocator_opts", "shape_optimization", b"shape_optimization", "use_plugin_optimizers", b"use_plugin_optimizers"]) -> None: ... global___RewriterConfig = RewriterConfig diff --git a/stubs/tensorflow/tensorflow/core/protobuf/rpc_options_pb2.pyi b/stubs/tensorflow/tensorflow/core/protobuf/rpc_options_pb2.pyi index f81919a4fc42..acc9e9bdb45a 100644 --- a/stubs/tensorflow/tensorflow/core/protobuf/rpc_options_pb2.pyi +++ b/stubs/tensorflow/tensorflow/core/protobuf/rpc_options_pb2.pyi @@ -2,6 +2,7 @@ @generated by mypy-protobuf. Do not edit manually! isort:skip_file """ + import google.protobuf.descriptor from tensorflow.tsl.protobuf.rpc_options_pb2 import RPCOptions as RPCOptions diff --git a/stubs/tensorflow/tensorflow/core/protobuf/saved_model_pb2.pyi b/stubs/tensorflow/tensorflow/core/protobuf/saved_model_pb2.pyi index da656e1b0886..cd2bdb7a2a13 100644 --- a/stubs/tensorflow/tensorflow/core/protobuf/saved_model_pb2.pyi +++ b/stubs/tensorflow/tensorflow/core/protobuf/saved_model_pb2.pyi @@ -2,9 +2,10 @@ @generated by mypy-protobuf. Do not edit manually! isort:skip_file """ + import builtins import collections.abc -import typing as typing_extensions +import typing import google.protobuf.descriptor import google.protobuf.internal.containers @@ -13,7 +14,7 @@ import tensorflow.core.protobuf.meta_graph_pb2 DESCRIPTOR: google.protobuf.descriptor.FileDescriptor -@typing_extensions.final +@typing.final class SavedModel(google.protobuf.message.Message): """SavedModel is the high level serialization format for TensorFlow Models. See [todo: doc links, similar to session_bundle] for more information. @@ -31,12 +32,13 @@ class SavedModel(google.protobuf.message.Message): @property def meta_graphs(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[tensorflow.core.protobuf.meta_graph_pb2.MetaGraphDef]: """One or more MetaGraphs.""" + def __init__( self, *, saved_model_schema_version: builtins.int | None = ..., meta_graphs: collections.abc.Iterable[tensorflow.core.protobuf.meta_graph_pb2.MetaGraphDef] | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["meta_graphs", b"meta_graphs", "saved_model_schema_version", b"saved_model_schema_version"]) -> None: ... + def ClearField(self, field_name: typing.Literal["meta_graphs", b"meta_graphs", "saved_model_schema_version", b"saved_model_schema_version"]) -> None: ... global___SavedModel = SavedModel diff --git a/stubs/tensorflow/tensorflow/core/protobuf/saved_object_graph_pb2.pyi b/stubs/tensorflow/tensorflow/core/protobuf/saved_object_graph_pb2.pyi index c74ca7cedfde..4a6f0c1d51e0 100644 --- a/stubs/tensorflow/tensorflow/core/protobuf/saved_object_graph_pb2.pyi +++ b/stubs/tensorflow/tensorflow/core/protobuf/saved_object_graph_pb2.pyi @@ -2,6 +2,7 @@ @generated by mypy-protobuf. Do not edit manually! isort:skip_file """ + import builtins import collections.abc import sys @@ -26,7 +27,7 @@ else: DESCRIPTOR: google.protobuf.descriptor.FileDescriptor -@typing_extensions.final +@typing.final class SavedObjectGraph(google.protobuf.message.Message): """SavedObjectGraph shares some structure with TrackableObjectGraph, but SavedObjectGraph belongs to the MetaGraph and contains pointers to functions @@ -36,7 +37,7 @@ class SavedObjectGraph(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor - @typing_extensions.final + @typing.final class ConcreteFunctionsEntry(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -51,8 +52,8 @@ class SavedObjectGraph(google.protobuf.message.Message): key: builtins.str | None = ..., value: global___SavedConcreteFunction | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["value", b"value"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["key", b"key", "value", b"value"]) -> None: ... + def HasField(self, field_name: typing.Literal["value", b"value"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["key", b"key", "value", b"value"]) -> None: ... NODES_FIELD_NUMBER: builtins.int CONCRETE_FUNCTIONS_FIELD_NUMBER: builtins.int @@ -63,26 +64,28 @@ class SavedObjectGraph(google.protobuf.message.Message): The position of the object in this list indicates its id. Nodes[0] is considered the root node. """ + @property def concrete_functions(self) -> google.protobuf.internal.containers.MessageMap[builtins.str, global___SavedConcreteFunction]: """Information about captures and output structures in concrete functions. Referenced from SavedBareConcreteFunction and SavedFunction. """ + def __init__( self, *, nodes: collections.abc.Iterable[global___SavedObject] | None = ..., concrete_functions: collections.abc.Mapping[builtins.str, global___SavedConcreteFunction] | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["concrete_functions", b"concrete_functions", "nodes", b"nodes"]) -> None: ... + def ClearField(self, field_name: typing.Literal["concrete_functions", b"concrete_functions", "nodes", b"nodes"]) -> None: ... global___SavedObjectGraph = SavedObjectGraph -@typing_extensions.final +@typing.final class SavedObject(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor - @typing_extensions.final + @typing.final class SaveableObjectsEntry(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -97,8 +100,8 @@ class SavedObject(google.protobuf.message.Message): key: builtins.str | None = ..., value: global___SaveableObject | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["value", b"value"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["key", b"key", "value", b"value"]) -> None: ... + def HasField(self, field_name: typing.Literal["value", b"value"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["key", b"key", "value", b"value"]) -> None: ... CHILDREN_FIELD_NUMBER: builtins.int DEPENDENCIES_FIELD_NUMBER: builtins.int @@ -115,6 +118,28 @@ class SavedObject(google.protobuf.message.Message): REGISTERED_NAME_FIELD_NUMBER: builtins.int SERIALIZED_USER_PROTO_FIELD_NUMBER: builtins.int REGISTERED_SAVER_FIELD_NUMBER: builtins.int + registered_name: builtins.str + """The fields below are filled when the user serializes a registered Trackable + class or an object with a registered saver function. + + Registered classes may save additional metadata and supersede the + default loading process where nodes are recreated from the proto. + If the registered class cannot be found, then the object will load as one + one of the default trackable objects: Autotrackable (a class similar to + tf.Module), tf.function, or tf.Variable. + + Unlike SaveableObjects, which store the functions for saving and restoring + from tensors, registered savers allow Trackables to write checkpoint shards + directly (e.g. for performance or coordination reasons). + *All registered savers must be available when loading the SavedModel.* + + The name of the registered class of the form "{package}.{class_name}". + This field is used to search for the registered class at loading time. + """ + registered_saver: builtins.str + """String name of the registered saver. At most one of `saveable_objects` or + `registered_saver` is defined for each SavedObject. + """ @property def children(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[tensorflow.core.protobuf.trackable_object_graph_pb2.TrackableObjectGraph.TrackableObject.ObjectReference]: """Objects which this object depends on: named edges in the dependency @@ -123,12 +148,14 @@ class SavedObject(google.protobuf.message.Message): Note: All kinds of SavedObject may have children, except "constant" and "captured_tensor". """ + @property def dependencies(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[tensorflow.core.protobuf.trackable_object_graph_pb2.TrackableObjectGraph.TrackableObject.ObjectReference]: """Ordered list of dependencies that must be loaded before this object. SavedModel loads with the bottom-up approach, by first creating all objects (in the order defined by the dependencies), then connecting the edges. """ + @property def slot_variables(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[tensorflow.core.protobuf.trackable_object_graph_pb2.TrackableObjectGraph.TrackableObject.SlotVariableReference]: """Slot variables owned by this object. This describes the three-way @@ -137,6 +164,7 @@ class SavedObject(google.protobuf.message.Message): Note: currently only valid if kind == "user_object". """ + @property def user_object(self) -> global___SavedUserObject: ... @property @@ -160,34 +188,14 @@ class SavedObject(google.protobuf.message.Message): See the comment below for the difference between SaveableObject and registered savers. """ - registered_name: builtins.str - """The fields below are filled when the user serializes a registered Trackable - class or an object with a registered saver function. - - Registered classes may save additional metadata and supersede the - default loading process where nodes are recreated from the proto. - If the registered class cannot be found, then the object will load as one - one of the default trackable objects: Autotrackable (a class similar to - tf.Module), tf.function, or tf.Variable. - - Unlike SaveableObjects, which store the functions for saving and restoring - from tensors, registered savers allow Trackables to write checkpoint shards - directly (e.g. for performance or coordination reasons). - *All registered savers must be available when loading the SavedModel.* - The name of the registered class of the form "{package}.{class_name}". - This field is used to search for the registered class at loading time. - """ @property def serialized_user_proto(self) -> google.protobuf.any_pb2.Any: """The user-generated proto storing metadata for this object, to be passed to the registered classes's _deserialize_from_proto method when this object is loaded from the SavedModel. """ - registered_saver: builtins.str - """String name of the registered saver. At most one of `saveable_objects` or - `registered_saver` is defined for each SavedObject. - """ + def __init__( self, *, @@ -207,13 +215,13 @@ class SavedObject(google.protobuf.message.Message): serialized_user_proto: google.protobuf.any_pb2.Any | None = ..., registered_saver: builtins.str | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["asset", b"asset", "bare_concrete_function", b"bare_concrete_function", "captured_tensor", b"captured_tensor", "constant", b"constant", "function", b"function", "kind", b"kind", "resource", b"resource", "serialized_user_proto", b"serialized_user_proto", "user_object", b"user_object", "variable", b"variable"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["asset", b"asset", "bare_concrete_function", b"bare_concrete_function", "captured_tensor", b"captured_tensor", "children", b"children", "constant", b"constant", "dependencies", b"dependencies", "function", b"function", "kind", b"kind", "registered_name", b"registered_name", "registered_saver", b"registered_saver", "resource", b"resource", "saveable_objects", b"saveable_objects", "serialized_user_proto", b"serialized_user_proto", "slot_variables", b"slot_variables", "user_object", b"user_object", "variable", b"variable"]) -> None: ... - def WhichOneof(self, oneof_group: typing_extensions.Literal["kind", b"kind"]) -> typing_extensions.Literal["user_object", "asset", "function", "variable", "bare_concrete_function", "constant", "resource", "captured_tensor"] | None: ... + def HasField(self, field_name: typing.Literal["asset", b"asset", "bare_concrete_function", b"bare_concrete_function", "captured_tensor", b"captured_tensor", "constant", b"constant", "function", b"function", "kind", b"kind", "resource", b"resource", "serialized_user_proto", b"serialized_user_proto", "user_object", b"user_object", "variable", b"variable"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["asset", b"asset", "bare_concrete_function", b"bare_concrete_function", "captured_tensor", b"captured_tensor", "children", b"children", "constant", b"constant", "dependencies", b"dependencies", "function", b"function", "kind", b"kind", "registered_name", b"registered_name", "registered_saver", b"registered_saver", "resource", b"resource", "saveable_objects", b"saveable_objects", "serialized_user_proto", b"serialized_user_proto", "slot_variables", b"slot_variables", "user_object", b"user_object", "variable", b"variable"]) -> None: ... + def WhichOneof(self, oneof_group: typing.Literal["kind", b"kind"]) -> typing.Literal["user_object", "asset", "function", "variable", "bare_concrete_function", "constant", "resource", "captured_tensor"] | None: ... global___SavedObject = SavedObject -@typing_extensions.final +@typing.final class SavedUserObject(google.protobuf.message.Message): """A SavedUserObject is an object (in the object-oriented language of the TensorFlow program) of some user- or framework-defined class other than @@ -230,9 +238,6 @@ class SavedUserObject(google.protobuf.message.Message): METADATA_FIELD_NUMBER: builtins.int identifier: builtins.str """Corresponds to a registration of the type to use in the loading program.""" - @property - def version(self) -> tensorflow.core.framework.versions_pb2.VersionDef: - """Version information from the producer of this SavedUserObject.""" metadata: builtins.str """Metadata for deserializing this object. @@ -240,6 +245,10 @@ class SavedUserObject(google.protobuf.message.Message): field, and its saving and loading code will be updated shortly. Please save your application-specific metadata to a separate file. """ + @property + def version(self) -> tensorflow.core.framework.versions_pb2.VersionDef: + """Version information from the producer of this SavedUserObject.""" + def __init__( self, *, @@ -247,12 +256,12 @@ class SavedUserObject(google.protobuf.message.Message): version: tensorflow.core.framework.versions_pb2.VersionDef | None = ..., metadata: builtins.str | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["version", b"version"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["identifier", b"identifier", "metadata", b"metadata", "version", b"version"]) -> None: ... + def HasField(self, field_name: typing.Literal["version", b"version"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["identifier", b"identifier", "metadata", b"metadata", "version", b"version"]) -> None: ... global___SavedUserObject = SavedUserObject -@typing_extensions.final +@typing.final class SavedAsset(google.protobuf.message.Message): """A SavedAsset points to an asset in the MetaGraph. @@ -275,11 +284,11 @@ class SavedAsset(google.protobuf.message.Message): *, asset_file_def_index: builtins.int | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["asset_file_def_index", b"asset_file_def_index"]) -> None: ... + def ClearField(self, field_name: typing.Literal["asset_file_def_index", b"asset_file_def_index"]) -> None: ... global___SavedAsset = SavedAsset -@typing_extensions.final +@typing.final class SavedFunction(google.protobuf.message.Message): """A function with multiple signatures, possibly with non-Tensor arguments.""" @@ -297,12 +306,12 @@ class SavedFunction(google.protobuf.message.Message): concrete_functions: collections.abc.Iterable[builtins.str] | None = ..., function_spec: global___FunctionSpec | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["function_spec", b"function_spec"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["concrete_functions", b"concrete_functions", "function_spec", b"function_spec"]) -> None: ... + def HasField(self, field_name: typing.Literal["function_spec", b"function_spec"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["concrete_functions", b"concrete_functions", "function_spec", b"function_spec"]) -> None: ... global___SavedFunction = SavedFunction -@typing_extensions.final +@typing.final class CapturedTensor(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -318,11 +327,11 @@ class CapturedTensor(google.protobuf.message.Message): name: builtins.str | None = ..., concrete_function: builtins.str | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["concrete_function", b"concrete_function", "name", b"name"]) -> None: ... + def ClearField(self, field_name: typing.Literal["concrete_function", b"concrete_function", "name", b"name"]) -> None: ... global___CapturedTensor = CapturedTensor -@typing_extensions.final +@typing.final class SavedConcreteFunction(google.protobuf.message.Message): """Stores low-level information about a concrete function. Referenced in either a SavedFunction or a SavedBareConcreteFunction. @@ -340,12 +349,14 @@ class SavedConcreteFunction(google.protobuf.message.Message): """Input in canonicalized form that was received to create this concrete function. """ + @property def output_signature(self) -> tensorflow.core.protobuf.struct_pb2.StructuredValue: """Output that was the return value of this function after replacing all Tensors with TensorSpecs. This can be an arbitrary nested function and will be used to reconstruct the full structure from pure tensors. """ + def __init__( self, *, @@ -353,12 +364,12 @@ class SavedConcreteFunction(google.protobuf.message.Message): canonicalized_input_signature: tensorflow.core.protobuf.struct_pb2.StructuredValue | None = ..., output_signature: tensorflow.core.protobuf.struct_pb2.StructuredValue | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["canonicalized_input_signature", b"canonicalized_input_signature", "output_signature", b"output_signature"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["bound_inputs", b"bound_inputs", "canonicalized_input_signature", b"canonicalized_input_signature", "output_signature", b"output_signature"]) -> None: ... + def HasField(self, field_name: typing.Literal["canonicalized_input_signature", b"canonicalized_input_signature", "output_signature", b"output_signature"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["bound_inputs", b"bound_inputs", "canonicalized_input_signature", b"canonicalized_input_signature", "output_signature", b"output_signature"]) -> None: ... global___SavedConcreteFunction = SavedConcreteFunction -@typing_extensions.final +@typing.final class SavedBareConcreteFunction(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -368,11 +379,12 @@ class SavedBareConcreteFunction(google.protobuf.message.Message): FUNCTION_SPEC_FIELD_NUMBER: builtins.int concrete_function_name: builtins.str """Identifies a SavedConcreteFunction.""" + allowed_positional_arguments: builtins.int + """The prefix of `argument_keywords` which may be identified by position.""" @property def argument_keywords(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.str]: """A sequence of unique strings, one per Tensor argument.""" - allowed_positional_arguments: builtins.int - """The prefix of `argument_keywords` which may be identified by position.""" + @property def function_spec(self) -> global___FunctionSpec: """The spec of the function that this ConcreteFunction is traced from. This @@ -382,6 +394,7 @@ class SavedBareConcreteFunction(google.protobuf.message.Message): TODO(b/169361281): support calling saved ConcreteFunction with structured inputs in C++ SavedModel API. """ + def __init__( self, *, @@ -390,12 +403,12 @@ class SavedBareConcreteFunction(google.protobuf.message.Message): allowed_positional_arguments: builtins.int | None = ..., function_spec: global___FunctionSpec | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["function_spec", b"function_spec"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["allowed_positional_arguments", b"allowed_positional_arguments", "argument_keywords", b"argument_keywords", "concrete_function_name", b"concrete_function_name", "function_spec", b"function_spec"]) -> None: ... + def HasField(self, field_name: typing.Literal["function_spec", b"function_spec"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["allowed_positional_arguments", b"allowed_positional_arguments", "argument_keywords", b"argument_keywords", "concrete_function_name", b"concrete_function_name", "function_spec", b"function_spec"]) -> None: ... global___SavedBareConcreteFunction = SavedBareConcreteFunction -@typing_extensions.final +@typing.final class SavedConstant(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -407,11 +420,11 @@ class SavedConstant(google.protobuf.message.Message): *, operation: builtins.str | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["operation", b"operation"]) -> None: ... + def ClearField(self, field_name: typing.Literal["operation", b"operation"]) -> None: ... global___SavedConstant = SavedConstant -@typing_extensions.final +@typing.final class SavedVariable(google.protobuf.message.Message): """Represents a Variable that is initialized by loading the contents from the checkpoint. @@ -428,14 +441,14 @@ class SavedVariable(google.protobuf.message.Message): DEVICE_FIELD_NUMBER: builtins.int EXPERIMENTAL_DISTRIBUTED_VARIABLE_COMPONENTS_FIELD_NUMBER: builtins.int dtype: tensorflow.core.framework.types_pb2.DataType.ValueType - @property - def shape(self) -> tensorflow.core.framework.tensor_shape_pb2.TensorShapeProto: ... trainable: builtins.bool synchronization: tensorflow.core.framework.variable_pb2.VariableSynchronization.ValueType aggregation: tensorflow.core.framework.variable_pb2.VariableAggregation.ValueType name: builtins.str device: builtins.str @property + def shape(self) -> tensorflow.core.framework.tensor_shape_pb2.TensorShapeProto: ... + @property def experimental_distributed_variable_components(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___SavedVariable]: """List of component variables for a distributed variable. @@ -444,6 +457,7 @@ class SavedVariable(google.protobuf.message.Message): This is only supported by experimental loaders at the moment. """ + def __init__( self, *, @@ -456,12 +470,12 @@ class SavedVariable(google.protobuf.message.Message): device: builtins.str | None = ..., experimental_distributed_variable_components: collections.abc.Iterable[global___SavedVariable] | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["shape", b"shape"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["aggregation", b"aggregation", "device", b"device", "dtype", b"dtype", "experimental_distributed_variable_components", b"experimental_distributed_variable_components", "name", b"name", "shape", b"shape", "synchronization", b"synchronization", "trainable", b"trainable"]) -> None: ... + def HasField(self, field_name: typing.Literal["shape", b"shape"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["aggregation", b"aggregation", "device", b"device", "dtype", b"dtype", "experimental_distributed_variable_components", b"experimental_distributed_variable_components", "name", b"name", "shape", b"shape", "synchronization", b"synchronization", "trainable", b"trainable"]) -> None: ... global___SavedVariable = SavedVariable -@typing_extensions.final +@typing.final class FunctionSpec(google.protobuf.message.Message): """Represents `FunctionSpec` used in `Function`. This represents a function that has been wrapped as a TensorFlow `Function`. @@ -498,15 +512,17 @@ class FunctionSpec(google.protobuf.message.Message): IS_METHOD_FIELD_NUMBER: builtins.int INPUT_SIGNATURE_FIELD_NUMBER: builtins.int JIT_COMPILE_FIELD_NUMBER: builtins.int + is_method: builtins.bool + """Whether this represents a class method.""" + jit_compile: global___FunctionSpec.JitCompile.ValueType @property def fullargspec(self) -> tensorflow.core.protobuf.struct_pb2.StructuredValue: """Full arg spec from inspect.getfullargspec().""" - is_method: builtins.bool - """Whether this represents a class method.""" + @property def input_signature(self) -> tensorflow.core.protobuf.struct_pb2.StructuredValue: """The input signature, if specified.""" - jit_compile: global___FunctionSpec.JitCompile.ValueType + def __init__( self, *, @@ -515,12 +531,12 @@ class FunctionSpec(google.protobuf.message.Message): input_signature: tensorflow.core.protobuf.struct_pb2.StructuredValue | None = ..., jit_compile: global___FunctionSpec.JitCompile.ValueType | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["fullargspec", b"fullargspec", "input_signature", b"input_signature"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["fullargspec", b"fullargspec", "input_signature", b"input_signature", "is_method", b"is_method", "jit_compile", b"jit_compile"]) -> None: ... + def HasField(self, field_name: typing.Literal["fullargspec", b"fullargspec", "input_signature", b"input_signature"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["fullargspec", b"fullargspec", "input_signature", b"input_signature", "is_method", b"is_method", "jit_compile", b"jit_compile"]) -> None: ... global___FunctionSpec = FunctionSpec -@typing_extensions.final +@typing.final class SavedResource(google.protobuf.message.Message): """A SavedResource represents a TF object that holds state during its lifetime. An object of this type can have a reference to a: @@ -540,11 +556,11 @@ class SavedResource(google.protobuf.message.Message): *, device: builtins.str | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["device", b"device"]) -> None: ... + def ClearField(self, field_name: typing.Literal["device", b"device"]) -> None: ... global___SavedResource = SavedResource -@typing_extensions.final +@typing.final class SaveableObject(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -561,6 +577,6 @@ class SaveableObject(google.protobuf.message.Message): save_function: builtins.int | None = ..., restore_function: builtins.int | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["restore_function", b"restore_function", "save_function", b"save_function"]) -> None: ... + def ClearField(self, field_name: typing.Literal["restore_function", b"restore_function", "save_function", b"save_function"]) -> None: ... global___SaveableObject = SaveableObject diff --git a/stubs/tensorflow/tensorflow/core/protobuf/saver_pb2.pyi b/stubs/tensorflow/tensorflow/core/protobuf/saver_pb2.pyi index a5acf0bec8f1..1f89eebf8f98 100644 --- a/stubs/tensorflow/tensorflow/core/protobuf/saver_pb2.pyi +++ b/stubs/tensorflow/tensorflow/core/protobuf/saver_pb2.pyi @@ -2,6 +2,7 @@ @generated by mypy-protobuf. Do not edit manually! isort:skip_file """ + import builtins import sys import typing @@ -17,7 +18,7 @@ else: DESCRIPTOR: google.protobuf.descriptor.FileDescriptor -@typing_extensions.final +@typing.final class SaverDef(google.protobuf.message.Message): """Protocol buffer representing the configuration of a Saver.""" @@ -87,6 +88,6 @@ class SaverDef(google.protobuf.message.Message): keep_checkpoint_every_n_hours: builtins.float | None = ..., version: global___SaverDef.CheckpointFormatVersion.ValueType | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["filename_tensor_name", b"filename_tensor_name", "keep_checkpoint_every_n_hours", b"keep_checkpoint_every_n_hours", "max_to_keep", b"max_to_keep", "restore_op_name", b"restore_op_name", "save_tensor_name", b"save_tensor_name", "sharded", b"sharded", "version", b"version"]) -> None: ... + def ClearField(self, field_name: typing.Literal["filename_tensor_name", b"filename_tensor_name", "keep_checkpoint_every_n_hours", b"keep_checkpoint_every_n_hours", "max_to_keep", b"max_to_keep", "restore_op_name", b"restore_op_name", "save_tensor_name", b"save_tensor_name", "sharded", b"sharded", "version", b"version"]) -> None: ... global___SaverDef = SaverDef diff --git a/stubs/tensorflow/tensorflow/core/protobuf/service_config_pb2.pyi b/stubs/tensorflow/tensorflow/core/protobuf/service_config_pb2.pyi index 96ae66ee2f29..a2e0264efabd 100644 --- a/stubs/tensorflow/tensorflow/core/protobuf/service_config_pb2.pyi +++ b/stubs/tensorflow/tensorflow/core/protobuf/service_config_pb2.pyi @@ -2,9 +2,10 @@ @generated by mypy-protobuf. Do not edit manually! isort:skip_file """ + import builtins import collections.abc -import typing as typing_extensions +import typing import google.protobuf.descriptor import google.protobuf.internal.containers @@ -13,7 +14,7 @@ import tensorflow.core.protobuf.data_service_pb2 DESCRIPTOR: google.protobuf.descriptor.FileDescriptor -@typing_extensions.final +@typing.final class DispatcherConfig(google.protobuf.message.Message): """Configuration for a tf.data service DispatchServer. Next id: 11 @@ -45,13 +46,6 @@ class DispatcherConfig(google.protobuf.message.Message): """Whether to run in fault tolerant mode, where dispatcher state is saved across restarts. Requires that `work_dir` is nonempty. """ - @property - def worker_addresses(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.str]: - """(Optional.) If the job uses auto-sharding, it needs to specify a fixed list - of worker addresses that will register with the dispatcher. The worker - addresses should be in the format "host" or "host:port", where "port" is an - integer, named port, or %port% to match any port. - """ deployment_mode: tensorflow.core.protobuf.data_service_pb2.DeploymentMode.ValueType """(Optional.) tf.data service deployment mode. Supported values are "REMOTE", "COLOCATED", and "HYBRID". If unspecified, it is assumed to be "REMOTE". @@ -76,6 +70,14 @@ class DispatcherConfig(google.protobuf.message.Message): """How long to wait for a worker to heartbeat before considering it missing. A value of 0 indicates that the timeout should be left to the runtime. """ + @property + def worker_addresses(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.str]: + """(Optional.) If the job uses auto-sharding, it needs to specify a fixed list + of worker addresses that will register with the dispatcher. The worker + addresses should be in the format "host" or "host:port", where "port" is an + integer, named port, or %port% to match any port. + """ + def __init__( self, *, @@ -90,11 +92,11 @@ class DispatcherConfig(google.protobuf.message.Message): client_timeout_ms: builtins.int | None = ..., worker_timeout_ms: builtins.int | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["client_timeout_ms", b"client_timeout_ms", "deployment_mode", b"deployment_mode", "fault_tolerant_mode", b"fault_tolerant_mode", "job_gc_check_interval_ms", b"job_gc_check_interval_ms", "job_gc_timeout_ms", b"job_gc_timeout_ms", "port", b"port", "protocol", b"protocol", "work_dir", b"work_dir", "worker_addresses", b"worker_addresses", "worker_timeout_ms", b"worker_timeout_ms"]) -> None: ... + def ClearField(self, field_name: typing.Literal["client_timeout_ms", b"client_timeout_ms", "deployment_mode", b"deployment_mode", "fault_tolerant_mode", b"fault_tolerant_mode", "job_gc_check_interval_ms", b"job_gc_check_interval_ms", "job_gc_timeout_ms", b"job_gc_timeout_ms", "port", b"port", "protocol", b"protocol", "work_dir", b"work_dir", "worker_addresses", b"worker_addresses", "worker_timeout_ms", b"worker_timeout_ms"]) -> None: ... global___DispatcherConfig = DispatcherConfig -@typing_extensions.final +@typing.final class WorkerConfig(google.protobuf.message.Message): """Configuration for a tf.data service WorkerServer. Next id: 12 @@ -126,13 +128,6 @@ class WorkerConfig(google.protobuf.message.Message): will be replaced with the worker's bound port. This is useful when the port is set to `0`. """ - @property - def worker_tags(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.str]: - """Tags attached to the worker. This allows reading from selected workers. - For example, by applying a "COLOCATED" tag, tf.data service is able to read - from the local tf.data worker if one exists, then from off-TF-host workers, - to avoid cross-TF-host reads. - """ heartbeat_interval_ms: builtins.int """How often the worker should heartbeat to the master. A value of 0 indicates that the decision should be left up to the runtime. @@ -158,6 +153,14 @@ class WorkerConfig(google.protobuf.message.Message): process the final requests. This is used to achieve clean shutdown in unit tests. """ + @property + def worker_tags(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.str]: + """Tags attached to the worker. This allows reading from selected workers. + For example, by applying a "COLOCATED" tag, tf.data service is able to read + from the local tf.data worker if one exists, then from off-TF-host workers, + to avoid cross-TF-host reads. + """ + def __init__( self, *, @@ -173,6 +176,6 @@ class WorkerConfig(google.protobuf.message.Message): cross_trainer_cache_size_bytes: builtins.int | None = ..., shutdown_quiet_period_ms: builtins.int | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["cross_trainer_cache_size_bytes", b"cross_trainer_cache_size_bytes", "data_transfer_address", b"data_transfer_address", "data_transfer_protocol", b"data_transfer_protocol", "dispatcher_address", b"dispatcher_address", "dispatcher_timeout_ms", b"dispatcher_timeout_ms", "heartbeat_interval_ms", b"heartbeat_interval_ms", "port", b"port", "protocol", b"protocol", "shutdown_quiet_period_ms", b"shutdown_quiet_period_ms", "worker_address", b"worker_address", "worker_tags", b"worker_tags"]) -> None: ... + def ClearField(self, field_name: typing.Literal["cross_trainer_cache_size_bytes", b"cross_trainer_cache_size_bytes", "data_transfer_address", b"data_transfer_address", "data_transfer_protocol", b"data_transfer_protocol", "dispatcher_address", b"dispatcher_address", "dispatcher_timeout_ms", b"dispatcher_timeout_ms", "heartbeat_interval_ms", b"heartbeat_interval_ms", "port", b"port", "protocol", b"protocol", "shutdown_quiet_period_ms", b"shutdown_quiet_period_ms", "worker_address", b"worker_address", "worker_tags", b"worker_tags"]) -> None: ... global___WorkerConfig = WorkerConfig diff --git a/stubs/tensorflow/tensorflow/core/protobuf/snapshot_pb2.pyi b/stubs/tensorflow/tensorflow/core/protobuf/snapshot_pb2.pyi index 78ec3103f6d0..daeb2da4ad65 100644 --- a/stubs/tensorflow/tensorflow/core/protobuf/snapshot_pb2.pyi +++ b/stubs/tensorflow/tensorflow/core/protobuf/snapshot_pb2.pyi @@ -2,9 +2,10 @@ @generated by mypy-protobuf. Do not edit manually! isort:skip_file """ + import builtins import collections.abc -import typing as typing_extensions +import typing import google.protobuf.descriptor import google.protobuf.internal.containers @@ -15,7 +16,7 @@ import tensorflow.core.framework.types_pb2 DESCRIPTOR: google.protobuf.descriptor.FileDescriptor -@typing_extensions.final +@typing.final class SnapshotRecord(google.protobuf.message.Message): """Each SnapshotRecord represents one batch of pre-processed input data. A batch consists of a list of tensors that we encode as TensorProtos. This message @@ -32,11 +33,11 @@ class SnapshotRecord(google.protobuf.message.Message): *, tensor: collections.abc.Iterable[tensorflow.core.framework.tensor_pb2.TensorProto] | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["tensor", b"tensor"]) -> None: ... + def ClearField(self, field_name: typing.Literal["tensor", b"tensor"]) -> None: ... global___SnapshotRecord = SnapshotRecord -@typing_extensions.final +@typing.final class SnapshotMetadataRecord(google.protobuf.message.Message): """This stores the metadata information present in each snapshot record.""" @@ -59,12 +60,13 @@ class SnapshotMetadataRecord(google.protobuf.message.Message): """Time when we started creating this snapshot.""" version: builtins.int """Version of the snapshot data file format.""" - @property - def dtype(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[tensorflow.core.framework.types_pb2.DataType.ValueType]: - """A list of tensor dtype corresponding to each element of the snapshot.""" num_elements: builtins.int """The number of elements in the snapshot.""" finalized: builtins.bool + @property + def dtype(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[tensorflow.core.framework.types_pb2.DataType.ValueType]: + """A list of tensor dtype corresponding to each element of the snapshot.""" + def __init__( self, *, @@ -76,11 +78,11 @@ class SnapshotMetadataRecord(google.protobuf.message.Message): num_elements: builtins.int | None = ..., finalized: builtins.bool | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["creation_timestamp", b"creation_timestamp", "dtype", b"dtype", "finalized", b"finalized", "graph_hash", b"graph_hash", "num_elements", b"num_elements", "run_id", b"run_id", "version", b"version"]) -> None: ... + def ClearField(self, field_name: typing.Literal["creation_timestamp", b"creation_timestamp", "dtype", b"dtype", "finalized", b"finalized", "graph_hash", b"graph_hash", "num_elements", b"num_elements", "run_id", b"run_id", "version", b"version"]) -> None: ... global___SnapshotMetadataRecord = SnapshotMetadataRecord -@typing_extensions.final +@typing.final class TensorMetadata(google.protobuf.message.Message): """Metadata for a single tensor in the Snapshot Record.""" @@ -88,22 +90,22 @@ class TensorMetadata(google.protobuf.message.Message): TENSOR_SHAPE_FIELD_NUMBER: builtins.int TENSOR_SIZE_BYTES_FIELD_NUMBER: builtins.int - @property - def tensor_shape(self) -> tensorflow.core.framework.tensor_shape_pb2.TensorShapeProto: ... tensor_size_bytes: builtins.int """Number of uncompressed bytes used to store the tensor representation.""" + @property + def tensor_shape(self) -> tensorflow.core.framework.tensor_shape_pb2.TensorShapeProto: ... def __init__( self, *, tensor_shape: tensorflow.core.framework.tensor_shape_pb2.TensorShapeProto | None = ..., tensor_size_bytes: builtins.int | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["tensor_shape", b"tensor_shape"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["tensor_shape", b"tensor_shape", "tensor_size_bytes", b"tensor_size_bytes"]) -> None: ... + def HasField(self, field_name: typing.Literal["tensor_shape", b"tensor_shape"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["tensor_shape", b"tensor_shape", "tensor_size_bytes", b"tensor_size_bytes"]) -> None: ... global___TensorMetadata = TensorMetadata -@typing_extensions.final +@typing.final class SnapshotTensorMetadata(google.protobuf.message.Message): """Metadata for all the tensors in a Snapshot Record.""" @@ -117,11 +119,11 @@ class SnapshotTensorMetadata(google.protobuf.message.Message): *, tensor_metadata: collections.abc.Iterable[global___TensorMetadata] | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["tensor_metadata", b"tensor_metadata"]) -> None: ... + def ClearField(self, field_name: typing.Literal["tensor_metadata", b"tensor_metadata"]) -> None: ... global___SnapshotTensorMetadata = SnapshotTensorMetadata -@typing_extensions.final +@typing.final class DistributedSnapshotMetadata(google.protobuf.message.Message): """Metadata for a `tf.data.Dataset` distributed snapshot.""" @@ -142,6 +144,6 @@ class DistributedSnapshotMetadata(google.protobuf.message.Message): element_spec: builtins.bytes | None = ..., compression: builtins.str | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["compression", b"compression", "element_spec", b"element_spec"]) -> None: ... + def ClearField(self, field_name: typing.Literal["compression", b"compression", "element_spec", b"element_spec"]) -> None: ... global___DistributedSnapshotMetadata = DistributedSnapshotMetadata diff --git a/stubs/tensorflow/tensorflow/core/protobuf/struct_pb2.pyi b/stubs/tensorflow/tensorflow/core/protobuf/struct_pb2.pyi index 9321d8378630..bcc6e5cd95f7 100644 --- a/stubs/tensorflow/tensorflow/core/protobuf/struct_pb2.pyi +++ b/stubs/tensorflow/tensorflow/core/protobuf/struct_pb2.pyi @@ -2,6 +2,7 @@ @generated by mypy-protobuf. Do not edit manually! isort:skip_file """ + import builtins import collections.abc import sys @@ -22,7 +23,7 @@ else: DESCRIPTOR: google.protobuf.descriptor.FileDescriptor -@typing_extensions.final +@typing.final class StructuredValue(google.protobuf.message.Message): """`StructuredValue` represents a dynamically typed value representing various data structures that are inspired by Python data structures typically used in @@ -66,9 +67,6 @@ class StructuredValue(google.protobuf.message.Message): TUPLE_VALUE_FIELD_NUMBER: builtins.int DICT_VALUE_FIELD_NUMBER: builtins.int NAMED_TUPLE_VALUE_FIELD_NUMBER: builtins.int - @property - def none_value(self) -> global___NoneValue: - """Represents None.""" float64_value: builtins.float """Represents a double-precision floating-point value (a Python `float`).""" int64_value: builtins.int @@ -85,32 +83,44 @@ class StructuredValue(google.protobuf.message.Message): """ bool_value: builtins.bool """Represents a boolean value.""" + tensor_dtype_value: tensorflow.core.framework.types_pb2.DataType.ValueType + """Represents an enum value for dtype.""" + @property + def none_value(self) -> global___NoneValue: + """Represents None.""" + @property def tensor_shape_value(self) -> tensorflow.core.framework.tensor_shape_pb2.TensorShapeProto: """Represents a TensorShape.""" - tensor_dtype_value: tensorflow.core.framework.types_pb2.DataType.ValueType - """Represents an enum value for dtype.""" + @property def tensor_spec_value(self) -> global___TensorSpecProto: """Represents a value for tf.TensorSpec.""" + @property def type_spec_value(self) -> global___TypeSpecProto: """Represents a value for tf.TypeSpec.""" + @property def bounded_tensor_spec_value(self) -> global___BoundedTensorSpecProto: """Represents a value for tf.BoundedTensorSpec.""" + @property def list_value(self) -> global___ListValue: """Represents a list of `Value`.""" + @property def tuple_value(self) -> global___TupleValue: """Represents a tuple of `Value`.""" + @property def dict_value(self) -> global___DictValue: """Represents a dict `Value`.""" + @property def named_tuple_value(self) -> global___NamedTupleValue: """Represents Python's namedtuple.""" + def __init__( self, *, @@ -129,13 +139,13 @@ class StructuredValue(google.protobuf.message.Message): dict_value: global___DictValue | None = ..., named_tuple_value: global___NamedTupleValue | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["bool_value", b"bool_value", "bounded_tensor_spec_value", b"bounded_tensor_spec_value", "dict_value", b"dict_value", "float64_value", b"float64_value", "int64_value", b"int64_value", "kind", b"kind", "list_value", b"list_value", "named_tuple_value", b"named_tuple_value", "none_value", b"none_value", "string_value", b"string_value", "tensor_dtype_value", b"tensor_dtype_value", "tensor_shape_value", b"tensor_shape_value", "tensor_spec_value", b"tensor_spec_value", "tuple_value", b"tuple_value", "type_spec_value", b"type_spec_value"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["bool_value", b"bool_value", "bounded_tensor_spec_value", b"bounded_tensor_spec_value", "dict_value", b"dict_value", "float64_value", b"float64_value", "int64_value", b"int64_value", "kind", b"kind", "list_value", b"list_value", "named_tuple_value", b"named_tuple_value", "none_value", b"none_value", "string_value", b"string_value", "tensor_dtype_value", b"tensor_dtype_value", "tensor_shape_value", b"tensor_shape_value", "tensor_spec_value", b"tensor_spec_value", "tuple_value", b"tuple_value", "type_spec_value", b"type_spec_value"]) -> None: ... - def WhichOneof(self, oneof_group: typing_extensions.Literal["kind", b"kind"]) -> typing_extensions.Literal["none_value", "float64_value", "int64_value", "string_value", "bool_value", "tensor_shape_value", "tensor_dtype_value", "tensor_spec_value", "type_spec_value", "bounded_tensor_spec_value", "list_value", "tuple_value", "dict_value", "named_tuple_value"] | None: ... + def HasField(self, field_name: typing.Literal["bool_value", b"bool_value", "bounded_tensor_spec_value", b"bounded_tensor_spec_value", "dict_value", b"dict_value", "float64_value", b"float64_value", "int64_value", b"int64_value", "kind", b"kind", "list_value", b"list_value", "named_tuple_value", b"named_tuple_value", "none_value", b"none_value", "string_value", b"string_value", "tensor_dtype_value", b"tensor_dtype_value", "tensor_shape_value", b"tensor_shape_value", "tensor_spec_value", b"tensor_spec_value", "tuple_value", b"tuple_value", "type_spec_value", b"type_spec_value"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["bool_value", b"bool_value", "bounded_tensor_spec_value", b"bounded_tensor_spec_value", "dict_value", b"dict_value", "float64_value", b"float64_value", "int64_value", b"int64_value", "kind", b"kind", "list_value", b"list_value", "named_tuple_value", b"named_tuple_value", "none_value", b"none_value", "string_value", b"string_value", "tensor_dtype_value", b"tensor_dtype_value", "tensor_shape_value", b"tensor_shape_value", "tensor_spec_value", b"tensor_spec_value", "tuple_value", b"tuple_value", "type_spec_value", b"type_spec_value"]) -> None: ... + def WhichOneof(self, oneof_group: typing.Literal["kind", b"kind"]) -> typing.Literal["none_value", "float64_value", "int64_value", "string_value", "bool_value", "tensor_shape_value", "tensor_dtype_value", "tensor_spec_value", "type_spec_value", "bounded_tensor_spec_value", "list_value", "tuple_value", "dict_value", "named_tuple_value"] | None: ... global___StructuredValue = StructuredValue -@typing_extensions.final +@typing.final class NoneValue(google.protobuf.message.Message): """Represents None.""" @@ -147,7 +157,7 @@ class NoneValue(google.protobuf.message.Message): global___NoneValue = NoneValue -@typing_extensions.final +@typing.final class ListValue(google.protobuf.message.Message): """Represents a Python list.""" @@ -161,11 +171,11 @@ class ListValue(google.protobuf.message.Message): *, values: collections.abc.Iterable[global___StructuredValue] | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["values", b"values"]) -> None: ... + def ClearField(self, field_name: typing.Literal["values", b"values"]) -> None: ... global___ListValue = ListValue -@typing_extensions.final +@typing.final class TupleValue(google.protobuf.message.Message): """Represents a Python tuple.""" @@ -179,11 +189,11 @@ class TupleValue(google.protobuf.message.Message): *, values: collections.abc.Iterable[global___StructuredValue] | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["values", b"values"]) -> None: ... + def ClearField(self, field_name: typing.Literal["values", b"values"]) -> None: ... global___TupleValue = TupleValue -@typing_extensions.final +@typing.final class DictValue(google.protobuf.message.Message): """Represents a Python dict keyed by `str`. The comment on Unicode from Value.string_value applies analogously. @@ -191,7 +201,7 @@ class DictValue(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor - @typing_extensions.final + @typing.final class FieldsEntry(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -206,8 +216,8 @@ class DictValue(google.protobuf.message.Message): key: builtins.str | None = ..., value: global___StructuredValue | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["value", b"value"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["key", b"key", "value", b"value"]) -> None: ... + def HasField(self, field_name: typing.Literal["value", b"value"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["key", b"key", "value", b"value"]) -> None: ... FIELDS_FIELD_NUMBER: builtins.int @property @@ -217,11 +227,11 @@ class DictValue(google.protobuf.message.Message): *, fields: collections.abc.Mapping[builtins.str, global___StructuredValue] | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["fields", b"fields"]) -> None: ... + def ClearField(self, field_name: typing.Literal["fields", b"fields"]) -> None: ... global___DictValue = DictValue -@typing_extensions.final +@typing.final class PairValue(google.protobuf.message.Message): """Represents a (key, value) pair.""" @@ -238,12 +248,12 @@ class PairValue(google.protobuf.message.Message): key: builtins.str | None = ..., value: global___StructuredValue | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["value", b"value"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["key", b"key", "value", b"value"]) -> None: ... + def HasField(self, field_name: typing.Literal["value", b"value"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["key", b"key", "value", b"value"]) -> None: ... global___PairValue = PairValue -@typing_extensions.final +@typing.final class NamedTupleValue(google.protobuf.message.Message): """Represents Python's namedtuple.""" @@ -260,11 +270,11 @@ class NamedTupleValue(google.protobuf.message.Message): name: builtins.str | None = ..., values: collections.abc.Iterable[global___PairValue] | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["name", b"name", "values", b"values"]) -> None: ... + def ClearField(self, field_name: typing.Literal["name", b"name", "values", b"values"]) -> None: ... global___NamedTupleValue = NamedTupleValue -@typing_extensions.final +@typing.final class TensorSpecProto(google.protobuf.message.Message): """A protobuf to represent tf.TensorSpec.""" @@ -274,9 +284,9 @@ class TensorSpecProto(google.protobuf.message.Message): SHAPE_FIELD_NUMBER: builtins.int DTYPE_FIELD_NUMBER: builtins.int name: builtins.str + dtype: tensorflow.core.framework.types_pb2.DataType.ValueType @property def shape(self) -> tensorflow.core.framework.tensor_shape_pb2.TensorShapeProto: ... - dtype: tensorflow.core.framework.types_pb2.DataType.ValueType def __init__( self, *, @@ -284,12 +294,12 @@ class TensorSpecProto(google.protobuf.message.Message): shape: tensorflow.core.framework.tensor_shape_pb2.TensorShapeProto | None = ..., dtype: tensorflow.core.framework.types_pb2.DataType.ValueType | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["shape", b"shape"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["dtype", b"dtype", "name", b"name", "shape", b"shape"]) -> None: ... + def HasField(self, field_name: typing.Literal["shape", b"shape"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["dtype", b"dtype", "name", b"name", "shape", b"shape"]) -> None: ... global___TensorSpecProto = TensorSpecProto -@typing_extensions.final +@typing.final class BoundedTensorSpecProto(google.protobuf.message.Message): """A protobuf to represent tf.BoundedTensorSpec.""" @@ -301,9 +311,9 @@ class BoundedTensorSpecProto(google.protobuf.message.Message): MINIMUM_FIELD_NUMBER: builtins.int MAXIMUM_FIELD_NUMBER: builtins.int name: builtins.str + dtype: tensorflow.core.framework.types_pb2.DataType.ValueType @property def shape(self) -> tensorflow.core.framework.tensor_shape_pb2.TensorShapeProto: ... - dtype: tensorflow.core.framework.types_pb2.DataType.ValueType @property def minimum(self) -> tensorflow.core.framework.tensor_pb2.TensorProto: ... @property @@ -317,12 +327,12 @@ class BoundedTensorSpecProto(google.protobuf.message.Message): minimum: tensorflow.core.framework.tensor_pb2.TensorProto | None = ..., maximum: tensorflow.core.framework.tensor_pb2.TensorProto | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["maximum", b"maximum", "minimum", b"minimum", "shape", b"shape"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["dtype", b"dtype", "maximum", b"maximum", "minimum", b"minimum", "name", b"name", "shape", b"shape"]) -> None: ... + def HasField(self, field_name: typing.Literal["maximum", b"maximum", "minimum", b"minimum", "shape", b"shape"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["dtype", b"dtype", "maximum", b"maximum", "minimum", b"minimum", "name", b"name", "shape", b"shape"]) -> None: ... global___BoundedTensorSpecProto = BoundedTensorSpecProto -@typing_extensions.final +@typing.final class TypeSpecProto(google.protobuf.message.Message): """Represents a tf.TypeSpec""" @@ -392,9 +402,6 @@ class TypeSpecProto(google.protobuf.message.Message): TYPE_SPEC_CLASS_NAME_FIELD_NUMBER: builtins.int NUM_FLAT_COMPONENTS_FIELD_NUMBER: builtins.int type_spec_class: global___TypeSpecProto.TypeSpecClass.ValueType - @property - def type_state(self) -> global___StructuredValue: - """The value returned by TypeSpec._serialize().""" type_spec_class_name: builtins.str """The name of the TypeSpec class. * If type_spec_class == REGISTERED_TYPE_SPEC, the TypeSpec class is @@ -407,6 +414,10 @@ class TypeSpecProto(google.protobuf.message.Message): """ num_flat_components: builtins.int """The number of flat tensor components required by this TypeSpec.""" + @property + def type_state(self) -> global___StructuredValue: + """The value returned by TypeSpec._serialize().""" + def __init__( self, *, @@ -415,7 +426,7 @@ class TypeSpecProto(google.protobuf.message.Message): type_spec_class_name: builtins.str | None = ..., num_flat_components: builtins.int | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["type_state", b"type_state"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["num_flat_components", b"num_flat_components", "type_spec_class", b"type_spec_class", "type_spec_class_name", b"type_spec_class_name", "type_state", b"type_state"]) -> None: ... + def HasField(self, field_name: typing.Literal["type_state", b"type_state"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["num_flat_components", b"num_flat_components", "type_spec_class", b"type_spec_class", "type_spec_class_name", b"type_spec_class_name", "type_state", b"type_state"]) -> None: ... global___TypeSpecProto = TypeSpecProto diff --git a/stubs/tensorflow/tensorflow/core/protobuf/tensor_bundle_pb2.pyi b/stubs/tensorflow/tensorflow/core/protobuf/tensor_bundle_pb2.pyi index a55ef36b3c49..b1b95ae3fab4 100644 --- a/stubs/tensorflow/tensorflow/core/protobuf/tensor_bundle_pb2.pyi +++ b/stubs/tensorflow/tensorflow/core/protobuf/tensor_bundle_pb2.pyi @@ -2,6 +2,7 @@ @generated by mypy-protobuf. Do not edit manually! isort:skip_file """ + import builtins import collections.abc import sys @@ -23,7 +24,7 @@ else: DESCRIPTOR: google.protobuf.descriptor.FileDescriptor -@typing_extensions.final +@typing.final class BundleHeaderProto(google.protobuf.message.Message): """Protos used in the tensor bundle module (tf/core/util/tensor_bundle/). @@ -67,6 +68,7 @@ class BundleHeaderProto(google.protobuf.message.Message): @property def version(self) -> tensorflow.core.framework.versions_pb2.VersionDef: """Versioning of the tensor bundle format.""" + def __init__( self, *, @@ -74,12 +76,12 @@ class BundleHeaderProto(google.protobuf.message.Message): endianness: global___BundleHeaderProto.Endianness.ValueType | None = ..., version: tensorflow.core.framework.versions_pb2.VersionDef | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["version", b"version"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["endianness", b"endianness", "num_shards", b"num_shards", "version", b"version"]) -> None: ... + def HasField(self, field_name: typing.Literal["version", b"version"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["endianness", b"endianness", "num_shards", b"num_shards", "version", b"version"]) -> None: ... global___BundleHeaderProto = BundleHeaderProto -@typing_extensions.final +@typing.final class BundleEntryProto(google.protobuf.message.Message): """Describes the metadata related to a checkpointed tensor.""" @@ -94,8 +96,6 @@ class BundleEntryProto(google.protobuf.message.Message): SLICES_FIELD_NUMBER: builtins.int dtype: tensorflow.core.framework.types_pb2.DataType.ValueType """The tensor dtype and shape.""" - @property - def shape(self) -> tensorflow.core.framework.tensor_shape_pb2.TensorShapeProto: ... shard_id: builtins.int """The binary content of the tensor lies in: File "shard_id": bytes [offset, offset + size). @@ -105,6 +105,8 @@ class BundleEntryProto(google.protobuf.message.Message): crc32c: builtins.int """The CRC32C checksum of the tensor bytes.""" @property + def shape(self) -> tensorflow.core.framework.tensor_shape_pb2.TensorShapeProto: ... + @property def slices(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[tensorflow.core.framework.tensor_slice_pb2.TensorSliceProto]: """Iff present, this entry represents a partitioned tensor. The previous fields are interpreted as follows: @@ -114,6 +116,7 @@ class BundleEntryProto(google.protobuf.message.Message): These information for each slice can be looked up in their own BundleEntryProto, keyed by each "slice_name". """ + def __init__( self, *, @@ -125,7 +128,7 @@ class BundleEntryProto(google.protobuf.message.Message): crc32c: builtins.int | None = ..., slices: collections.abc.Iterable[tensorflow.core.framework.tensor_slice_pb2.TensorSliceProto] | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["shape", b"shape"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["crc32c", b"crc32c", "dtype", b"dtype", "offset", b"offset", "shape", b"shape", "shard_id", b"shard_id", "size", b"size", "slices", b"slices"]) -> None: ... + def HasField(self, field_name: typing.Literal["shape", b"shape"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["crc32c", b"crc32c", "dtype", b"dtype", "offset", b"offset", "shape", b"shape", "shard_id", b"shard_id", "size", b"size", "slices", b"slices"]) -> None: ... global___BundleEntryProto = BundleEntryProto diff --git a/stubs/tensorflow/tensorflow/core/protobuf/tensorflow_server_pb2.pyi b/stubs/tensorflow/tensorflow/core/protobuf/tensorflow_server_pb2.pyi index 4b1516ef16b0..2d897647f5cb 100644 --- a/stubs/tensorflow/tensorflow/core/protobuf/tensorflow_server_pb2.pyi +++ b/stubs/tensorflow/tensorflow/core/protobuf/tensorflow_server_pb2.pyi @@ -16,8 +16,9 @@ See the License for the specific language governing permissions and limitations under the License. ============================================================================== """ + import builtins -import typing as typing_extensions +import typing import google.protobuf.descriptor import google.protobuf.message @@ -27,7 +28,7 @@ import tensorflow.core.protobuf.device_filters_pb2 DESCRIPTOR: google.protobuf.descriptor.FileDescriptor -@typing_extensions.final +@typing.final class ServerDef(google.protobuf.message.Message): """Defines the configuration of a single TensorFlow server.""" @@ -40,9 +41,6 @@ class ServerDef(google.protobuf.message.Message): PROTOCOL_FIELD_NUMBER: builtins.int PORT_FIELD_NUMBER: builtins.int CLUSTER_DEVICE_FILTERS_FIELD_NUMBER: builtins.int - @property - def cluster(self) -> tensorflow.core.protobuf.cluster_pb2.ClusterDef: - """The cluster of which this server is a member.""" job_name: builtins.str """The name of the job of which this server is a member. @@ -55,9 +53,6 @@ class ServerDef(google.protobuf.message.Message): NOTE: The `cluster` field must contain a `JobDef` with a matching `name` and a mapping in its `tasks` field for this index. """ - @property - def default_session_config(self) -> tensorflow.core.protobuf.config_pb2.ConfigProto: - """The default configuration for sessions that run on this server.""" protocol: builtins.str """The protocol to be used by this server. @@ -65,11 +60,20 @@ class ServerDef(google.protobuf.message.Message): """ port: builtins.int """The server port. If not set, then we identify the port from the job_name.""" + @property + def cluster(self) -> tensorflow.core.protobuf.cluster_pb2.ClusterDef: + """The cluster of which this server is a member.""" + + @property + def default_session_config(self) -> tensorflow.core.protobuf.config_pb2.ConfigProto: + """The default configuration for sessions that run on this server.""" + @property def cluster_device_filters(self) -> tensorflow.core.protobuf.device_filters_pb2.ClusterDeviceFilters: """Device filters for remote tasks in the cluster. NOTE: This is an experimental feature and only effective in TensorFlow 2.x. """ + def __init__( self, *, @@ -81,7 +85,7 @@ class ServerDef(google.protobuf.message.Message): port: builtins.int | None = ..., cluster_device_filters: tensorflow.core.protobuf.device_filters_pb2.ClusterDeviceFilters | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["cluster", b"cluster", "cluster_device_filters", b"cluster_device_filters", "default_session_config", b"default_session_config"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["cluster", b"cluster", "cluster_device_filters", b"cluster_device_filters", "default_session_config", b"default_session_config", "job_name", b"job_name", "port", b"port", "protocol", b"protocol", "task_index", b"task_index"]) -> None: ... + def HasField(self, field_name: typing.Literal["cluster", b"cluster", "cluster_device_filters", b"cluster_device_filters", "default_session_config", b"default_session_config"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["cluster", b"cluster", "cluster_device_filters", b"cluster_device_filters", "default_session_config", b"default_session_config", "job_name", b"job_name", "port", b"port", "protocol", b"protocol", "task_index", b"task_index"]) -> None: ... global___ServerDef = ServerDef diff --git a/stubs/tensorflow/tensorflow/core/protobuf/tpu/compilation_result_pb2.pyi b/stubs/tensorflow/tensorflow/core/protobuf/tpu/compilation_result_pb2.pyi index 639d1049656b..6d04ebf01637 100644 --- a/stubs/tensorflow/tensorflow/core/protobuf/tpu/compilation_result_pb2.pyi +++ b/stubs/tensorflow/tensorflow/core/protobuf/tpu/compilation_result_pb2.pyi @@ -2,6 +2,7 @@ @generated by mypy-protobuf. Do not edit manually! isort:skip_file """ + import builtins import collections.abc import sys @@ -21,7 +22,7 @@ else: DESCRIPTOR: google.protobuf.descriptor.FileDescriptor -@typing_extensions.final +@typing.final class CompilationResultProto(google.protobuf.message.Message): """Describes the result of a TPU compilation. This is also used as TPU compilation result status payload. @@ -50,10 +51,11 @@ class CompilationResultProto(google.protobuf.message.Message): status_code: tensorflow.tsl.protobuf.error_codes_pb2.Code.ValueType """The error message, if any, returned during compilation.""" status_error_message: builtins.str + error_code: global___CompilationResultProto.ErrorCode.ValueType @property def hlo_protos(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[tensorflow.compiler.xla.service.hlo_pb2.HloProto]: """HLO proto.""" - error_code: global___CompilationResultProto.ErrorCode.ValueType + def __init__( self, *, @@ -62,6 +64,6 @@ class CompilationResultProto(google.protobuf.message.Message): hlo_protos: collections.abc.Iterable[tensorflow.compiler.xla.service.hlo_pb2.HloProto] | None = ..., error_code: global___CompilationResultProto.ErrorCode.ValueType | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["error_code", b"error_code", "hlo_protos", b"hlo_protos", "status_code", b"status_code", "status_error_message", b"status_error_message"]) -> None: ... + def ClearField(self, field_name: typing.Literal["error_code", b"error_code", "hlo_protos", b"hlo_protos", "status_code", b"status_code", "status_error_message", b"status_error_message"]) -> None: ... global___CompilationResultProto = CompilationResultProto diff --git a/stubs/tensorflow/tensorflow/core/protobuf/tpu/dynamic_padding_pb2.pyi b/stubs/tensorflow/tensorflow/core/protobuf/tpu/dynamic_padding_pb2.pyi index 081d859f7553..e8e639bc0b2d 100644 --- a/stubs/tensorflow/tensorflow/core/protobuf/tpu/dynamic_padding_pb2.pyi +++ b/stubs/tensorflow/tensorflow/core/protobuf/tpu/dynamic_padding_pb2.pyi @@ -2,15 +2,16 @@ @generated by mypy-protobuf. Do not edit manually! isort:skip_file """ + import builtins -import typing as typing_extensions +import typing import google.protobuf.descriptor import google.protobuf.message DESCRIPTOR: google.protobuf.descriptor.FileDescriptor -@typing_extensions.final +@typing.final class PaddingMap(google.protobuf.message.Message): """A mapping between the dynamic shape dimension of an input and the arg that represents the real shape. @@ -36,6 +37,6 @@ class PaddingMap(google.protobuf.message.Message): shape_index: builtins.int | None = ..., padding_arg_index: builtins.int | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["arg_index", b"arg_index", "padding_arg_index", b"padding_arg_index", "shape_index", b"shape_index"]) -> None: ... + def ClearField(self, field_name: typing.Literal["arg_index", b"arg_index", "padding_arg_index", b"padding_arg_index", "shape_index", b"shape_index"]) -> None: ... global___PaddingMap = PaddingMap diff --git a/stubs/tensorflow/tensorflow/core/protobuf/tpu/optimization_parameters_pb2.pyi b/stubs/tensorflow/tensorflow/core/protobuf/tpu/optimization_parameters_pb2.pyi index c9b6adebc541..8d1a768efa67 100644 --- a/stubs/tensorflow/tensorflow/core/protobuf/tpu/optimization_parameters_pb2.pyi +++ b/stubs/tensorflow/tensorflow/core/protobuf/tpu/optimization_parameters_pb2.pyi @@ -2,6 +2,7 @@ @generated by mypy-protobuf. Do not edit manually! isort:skip_file """ + import builtins import sys import typing @@ -19,7 +20,7 @@ else: DESCRIPTOR: google.protobuf.descriptor.FileDescriptor -@typing_extensions.final +@typing.final class ClippingLimits(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -28,21 +29,23 @@ class ClippingLimits(google.protobuf.message.Message): @property def lower(self) -> google.protobuf.wrappers_pb2.FloatValue: """-inf if not set""" + @property def upper(self) -> google.protobuf.wrappers_pb2.FloatValue: """+inf if not set""" + def __init__( self, *, lower: google.protobuf.wrappers_pb2.FloatValue | None = ..., upper: google.protobuf.wrappers_pb2.FloatValue | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["lower", b"lower", "upper", b"upper"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["lower", b"lower", "upper", b"upper"]) -> None: ... + def HasField(self, field_name: typing.Literal["lower", b"lower", "upper", b"upper"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["lower", b"lower", "upper", b"upper"]) -> None: ... global___ClippingLimits = ClippingLimits -@typing_extensions.final +@typing.final class SimulatedQuantization(google.protobuf.message.Message): """Configuration for simulated quantization; simulated quantization is used to reduce training/serving skew when the serving variables are quantized. The @@ -66,11 +69,12 @@ class SimulatedQuantization(google.protobuf.message.Message): NUM_BUCKETS_FIELD_NUMBER: builtins.int enabled: builtins.bool """Whether simulated quantization is enabled.""" + num_buckets: builtins.int + """Number of possible quantized values.""" @property def clipping_limits(self) -> global___ClippingLimits: """Minimum and maximum values of the range used for quantization.""" - num_buckets: builtins.int - """Number of possible quantized values.""" + def __init__( self, *, @@ -78,12 +82,12 @@ class SimulatedQuantization(google.protobuf.message.Message): clipping_limits: global___ClippingLimits | None = ..., num_buckets: builtins.int | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["clipping_limits", b"clipping_limits"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["clipping_limits", b"clipping_limits", "enabled", b"enabled", "num_buckets", b"num_buckets"]) -> None: ... + def HasField(self, field_name: typing.Literal["clipping_limits", b"clipping_limits"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["clipping_limits", b"clipping_limits", "enabled", b"enabled", "num_buckets", b"num_buckets"]) -> None: ... global___SimulatedQuantization = SimulatedQuantization -@typing_extensions.final +@typing.final class DynamicLearningRate(google.protobuf.message.Message): """Dynamic learning rate specification in the TPUEmbeddingConfiguration. The actual learning rates are provided as a scalar input list to the @@ -127,11 +131,11 @@ class DynamicLearningRate(google.protobuf.message.Message): *, tag: builtins.int | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["tag", b"tag"]) -> None: ... + def ClearField(self, field_name: typing.Literal["tag", b"tag"]) -> None: ... global___DynamicLearningRate = DynamicLearningRate -@typing_extensions.final +@typing.final class LearningRate(google.protobuf.message.Message): """Source of learning rate to use.""" @@ -148,13 +152,13 @@ class LearningRate(google.protobuf.message.Message): constant: builtins.float | None = ..., dynamic: global___DynamicLearningRate | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["constant", b"constant", "dynamic", b"dynamic", "learning_rate", b"learning_rate"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["constant", b"constant", "dynamic", b"dynamic", "learning_rate", b"learning_rate"]) -> None: ... - def WhichOneof(self, oneof_group: typing_extensions.Literal["learning_rate", b"learning_rate"]) -> typing_extensions.Literal["constant", "dynamic"] | None: ... + def HasField(self, field_name: typing.Literal["constant", b"constant", "dynamic", b"dynamic", "learning_rate", b"learning_rate"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["constant", b"constant", "dynamic", b"dynamic", "learning_rate", b"learning_rate"]) -> None: ... + def WhichOneof(self, oneof_group: typing.Literal["learning_rate", b"learning_rate"]) -> typing.Literal["constant", "dynamic"] | None: ... global___LearningRate = LearningRate -@typing_extensions.final +@typing.final class AdagradParameters(google.protobuf.message.Message): """Each optimizer's parameter proto has a link to its documentation and CPU implementation (if available) for user reference. @@ -171,7 +175,7 @@ class AdagradParameters(google.protobuf.message.Message): global___AdagradParameters = AdagradParameters -@typing_extensions.final +@typing.final class AdagradMomentumParameters(google.protobuf.message.Message): """This optimizer combines the Adagrad and Momentum update rules. accum(new) = beta2 == 1.0 ? @@ -212,11 +216,11 @@ class AdagradMomentumParameters(google.protobuf.message.Message): beta2: builtins.float | None = ..., epsilon: builtins.float | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["beta2", b"beta2", "epsilon", b"epsilon", "exponent", b"exponent", "momentum", b"momentum", "use_nesterov", b"use_nesterov"]) -> None: ... + def ClearField(self, field_name: typing.Literal["beta2", b"beta2", "epsilon", b"epsilon", "exponent", b"exponent", "momentum", b"momentum", "use_nesterov", b"use_nesterov"]) -> None: ... global___AdagradMomentumParameters = AdagradMomentumParameters -@typing_extensions.final +@typing.final class BoundedAdagradParameters(google.protobuf.message.Message): """Algorithm in http://www.jmlr.org/papers/volume12/duchi11a/duchi11a.pdf.""" @@ -245,11 +249,11 @@ class BoundedAdagradParameters(google.protobuf.message.Message): max_var_update: builtins.float | None = ..., max_accumulator: builtins.float | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["max_accumulator", b"max_accumulator", "max_var_update", b"max_var_update", "update_accumulator_first", b"update_accumulator_first"]) -> None: ... + def ClearField(self, field_name: typing.Literal["max_accumulator", b"max_accumulator", "max_var_update", b"max_var_update", "update_accumulator_first", b"update_accumulator_first"]) -> None: ... global___BoundedAdagradParameters = BoundedAdagradParameters -@typing_extensions.final +@typing.final class StochasticGradientDescentParameters(google.protobuf.message.Message): """https://www.tensorflow.org/api_docs/python/tf/keras/optimizers/SGD https://github.com/tensorflow/tensorflow/blob/6b6471f3ffb7f1fefe42d814aa5fb9ab7a535b58/tensorflow/core/kernels/training_ops.cc#L629 @@ -263,7 +267,7 @@ class StochasticGradientDescentParameters(google.protobuf.message.Message): global___StochasticGradientDescentParameters = StochasticGradientDescentParameters -@typing_extensions.final +@typing.final class FtrlParameters(google.protobuf.message.Message): """https://www.tensorflow.org/api_docs/python/tf/keras/optimizers/Ftrl https://static.googleusercontent.com/media/research.google.com/en//pubs/archive/41159.pdf @@ -313,11 +317,11 @@ class FtrlParameters(google.protobuf.message.Message): multiply_linear_by_lr: builtins.bool | None = ..., allow_zero_accumulator: builtins.bool | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["allow_zero_accumulator", b"allow_zero_accumulator", "beta", b"beta", "l1", b"l1", "l2", b"l2", "lr_power", b"lr_power", "multiply_linear_by_lr", b"multiply_linear_by_lr"]) -> None: ... + def ClearField(self, field_name: typing.Literal["allow_zero_accumulator", b"allow_zero_accumulator", "beta", b"beta", "l1", b"l1", "l2", b"l2", "lr_power", b"lr_power", "multiply_linear_by_lr", b"multiply_linear_by_lr"]) -> None: ... global___FtrlParameters = FtrlParameters -@typing_extensions.final +@typing.final class AdamParameters(google.protobuf.message.Message): """The Adam optimizer does not implement hyper-parameter update due to hardware limitations; use the dynamic learning rate feature instead, setting the @@ -362,11 +366,11 @@ class AdamParameters(google.protobuf.message.Message): use_non_lazy_adam: builtins.bool | None = ..., use_sum_inside_sqrt: builtins.bool | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["beta1", b"beta1", "beta2", b"beta2", "epsilon", b"epsilon", "use_non_lazy_adam", b"use_non_lazy_adam", "use_sum_inside_sqrt", b"use_sum_inside_sqrt"]) -> None: ... + def ClearField(self, field_name: typing.Literal["beta1", b"beta1", "beta2", b"beta2", "epsilon", b"epsilon", "use_non_lazy_adam", b"use_non_lazy_adam", "use_sum_inside_sqrt", b"use_sum_inside_sqrt"]) -> None: ... global___AdamParameters = AdamParameters -@typing_extensions.final +@typing.final class MomentumParameters(google.protobuf.message.Message): """https://www.tensorflow.org/api_docs/python/tf/keras/optimizers/SGD https://github.com/tensorflow/tensorflow/blob/6b6471f3ffb7f1fefe42d814aa5fb9ab7a535b58/tensorflow/core/kernels/training_ops.cc#L3068 @@ -384,11 +388,11 @@ class MomentumParameters(google.protobuf.message.Message): momentum: builtins.float | None = ..., use_nesterov: builtins.bool | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["momentum", b"momentum", "use_nesterov", b"use_nesterov"]) -> None: ... + def ClearField(self, field_name: typing.Literal["momentum", b"momentum", "use_nesterov", b"use_nesterov"]) -> None: ... global___MomentumParameters = MomentumParameters -@typing_extensions.final +@typing.final class RmsPropParameters(google.protobuf.message.Message): """https://www.tensorflow.org/api_docs/python/tf/keras/optimizers/RMSprop https://github.com/tensorflow/tensorflow/blob/6b6471f3ffb7f1fefe42d814aa5fb9ab7a535b58/tensorflow/core/kernels/training_ops.cc#L4229 @@ -409,11 +413,11 @@ class RmsPropParameters(google.protobuf.message.Message): momentum: builtins.float | None = ..., epsilon: builtins.float | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["epsilon", b"epsilon", "momentum", b"momentum", "rho", b"rho"]) -> None: ... + def ClearField(self, field_name: typing.Literal["epsilon", b"epsilon", "momentum", b"momentum", "rho", b"rho"]) -> None: ... global___RmsPropParameters = RmsPropParameters -@typing_extensions.final +@typing.final class CenteredRmsPropParameters(google.protobuf.message.Message): """https://www.tensorflow.org/api_docs/python/tf/keras/optimizers/RMSprop https://github.com/tensorflow/tensorflow/blob/6b6471f3ffb7f1fefe42d814aa5fb9ab7a535b58/tensorflow/core/kernels/training_ops.cc#L4358 @@ -434,11 +438,11 @@ class CenteredRmsPropParameters(google.protobuf.message.Message): momentum: builtins.float | None = ..., epsilon: builtins.float | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["epsilon", b"epsilon", "momentum", b"momentum", "rho", b"rho"]) -> None: ... + def ClearField(self, field_name: typing.Literal["epsilon", b"epsilon", "momentum", b"momentum", "rho", b"rho"]) -> None: ... global___CenteredRmsPropParameters = CenteredRmsPropParameters -@typing_extensions.final +@typing.final class MdlAdagradLightParameters(google.protobuf.message.Message): """Variant of algorithm in http://proceedings.mlr.press/v44/shamir15.pdf""" @@ -484,11 +488,11 @@ class MdlAdagradLightParameters(google.protobuf.message.Message): hard_limit_min_benefit: builtins.bool | None = ..., mdl_regularize: builtins.bool | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["benefit_revisit_scale", b"benefit_revisit_scale", "hard_limit_min_benefit", b"hard_limit_min_benefit", "l2", b"l2", "lr_power", b"lr_power", "max_event_benefit", b"max_event_benefit", "max_total_benefit", b"max_total_benefit", "mdl_benefit_rampup_coeff", b"mdl_benefit_rampup_coeff", "mdl_hard_limit", b"mdl_hard_limit", "mdl_min_weight", b"mdl_min_weight", "mdl_mix_in_margin", b"mdl_mix_in_margin", "mdl_regularize", b"mdl_regularize", "min_servable_mdl_benefit", b"min_servable_mdl_benefit"]) -> None: ... + def ClearField(self, field_name: typing.Literal["benefit_revisit_scale", b"benefit_revisit_scale", "hard_limit_min_benefit", b"hard_limit_min_benefit", "l2", b"l2", "lr_power", b"lr_power", "max_event_benefit", b"max_event_benefit", "max_total_benefit", b"max_total_benefit", "mdl_benefit_rampup_coeff", b"mdl_benefit_rampup_coeff", "mdl_hard_limit", b"mdl_hard_limit", "mdl_min_weight", b"mdl_min_weight", "mdl_mix_in_margin", b"mdl_mix_in_margin", "mdl_regularize", b"mdl_regularize", "min_servable_mdl_benefit", b"min_servable_mdl_benefit"]) -> None: ... global___MdlAdagradLightParameters = MdlAdagradLightParameters -@typing_extensions.final +@typing.final class AdadeltaParameters(google.protobuf.message.Message): """https://www.tensorflow.org/api_docs/python/tf/keras/optimizers/Adadelta https://github.com/tensorflow/tensorflow/blob/6b6471f3ffb7f1fefe42d814aa5fb9ab7a535b58/tensorflow/core/kernels/training_ops.cc#L933 @@ -506,11 +510,11 @@ class AdadeltaParameters(google.protobuf.message.Message): rho: builtins.float | None = ..., epsilon: builtins.float | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["epsilon", b"epsilon", "rho", b"rho"]) -> None: ... + def ClearField(self, field_name: typing.Literal["epsilon", b"epsilon", "rho", b"rho"]) -> None: ... global___AdadeltaParameters = AdadeltaParameters -@typing_extensions.final +@typing.final class ProximalAdagradParameters(google.protobuf.message.Message): """https://www.tensorflow.org/api_docs/python/tf/compat/v1/train/ProximalAdagradOptimizer https://github.com/tensorflow/tensorflow/blob/6b6471f3ffb7f1fefe42d814aa5fb9ab7a535b58/tensorflow/core/kernels/training_ops.cc#L1961 @@ -528,11 +532,11 @@ class ProximalAdagradParameters(google.protobuf.message.Message): l1: builtins.float | None = ..., l2: builtins.float | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["l1", b"l1", "l2", b"l2"]) -> None: ... + def ClearField(self, field_name: typing.Literal["l1", b"l1", "l2", b"l2"]) -> None: ... global___ProximalAdagradParameters = ProximalAdagradParameters -@typing_extensions.final +@typing.final class OnlineYogiParameters(google.protobuf.message.Message): """The online Yogi optimizer does not implement hyper-parameter update; use the dynamic learning rate feature instead, setting the learning rate to: @@ -563,11 +567,11 @@ class OnlineYogiParameters(google.protobuf.message.Message): l2: builtins.float | None = ..., beta2: builtins.float | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["beta2", b"beta2", "l1", b"l1", "l2", b"l2"]) -> None: ... + def ClearField(self, field_name: typing.Literal["beta2", b"beta2", "l1", b"l1", "l2", b"l2"]) -> None: ... global___OnlineYogiParameters = OnlineYogiParameters -@typing_extensions.final +@typing.final class ProximalYogiParameters(google.protobuf.message.Message): """The online Yogi optimizer does not implement hyper-parameter update; use the dynamic learning rate feature instead, setting the learning rate to: @@ -606,11 +610,11 @@ class ProximalYogiParameters(google.protobuf.message.Message): beta2: builtins.float | None = ..., epsilon: builtins.float | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["beta1", b"beta1", "beta2", b"beta2", "epsilon", b"epsilon", "l1", b"l1", "l2", b"l2"]) -> None: ... + def ClearField(self, field_name: typing.Literal["beta1", b"beta1", "beta2", b"beta2", "epsilon", b"epsilon", "l1", b"l1", "l2", b"l2"]) -> None: ... global___ProximalYogiParameters = ProximalYogiParameters -@typing_extensions.final +@typing.final class FrequencyEstimatorParameters(google.protobuf.message.Message): """Estimator for the frequency of updates to a lookup table. It maintains an array (tf.Variable) D, where each element records the average number of @@ -664,11 +668,11 @@ class FrequencyEstimatorParameters(google.protobuf.message.Message): outlier_threshold: builtins.float | None = ..., weight_exponent: builtins.float | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["max_delta", b"max_delta", "outlier_threshold", b"outlier_threshold", "tau", b"tau", "weight_exponent", b"weight_exponent"]) -> None: ... + def ClearField(self, field_name: typing.Literal["max_delta", b"max_delta", "outlier_threshold", b"outlier_threshold", "tau", b"tau", "weight_exponent", b"weight_exponent"]) -> None: ... global___FrequencyEstimatorParameters = FrequencyEstimatorParameters -@typing_extensions.final +@typing.final class UserDefinedProgramParameters(google.protobuf.message.Message): """A user-defined optimizer. The contained HLO program must take the following arguments in the following @@ -701,12 +705,12 @@ class UserDefinedProgramParameters(google.protobuf.message.Message): *, program: tensorflow.compiler.xla.service.hlo_pb2.HloModuleProto | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["program", b"program"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["program", b"program"]) -> None: ... + def HasField(self, field_name: typing.Literal["program", b"program"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["program", b"program"]) -> None: ... global___UserDefinedProgramParameters = UserDefinedProgramParameters -@typing_extensions.final +@typing.final class AssignParameters(google.protobuf.message.Message): """Optimizer that just sets the variable to the value of the gradient. To be correct, this requires either gradient accumulation (to sum the values of a @@ -722,7 +726,7 @@ class AssignParameters(google.protobuf.message.Message): global___AssignParameters = AssignParameters -@typing_extensions.final +@typing.final class GradientAccumulationStatus(google.protobuf.message.Message): """Status of using gradient accumulation (doing two passes over the input gradients: one to accumulate them into a temporary array and another to apply @@ -755,7 +759,7 @@ class GradientAccumulationStatus(google.protobuf.message.Message): global___GradientAccumulationStatus = GradientAccumulationStatus -@typing_extensions.final +@typing.final class LowDimensionalPackingStatus(google.protobuf.message.Message): """Whether to optimize the packing of low-dimensional embedding tables in HBM (high bandwidth memory). TPUs access HBM at 32-byte (8-float) granularity. @@ -832,7 +836,7 @@ class LowDimensionalPackingStatus(google.protobuf.message.Message): global___LowDimensionalPackingStatus = LowDimensionalPackingStatus -@typing_extensions.final +@typing.final class HotIdReplicationConfiguration(google.protobuf.message.Message): """Configuration proto for hot ID optimization. This is an experimental feature that is currently disabled (by default). @@ -870,11 +874,11 @@ class HotIdReplicationConfiguration(google.protobuf.message.Message): *, status: global___HotIdReplicationConfiguration.Status.ValueType | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["status", b"status"]) -> None: ... + def ClearField(self, field_name: typing.Literal["status", b"status"]) -> None: ... global___HotIdReplicationConfiguration = HotIdReplicationConfiguration -@typing_extensions.final +@typing.final class OptimizationParameters(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -904,19 +908,6 @@ class OptimizationParameters(google.protobuf.message.Message): FREQUENCY_ESTIMATOR_FIELD_NUMBER: builtins.int USER_DEFINED_PROGRAM_FIELD_NUMBER: builtins.int ASSIGN_FIELD_NUMBER: builtins.int - @property - def learning_rate(self) -> global___LearningRate: - """Learning rate used for updating the embedding layer parameters.""" - @property - def clipping_limits(self) -> global___ClippingLimits: - """Limits to which to clip the weight values after the backward pass; not - present means no limits are applied. - """ - @property - def gradient_clipping_limits(self) -> global___ClippingLimits: - """Limits to which to clip the backward pass gradient before using it for - updates; not present means no limits are applied. - """ weight_decay_factor: builtins.float """Amount of weight decay to apply; see weight_decay_optimizers.py for details. All optimizers except MDL Adagrad Light are supported with this @@ -929,13 +920,6 @@ class OptimizationParameters(google.protobuf.message.Message): before use; this is to match the note in DecoupledWeightDecayExtension in weight_decay_optimizers.py. """ - @property - def simulated_quantization(self) -> global___SimulatedQuantization: - """Configuration for simulated quantization which is used to reduce - training/serving skew when the serving variables are quantized. The same - quantization operations are executed during training to minimize - differences with serving. - """ gradient_accumulation_status: global___GradientAccumulationStatus.Status.ValueType """Status of using gradient accumulation (doing two passes over the input gradients: one to accumulate them into a temporary array and another to @@ -946,11 +930,36 @@ class OptimizationParameters(google.protobuf.message.Message): whether to optimize the packing of 1-dimensional, 2-dimensional, and 4-dimensional embedding tables in memory. """ + @property + def learning_rate(self) -> global___LearningRate: + """Learning rate used for updating the embedding layer parameters.""" + + @property + def clipping_limits(self) -> global___ClippingLimits: + """Limits to which to clip the weight values after the backward pass; not + present means no limits are applied. + """ + + @property + def gradient_clipping_limits(self) -> global___ClippingLimits: + """Limits to which to clip the backward pass gradient before using it for + updates; not present means no limits are applied. + """ + + @property + def simulated_quantization(self) -> global___SimulatedQuantization: + """Configuration for simulated quantization which is used to reduce + training/serving skew when the serving variables are quantized. The same + quantization operations are executed during training to minimize + differences with serving. + """ + @property def hot_id_replication_configuration(self) -> global___HotIdReplicationConfiguration: """Configuration proto for hot ID replication. This is an experimental feature that is currently disabled (by default). """ + @property def adagrad(self) -> global___AdagradParameters: ... @property @@ -1015,13 +1024,13 @@ class OptimizationParameters(google.protobuf.message.Message): user_defined_program: global___UserDefinedProgramParameters | None = ..., assign: global___AssignParameters | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["adadelta", b"adadelta", "adagrad", b"adagrad", "adagrad_momentum", b"adagrad_momentum", "adam", b"adam", "assign", b"assign", "bounded_adagrad", b"bounded_adagrad", "centered_rms_prop", b"centered_rms_prop", "clipping_limits", b"clipping_limits", "frequency_estimator", b"frequency_estimator", "ftrl", b"ftrl", "gradient_clipping_limits", b"gradient_clipping_limits", "hot_id_replication_configuration", b"hot_id_replication_configuration", "learning_rate", b"learning_rate", "mdl_adagrad_light", b"mdl_adagrad_light", "momentum", b"momentum", "online_yogi", b"online_yogi", "parameters", b"parameters", "proximal_adagrad", b"proximal_adagrad", "proximal_yogi", b"proximal_yogi", "rms_prop", b"rms_prop", "simulated_quantization", b"simulated_quantization", "stochastic_gradient_descent", b"stochastic_gradient_descent", "user_defined_program", b"user_defined_program"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["adadelta", b"adadelta", "adagrad", b"adagrad", "adagrad_momentum", b"adagrad_momentum", "adam", b"adam", "assign", b"assign", "bounded_adagrad", b"bounded_adagrad", "centered_rms_prop", b"centered_rms_prop", "clipping_limits", b"clipping_limits", "frequency_estimator", b"frequency_estimator", "ftrl", b"ftrl", "gradient_accumulation_status", b"gradient_accumulation_status", "gradient_clipping_limits", b"gradient_clipping_limits", "hot_id_replication_configuration", b"hot_id_replication_configuration", "learning_rate", b"learning_rate", "low_dimensional_packing_status", b"low_dimensional_packing_status", "mdl_adagrad_light", b"mdl_adagrad_light", "momentum", b"momentum", "multiply_weight_decay_factor_by_learning_rate", b"multiply_weight_decay_factor_by_learning_rate", "online_yogi", b"online_yogi", "parameters", b"parameters", "proximal_adagrad", b"proximal_adagrad", "proximal_yogi", b"proximal_yogi", "rms_prop", b"rms_prop", "simulated_quantization", b"simulated_quantization", "stochastic_gradient_descent", b"stochastic_gradient_descent", "user_defined_program", b"user_defined_program", "weight_decay_factor", b"weight_decay_factor"]) -> None: ... - def WhichOneof(self, oneof_group: typing_extensions.Literal["parameters", b"parameters"]) -> typing_extensions.Literal["adagrad", "adagrad_momentum", "bounded_adagrad", "stochastic_gradient_descent", "ftrl", "adam", "momentum", "rms_prop", "centered_rms_prop", "mdl_adagrad_light", "adadelta", "proximal_adagrad", "online_yogi", "proximal_yogi", "frequency_estimator", "user_defined_program", "assign"] | None: ... + def HasField(self, field_name: typing.Literal["adadelta", b"adadelta", "adagrad", b"adagrad", "adagrad_momentum", b"adagrad_momentum", "adam", b"adam", "assign", b"assign", "bounded_adagrad", b"bounded_adagrad", "centered_rms_prop", b"centered_rms_prop", "clipping_limits", b"clipping_limits", "frequency_estimator", b"frequency_estimator", "ftrl", b"ftrl", "gradient_clipping_limits", b"gradient_clipping_limits", "hot_id_replication_configuration", b"hot_id_replication_configuration", "learning_rate", b"learning_rate", "mdl_adagrad_light", b"mdl_adagrad_light", "momentum", b"momentum", "online_yogi", b"online_yogi", "parameters", b"parameters", "proximal_adagrad", b"proximal_adagrad", "proximal_yogi", b"proximal_yogi", "rms_prop", b"rms_prop", "simulated_quantization", b"simulated_quantization", "stochastic_gradient_descent", b"stochastic_gradient_descent", "user_defined_program", b"user_defined_program"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["adadelta", b"adadelta", "adagrad", b"adagrad", "adagrad_momentum", b"adagrad_momentum", "adam", b"adam", "assign", b"assign", "bounded_adagrad", b"bounded_adagrad", "centered_rms_prop", b"centered_rms_prop", "clipping_limits", b"clipping_limits", "frequency_estimator", b"frequency_estimator", "ftrl", b"ftrl", "gradient_accumulation_status", b"gradient_accumulation_status", "gradient_clipping_limits", b"gradient_clipping_limits", "hot_id_replication_configuration", b"hot_id_replication_configuration", "learning_rate", b"learning_rate", "low_dimensional_packing_status", b"low_dimensional_packing_status", "mdl_adagrad_light", b"mdl_adagrad_light", "momentum", b"momentum", "multiply_weight_decay_factor_by_learning_rate", b"multiply_weight_decay_factor_by_learning_rate", "online_yogi", b"online_yogi", "parameters", b"parameters", "proximal_adagrad", b"proximal_adagrad", "proximal_yogi", b"proximal_yogi", "rms_prop", b"rms_prop", "simulated_quantization", b"simulated_quantization", "stochastic_gradient_descent", b"stochastic_gradient_descent", "user_defined_program", b"user_defined_program", "weight_decay_factor", b"weight_decay_factor"]) -> None: ... + def WhichOneof(self, oneof_group: typing.Literal["parameters", b"parameters"]) -> typing.Literal["adagrad", "adagrad_momentum", "bounded_adagrad", "stochastic_gradient_descent", "ftrl", "adam", "momentum", "rms_prop", "centered_rms_prop", "mdl_adagrad_light", "adadelta", "proximal_adagrad", "online_yogi", "proximal_yogi", "frequency_estimator", "user_defined_program", "assign"] | None: ... global___OptimizationParameters = OptimizationParameters -@typing_extensions.final +@typing.final class StateVariableSpecification(google.protobuf.message.Message): """Specification of an optimization algorithm's state variables (both the main value vector and any extra accumulators, etc.). This proto is only used @@ -1030,7 +1039,7 @@ class StateVariableSpecification(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor - @typing_extensions.final + @typing.final class UserDefined(google.protobuf.message.Message): """A normal state variable that should be saved and restored in checkpoints and used as an input or output to non-debug TensorFlow ops. @@ -1042,7 +1051,7 @@ class StateVariableSpecification(google.protobuf.message.Message): self, ) -> None: ... - @typing_extensions.final + @typing.final class FillWithConstant(google.protobuf.message.Message): """A state variable that should be filled with a constant and normally hidden from users (used for intermediate gradients being accumulated, for @@ -1058,7 +1067,7 @@ class StateVariableSpecification(google.protobuf.message.Message): *, initial_value: builtins.float | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["initial_value", b"initial_value"]) -> None: ... + def ClearField(self, field_name: typing.Literal["initial_value", b"initial_value"]) -> None: ... NAME_FIELD_NUMBER: builtins.int USER_DEFINED_FIELD_NUMBER: builtins.int @@ -1076,8 +1085,8 @@ class StateVariableSpecification(google.protobuf.message.Message): user_defined: global___StateVariableSpecification.UserDefined | None = ..., fill_with_constant: global___StateVariableSpecification.FillWithConstant | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["fill_with_constant", b"fill_with_constant", "usage", b"usage", "user_defined", b"user_defined"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["fill_with_constant", b"fill_with_constant", "name", b"name", "usage", b"usage", "user_defined", b"user_defined"]) -> None: ... - def WhichOneof(self, oneof_group: typing_extensions.Literal["usage", b"usage"]) -> typing_extensions.Literal["user_defined", "fill_with_constant"] | None: ... + def HasField(self, field_name: typing.Literal["fill_with_constant", b"fill_with_constant", "usage", b"usage", "user_defined", b"user_defined"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["fill_with_constant", b"fill_with_constant", "name", b"name", "usage", b"usage", "user_defined", b"user_defined"]) -> None: ... + def WhichOneof(self, oneof_group: typing.Literal["usage", b"usage"]) -> typing.Literal["user_defined", "fill_with_constant"] | None: ... global___StateVariableSpecification = StateVariableSpecification diff --git a/stubs/tensorflow/tensorflow/core/protobuf/tpu/topology_pb2.pyi b/stubs/tensorflow/tensorflow/core/protobuf/tpu/topology_pb2.pyi index be5e58a28d5d..d0f1eda12941 100644 --- a/stubs/tensorflow/tensorflow/core/protobuf/tpu/topology_pb2.pyi +++ b/stubs/tensorflow/tensorflow/core/protobuf/tpu/topology_pb2.pyi @@ -2,6 +2,7 @@ @generated by mypy-protobuf. Do not edit manually! isort:skip_file """ + import builtins import collections.abc import sys @@ -19,7 +20,7 @@ else: DESCRIPTOR: google.protobuf.descriptor.FileDescriptor -@typing_extensions.final +@typing.final class TPUHardwareFeature(google.protobuf.message.Message): """Describes features of a tpu.""" @@ -67,11 +68,11 @@ class TPUHardwareFeature(google.protobuf.message.Message): *, embedding_feature: global___TPUHardwareFeature.EmbeddingFeature.ValueType | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["embedding_feature", b"embedding_feature"]) -> None: ... + def ClearField(self, field_name: typing.Literal["embedding_feature", b"embedding_feature"]) -> None: ... global___TPUHardwareFeature = TPUHardwareFeature -@typing_extensions.final +@typing.final class TopologyProto(google.protobuf.message.Message): """Describes the geometry of a TPU mesh.""" @@ -82,6 +83,10 @@ class TopologyProto(google.protobuf.message.Message): NUM_TPU_DEVICES_PER_TASK_FIELD_NUMBER: builtins.int DEVICE_COORDINATES_FIELD_NUMBER: builtins.int TPU_HARDWARE_FEATURE_FIELD_NUMBER: builtins.int + num_tasks: builtins.int + """Number of TensorFlow tasks in the cluster.""" + num_tpu_devices_per_task: builtins.int + """Number of TPU devices per task.""" @property def mesh_shape(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.int]: """The dimensions of the TPU topology, in cores. Typically, this is a 4D @@ -89,10 +94,7 @@ class TopologyProto(google.protobuf.message.Message): chips, and the minor dimension describes the number of cores on a multicore chip. """ - num_tasks: builtins.int - """Number of TensorFlow tasks in the cluster.""" - num_tpu_devices_per_task: builtins.int - """Number of TPU devices per task.""" + @property def device_coordinates(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.int]: """A flattened rank 3 int32 array with shape @@ -102,9 +104,11 @@ class TopologyProto(google.protobuf.message.Message): in the TPU mesh topology. Each entry [task, device, axis] gives the `axis`-th coordinate in the topology of a task/device pair. """ + @property def tpu_hardware_feature(self) -> global___TPUHardwareFeature: """TPU supported features.""" + def __init__( self, *, @@ -114,7 +118,7 @@ class TopologyProto(google.protobuf.message.Message): device_coordinates: collections.abc.Iterable[builtins.int] | None = ..., tpu_hardware_feature: global___TPUHardwareFeature | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["tpu_hardware_feature", b"tpu_hardware_feature"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["device_coordinates", b"device_coordinates", "mesh_shape", b"mesh_shape", "num_tasks", b"num_tasks", "num_tpu_devices_per_task", b"num_tpu_devices_per_task", "tpu_hardware_feature", b"tpu_hardware_feature"]) -> None: ... + def HasField(self, field_name: typing.Literal["tpu_hardware_feature", b"tpu_hardware_feature"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["device_coordinates", b"device_coordinates", "mesh_shape", b"mesh_shape", "num_tasks", b"num_tasks", "num_tpu_devices_per_task", b"num_tpu_devices_per_task", "tpu_hardware_feature", b"tpu_hardware_feature"]) -> None: ... global___TopologyProto = TopologyProto diff --git a/stubs/tensorflow/tensorflow/core/protobuf/tpu/tpu_embedding_configuration_pb2.pyi b/stubs/tensorflow/tensorflow/core/protobuf/tpu/tpu_embedding_configuration_pb2.pyi index 2568ba183172..c33925975268 100644 --- a/stubs/tensorflow/tensorflow/core/protobuf/tpu/tpu_embedding_configuration_pb2.pyi +++ b/stubs/tensorflow/tensorflow/core/protobuf/tpu/tpu_embedding_configuration_pb2.pyi @@ -2,6 +2,7 @@ @generated by mypy-protobuf. Do not edit manually! isort:skip_file """ + import builtins import collections.abc import sys @@ -20,7 +21,7 @@ else: DESCRIPTOR: google.protobuf.descriptor.FileDescriptor -@typing_extensions.final +@typing.final class TPUEmbeddingConfiguration(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -72,7 +73,7 @@ class TPUEmbeddingConfiguration(google.protobuf.message.Message): DIV_DEFAULT: TPUEmbeddingConfiguration.ShardingStrategy.ValueType # 0 MOD: TPUEmbeddingConfiguration.ShardingStrategy.ValueType # 1 - @typing_extensions.final + @typing.final class TableDescriptor(google.protobuf.message.Message): """Description of the various embedding tables.""" @@ -96,6 +97,7 @@ class TPUEmbeddingConfiguration(google.protobuf.message.Message): """Details of the learning algorithm used to update the embedding parameters. """ + def __init__( self, *, @@ -105,10 +107,10 @@ class TPUEmbeddingConfiguration(google.protobuf.message.Message): num_features: builtins.int | None = ..., optimization_parameters: tensorflow.core.protobuf.tpu.optimization_parameters_pb2.OptimizationParameters | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["optimization_parameters", b"optimization_parameters"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["dimension", b"dimension", "name", b"name", "num_features", b"num_features", "optimization_parameters", b"optimization_parameters", "vocabulary_size", b"vocabulary_size"]) -> None: ... + def HasField(self, field_name: typing.Literal["optimization_parameters", b"optimization_parameters"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["dimension", b"dimension", "name", b"name", "num_features", b"num_features", "optimization_parameters", b"optimization_parameters", "vocabulary_size", b"vocabulary_size"]) -> None: ... - @typing_extensions.final + @typing.final class FeatureDescriptor(google.protobuf.message.Message): """Description of different input features.""" @@ -131,6 +133,7 @@ class TPUEmbeddingConfiguration(google.protobuf.message.Message): the reduction axis) and the embedding dimension is d, the output received at the TensorCore will have shape [m, n, k, d]. """ + def __init__( self, *, @@ -138,9 +141,9 @@ class TPUEmbeddingConfiguration(google.protobuf.message.Message): table_id: builtins.int | None = ..., input_shape: collections.abc.Iterable[builtins.int] | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["input_shape", b"input_shape", "name", b"name", "table_id", b"table_id"]) -> None: ... + def ClearField(self, field_name: typing.Literal["input_shape", b"input_shape", "name", b"name", "table_id", b"table_id"]) -> None: ... - @typing_extensions.final + @typing.final class SpmdSharding(google.protobuf.message.Message): """SPMD (Single Program Multiple Data) sharding configuration for TPUEmbedding. When model parallelism is used on the TensorCore, the number @@ -162,7 +165,7 @@ class TPUEmbeddingConfiguration(google.protobuf.message.Message): enabled: builtins.bool | None = ..., num_cores_per_replica: builtins.int | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["enabled", b"enabled", "num_cores_per_replica", b"num_cores_per_replica"]) -> None: ... + def ClearField(self, field_name: typing.Literal["enabled", b"enabled", "num_cores_per_replica", b"num_cores_per_replica"]) -> None: ... TABLE_DESCRIPTOR_FIELD_NUMBER: builtins.int MODE_FIELD_NUMBER: builtins.int @@ -174,8 +177,6 @@ class TPUEmbeddingConfiguration(google.protobuf.message.Message): PROFILE_DATA_DIRECTORY_FIELD_NUMBER: builtins.int FEATURE_DESCRIPTOR_FIELD_NUMBER: builtins.int SPMD_SHARDING_FIELD_NUMBER: builtins.int - @property - def table_descriptor(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___TPUEmbeddingConfiguration.TableDescriptor]: ... mode: global___TPUEmbeddingConfiguration.Mode.ValueType batch_size_per_tensor_core: builtins.int """Number of samples in each batch of embedding layer activations sent to @@ -231,11 +232,14 @@ class TPUEmbeddingConfiguration(google.protobuf.message.Message): models to reuse embedding lookup statistics. """ @property + def table_descriptor(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___TPUEmbeddingConfiguration.TableDescriptor]: ... + @property def feature_descriptor(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___TPUEmbeddingConfiguration.FeatureDescriptor]: """If the feature_descriptor field is populated, the model should NOT populate TableDescriptor.num_features and batch_size_per_tensor_core. These two fields will be auto-populated by the TPUEmbedding rewrite passes. """ + @property def spmd_sharding(self) -> global___TPUEmbeddingConfiguration.SpmdSharding: ... def __init__( @@ -252,12 +256,12 @@ class TPUEmbeddingConfiguration(google.protobuf.message.Message): feature_descriptor: collections.abc.Iterable[global___TPUEmbeddingConfiguration.FeatureDescriptor] | None = ..., spmd_sharding: global___TPUEmbeddingConfiguration.SpmdSharding | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["spmd_sharding", b"spmd_sharding"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["batch_size_per_tensor_core", b"batch_size_per_tensor_core", "feature_descriptor", b"feature_descriptor", "mode", b"mode", "num_hosts", b"num_hosts", "num_tensor_cores", b"num_tensor_cores", "pipeline_execution_with_tensor_core", b"pipeline_execution_with_tensor_core", "profile_data_directory", b"profile_data_directory", "sharding_strategy", b"sharding_strategy", "spmd_sharding", b"spmd_sharding", "table_descriptor", b"table_descriptor"]) -> None: ... + def HasField(self, field_name: typing.Literal["spmd_sharding", b"spmd_sharding"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["batch_size_per_tensor_core", b"batch_size_per_tensor_core", "feature_descriptor", b"feature_descriptor", "mode", b"mode", "num_hosts", b"num_hosts", "num_tensor_cores", b"num_tensor_cores", "pipeline_execution_with_tensor_core", b"pipeline_execution_with_tensor_core", "profile_data_directory", b"profile_data_directory", "sharding_strategy", b"sharding_strategy", "spmd_sharding", b"spmd_sharding", "table_descriptor", b"table_descriptor"]) -> None: ... global___TPUEmbeddingConfiguration = TPUEmbeddingConfiguration -@typing_extensions.final +@typing.final class TPUEmbeddingError(google.protobuf.message.Message): """A placeholder message that is used to define a unique Status payload URL for TPU embedding errors. diff --git a/stubs/tensorflow/tensorflow/core/protobuf/trackable_object_graph_pb2.pyi b/stubs/tensorflow/tensorflow/core/protobuf/trackable_object_graph_pb2.pyi index e786a783526a..63730b6360c6 100644 --- a/stubs/tensorflow/tensorflow/core/protobuf/trackable_object_graph_pb2.pyi +++ b/stubs/tensorflow/tensorflow/core/protobuf/trackable_object_graph_pb2.pyi @@ -2,9 +2,10 @@ @generated by mypy-protobuf. Do not edit manually! isort:skip_file """ + import builtins import collections.abc -import typing as typing_extensions +import typing import google.protobuf.descriptor import google.protobuf.internal.containers @@ -13,7 +14,7 @@ import google.protobuf.wrappers_pb2 DESCRIPTOR: google.protobuf.descriptor.FileDescriptor -@typing_extensions.final +@typing.final class TrackableObjectGraph(google.protobuf.message.Message): """A TensorBundle addition which saves extra information about the objects which own variables, allowing for more robust checkpoint loading into modified @@ -22,11 +23,11 @@ class TrackableObjectGraph(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor - @typing_extensions.final + @typing.final class TrackableObject(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor - @typing_extensions.final + @typing.final class ObjectReference(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -44,9 +45,9 @@ class TrackableObjectGraph(google.protobuf.message.Message): node_id: builtins.int | None = ..., local_name: builtins.str | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["local_name", b"local_name", "node_id", b"node_id"]) -> None: ... + def ClearField(self, field_name: typing.Literal["local_name", b"local_name", "node_id", b"node_id"]) -> None: ... - @typing_extensions.final + @typing.final class SerializedTensor(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -73,9 +74,9 @@ class TrackableObjectGraph(google.protobuf.message.Message): full_name: builtins.str | None = ..., checkpoint_key: builtins.str | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["checkpoint_key", b"checkpoint_key", "full_name", b"full_name", "name", b"name"]) -> None: ... + def ClearField(self, field_name: typing.Literal["checkpoint_key", b"checkpoint_key", "full_name", b"full_name", "name", b"name"]) -> None: ... - @typing_extensions.final + @typing.final class SlotVariableReference(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -99,7 +100,7 @@ class TrackableObjectGraph(google.protobuf.message.Message): slot_name: builtins.str | None = ..., slot_variable_node_id: builtins.int | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["original_variable_node_id", b"original_variable_node_id", "slot_name", b"slot_name", "slot_variable_node_id", b"slot_variable_node_id"]) -> None: ... + def ClearField(self, field_name: typing.Literal["original_variable_node_id", b"original_variable_node_id", "slot_name", b"slot_name", "slot_variable_node_id", b"slot_variable_node_id"]) -> None: ... CHILDREN_FIELD_NUMBER: builtins.int ATTRIBUTES_FIELD_NUMBER: builtins.int @@ -109,17 +110,21 @@ class TrackableObjectGraph(google.protobuf.message.Message): @property def children(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___TrackableObjectGraph.TrackableObject.ObjectReference]: """Objects which this object depends on.""" + @property def attributes(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___TrackableObjectGraph.TrackableObject.SerializedTensor]: """Serialized data specific to this object.""" + @property def slot_variables(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___TrackableObjectGraph.TrackableObject.SlotVariableReference]: """Slot variables owned by this object.""" + @property def registered_saver(self) -> global___RegisteredSaver: """The registered saver used to save this object. If this saver is not present when loading the checkpoint, then loading will fail. """ + @property def has_checkpoint_values(self) -> google.protobuf.wrappers_pb2.BoolValue: """Whether this object has checkpoint values or descendants with checkpoint @@ -127,6 +132,7 @@ class TrackableObjectGraph(google.protobuf.message.Message): object graph proto when restoring (which also has to traverse the live object graph). """ + def __init__( self, *, @@ -136,8 +142,8 @@ class TrackableObjectGraph(google.protobuf.message.Message): registered_saver: global___RegisteredSaver | None = ..., has_checkpoint_values: google.protobuf.wrappers_pb2.BoolValue | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["has_checkpoint_values", b"has_checkpoint_values", "registered_saver", b"registered_saver"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["attributes", b"attributes", "children", b"children", "has_checkpoint_values", b"has_checkpoint_values", "registered_saver", b"registered_saver", "slot_variables", b"slot_variables"]) -> None: ... + def HasField(self, field_name: typing.Literal["has_checkpoint_values", b"has_checkpoint_values", "registered_saver", b"registered_saver"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["attributes", b"attributes", "children", b"children", "has_checkpoint_values", b"has_checkpoint_values", "registered_saver", b"registered_saver", "slot_variables", b"slot_variables"]) -> None: ... NODES_FIELD_NUMBER: builtins.int @property @@ -147,11 +153,11 @@ class TrackableObjectGraph(google.protobuf.message.Message): *, nodes: collections.abc.Iterable[global___TrackableObjectGraph.TrackableObject] | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["nodes", b"nodes"]) -> None: ... + def ClearField(self, field_name: typing.Literal["nodes", b"nodes"]) -> None: ... global___TrackableObjectGraph = TrackableObjectGraph -@typing_extensions.final +@typing.final class RegisteredSaver(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -167,6 +173,6 @@ class RegisteredSaver(google.protobuf.message.Message): name: builtins.str | None = ..., object_name: builtins.str | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["name", b"name", "object_name", b"object_name"]) -> None: ... + def ClearField(self, field_name: typing.Literal["name", b"name", "object_name", b"object_name"]) -> None: ... global___RegisteredSaver = RegisteredSaver diff --git a/stubs/tensorflow/tensorflow/core/protobuf/transport_options_pb2.pyi b/stubs/tensorflow/tensorflow/core/protobuf/transport_options_pb2.pyi index e515e2968055..26d7b1406dae 100644 --- a/stubs/tensorflow/tensorflow/core/protobuf/transport_options_pb2.pyi +++ b/stubs/tensorflow/tensorflow/core/protobuf/transport_options_pb2.pyi @@ -2,9 +2,10 @@ @generated by mypy-protobuf. Do not edit manually! isort:skip_file """ + import builtins import collections.abc -import typing as typing_extensions +import typing import google.protobuf.descriptor import google.protobuf.internal.containers @@ -12,7 +13,7 @@ import google.protobuf.message DESCRIPTOR: google.protobuf.descriptor.FileDescriptor -@typing_extensions.final +@typing.final class RecvBufRespExtra(google.protobuf.message.Message): """Extra data needed on a non-RDMA RecvBufResponse.""" @@ -26,6 +27,6 @@ class RecvBufRespExtra(google.protobuf.message.Message): *, tensor_content: collections.abc.Iterable[builtins.bytes] | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["tensor_content", b"tensor_content"]) -> None: ... + def ClearField(self, field_name: typing.Literal["tensor_content", b"tensor_content"]) -> None: ... global___RecvBufRespExtra = RecvBufRespExtra diff --git a/stubs/tensorflow/tensorflow/core/protobuf/verifier_config_pb2.pyi b/stubs/tensorflow/tensorflow/core/protobuf/verifier_config_pb2.pyi index 4be67334c55f..405ab99a2dd5 100644 --- a/stubs/tensorflow/tensorflow/core/protobuf/verifier_config_pb2.pyi +++ b/stubs/tensorflow/tensorflow/core/protobuf/verifier_config_pb2.pyi @@ -2,6 +2,7 @@ @generated by mypy-protobuf. Do not edit manually! isort:skip_file """ + import builtins import sys import typing @@ -17,7 +18,7 @@ else: DESCRIPTOR: google.protobuf.descriptor.FileDescriptor -@typing_extensions.final +@typing.final class VerifierConfig(google.protobuf.message.Message): """The config for graph verifiers.""" @@ -52,6 +53,6 @@ class VerifierConfig(google.protobuf.message.Message): verification_timeout_in_ms: builtins.int | None = ..., structure_verifier: global___VerifierConfig.Toggle.ValueType | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["structure_verifier", b"structure_verifier", "verification_timeout_in_ms", b"verification_timeout_in_ms"]) -> None: ... + def ClearField(self, field_name: typing.Literal["structure_verifier", b"structure_verifier", "verification_timeout_in_ms", b"verification_timeout_in_ms"]) -> None: ... global___VerifierConfig = VerifierConfig diff --git a/stubs/tensorflow/tensorflow/core/util/event_pb2.pyi b/stubs/tensorflow/tensorflow/core/util/event_pb2.pyi index 7cfa8385cd48..9d6a986624bc 100644 --- a/stubs/tensorflow/tensorflow/core/util/event_pb2.pyi +++ b/stubs/tensorflow/tensorflow/core/util/event_pb2.pyi @@ -2,6 +2,7 @@ @generated by mypy-protobuf. Do not edit manually! isort:skip_file """ + import builtins import collections.abc import sys @@ -70,7 +71,7 @@ WAIT_FOR_COORDINATOR: WorkerShutdownMode.ValueType # 2 SHUTDOWN_AFTER_TIMEOUT: WorkerShutdownMode.ValueType # 3 global___WorkerShutdownMode = WorkerShutdownMode -@typing_extensions.final +@typing.final class Event(google.protobuf.message.Message): """Protocol buffer representing an event that happened during the execution of a Brain model. @@ -100,28 +101,33 @@ class Event(google.protobuf.message.Message): """ graph_def: builtins.bytes """An encoded version of a GraphDef.""" + meta_graph_def: builtins.bytes + """An encoded version of a MetaGraphDef.""" @property def summary(self) -> tensorflow.core.framework.summary_pb2.Summary: """A summary was generated.""" + @property def log_message(self) -> global___LogMessage: """The user output a log message. This was theoretically used by the defunct tensorboard_logging module, which has since been removed; this field is now deprecated and should not be used. """ + @property def session_log(self) -> global___SessionLog: """The state of the session which can be used for restarting after crashes.""" + @property def tagged_run_metadata(self) -> global___TaggedRunMetadata: """The metadata returned by running a session.run() call.""" - meta_graph_def: builtins.bytes - """An encoded version of a MetaGraphDef.""" + @property def source_metadata(self) -> global___SourceMetadata: """Information of the source that writes the events, this is only logged in the very first event along with the `file_version` field. """ + def __init__( self, *, @@ -136,13 +142,13 @@ class Event(google.protobuf.message.Message): meta_graph_def: builtins.bytes | None = ..., source_metadata: global___SourceMetadata | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["file_version", b"file_version", "graph_def", b"graph_def", "log_message", b"log_message", "meta_graph_def", b"meta_graph_def", "session_log", b"session_log", "source_metadata", b"source_metadata", "summary", b"summary", "tagged_run_metadata", b"tagged_run_metadata", "what", b"what"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["file_version", b"file_version", "graph_def", b"graph_def", "log_message", b"log_message", "meta_graph_def", b"meta_graph_def", "session_log", b"session_log", "source_metadata", b"source_metadata", "step", b"step", "summary", b"summary", "tagged_run_metadata", b"tagged_run_metadata", "wall_time", b"wall_time", "what", b"what"]) -> None: ... - def WhichOneof(self, oneof_group: typing_extensions.Literal["what", b"what"]) -> typing_extensions.Literal["file_version", "graph_def", "summary", "log_message", "session_log", "tagged_run_metadata", "meta_graph_def"] | None: ... + def HasField(self, field_name: typing.Literal["file_version", b"file_version", "graph_def", b"graph_def", "log_message", b"log_message", "meta_graph_def", b"meta_graph_def", "session_log", b"session_log", "source_metadata", b"source_metadata", "summary", b"summary", "tagged_run_metadata", b"tagged_run_metadata", "what", b"what"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["file_version", b"file_version", "graph_def", b"graph_def", "log_message", b"log_message", "meta_graph_def", b"meta_graph_def", "session_log", b"session_log", "source_metadata", b"source_metadata", "step", b"step", "summary", b"summary", "tagged_run_metadata", b"tagged_run_metadata", "wall_time", b"wall_time", "what", b"what"]) -> None: ... + def WhichOneof(self, oneof_group: typing.Literal["what", b"what"]) -> typing.Literal["file_version", "graph_def", "summary", "log_message", "session_log", "tagged_run_metadata", "meta_graph_def"] | None: ... global___Event = Event -@typing_extensions.final +@typing.final class SourceMetadata(google.protobuf.message.Message): """Holds the information of the source that writes the events.""" @@ -158,11 +164,11 @@ class SourceMetadata(google.protobuf.message.Message): *, writer: builtins.str | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["writer", b"writer"]) -> None: ... + def ClearField(self, field_name: typing.Literal["writer", b"writer"]) -> None: ... global___SourceMetadata = SourceMetadata -@typing_extensions.final +@typing.final class LogMessage(google.protobuf.message.Message): """Protocol buffer used for logging messages to the events file. @@ -213,11 +219,11 @@ class LogMessage(google.protobuf.message.Message): level: global___LogMessage.Level.ValueType | None = ..., message: builtins.str | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["level", b"level", "message", b"message"]) -> None: ... + def ClearField(self, field_name: typing.Literal["level", b"level", "message", b"message"]) -> None: ... global___LogMessage = LogMessage -@typing_extensions.final +@typing.final class SessionLog(google.protobuf.message.Message): """Protocol buffer used for logging session state.""" @@ -254,11 +260,11 @@ class SessionLog(google.protobuf.message.Message): checkpoint_path: builtins.str | None = ..., msg: builtins.str | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["checkpoint_path", b"checkpoint_path", "msg", b"msg", "status", b"status"]) -> None: ... + def ClearField(self, field_name: typing.Literal["checkpoint_path", b"checkpoint_path", "msg", b"msg", "status", b"status"]) -> None: ... global___SessionLog = SessionLog -@typing_extensions.final +@typing.final class TaggedRunMetadata(google.protobuf.message.Message): """For logging the metadata output for a single session.run() call.""" @@ -278,11 +284,11 @@ class TaggedRunMetadata(google.protobuf.message.Message): tag: builtins.str | None = ..., run_metadata: builtins.bytes | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["run_metadata", b"run_metadata", "tag", b"tag"]) -> None: ... + def ClearField(self, field_name: typing.Literal["run_metadata", b"run_metadata", "tag", b"tag"]) -> None: ... global___TaggedRunMetadata = TaggedRunMetadata -@typing_extensions.final +@typing.final class WatchdogConfig(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -293,11 +299,11 @@ class WatchdogConfig(google.protobuf.message.Message): *, timeout_ms: builtins.int | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["timeout_ms", b"timeout_ms"]) -> None: ... + def ClearField(self, field_name: typing.Literal["timeout_ms", b"timeout_ms"]) -> None: ... global___WatchdogConfig = WatchdogConfig -@typing_extensions.final +@typing.final class RequestedExitCode(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -308,11 +314,11 @@ class RequestedExitCode(google.protobuf.message.Message): *, exit_code: builtins.int | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["exit_code", b"exit_code"]) -> None: ... + def ClearField(self, field_name: typing.Literal["exit_code", b"exit_code"]) -> None: ... global___RequestedExitCode = RequestedExitCode -@typing_extensions.final +@typing.final class WorkerHeartbeatRequest(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -331,12 +337,12 @@ class WorkerHeartbeatRequest(google.protobuf.message.Message): watchdog_config: global___WatchdogConfig | None = ..., exit_code: global___RequestedExitCode | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["exit_code", b"exit_code", "watchdog_config", b"watchdog_config"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["exit_code", b"exit_code", "shutdown_mode", b"shutdown_mode", "watchdog_config", b"watchdog_config"]) -> None: ... + def HasField(self, field_name: typing.Literal["exit_code", b"exit_code", "watchdog_config", b"watchdog_config"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["exit_code", b"exit_code", "shutdown_mode", b"shutdown_mode", "watchdog_config", b"watchdog_config"]) -> None: ... global___WorkerHeartbeatRequest = WorkerHeartbeatRequest -@typing_extensions.final +@typing.final class WorkerHeartbeatResponse(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -344,9 +350,9 @@ class WorkerHeartbeatResponse(google.protobuf.message.Message): WORKER_LOG_FIELD_NUMBER: builtins.int HOSTNAME_FIELD_NUMBER: builtins.int health_status: global___WorkerHealth.ValueType + hostname: builtins.str @property def worker_log(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___Event]: ... - hostname: builtins.str def __init__( self, *, @@ -354,6 +360,6 @@ class WorkerHeartbeatResponse(google.protobuf.message.Message): worker_log: collections.abc.Iterable[global___Event] | None = ..., hostname: builtins.str | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["health_status", b"health_status", "hostname", b"hostname", "worker_log", b"worker_log"]) -> None: ... + def ClearField(self, field_name: typing.Literal["health_status", b"health_status", "hostname", b"hostname", "worker_log", b"worker_log"]) -> None: ... global___WorkerHeartbeatResponse = WorkerHeartbeatResponse diff --git a/stubs/tensorflow/tensorflow/core/util/memmapped_file_system_pb2.pyi b/stubs/tensorflow/tensorflow/core/util/memmapped_file_system_pb2.pyi index 89c6608f6127..266b0ed6e5d3 100644 --- a/stubs/tensorflow/tensorflow/core/util/memmapped_file_system_pb2.pyi +++ b/stubs/tensorflow/tensorflow/core/util/memmapped_file_system_pb2.pyi @@ -16,9 +16,10 @@ See the License for the specific language governing permissions and limitations under the License. ============================================================================== """ + import builtins import collections.abc -import typing as typing_extensions +import typing import google.protobuf.descriptor import google.protobuf.internal.containers @@ -26,7 +27,7 @@ import google.protobuf.message DESCRIPTOR: google.protobuf.descriptor.FileDescriptor -@typing_extensions.final +@typing.final class MemmappedFileSystemDirectoryElement(google.protobuf.message.Message): """A message that describes one region of memmapped file.""" @@ -45,11 +46,11 @@ class MemmappedFileSystemDirectoryElement(google.protobuf.message.Message): name: builtins.str | None = ..., length: builtins.int | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["length", b"length", "name", b"name", "offset", b"offset"]) -> None: ... + def ClearField(self, field_name: typing.Literal["length", b"length", "name", b"name", "offset", b"offset"]) -> None: ... global___MemmappedFileSystemDirectoryElement = MemmappedFileSystemDirectoryElement -@typing_extensions.final +@typing.final class MemmappedFileSystemDirectory(google.protobuf.message.Message): """A directory of regions in a memmapped file.""" @@ -63,6 +64,6 @@ class MemmappedFileSystemDirectory(google.protobuf.message.Message): *, element: collections.abc.Iterable[global___MemmappedFileSystemDirectoryElement] | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["element", b"element"]) -> None: ... + def ClearField(self, field_name: typing.Literal["element", b"element"]) -> None: ... global___MemmappedFileSystemDirectory = MemmappedFileSystemDirectory diff --git a/stubs/tensorflow/tensorflow/core/util/saved_tensor_slice_pb2.pyi b/stubs/tensorflow/tensorflow/core/util/saved_tensor_slice_pb2.pyi index 23f69669b117..9b492465ac4f 100644 --- a/stubs/tensorflow/tensorflow/core/util/saved_tensor_slice_pb2.pyi +++ b/stubs/tensorflow/tensorflow/core/util/saved_tensor_slice_pb2.pyi @@ -15,9 +15,10 @@ ordered code that encodes the name of the tensor and the slice information. The name is also stored in the SaveSlice message for ease of debugging and manual examination. """ + import builtins import collections.abc -import typing as typing_extensions +import typing import google.protobuf.descriptor import google.protobuf.internal.containers @@ -30,7 +31,7 @@ import tensorflow.core.framework.versions_pb2 DESCRIPTOR: google.protobuf.descriptor.FileDescriptor -@typing_extensions.final +@typing.final class SavedSliceMeta(google.protobuf.message.Message): """Metadata describing the set of slices of the same tensor saved in a checkpoint file. @@ -44,14 +45,16 @@ class SavedSliceMeta(google.protobuf.message.Message): SLICE_FIELD_NUMBER: builtins.int name: builtins.str """Name of the tensor.""" + type: tensorflow.core.framework.types_pb2.DataType.ValueType + """Type of the tensor""" @property def shape(self) -> tensorflow.core.framework.tensor_shape_pb2.TensorShapeProto: """Shape of the tensor""" - type: tensorflow.core.framework.types_pb2.DataType.ValueType - """Type of the tensor""" + @property def slice(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[tensorflow.core.framework.tensor_slice_pb2.TensorSliceProto]: """Explicit list of slices saved in the checkpoint file.""" + def __init__( self, *, @@ -60,12 +63,12 @@ class SavedSliceMeta(google.protobuf.message.Message): type: tensorflow.core.framework.types_pb2.DataType.ValueType | None = ..., slice: collections.abc.Iterable[tensorflow.core.framework.tensor_slice_pb2.TensorSliceProto] | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["shape", b"shape"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["name", b"name", "shape", b"shape", "slice", b"slice", "type", b"type"]) -> None: ... + def HasField(self, field_name: typing.Literal["shape", b"shape"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["name", b"name", "shape", b"shape", "slice", b"slice", "type", b"type"]) -> None: ... global___SavedSliceMeta = SavedSliceMeta -@typing_extensions.final +@typing.final class SavedTensorSliceMeta(google.protobuf.message.Message): """Metadata describing the set of tensor slices saved in a checkpoint file. It is always stored at the beginning of each checkpoint file. @@ -78,23 +81,25 @@ class SavedTensorSliceMeta(google.protobuf.message.Message): @property def tensor(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___SavedSliceMeta]: """Each SavedSliceMeta describes the slices for one tensor.""" + @property def versions(self) -> tensorflow.core.framework.versions_pb2.VersionDef: """Compatibility version of this checkpoint. See core/public/version.h for version history. """ + def __init__( self, *, tensor: collections.abc.Iterable[global___SavedSliceMeta] | None = ..., versions: tensorflow.core.framework.versions_pb2.VersionDef | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["versions", b"versions"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["tensor", b"tensor", "versions", b"versions"]) -> None: ... + def HasField(self, field_name: typing.Literal["versions", b"versions"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["tensor", b"tensor", "versions", b"versions"]) -> None: ... global___SavedTensorSliceMeta = SavedTensorSliceMeta -@typing_extensions.final +@typing.final class SavedSlice(google.protobuf.message.Message): """Saved tensor slice: it stores the name of the tensors, the slice, and the raw data. @@ -114,11 +119,13 @@ class SavedSlice(google.protobuf.message.Message): """Extent of the slice. Must have one entry for each of the dimension of the tensor that this slice belongs to. """ + @property def data(self) -> tensorflow.core.framework.tensor_pb2.TensorProto: """The raw data of the slice is stored as a TensorProto. Only raw data are stored (we don't fill in fields such as dtype or tensor_shape). """ + def __init__( self, *, @@ -126,12 +133,12 @@ class SavedSlice(google.protobuf.message.Message): slice: tensorflow.core.framework.tensor_slice_pb2.TensorSliceProto | None = ..., data: tensorflow.core.framework.tensor_pb2.TensorProto | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["data", b"data", "slice", b"slice"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["data", b"data", "name", b"name", "slice", b"slice"]) -> None: ... + def HasField(self, field_name: typing.Literal["data", b"data", "slice", b"slice"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["data", b"data", "name", b"name", "slice", b"slice"]) -> None: ... global___SavedSlice = SavedSlice -@typing_extensions.final +@typing.final class SavedTensorSlices(google.protobuf.message.Message): """Each record in a v3 checkpoint file is a serialized SavedTensorSlices message. @@ -146,16 +153,18 @@ class SavedTensorSlices(google.protobuf.message.Message): """This is only present at the first item of each checkpoint file and serves as a table of contents, listing all the tensor slices saved in this file. """ + @property def data(self) -> global___SavedSlice: """This exists in all but the first item of each checkpoint file.""" + def __init__( self, *, meta: global___SavedTensorSliceMeta | None = ..., data: global___SavedSlice | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["data", b"data", "meta", b"meta"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["data", b"data", "meta", b"meta"]) -> None: ... + def HasField(self, field_name: typing.Literal["data", b"data", "meta", b"meta"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["data", b"data", "meta", b"meta"]) -> None: ... global___SavedTensorSlices = SavedTensorSlices diff --git a/stubs/tensorflow/tensorflow/core/util/test_log_pb2.pyi b/stubs/tensorflow/tensorflow/core/util/test_log_pb2.pyi index c58568965d3c..d210ba06d2fa 100644 --- a/stubs/tensorflow/tensorflow/core/util/test_log_pb2.pyi +++ b/stubs/tensorflow/tensorflow/core/util/test_log_pb2.pyi @@ -2,6 +2,7 @@ @generated by mypy-protobuf. Do not edit manually! isort:skip_file Protocol messages for describing the results of benchmarks and unit tests.""" + import google.protobuf.descriptor from tensorflow.tsl.protobuf.test_log_pb2 import ( AvailableDeviceInfo as AvailableDeviceInfo, diff --git a/stubs/tensorflow/tensorflow/python/keras/protobuf/projector_config_pb2.pyi b/stubs/tensorflow/tensorflow/python/keras/protobuf/projector_config_pb2.pyi index e034d4a52a7f..22be35d7d6bc 100644 --- a/stubs/tensorflow/tensorflow/python/keras/protobuf/projector_config_pb2.pyi +++ b/stubs/tensorflow/tensorflow/python/keras/protobuf/projector_config_pb2.pyi @@ -5,9 +5,10 @@ This file is a copy of the TensorBoard ProjectorConfig proto. Keep this file in sync with the source proto definition at https://github.com/tensorflow/tensorboard/blob/master/tensorboard/plugins/projector/projector_config.proto """ + import builtins import collections.abc -import typing as typing_extensions +import typing import google.protobuf.descriptor import google.protobuf.internal.containers @@ -15,7 +16,7 @@ import google.protobuf.message DESCRIPTOR: google.protobuf.descriptor.FileDescriptor -@typing_extensions.final +@typing.final class SpriteMetadata(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -25,17 +26,18 @@ class SpriteMetadata(google.protobuf.message.Message): @property def single_image_dim(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.int]: """[width, height] of a single image in the sprite.""" + def __init__( self, *, image_path: builtins.str | None = ..., single_image_dim: collections.abc.Iterable[builtins.int] | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["image_path", b"image_path", "single_image_dim", b"single_image_dim"]) -> None: ... + def ClearField(self, field_name: typing.Literal["image_path", b"image_path", "single_image_dim", b"single_image_dim"]) -> None: ... global___SpriteMetadata = SpriteMetadata -@typing_extensions.final +@typing.final class EmbeddingInfo(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -48,17 +50,18 @@ class EmbeddingInfo(google.protobuf.message.Message): tensor_name: builtins.str metadata_path: builtins.str bookmarks_path: builtins.str + tensor_path: builtins.str + """Path to the TSV file holding the tensor values. If missing, the tensor + is assumed to be stored in the model checkpoint. + """ @property def tensor_shape(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.int]: """Shape of the 2D tensor [N x D]. If missing, it will be inferred from the model checkpoint. """ + @property def sprite(self) -> global___SpriteMetadata: ... - tensor_path: builtins.str - """Path to the TSV file holding the tensor values. If missing, the tensor - is assumed to be stored in the model checkpoint. - """ def __init__( self, *, @@ -69,12 +72,12 @@ class EmbeddingInfo(google.protobuf.message.Message): sprite: global___SpriteMetadata | None = ..., tensor_path: builtins.str | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["sprite", b"sprite"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["bookmarks_path", b"bookmarks_path", "metadata_path", b"metadata_path", "sprite", b"sprite", "tensor_name", b"tensor_name", "tensor_path", b"tensor_path", "tensor_shape", b"tensor_shape"]) -> None: ... + def HasField(self, field_name: typing.Literal["sprite", b"sprite"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["bookmarks_path", b"bookmarks_path", "metadata_path", b"metadata_path", "sprite", b"sprite", "tensor_name", b"tensor_name", "tensor_path", b"tensor_path", "tensor_shape", b"tensor_shape"]) -> None: ... global___EmbeddingInfo = EmbeddingInfo -@typing_extensions.final +@typing.final class ProjectorConfig(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -83,12 +86,12 @@ class ProjectorConfig(google.protobuf.message.Message): MODEL_CHECKPOINT_DIR_FIELD_NUMBER: builtins.int model_checkpoint_path: builtins.str """Path to the checkpoint file. Use either this or model_checkpoint_dir.""" - @property - def embeddings(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___EmbeddingInfo]: ... model_checkpoint_dir: builtins.str """Path to the checkpoint directory. The directory will be scanned for the latest checkpoint file. """ + @property + def embeddings(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___EmbeddingInfo]: ... def __init__( self, *, @@ -96,6 +99,6 @@ class ProjectorConfig(google.protobuf.message.Message): embeddings: collections.abc.Iterable[global___EmbeddingInfo] | None = ..., model_checkpoint_dir: builtins.str | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["embeddings", b"embeddings", "model_checkpoint_dir", b"model_checkpoint_dir", "model_checkpoint_path", b"model_checkpoint_path"]) -> None: ... + def ClearField(self, field_name: typing.Literal["embeddings", b"embeddings", "model_checkpoint_dir", b"model_checkpoint_dir", "model_checkpoint_path", b"model_checkpoint_path"]) -> None: ... global___ProjectorConfig = ProjectorConfig diff --git a/stubs/tensorflow/tensorflow/python/keras/protobuf/saved_metadata_pb2.pyi b/stubs/tensorflow/tensorflow/python/keras/protobuf/saved_metadata_pb2.pyi index 391c7b0dcd24..0133517d273f 100644 --- a/stubs/tensorflow/tensorflow/python/keras/protobuf/saved_metadata_pb2.pyi +++ b/stubs/tensorflow/tensorflow/python/keras/protobuf/saved_metadata_pb2.pyi @@ -2,9 +2,10 @@ @generated by mypy-protobuf. Do not edit manually! isort:skip_file Protobuf containing the metadata for each Keras object saved in a SavedModel.""" + import builtins import collections.abc -import typing as typing_extensions +import typing import google.protobuf.descriptor import google.protobuf.internal.containers @@ -13,7 +14,7 @@ import tensorflow.python.keras.protobuf.versions_pb2 DESCRIPTOR: google.protobuf.descriptor.FileDescriptor -@typing_extensions.final +@typing.final class SavedMetadata(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -23,16 +24,17 @@ class SavedMetadata(google.protobuf.message.Message): """Nodes represent trackable objects in the SavedModel. The data for every Keras object is stored. """ + def __init__( self, *, nodes: collections.abc.Iterable[global___SavedObject] | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["nodes", b"nodes"]) -> None: ... + def ClearField(self, field_name: typing.Literal["nodes", b"nodes"]) -> None: ... global___SavedMetadata = SavedMetadata -@typing_extensions.final +@typing.final class SavedObject(google.protobuf.message.Message): """Metadata of an individual Keras object.""" @@ -61,6 +63,7 @@ class SavedObject(google.protobuf.message.Message): @property def version(self) -> tensorflow.python.keras.protobuf.versions_pb2.VersionDef: """Version defined by the code serializing this Keras object.""" + def __init__( self, *, @@ -70,7 +73,7 @@ class SavedObject(google.protobuf.message.Message): metadata: builtins.str | None = ..., version: tensorflow.python.keras.protobuf.versions_pb2.VersionDef | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["version", b"version"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["identifier", b"identifier", "metadata", b"metadata", "node_id", b"node_id", "node_path", b"node_path", "version", b"version"]) -> None: ... + def HasField(self, field_name: typing.Literal["version", b"version"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["identifier", b"identifier", "metadata", b"metadata", "node_id", b"node_id", "node_path", b"node_path", "version", b"version"]) -> None: ... global___SavedObject = SavedObject diff --git a/stubs/tensorflow/tensorflow/python/keras/protobuf/versions_pb2.pyi b/stubs/tensorflow/tensorflow/python/keras/protobuf/versions_pb2.pyi index 50d547c82207..55d2e725bc0d 100644 --- a/stubs/tensorflow/tensorflow/python/keras/protobuf/versions_pb2.pyi +++ b/stubs/tensorflow/tensorflow/python/keras/protobuf/versions_pb2.pyi @@ -2,9 +2,10 @@ @generated by mypy-protobuf. Do not edit manually! isort:skip_file """ + import builtins import collections.abc -import typing as typing_extensions +import typing import google.protobuf.descriptor import google.protobuf.internal.containers @@ -12,7 +13,7 @@ import google.protobuf.message DESCRIPTOR: google.protobuf.descriptor.FileDescriptor -@typing_extensions.final +@typing.final class VersionDef(google.protobuf.message.Message): """This file is a copy of the TensorFlow Versions proto. Keep this file in sync with the source proto definition at @@ -46,6 +47,7 @@ class VersionDef(google.protobuf.message.Message): @property def bad_consumers(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.int]: """Specific consumer versions which are disallowed (e.g. due to bugs).""" + def __init__( self, *, @@ -53,6 +55,6 @@ class VersionDef(google.protobuf.message.Message): min_consumer: builtins.int | None = ..., bad_consumers: collections.abc.Iterable[builtins.int] | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["bad_consumers", b"bad_consumers", "min_consumer", b"min_consumer", "producer", b"producer"]) -> None: ... + def ClearField(self, field_name: typing.Literal["bad_consumers", b"bad_consumers", "min_consumer", b"min_consumer", "producer", b"producer"]) -> None: ... global___VersionDef = VersionDef diff --git a/stubs/tensorflow/tensorflow/tsl/protobuf/autotuning_pb2.pyi b/stubs/tensorflow/tensorflow/tsl/protobuf/autotuning_pb2.pyi index 38ee640d0923..4036f52fdb1b 100644 --- a/stubs/tensorflow/tensorflow/tsl/protobuf/autotuning_pb2.pyi +++ b/stubs/tensorflow/tensorflow/tsl/protobuf/autotuning_pb2.pyi @@ -7,6 +7,7 @@ operations. They are in proto format because we want to log them structured. They offer tremendous statistical, testing, and debugging value. """ + import builtins import collections.abc import sys @@ -27,7 +28,7 @@ else: DESCRIPTOR: google.protobuf.descriptor.FileDescriptor -@typing_extensions.final +@typing.final class CudnnVersion(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -44,11 +45,11 @@ class CudnnVersion(google.protobuf.message.Message): minor: builtins.int | None = ..., patch: builtins.int | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["major", b"major", "minor", b"minor", "patch", b"patch"]) -> None: ... + def ClearField(self, field_name: typing.Literal["major", b"major", "minor", b"minor", "patch", b"patch"]) -> None: ... global___CudnnVersion = CudnnVersion -@typing_extensions.final +@typing.final class ComputeCapability(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -62,11 +63,11 @@ class ComputeCapability(google.protobuf.message.Message): major: builtins.int | None = ..., minor: builtins.int | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["major", b"major", "minor", b"minor"]) -> None: ... + def ClearField(self, field_name: typing.Literal["major", b"major", "minor", b"minor"]) -> None: ... global___ComputeCapability = ComputeCapability -@typing_extensions.final +@typing.final class AutotuneResult(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -93,7 +94,7 @@ class AutotuneResult(google.protobuf.message.Message): DISQUALIFIED: AutotuneResult.FailureKind.ValueType # 3 """Algorithm was rejected for failing to run or for known bugs.""" - @typing_extensions.final + @typing.final class FailureResult(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -106,6 +107,7 @@ class AutotuneResult(google.protobuf.message.Message): BUFFER_ADDRESS_FIELD_NUMBER: builtins.int kind: global___AutotuneResult.FailureKind.ValueType msg: builtins.str + buffer_address: builtins.int @property def reference_conv(self) -> global___AutotuneResult.ConvKey: ... @property @@ -114,7 +116,6 @@ class AutotuneResult(google.protobuf.message.Message): def reference_cuda_conv_plan(self) -> global___AutotuneResult.CudaConvPlanKey: ... @property def reference_algorithm(self) -> tensorflow.tsl.protobuf.dnn_pb2.AlgorithmProto: ... - buffer_address: builtins.int def __init__( self, *, @@ -126,11 +127,11 @@ class AutotuneResult(google.protobuf.message.Message): reference_algorithm: tensorflow.tsl.protobuf.dnn_pb2.AlgorithmProto | None = ..., buffer_address: builtins.int | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["key", b"key", "reference_algorithm", b"reference_algorithm", "reference_conv", b"reference_conv", "reference_cuda_conv_plan", b"reference_cuda_conv_plan", "reference_gemm", b"reference_gemm"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["buffer_address", b"buffer_address", "key", b"key", "kind", b"kind", "msg", b"msg", "reference_algorithm", b"reference_algorithm", "reference_conv", b"reference_conv", "reference_cuda_conv_plan", b"reference_cuda_conv_plan", "reference_gemm", b"reference_gemm"]) -> None: ... - def WhichOneof(self, oneof_group: typing_extensions.Literal["key", b"key"]) -> typing_extensions.Literal["reference_conv", "reference_gemm", "reference_cuda_conv_plan", "reference_algorithm"] | None: ... + def HasField(self, field_name: typing.Literal["key", b"key", "reference_algorithm", b"reference_algorithm", "reference_conv", b"reference_conv", "reference_cuda_conv_plan", b"reference_cuda_conv_plan", "reference_gemm", b"reference_gemm"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["buffer_address", b"buffer_address", "key", b"key", "kind", b"kind", "msg", b"msg", "reference_algorithm", b"reference_algorithm", "reference_conv", b"reference_conv", "reference_cuda_conv_plan", b"reference_cuda_conv_plan", "reference_gemm", b"reference_gemm"]) -> None: ... + def WhichOneof(self, oneof_group: typing.Literal["key", b"key"]) -> typing.Literal["reference_conv", "reference_gemm", "reference_cuda_conv_plan", "reference_algorithm"] | None: ... - @typing_extensions.final + @typing.final class ConvKey(google.protobuf.message.Message): """Legacy and unused in new data; superseded by AlgorithmProto.""" @@ -146,9 +147,9 @@ class AutotuneResult(google.protobuf.message.Message): algorithm: builtins.int | None = ..., tensor_ops_enabled: builtins.bool | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["algorithm", b"algorithm", "tensor_ops_enabled", b"tensor_ops_enabled"]) -> None: ... + def ClearField(self, field_name: typing.Literal["algorithm", b"algorithm", "tensor_ops_enabled", b"tensor_ops_enabled"]) -> None: ... - @typing_extensions.final + @typing.final class GemmKey(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -159,9 +160,9 @@ class AutotuneResult(google.protobuf.message.Message): *, algorithm: builtins.int | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["algorithm", b"algorithm"]) -> None: ... + def ClearField(self, field_name: typing.Literal["algorithm", b"algorithm"]) -> None: ... - @typing_extensions.final + @typing.final class CudaConvPlanKey(google.protobuf.message.Message): """Legacy and unused in new data; superseded by AlgorithmProto.""" @@ -174,7 +175,7 @@ class AutotuneResult(google.protobuf.message.Message): *, exec_plan_id: builtins.str | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["exec_plan_id", b"exec_plan_id"]) -> None: ... + def ClearField(self, field_name: typing.Literal["exec_plan_id", b"exec_plan_id"]) -> None: ... SCRATCH_BYTES_FIELD_NUMBER: builtins.int RUN_TIME_FIELD_NUMBER: builtins.int @@ -207,13 +208,13 @@ class AutotuneResult(google.protobuf.message.Message): cuda_conv_plan: global___AutotuneResult.CudaConvPlanKey | None = ..., algorithm: tensorflow.tsl.protobuf.dnn_pb2.AlgorithmProto | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["algorithm", b"algorithm", "conv", b"conv", "cuda_conv_plan", b"cuda_conv_plan", "failure", b"failure", "gemm", b"gemm", "key", b"key", "run_time", b"run_time"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["algorithm", b"algorithm", "conv", b"conv", "cuda_conv_plan", b"cuda_conv_plan", "failure", b"failure", "gemm", b"gemm", "key", b"key", "run_time", b"run_time", "scratch_bytes", b"scratch_bytes"]) -> None: ... - def WhichOneof(self, oneof_group: typing_extensions.Literal["key", b"key"]) -> typing_extensions.Literal["conv", "gemm", "cuda_conv_plan", "algorithm"] | None: ... + def HasField(self, field_name: typing.Literal["algorithm", b"algorithm", "conv", b"conv", "cuda_conv_plan", b"cuda_conv_plan", "failure", b"failure", "gemm", b"gemm", "key", b"key", "run_time", b"run_time"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["algorithm", b"algorithm", "conv", b"conv", "cuda_conv_plan", b"cuda_conv_plan", "failure", b"failure", "gemm", b"gemm", "key", b"key", "run_time", b"run_time", "scratch_bytes", b"scratch_bytes"]) -> None: ... + def WhichOneof(self, oneof_group: typing.Literal["key", b"key"]) -> typing.Literal["conv", "gemm", "cuda_conv_plan", "algorithm"] | None: ... global___AutotuneResult = AutotuneResult -@typing_extensions.final +@typing.final class AutotuningLog(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -223,18 +224,19 @@ class AutotuningLog(google.protobuf.message.Message): COMPUTE_CAPABILITY_FIELD_NUMBER: builtins.int DEVICE_PCI_BUS_ID_FIELD_NUMBER: builtins.int BLAS_VERSION_FIELD_NUMBER: builtins.int + device_pci_bus_id: builtins.str + """stream_executor::DeviceDescription::pci_bus_id.""" + blas_version: builtins.str @property def instr(self) -> google.protobuf.any_pb2.Any: ... @property def results(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___AutotuneResult]: """Records all auto-tuning results per algorithm.""" + @property def cudnn_version(self) -> global___CudnnVersion: ... @property def compute_capability(self) -> global___ComputeCapability: ... - device_pci_bus_id: builtins.str - """stream_executor::DeviceDescription::pci_bus_id.""" - blas_version: builtins.str def __init__( self, *, @@ -245,7 +247,7 @@ class AutotuningLog(google.protobuf.message.Message): device_pci_bus_id: builtins.str | None = ..., blas_version: builtins.str | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["compute_capability", b"compute_capability", "cudnn_version", b"cudnn_version", "instr", b"instr"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["blas_version", b"blas_version", "compute_capability", b"compute_capability", "cudnn_version", b"cudnn_version", "device_pci_bus_id", b"device_pci_bus_id", "instr", b"instr", "results", b"results"]) -> None: ... + def HasField(self, field_name: typing.Literal["compute_capability", b"compute_capability", "cudnn_version", b"cudnn_version", "instr", b"instr"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["blas_version", b"blas_version", "compute_capability", b"compute_capability", "cudnn_version", b"cudnn_version", "device_pci_bus_id", b"device_pci_bus_id", "instr", b"instr", "results", b"results"]) -> None: ... global___AutotuningLog = AutotuningLog diff --git a/stubs/tensorflow/tensorflow/tsl/protobuf/bfc_memory_map_pb2.pyi b/stubs/tensorflow/tensorflow/tsl/protobuf/bfc_memory_map_pb2.pyi index 7201e2fb5da2..9e1871be16a8 100644 --- a/stubs/tensorflow/tensorflow/tsl/protobuf/bfc_memory_map_pb2.pyi +++ b/stubs/tensorflow/tensorflow/tsl/protobuf/bfc_memory_map_pb2.pyi @@ -2,9 +2,10 @@ @generated by mypy-protobuf. Do not edit manually! isort:skip_file """ + import builtins import collections.abc -import typing as typing_extensions +import typing import google.protobuf.descriptor import google.protobuf.internal.containers @@ -12,7 +13,7 @@ import google.protobuf.message DESCRIPTOR: google.protobuf.descriptor.FileDescriptor -@typing_extensions.final +@typing.final class MemAllocatorStats(google.protobuf.message.Message): """Some of the data from AllocatorStats""" @@ -37,11 +38,11 @@ class MemAllocatorStats(google.protobuf.message.Message): largest_alloc_size: builtins.int | None = ..., fragmentation_metric: builtins.float | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["bytes_in_use", b"bytes_in_use", "fragmentation_metric", b"fragmentation_metric", "largest_alloc_size", b"largest_alloc_size", "num_allocs", b"num_allocs", "peak_bytes_in_use", b"peak_bytes_in_use"]) -> None: ... + def ClearField(self, field_name: typing.Literal["bytes_in_use", b"bytes_in_use", "fragmentation_metric", b"fragmentation_metric", "largest_alloc_size", b"largest_alloc_size", "num_allocs", b"num_allocs", "peak_bytes_in_use", b"peak_bytes_in_use"]) -> None: ... global___MemAllocatorStats = MemAllocatorStats -@typing_extensions.final +@typing.final class MemChunk(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -76,11 +77,11 @@ class MemChunk(google.protobuf.message.Message): in_use: builtins.bool | None = ..., step_id: builtins.int | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["action_count", b"action_count", "address", b"address", "bin", b"bin", "freed_at_count", b"freed_at_count", "in_use", b"in_use", "op_name", b"op_name", "requested_size", b"requested_size", "size", b"size", "step_id", b"step_id"]) -> None: ... + def ClearField(self, field_name: typing.Literal["action_count", b"action_count", "address", b"address", "bin", b"bin", "freed_at_count", b"freed_at_count", "in_use", b"in_use", "op_name", b"op_name", "requested_size", b"requested_size", "size", b"size", "step_id", b"step_id"]) -> None: ... global___MemChunk = MemChunk -@typing_extensions.final +@typing.final class BinSummary(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -103,11 +104,11 @@ class BinSummary(google.protobuf.message.Message): total_chunks_in_use: builtins.int | None = ..., total_chunks_in_bin: builtins.int | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["bin", b"bin", "total_bytes_in_bin", b"total_bytes_in_bin", "total_bytes_in_use", b"total_bytes_in_use", "total_chunks_in_bin", b"total_chunks_in_bin", "total_chunks_in_use", b"total_chunks_in_use"]) -> None: ... + def ClearField(self, field_name: typing.Literal["bin", b"bin", "total_bytes_in_bin", b"total_bytes_in_bin", "total_bytes_in_use", b"total_bytes_in_use", "total_chunks_in_bin", b"total_chunks_in_bin", "total_chunks_in_use", b"total_chunks_in_use"]) -> None: ... global___BinSummary = BinSummary -@typing_extensions.final +@typing.final class SnapShot(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -121,11 +122,11 @@ class SnapShot(google.protobuf.message.Message): action_count: builtins.int | None = ..., size: builtins.int | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["action_count", b"action_count", "size", b"size"]) -> None: ... + def ClearField(self, field_name: typing.Literal["action_count", b"action_count", "size", b"size"]) -> None: ... global___SnapShot = SnapShot -@typing_extensions.final +@typing.final class MemoryDump(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -152,7 +153,7 @@ class MemoryDump(google.protobuf.message.Message): snap_shot: collections.abc.Iterable[global___SnapShot] | None = ..., stats: global___MemAllocatorStats | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["stats", b"stats"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["allocator_name", b"allocator_name", "bin_summary", b"bin_summary", "chunk", b"chunk", "snap_shot", b"snap_shot", "stats", b"stats"]) -> None: ... + def HasField(self, field_name: typing.Literal["stats", b"stats"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["allocator_name", b"allocator_name", "bin_summary", b"bin_summary", "chunk", b"chunk", "snap_shot", b"snap_shot", "stats", b"stats"]) -> None: ... global___MemoryDump = MemoryDump diff --git a/stubs/tensorflow/tensorflow/tsl/protobuf/coordination_config_pb2.pyi b/stubs/tensorflow/tensorflow/tsl/protobuf/coordination_config_pb2.pyi index c4855fe17c53..ef57b76ee152 100644 --- a/stubs/tensorflow/tensorflow/tsl/protobuf/coordination_config_pb2.pyi +++ b/stubs/tensorflow/tensorflow/tsl/protobuf/coordination_config_pb2.pyi @@ -2,9 +2,10 @@ @generated by mypy-protobuf. Do not edit manually! isort:skip_file """ + import builtins import collections.abc -import typing as typing_extensions +import typing import google.protobuf.descriptor import google.protobuf.internal.containers @@ -12,7 +13,7 @@ import google.protobuf.message DESCRIPTOR: google.protobuf.descriptor.FileDescriptor -@typing_extensions.final +@typing.final class CoordinatedJob(google.protobuf.message.Message): """Represents a job type and the number of tasks under this job. For example, ("worker", 20) implies that there will be 20 worker tasks. @@ -30,11 +31,11 @@ class CoordinatedJob(google.protobuf.message.Message): name: builtins.str | None = ..., num_tasks: builtins.int | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["name", b"name", "num_tasks", b"num_tasks"]) -> None: ... + def ClearField(self, field_name: typing.Literal["name", b"name", "num_tasks", b"num_tasks"]) -> None: ... global___CoordinatedJob = CoordinatedJob -@typing_extensions.final +@typing.final class CoordinationServiceConfig(google.protobuf.message.Message): """Coordination service configuration parameters. The system picks appropriate values for fields that are not set. @@ -70,8 +71,6 @@ class CoordinationServiceConfig(google.protobuf.message.Message): the agent has disconnected, to account for the lag time between the service recording the state change and the agent stopping heartbeats. """ - @property - def coordinated_job_list(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___CoordinatedJob]: ... shutdown_barrier_timeout_in_ms: builtins.int """Denotes how long to wait for all coordination agents to reach the barriers (after the first shutdown request) before disconnecting together. If @@ -84,12 +83,15 @@ class CoordinationServiceConfig(google.protobuf.message.Message): testing. """ @property + def coordinated_job_list(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___CoordinatedJob]: ... + @property def recoverable_jobs(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.str]: """The list of jobs which are recoverable. If a task in this list fails, it will not propagate error to other tasks. If empty, no jobs will be recoverable and every task failure will cause error propagation to other tasks. """ + def __init__( self, *, @@ -103,6 +105,6 @@ class CoordinationServiceConfig(google.protobuf.message.Message): agent_destruction_without_shutdown: builtins.bool | None = ..., recoverable_jobs: collections.abc.Iterable[builtins.str] | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["agent_destruction_without_shutdown", b"agent_destruction_without_shutdown", "cluster_register_timeout_in_ms", b"cluster_register_timeout_in_ms", "coordinated_job_list", b"coordinated_job_list", "enable_health_check", b"enable_health_check", "heartbeat_timeout_in_ms", b"heartbeat_timeout_in_ms", "recoverable_jobs", b"recoverable_jobs", "service_leader", b"service_leader", "service_type", b"service_type", "shutdown_barrier_timeout_in_ms", b"shutdown_barrier_timeout_in_ms"]) -> None: ... + def ClearField(self, field_name: typing.Literal["agent_destruction_without_shutdown", b"agent_destruction_without_shutdown", "cluster_register_timeout_in_ms", b"cluster_register_timeout_in_ms", "coordinated_job_list", b"coordinated_job_list", "enable_health_check", b"enable_health_check", "heartbeat_timeout_in_ms", b"heartbeat_timeout_in_ms", "recoverable_jobs", b"recoverable_jobs", "service_leader", b"service_leader", "service_type", b"service_type", "shutdown_barrier_timeout_in_ms", b"shutdown_barrier_timeout_in_ms"]) -> None: ... global___CoordinationServiceConfig = CoordinationServiceConfig diff --git a/stubs/tensorflow/tensorflow/tsl/protobuf/coordination_service_pb2.pyi b/stubs/tensorflow/tensorflow/tsl/protobuf/coordination_service_pb2.pyi index 7165c7199683..6054bb13f79d 100644 --- a/stubs/tensorflow/tensorflow/tsl/protobuf/coordination_service_pb2.pyi +++ b/stubs/tensorflow/tensorflow/tsl/protobuf/coordination_service_pb2.pyi @@ -2,6 +2,7 @@ @generated by mypy-protobuf. Do not edit manually! isort:skip_file """ + import builtins import collections.abc import sys @@ -52,7 +53,7 @@ TASKSTATE_CONNECTED: CoordinatedTaskState.ValueType # 3 TASKSTATE_ERROR: CoordinatedTaskState.ValueType # 4 global___CoordinatedTaskState = CoordinatedTaskState -@typing_extensions.final +@typing.final class CoordinatedTask(google.protobuf.message.Message): """Represents a remote worker task, specified by job name and task id.""" @@ -68,11 +69,11 @@ class CoordinatedTask(google.protobuf.message.Message): job_name: builtins.str | None = ..., task_id: builtins.int | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["job_name", b"job_name", "task_id", b"task_id"]) -> None: ... + def ClearField(self, field_name: typing.Literal["job_name", b"job_name", "task_id", b"task_id"]) -> None: ... global___CoordinatedTask = CoordinatedTask -@typing_extensions.final +@typing.final class CoordinationServiceError(google.protobuf.message.Message): """Status payload for all coordination service errors. Note: an empty proto may be set if the error is triggered by the task's own @@ -92,18 +93,19 @@ class CoordinationServiceError(google.protobuf.message.Message): """Denotes which task hit the error. If unset, the error originated from the same task that is processing this error. """ + def __init__( self, *, is_reported_error: builtins.bool | None = ..., source_task: global___CoordinatedTask | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["source_task", b"source_task"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["is_reported_error", b"is_reported_error", "source_task", b"source_task"]) -> None: ... + def HasField(self, field_name: typing.Literal["source_task", b"source_task"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["is_reported_error", b"is_reported_error", "source_task", b"source_task"]) -> None: ... global___CoordinationServiceError = CoordinationServiceError -@typing_extensions.final +@typing.final class CoordinatedTaskStateInfo(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -112,12 +114,12 @@ class CoordinatedTaskStateInfo(google.protobuf.message.Message): ERROR_CODE_FIELD_NUMBER: builtins.int ERROR_MESSAGE_FIELD_NUMBER: builtins.int ERROR_PAYLOAD_FIELD_NUMBER: builtins.int - @property - def task(self) -> global___CoordinatedTask: ... state: global___CoordinatedTaskState.ValueType error_code: builtins.int error_message: builtins.str @property + def task(self) -> global___CoordinatedTask: ... + @property def error_payload(self) -> global___CoordinationServiceError: ... def __init__( self, @@ -128,12 +130,12 @@ class CoordinatedTaskStateInfo(google.protobuf.message.Message): error_message: builtins.str | None = ..., error_payload: global___CoordinationServiceError | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["error_payload", b"error_payload", "task", b"task"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["error_code", b"error_code", "error_message", b"error_message", "error_payload", b"error_payload", "state", b"state", "task", b"task"]) -> None: ... + def HasField(self, field_name: typing.Literal["error_payload", b"error_payload", "task", b"task"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["error_code", b"error_code", "error_message", b"error_message", "error_payload", b"error_payload", "state", b"state", "task", b"task"]) -> None: ... global___CoordinatedTaskStateInfo = CoordinatedTaskStateInfo -@typing_extensions.final +@typing.final class DeviceInfo(google.protobuf.message.Message): """Placeholder message to be extended by other runtimes' device representations.""" @@ -147,11 +149,11 @@ class DeviceInfo(google.protobuf.message.Message): *, device: collections.abc.Iterable[google.protobuf.any_pb2.Any] | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["device", b"device"]) -> None: ... + def ClearField(self, field_name: typing.Literal["device", b"device"]) -> None: ... global___DeviceInfo = DeviceInfo -@typing_extensions.final +@typing.final class RegisterTaskRequest(google.protobuf.message.Message): """Request and response messages for registering a task to the cluster leader. A task is uniquely represented by its `job_name`, `task_id` and @@ -172,12 +174,12 @@ class RegisterTaskRequest(google.protobuf.message.Message): incarnation: builtins.int | None = ..., source_task: global___CoordinatedTask | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["source_task", b"source_task"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["incarnation", b"incarnation", "source_task", b"source_task"]) -> None: ... + def HasField(self, field_name: typing.Literal["source_task", b"source_task"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["incarnation", b"incarnation", "source_task", b"source_task"]) -> None: ... global___RegisterTaskRequest = RegisterTaskRequest -@typing_extensions.final +@typing.final class RegisterTaskResponse(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -188,11 +190,11 @@ class RegisterTaskResponse(google.protobuf.message.Message): *, leader_incarnation: builtins.int | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["leader_incarnation", b"leader_incarnation"]) -> None: ... + def ClearField(self, field_name: typing.Literal["leader_incarnation", b"leader_incarnation"]) -> None: ... global___RegisterTaskResponse = RegisterTaskResponse -@typing_extensions.final +@typing.final class HeartbeatRequest(google.protobuf.message.Message): """Request and response messages for sending heartbeats.""" @@ -209,12 +211,12 @@ class HeartbeatRequest(google.protobuf.message.Message): incarnation: builtins.int | None = ..., source_task: global___CoordinatedTask | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["source_task", b"source_task"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["incarnation", b"incarnation", "source_task", b"source_task"]) -> None: ... + def HasField(self, field_name: typing.Literal["source_task", b"source_task"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["incarnation", b"incarnation", "source_task", b"source_task"]) -> None: ... global___HeartbeatRequest = HeartbeatRequest -@typing_extensions.final +@typing.final class HeartbeatResponse(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -228,11 +230,11 @@ class HeartbeatResponse(google.protobuf.message.Message): *, leader_incarnation: builtins.int | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["leader_incarnation", b"leader_incarnation"]) -> None: ... + def ClearField(self, field_name: typing.Literal["leader_incarnation", b"leader_incarnation"]) -> None: ... global___HeartbeatResponse = HeartbeatResponse -@typing_extensions.final +@typing.final class WaitForAllTasksRequest(google.protobuf.message.Message): """Request and response messages for waiting for all tasks.""" @@ -245,18 +247,19 @@ class WaitForAllTasksRequest(google.protobuf.message.Message): @property def device_info(self) -> global___DeviceInfo: """All local device attributes on the request sender;""" + def __init__( self, *, source_task: global___CoordinatedTask | None = ..., device_info: global___DeviceInfo | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["device_info", b"device_info", "source_task", b"source_task"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["device_info", b"device_info", "source_task", b"source_task"]) -> None: ... + def HasField(self, field_name: typing.Literal["device_info", b"device_info", "source_task", b"source_task"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["device_info", b"device_info", "source_task", b"source_task"]) -> None: ... global___WaitForAllTasksRequest = WaitForAllTasksRequest -@typing_extensions.final +@typing.final class WaitForAllTasksResponse(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -266,18 +269,19 @@ class WaitForAllTasksResponse(google.protobuf.message.Message): @property def device_info(self) -> global___DeviceInfo: """All devices in the cluster.""" + def __init__( self, *, leader_incarnation: builtins.int | None = ..., device_info: global___DeviceInfo | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["device_info", b"device_info"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["device_info", b"device_info", "leader_incarnation", b"leader_incarnation"]) -> None: ... + def HasField(self, field_name: typing.Literal["device_info", b"device_info"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["device_info", b"device_info", "leader_incarnation", b"leader_incarnation"]) -> None: ... global___WaitForAllTasksResponse = WaitForAllTasksResponse -@typing_extensions.final +@typing.final class ShutdownTaskRequest(google.protobuf.message.Message): """Request and response messages for disconnecting a task from the service.""" @@ -291,12 +295,12 @@ class ShutdownTaskRequest(google.protobuf.message.Message): *, source_task: global___CoordinatedTask | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["source_task", b"source_task"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["source_task", b"source_task"]) -> None: ... + def HasField(self, field_name: typing.Literal["source_task", b"source_task"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["source_task", b"source_task"]) -> None: ... global___ShutdownTaskRequest = ShutdownTaskRequest -@typing_extensions.final +@typing.final class ShutdownTaskResponse(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -306,7 +310,7 @@ class ShutdownTaskResponse(google.protobuf.message.Message): global___ShutdownTaskResponse = ShutdownTaskResponse -@typing_extensions.final +@typing.final class ResetTaskRequest(google.protobuf.message.Message): """Request and response messages for resetting a task state in the service.""" @@ -320,12 +324,12 @@ class ResetTaskRequest(google.protobuf.message.Message): *, source_task: global___CoordinatedTask | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["source_task", b"source_task"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["source_task", b"source_task"]) -> None: ... + def HasField(self, field_name: typing.Literal["source_task", b"source_task"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["source_task", b"source_task"]) -> None: ... global___ResetTaskRequest = ResetTaskRequest -@typing_extensions.final +@typing.final class ResetTaskResponse(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -335,7 +339,7 @@ class ResetTaskResponse(google.protobuf.message.Message): global___ResetTaskResponse = ResetTaskResponse -@typing_extensions.final +@typing.final class ReportErrorToTaskRequest(google.protobuf.message.Message): """Request and response messages for reporting errors to task.""" @@ -355,12 +359,12 @@ class ReportErrorToTaskRequest(google.protobuf.message.Message): error_message: builtins.str | None = ..., error_payload: global___CoordinationServiceError | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["error_payload", b"error_payload"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["error_code", b"error_code", "error_message", b"error_message", "error_payload", b"error_payload"]) -> None: ... + def HasField(self, field_name: typing.Literal["error_payload", b"error_payload"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["error_code", b"error_code", "error_message", b"error_message", "error_payload", b"error_payload"]) -> None: ... global___ReportErrorToTaskRequest = ReportErrorToTaskRequest -@typing_extensions.final +@typing.final class ReportErrorToTaskResponse(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -370,7 +374,7 @@ class ReportErrorToTaskResponse(google.protobuf.message.Message): global___ReportErrorToTaskResponse = ReportErrorToTaskResponse -@typing_extensions.final +@typing.final class ReportErrorToServiceRequest(google.protobuf.message.Message): """Request and response messages for reporting errors to service instance.""" @@ -390,12 +394,12 @@ class ReportErrorToServiceRequest(google.protobuf.message.Message): error_message: builtins.str | None = ..., error_origin: global___CoordinatedTask | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["error_origin", b"error_origin"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["error_code", b"error_code", "error_message", b"error_message", "error_origin", b"error_origin"]) -> None: ... + def HasField(self, field_name: typing.Literal["error_origin", b"error_origin"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["error_code", b"error_code", "error_message", b"error_message", "error_origin", b"error_origin"]) -> None: ... global___ReportErrorToServiceRequest = ReportErrorToServiceRequest -@typing_extensions.final +@typing.final class ReportErrorToServiceResponse(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -405,7 +409,7 @@ class ReportErrorToServiceResponse(google.protobuf.message.Message): global___ReportErrorToServiceResponse = ReportErrorToServiceResponse -@typing_extensions.final +@typing.final class GetTaskStateRequest(google.protobuf.message.Message): """Request and response messages for getting state of a remote task.""" @@ -419,11 +423,11 @@ class GetTaskStateRequest(google.protobuf.message.Message): *, source_task: collections.abc.Iterable[global___CoordinatedTask] | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["source_task", b"source_task"]) -> None: ... + def ClearField(self, field_name: typing.Literal["source_task", b"source_task"]) -> None: ... global___GetTaskStateRequest = GetTaskStateRequest -@typing_extensions.final +@typing.final class GetTaskStateResponse(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -435,11 +439,11 @@ class GetTaskStateResponse(google.protobuf.message.Message): *, task_state: collections.abc.Iterable[global___CoordinatedTaskStateInfo] | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["task_state", b"task_state"]) -> None: ... + def ClearField(self, field_name: typing.Literal["task_state", b"task_state"]) -> None: ... global___GetTaskStateResponse = GetTaskStateResponse -@typing_extensions.final +@typing.final class KeyValueEntry(google.protobuf.message.Message): """Message for configuration key value. Key is structured like Unix file system, with multiple levels of directory @@ -458,11 +462,11 @@ class KeyValueEntry(google.protobuf.message.Message): key: builtins.str | None = ..., value: builtins.bytes | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["key", b"key", "value", b"value"]) -> None: ... + def ClearField(self, field_name: typing.Literal["key", b"key", "value", b"value"]) -> None: ... global___KeyValueEntry = KeyValueEntry -@typing_extensions.final +@typing.final class InsertKeyValueRequest(google.protobuf.message.Message): """Request and response messages for inserting configuration key-value data.""" @@ -476,12 +480,12 @@ class InsertKeyValueRequest(google.protobuf.message.Message): *, kv: global___KeyValueEntry | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["kv", b"kv"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["kv", b"kv"]) -> None: ... + def HasField(self, field_name: typing.Literal["kv", b"kv"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["kv", b"kv"]) -> None: ... global___InsertKeyValueRequest = InsertKeyValueRequest -@typing_extensions.final +@typing.final class InsertKeyValueResponse(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -491,7 +495,7 @@ class InsertKeyValueResponse(google.protobuf.message.Message): global___InsertKeyValueResponse = InsertKeyValueResponse -@typing_extensions.final +@typing.final class GetKeyValueRequest(google.protobuf.message.Message): """Request and response messages for getting configuration key-value data.""" @@ -504,11 +508,11 @@ class GetKeyValueRequest(google.protobuf.message.Message): *, key: builtins.str | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["key", b"key"]) -> None: ... + def ClearField(self, field_name: typing.Literal["key", b"key"]) -> None: ... global___GetKeyValueRequest = GetKeyValueRequest -@typing_extensions.final +@typing.final class GetKeyValueResponse(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -520,12 +524,12 @@ class GetKeyValueResponse(google.protobuf.message.Message): *, kv: global___KeyValueEntry | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["kv", b"kv"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["kv", b"kv"]) -> None: ... + def HasField(self, field_name: typing.Literal["kv", b"kv"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["kv", b"kv"]) -> None: ... global___GetKeyValueResponse = GetKeyValueResponse -@typing_extensions.final +@typing.final class TryGetKeyValueRequest(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -536,11 +540,11 @@ class TryGetKeyValueRequest(google.protobuf.message.Message): *, key: builtins.str | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["key", b"key"]) -> None: ... + def ClearField(self, field_name: typing.Literal["key", b"key"]) -> None: ... global___TryGetKeyValueRequest = TryGetKeyValueRequest -@typing_extensions.final +@typing.final class TryGetKeyValueResponse(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -552,12 +556,12 @@ class TryGetKeyValueResponse(google.protobuf.message.Message): *, kv: global___KeyValueEntry | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["kv", b"kv"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["kv", b"kv"]) -> None: ... + def HasField(self, field_name: typing.Literal["kv", b"kv"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["kv", b"kv"]) -> None: ... global___TryGetKeyValueResponse = TryGetKeyValueResponse -@typing_extensions.final +@typing.final class GetKeyValueDirRequest(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -568,11 +572,11 @@ class GetKeyValueDirRequest(google.protobuf.message.Message): *, directory_key: builtins.str | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["directory_key", b"directory_key"]) -> None: ... + def ClearField(self, field_name: typing.Literal["directory_key", b"directory_key"]) -> None: ... global___GetKeyValueDirRequest = GetKeyValueDirRequest -@typing_extensions.final +@typing.final class GetKeyValueDirResponse(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -587,11 +591,11 @@ class GetKeyValueDirResponse(google.protobuf.message.Message): directory_key: builtins.str | None = ..., kv: collections.abc.Iterable[global___KeyValueEntry] | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["directory_key", b"directory_key", "kv", b"kv"]) -> None: ... + def ClearField(self, field_name: typing.Literal["directory_key", b"directory_key", "kv", b"kv"]) -> None: ... global___GetKeyValueDirResponse = GetKeyValueDirResponse -@typing_extensions.final +@typing.final class DeleteKeyValueRequest(google.protobuf.message.Message): """Request and response messages for deleting configuration key-value data. When is_directory is true, delete key-values recursively under `key`. @@ -609,11 +613,11 @@ class DeleteKeyValueRequest(google.protobuf.message.Message): key: builtins.str | None = ..., is_directory: builtins.bool | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["is_directory", b"is_directory", "key", b"key"]) -> None: ... + def ClearField(self, field_name: typing.Literal["is_directory", b"is_directory", "key", b"key"]) -> None: ... global___DeleteKeyValueRequest = DeleteKeyValueRequest -@typing_extensions.final +@typing.final class DeleteKeyValueResponse(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -623,7 +627,7 @@ class DeleteKeyValueResponse(google.protobuf.message.Message): global___DeleteKeyValueResponse = DeleteKeyValueResponse -@typing_extensions.final +@typing.final class BarrierRequest(google.protobuf.message.Message): """Request and response messages for generic sync barriers.""" @@ -640,9 +644,11 @@ class BarrierRequest(google.protobuf.message.Message): """Denotes list of tasks that will wait for the barrier. If unspecified, it implies that the entire cluster is participating in the barrier. """ + @property def source_task(self) -> global___CoordinatedTask: """Task that is making the request.""" + def __init__( self, *, @@ -651,12 +657,12 @@ class BarrierRequest(google.protobuf.message.Message): tasks: collections.abc.Iterable[global___CoordinatedTask] | None = ..., source_task: global___CoordinatedTask | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["source_task", b"source_task"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["barrier_id", b"barrier_id", "barrier_timeout_in_ms", b"barrier_timeout_in_ms", "source_task", b"source_task", "tasks", b"tasks"]) -> None: ... + def HasField(self, field_name: typing.Literal["source_task", b"source_task"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["barrier_id", b"barrier_id", "barrier_timeout_in_ms", b"barrier_timeout_in_ms", "source_task", b"source_task", "tasks", b"tasks"]) -> None: ... global___BarrierRequest = BarrierRequest -@typing_extensions.final +@typing.final class BarrierResponse(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -666,7 +672,7 @@ class BarrierResponse(google.protobuf.message.Message): global___BarrierResponse = BarrierResponse -@typing_extensions.final +@typing.final class CancelBarrierRequest(google.protobuf.message.Message): """Request and response messages for cancelling generic sync barriers.""" @@ -678,18 +684,19 @@ class CancelBarrierRequest(google.protobuf.message.Message): @property def source_task(self) -> global___CoordinatedTask: """Task that is making the request.""" + def __init__( self, *, barrier_id: builtins.str | None = ..., source_task: global___CoordinatedTask | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["source_task", b"source_task"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["barrier_id", b"barrier_id", "source_task", b"source_task"]) -> None: ... + def HasField(self, field_name: typing.Literal["source_task", b"source_task"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["barrier_id", b"barrier_id", "source_task", b"source_task"]) -> None: ... global___CancelBarrierRequest = CancelBarrierRequest -@typing_extensions.final +@typing.final class CancelBarrierResponse(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor diff --git a/stubs/tensorflow/tensorflow/tsl/protobuf/distributed_runtime_payloads_pb2.pyi b/stubs/tensorflow/tensorflow/tsl/protobuf/distributed_runtime_payloads_pb2.pyi index b27a37c32cc3..57202db5c159 100644 --- a/stubs/tensorflow/tensorflow/tsl/protobuf/distributed_runtime_payloads_pb2.pyi +++ b/stubs/tensorflow/tensorflow/tsl/protobuf/distributed_runtime_payloads_pb2.pyi @@ -2,9 +2,10 @@ @generated by mypy-protobuf. Do not edit manually! isort:skip_file """ + import builtins import collections.abc -import typing as typing_extensions +import typing import google.protobuf.descriptor import google.protobuf.internal.containers @@ -12,7 +13,7 @@ import google.protobuf.message DESCRIPTOR: google.protobuf.descriptor.FileDescriptor -@typing_extensions.final +@typing.final class GrpcPayloadContainer(google.protobuf.message.Message): """Used to serialize and transmit tensorflow::Status payloads through grpc::Status `error_details` since grpc::Status lacks payload API. @@ -21,7 +22,7 @@ class GrpcPayloadContainer(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor - @typing_extensions.final + @typing.final class PayloadsEntry(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -35,7 +36,7 @@ class GrpcPayloadContainer(google.protobuf.message.Message): key: builtins.str | None = ..., value: builtins.bytes | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["key", b"key", "value", b"value"]) -> None: ... + def ClearField(self, field_name: typing.Literal["key", b"key", "value", b"value"]) -> None: ... PAYLOADS_FIELD_NUMBER: builtins.int @property @@ -45,11 +46,11 @@ class GrpcPayloadContainer(google.protobuf.message.Message): *, payloads: collections.abc.Mapping[builtins.str, builtins.bytes] | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["payloads", b"payloads"]) -> None: ... + def ClearField(self, field_name: typing.Literal["payloads", b"payloads"]) -> None: ... global___GrpcPayloadContainer = GrpcPayloadContainer -@typing_extensions.final +@typing.final class GrpcPayloadsLost(google.protobuf.message.Message): """If included as a payload, this message flags the Status to have lost payloads during the GRPC transmission. @@ -64,7 +65,7 @@ class GrpcPayloadsLost(google.protobuf.message.Message): global___GrpcPayloadsLost = GrpcPayloadsLost -@typing_extensions.final +@typing.final class WorkerPossiblyRestarted(google.protobuf.message.Message): """If included as a payload, this message flags the Status to be a possible outcome of a worker restart. diff --git a/stubs/tensorflow/tensorflow/tsl/protobuf/dnn_pb2.pyi b/stubs/tensorflow/tensorflow/tsl/protobuf/dnn_pb2.pyi index 34faf347349c..13b1abf8822e 100644 --- a/stubs/tensorflow/tensorflow/tsl/protobuf/dnn_pb2.pyi +++ b/stubs/tensorflow/tensorflow/tsl/protobuf/dnn_pb2.pyi @@ -2,6 +2,7 @@ @generated by mypy-protobuf. Do not edit manually! isort:skip_file LINT: LEGACY_NAMES""" + import builtins import collections.abc import sys @@ -250,7 +251,7 @@ BACKWARD_DATA: ConvolutionKind.ValueType # 3 FORWARD_BIAS_ACTIVATION: ConvolutionKind.ValueType # 4 global___ConvolutionKind = ConvolutionKind -@typing_extensions.final +@typing.final class TensorDescriptorProto(google.protobuf.message.Message): """Generic tensor representation.""" @@ -260,11 +261,11 @@ class TensorDescriptorProto(google.protobuf.message.Message): DATA_TYPE_FIELD_NUMBER: builtins.int DATA_LAYOUT_FIELD_NUMBER: builtins.int FILTER_LAYOUT_FIELD_NUMBER: builtins.int - @property - def dimensions(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.int]: ... data_type: global___DataType.ValueType data_layout: global___DataLayout.ValueType filter_layout: global___FilterLayout.ValueType + @property + def dimensions(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.int]: ... def __init__( self, *, @@ -273,13 +274,13 @@ class TensorDescriptorProto(google.protobuf.message.Message): data_layout: global___DataLayout.ValueType | None = ..., filter_layout: global___FilterLayout.ValueType | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["data_layout", b"data_layout", "filter_layout", b"filter_layout", "layout_oneof", b"layout_oneof"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["data_layout", b"data_layout", "data_type", b"data_type", "dimensions", b"dimensions", "filter_layout", b"filter_layout", "layout_oneof", b"layout_oneof"]) -> None: ... - def WhichOneof(self, oneof_group: typing_extensions.Literal["layout_oneof", b"layout_oneof"]) -> typing_extensions.Literal["data_layout", "filter_layout"] | None: ... + def HasField(self, field_name: typing.Literal["data_layout", b"data_layout", "filter_layout", b"filter_layout", "layout_oneof", b"layout_oneof"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["data_layout", b"data_layout", "data_type", b"data_type", "dimensions", b"dimensions", "filter_layout", b"filter_layout", "layout_oneof", b"layout_oneof"]) -> None: ... + def WhichOneof(self, oneof_group: typing.Literal["layout_oneof", b"layout_oneof"]) -> typing.Literal["data_layout", "filter_layout"] | None: ... global___TensorDescriptorProto = TensorDescriptorProto -@typing_extensions.final +@typing.final class AlgorithmProto(google.protobuf.message.Message): """Generic algorithm representation.""" @@ -304,7 +305,7 @@ class AlgorithmProto(google.protobuf.message.Message): See cuDNN's documentation for CUDNN_TENSOR_OP_MATH. """ - @typing_extensions.final + @typing.final class TuningKnobsEntry(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -318,7 +319,7 @@ class AlgorithmProto(google.protobuf.message.Message): key: builtins.int | None = ..., value: builtins.int | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["key", b"key", "value", b"value"]) -> None: ... + def ClearField(self, field_name: typing.Literal["key", b"key", "value", b"value"]) -> None: ... ALGO_ID_FIELD_NUMBER: builtins.int MATH_TYPE_FIELD_NUMBER: builtins.int @@ -327,8 +328,6 @@ class AlgorithmProto(google.protobuf.message.Message): WORKSPACE_SIZE_FIELD_NUMBER: builtins.int algo_id: builtins.int math_type: global___AlgorithmProto.MathType.ValueType - @property - def tuning_knobs(self) -> google.protobuf.internal.containers.ScalarMap[builtins.int, builtins.int]: ... is_cudnn_frontend: builtins.bool """Legacy algorithm enums and cuDNN Frontend engine numbers need to coexist in the same proto medium-term, until we can be confident of no longer needing @@ -336,6 +335,8 @@ class AlgorithmProto(google.protobuf.message.Message): stop producing legacy algorithm enums and remove this field. """ @property + def tuning_knobs(self) -> google.protobuf.internal.containers.ScalarMap[builtins.int, builtins.int]: ... + @property def workspace_size(self) -> google.protobuf.wrappers_pb2.UInt64Value: """For ROCm only, it's impossible to re-query the required workspace size after running the algorithm search, so we must store the workspace size @@ -347,6 +348,7 @@ class AlgorithmProto(google.protobuf.message.Message): 0 workspace size from unknown workspace size in an old message, so this is a message field. """ + def __init__( self, *, @@ -356,12 +358,12 @@ class AlgorithmProto(google.protobuf.message.Message): is_cudnn_frontend: builtins.bool | None = ..., workspace_size: google.protobuf.wrappers_pb2.UInt64Value | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["workspace_size", b"workspace_size"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["algo_id", b"algo_id", "is_cudnn_frontend", b"is_cudnn_frontend", "math_type", b"math_type", "tuning_knobs", b"tuning_knobs", "workspace_size", b"workspace_size"]) -> None: ... + def HasField(self, field_name: typing.Literal["workspace_size", b"workspace_size"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["algo_id", b"algo_id", "is_cudnn_frontend", b"is_cudnn_frontend", "math_type", b"math_type", "tuning_knobs", b"tuning_knobs", "workspace_size", b"workspace_size"]) -> None: ... global___AlgorithmProto = AlgorithmProto -@typing_extensions.final +@typing.final class AlgorithmConfigProto(google.protobuf.message.Message): """Proto definition of AlgorithmConfig in "dnn.h". TODO(ruochengw): After cl/380702564 is submitted, add support for algorithm @@ -373,11 +375,11 @@ class AlgorithmConfigProto(google.protobuf.message.Message): ALGORITHM_FIELD_NUMBER: builtins.int ALGORITHM_NO_SCRATCH_FIELD_NUMBER: builtins.int SCRATCH_SIZE_FIELD_NUMBER: builtins.int + scratch_size: builtins.int @property def algorithm(self) -> global___AlgorithmProto: ... @property def algorithm_no_scratch(self) -> global___AlgorithmProto: ... - scratch_size: builtins.int def __init__( self, *, @@ -385,18 +387,18 @@ class AlgorithmConfigProto(google.protobuf.message.Message): algorithm_no_scratch: global___AlgorithmProto | None = ..., scratch_size: builtins.int | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["algorithm", b"algorithm", "algorithm_no_scratch", b"algorithm_no_scratch", "optional_algorithm", b"optional_algorithm", "optional_algorithm_no_scratch", b"optional_algorithm_no_scratch", "optional_scratch_size", b"optional_scratch_size", "scratch_size", b"scratch_size"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["algorithm", b"algorithm", "algorithm_no_scratch", b"algorithm_no_scratch", "optional_algorithm", b"optional_algorithm", "optional_algorithm_no_scratch", b"optional_algorithm_no_scratch", "optional_scratch_size", b"optional_scratch_size", "scratch_size", b"scratch_size"]) -> None: ... + def HasField(self, field_name: typing.Literal["algorithm", b"algorithm", "algorithm_no_scratch", b"algorithm_no_scratch", "optional_algorithm", b"optional_algorithm", "optional_algorithm_no_scratch", b"optional_algorithm_no_scratch", "optional_scratch_size", b"optional_scratch_size", "scratch_size", b"scratch_size"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["algorithm", b"algorithm", "algorithm_no_scratch", b"algorithm_no_scratch", "optional_algorithm", b"optional_algorithm", "optional_algorithm_no_scratch", b"optional_algorithm_no_scratch", "optional_scratch_size", b"optional_scratch_size", "scratch_size", b"scratch_size"]) -> None: ... @typing.overload - def WhichOneof(self, oneof_group: typing_extensions.Literal["optional_algorithm", b"optional_algorithm"]) -> typing_extensions.Literal["algorithm"] | None: ... + def WhichOneof(self, oneof_group: typing.Literal["optional_algorithm", b"optional_algorithm"]) -> typing.Literal["algorithm"] | None: ... @typing.overload - def WhichOneof(self, oneof_group: typing_extensions.Literal["optional_algorithm_no_scratch", b"optional_algorithm_no_scratch"]) -> typing_extensions.Literal["algorithm_no_scratch"] | None: ... + def WhichOneof(self, oneof_group: typing.Literal["optional_algorithm_no_scratch", b"optional_algorithm_no_scratch"]) -> typing.Literal["algorithm_no_scratch"] | None: ... @typing.overload - def WhichOneof(self, oneof_group: typing_extensions.Literal["optional_scratch_size", b"optional_scratch_size"]) -> typing_extensions.Literal["scratch_size"] | None: ... + def WhichOneof(self, oneof_group: typing.Literal["optional_scratch_size", b"optional_scratch_size"]) -> typing.Literal["scratch_size"] | None: ... global___AlgorithmConfigProto = AlgorithmConfigProto -@typing_extensions.final +@typing.final class ConvolutionDescriptorProto(google.protobuf.message.Message): """Convolution-specific parameters.""" @@ -409,12 +411,6 @@ class ConvolutionDescriptorProto(google.protobuf.message.Message): GROUP_COUNT_FIELD_NUMBER: builtins.int CONVOLUTION_MODE_FIELD_NUMBER: builtins.int NAME_FIELD_NUMBER: builtins.int - @property - def paddings(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.int]: ... - @property - def strides(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.int]: ... - @property - def dilations(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.int]: ... compute_mode: global___DataType.ValueType """The "accumulator" type. For example, use F32 as an accumulator for F16 convolutions. @@ -425,6 +421,12 @@ class ConvolutionDescriptorProto(google.protobuf.message.Message): convolution_mode: global___ConvolutionMode.ValueType name: builtins.str """Tensorflow node name, same as in NodeDef, for debugging purposes.""" + @property + def paddings(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.int]: ... + @property + def strides(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.int]: ... + @property + def dilations(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.int]: ... def __init__( self, *, @@ -436,6 +438,6 @@ class ConvolutionDescriptorProto(google.protobuf.message.Message): convolution_mode: global___ConvolutionMode.ValueType | None = ..., name: builtins.str | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["compute_mode", b"compute_mode", "convolution_mode", b"convolution_mode", "dilations", b"dilations", "group_count", b"group_count", "name", b"name", "paddings", b"paddings", "strides", b"strides"]) -> None: ... + def ClearField(self, field_name: typing.Literal["compute_mode", b"compute_mode", "convolution_mode", b"convolution_mode", "dilations", b"dilations", "group_count", b"group_count", "name", b"name", "paddings", b"paddings", "strides", b"strides"]) -> None: ... global___ConvolutionDescriptorProto = ConvolutionDescriptorProto diff --git a/stubs/tensorflow/tensorflow/tsl/protobuf/error_codes_pb2.pyi b/stubs/tensorflow/tensorflow/tsl/protobuf/error_codes_pb2.pyi index 0aa45efaf8cc..3b0b8dcf4b37 100644 --- a/stubs/tensorflow/tensorflow/tsl/protobuf/error_codes_pb2.pyi +++ b/stubs/tensorflow/tensorflow/tsl/protobuf/error_codes_pb2.pyi @@ -4,6 +4,7 @@ isort:skip_file TODO(b/247876220): Change package and java_package once we figure out how to migrate. """ + import builtins import sys import typing diff --git a/stubs/tensorflow/tensorflow/tsl/protobuf/histogram_pb2.pyi b/stubs/tensorflow/tensorflow/tsl/protobuf/histogram_pb2.pyi index 8e1e4be2c7e7..a33728dc47e4 100644 --- a/stubs/tensorflow/tensorflow/tsl/protobuf/histogram_pb2.pyi +++ b/stubs/tensorflow/tensorflow/tsl/protobuf/histogram_pb2.pyi @@ -2,9 +2,10 @@ @generated by mypy-protobuf. Do not edit manually! isort:skip_file """ + import builtins import collections.abc -import typing as typing_extensions +import typing import google.protobuf.descriptor import google.protobuf.internal.containers @@ -12,7 +13,7 @@ import google.protobuf.message DESCRIPTOR: google.protobuf.descriptor.FileDescriptor -@typing_extensions.final +@typing.final class HistogramProto(google.protobuf.message.Message): """Serialization format for histogram module in tsl/lib/histogram/histogram.h @@ -40,6 +41,7 @@ class HistogramProto(google.protobuf.message.Message): i == 0: -DBL_MAX .. bucket_limit(0) i != 0: bucket_limit(i-1) .. bucket_limit(i) """ + @property def bucket(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.float]: ... def __init__( @@ -53,6 +55,6 @@ class HistogramProto(google.protobuf.message.Message): bucket_limit: collections.abc.Iterable[builtins.float] | None = ..., bucket: collections.abc.Iterable[builtins.float] | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["bucket", b"bucket", "bucket_limit", b"bucket_limit", "max", b"max", "min", b"min", "num", b"num", "sum", b"sum", "sum_squares", b"sum_squares"]) -> None: ... + def ClearField(self, field_name: typing.Literal["bucket", b"bucket", "bucket_limit", b"bucket_limit", "max", b"max", "min", b"min", "num", b"num", "sum", b"sum", "sum_squares", b"sum_squares"]) -> None: ... global___HistogramProto = HistogramProto diff --git a/stubs/tensorflow/tensorflow/tsl/protobuf/rpc_options_pb2.pyi b/stubs/tensorflow/tensorflow/tsl/protobuf/rpc_options_pb2.pyi index 0d76b7d2ea65..6e08a2bf99ef 100644 --- a/stubs/tensorflow/tensorflow/tsl/protobuf/rpc_options_pb2.pyi +++ b/stubs/tensorflow/tensorflow/tsl/protobuf/rpc_options_pb2.pyi @@ -2,15 +2,16 @@ @generated by mypy-protobuf. Do not edit manually! isort:skip_file """ + import builtins -import typing as typing_extensions +import typing import google.protobuf.descriptor import google.protobuf.message DESCRIPTOR: google.protobuf.descriptor.FileDescriptor -@typing_extensions.final +@typing.final class RPCOptions(google.protobuf.message.Message): """RPC options for distributed runtime.""" @@ -63,6 +64,6 @@ class RPCOptions(google.protobuf.message.Message): disable_session_connection_sharing: builtins.bool | None = ..., num_channels_per_target: builtins.int | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["cache_rpc_response", b"cache_rpc_response", "compression_algorithm", b"compression_algorithm", "compression_level", b"compression_level", "disable_session_connection_sharing", b"disable_session_connection_sharing", "num_channels_per_target", b"num_channels_per_target", "use_rpc_for_inprocess_master", b"use_rpc_for_inprocess_master"]) -> None: ... + def ClearField(self, field_name: typing.Literal["cache_rpc_response", b"cache_rpc_response", "compression_algorithm", b"compression_algorithm", "compression_level", b"compression_level", "disable_session_connection_sharing", b"disable_session_connection_sharing", "num_channels_per_target", b"num_channels_per_target", "use_rpc_for_inprocess_master", b"use_rpc_for_inprocess_master"]) -> None: ... global___RPCOptions = RPCOptions diff --git a/stubs/tensorflow/tensorflow/tsl/protobuf/test_log_pb2.pyi b/stubs/tensorflow/tensorflow/tsl/protobuf/test_log_pb2.pyi index 48b4f7a5b43c..0e06ea85faa7 100644 --- a/stubs/tensorflow/tensorflow/tsl/protobuf/test_log_pb2.pyi +++ b/stubs/tensorflow/tensorflow/tsl/protobuf/test_log_pb2.pyi @@ -2,6 +2,7 @@ @generated by mypy-protobuf. Do not edit manually! isort:skip_file Protocol messages for describing the results of benchmarks and unit tests.""" + import builtins import collections.abc import sys @@ -21,7 +22,7 @@ else: DESCRIPTOR: google.protobuf.descriptor.FileDescriptor -@typing_extensions.final +@typing.final class EntryValue(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -35,13 +36,13 @@ class EntryValue(google.protobuf.message.Message): double_value: builtins.float | None = ..., string_value: builtins.str | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["double_value", b"double_value", "kind", b"kind", "string_value", b"string_value"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["double_value", b"double_value", "kind", b"kind", "string_value", b"string_value"]) -> None: ... - def WhichOneof(self, oneof_group: typing_extensions.Literal["kind", b"kind"]) -> typing_extensions.Literal["double_value", "string_value"] | None: ... + def HasField(self, field_name: typing.Literal["double_value", b"double_value", "kind", b"kind", "string_value", b"string_value"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["double_value", b"double_value", "kind", b"kind", "string_value", b"string_value"]) -> None: ... + def WhichOneof(self, oneof_group: typing.Literal["kind", b"kind"]) -> typing.Literal["double_value", "string_value"] | None: ... global___EntryValue = EntryValue -@typing_extensions.final +@typing.final class MetricEntry(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -56,9 +57,11 @@ class MetricEntry(google.protobuf.message.Message): @property def min_value(self) -> google.protobuf.wrappers_pb2.DoubleValue: """The minimum acceptable value for the metric if specified""" + @property def max_value(self) -> google.protobuf.wrappers_pb2.DoubleValue: """The maximum acceptable value for the metric if specified""" + def __init__( self, *, @@ -67,12 +70,12 @@ class MetricEntry(google.protobuf.message.Message): min_value: google.protobuf.wrappers_pb2.DoubleValue | None = ..., max_value: google.protobuf.wrappers_pb2.DoubleValue | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["max_value", b"max_value", "min_value", b"min_value"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["max_value", b"max_value", "min_value", b"min_value", "name", b"name", "value", b"value"]) -> None: ... + def HasField(self, field_name: typing.Literal["max_value", b"max_value", "min_value", b"min_value"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["max_value", b"max_value", "min_value", b"min_value", "name", b"name", "value", b"value"]) -> None: ... global___MetricEntry = MetricEntry -@typing_extensions.final +@typing.final class BenchmarkEntry(google.protobuf.message.Message): """Each unit test or benchmark in a test or benchmark run provides some set of information. Here we provide some reasonable keys @@ -85,7 +88,7 @@ class BenchmarkEntry(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor - @typing_extensions.final + @typing.final class ExtrasEntry(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -100,8 +103,8 @@ class BenchmarkEntry(google.protobuf.message.Message): key: builtins.str | None = ..., value: global___EntryValue | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["value", b"value"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["key", b"key", "value", b"value"]) -> None: ... + def HasField(self, field_name: typing.Literal["value", b"value"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["key", b"key", "value", b"value"]) -> None: ... NAME_FIELD_NUMBER: builtins.int ITERS_FIELD_NUMBER: builtins.int @@ -125,11 +128,13 @@ class BenchmarkEntry(google.protobuf.message.Message): @property def extras(self) -> google.protobuf.internal.containers.MessageMap[builtins.str, global___EntryValue]: """Generic map from result key to value.""" + @property def metrics(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___MetricEntry]: """Metric name, value and expected range. This can include accuracy metrics typically used to determine whether the accuracy test has passed """ + def __init__( self, *, @@ -141,11 +146,11 @@ class BenchmarkEntry(google.protobuf.message.Message): extras: collections.abc.Mapping[builtins.str, global___EntryValue] | None = ..., metrics: collections.abc.Iterable[global___MetricEntry] | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["cpu_time", b"cpu_time", "extras", b"extras", "iters", b"iters", "metrics", b"metrics", "name", b"name", "throughput", b"throughput", "wall_time", b"wall_time"]) -> None: ... + def ClearField(self, field_name: typing.Literal["cpu_time", b"cpu_time", "extras", b"extras", "iters", b"iters", "metrics", b"metrics", "name", b"name", "throughput", b"throughput", "wall_time", b"wall_time"]) -> None: ... global___BenchmarkEntry = BenchmarkEntry -@typing_extensions.final +@typing.final class BenchmarkEntries(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -157,11 +162,11 @@ class BenchmarkEntries(google.protobuf.message.Message): *, entry: collections.abc.Iterable[global___BenchmarkEntry] | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["entry", b"entry"]) -> None: ... + def ClearField(self, field_name: typing.Literal["entry", b"entry"]) -> None: ... global___BenchmarkEntries = BenchmarkEntries -@typing_extensions.final +@typing.final class BuildConfiguration(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -173,9 +178,11 @@ class BuildConfiguration(google.protobuf.message.Message): @property def cc_flags(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.str]: """CC compiler flags, if known""" + @property def opts(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.str]: """Bazel compilation options, if known""" + def __init__( self, *, @@ -183,11 +190,11 @@ class BuildConfiguration(google.protobuf.message.Message): cc_flags: collections.abc.Iterable[builtins.str] | None = ..., opts: collections.abc.Iterable[builtins.str] | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["cc_flags", b"cc_flags", "mode", b"mode", "opts", b"opts"]) -> None: ... + def ClearField(self, field_name: typing.Literal["cc_flags", b"cc_flags", "mode", b"mode", "opts", b"opts"]) -> None: ... global___BuildConfiguration = BuildConfiguration -@typing_extensions.final +@typing.final class CommitId(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -212,17 +219,17 @@ class CommitId(google.protobuf.message.Message): snapshot: builtins.str | None = ..., pending_changelist: builtins.int | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["changelist", b"changelist", "hash", b"hash", "kind", b"kind"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["changelist", b"changelist", "hash", b"hash", "kind", b"kind", "pending_changelist", b"pending_changelist", "snapshot", b"snapshot"]) -> None: ... - def WhichOneof(self, oneof_group: typing_extensions.Literal["kind", b"kind"]) -> typing_extensions.Literal["changelist", "hash"] | None: ... + def HasField(self, field_name: typing.Literal["changelist", b"changelist", "hash", b"hash", "kind", b"kind"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["changelist", b"changelist", "hash", b"hash", "kind", b"kind", "pending_changelist", b"pending_changelist", "snapshot", b"snapshot"]) -> None: ... + def WhichOneof(self, oneof_group: typing.Literal["kind", b"kind"]) -> typing.Literal["changelist", "hash"] | None: ... global___CommitId = CommitId -@typing_extensions.final +@typing.final class CPUInfo(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor - @typing_extensions.final + @typing.final class CacheSizeEntry(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -236,7 +243,7 @@ class CPUInfo(google.protobuf.message.Message): key: builtins.str | None = ..., value: builtins.int | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["key", b"key", "value", b"value"]) -> None: ... + def ClearField(self, field_name: typing.Literal["key", b"key", "value", b"value"]) -> None: ... NUM_CORES_FIELD_NUMBER: builtins.int NUM_CORES_ALLOWED_FIELD_NUMBER: builtins.int @@ -259,6 +266,7 @@ class CPUInfo(google.protobuf.message.Message): @property def cache_size(self) -> google.protobuf.internal.containers.ScalarMap[builtins.str, builtins.int]: """Cache sizes (in bytes), e.g. "L2": 262144 (for 256KB)""" + def __init__( self, *, @@ -269,11 +277,11 @@ class CPUInfo(google.protobuf.message.Message): cpu_governor: builtins.str | None = ..., cache_size: collections.abc.Mapping[builtins.str, builtins.int] | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["cache_size", b"cache_size", "cpu_governor", b"cpu_governor", "cpu_info", b"cpu_info", "mhz_per_cpu", b"mhz_per_cpu", "num_cores", b"num_cores", "num_cores_allowed", b"num_cores_allowed"]) -> None: ... + def ClearField(self, field_name: typing.Literal["cache_size", b"cache_size", "cpu_governor", b"cpu_governor", "cpu_info", b"cpu_info", "mhz_per_cpu", b"mhz_per_cpu", "num_cores", b"num_cores", "num_cores_allowed", b"num_cores_allowed"]) -> None: ... global___CPUInfo = CPUInfo -@typing_extensions.final +@typing.final class MemoryInfo(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -289,11 +297,11 @@ class MemoryInfo(google.protobuf.message.Message): total: builtins.int | None = ..., available: builtins.int | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["available", b"available", "total", b"total"]) -> None: ... + def ClearField(self, field_name: typing.Literal["available", b"available", "total", b"total"]) -> None: ... global___MemoryInfo = MemoryInfo -@typing_extensions.final +@typing.final class GPUInfo(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -313,11 +321,11 @@ class GPUInfo(google.protobuf.message.Message): uuid: builtins.str | None = ..., bus_id: builtins.str | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["bus_id", b"bus_id", "model", b"model", "uuid", b"uuid"]) -> None: ... + def ClearField(self, field_name: typing.Literal["bus_id", b"bus_id", "model", b"model", "uuid", b"uuid"]) -> None: ... global___GPUInfo = GPUInfo -@typing_extensions.final +@typing.final class PlatformInfo(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -349,11 +357,11 @@ class PlatformInfo(google.protobuf.message.Message): system: builtins.str | None = ..., version: builtins.str | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["bits", b"bits", "linkage", b"linkage", "machine", b"machine", "release", b"release", "system", b"system", "version", b"version"]) -> None: ... + def ClearField(self, field_name: typing.Literal["bits", b"bits", "linkage", b"linkage", "machine", b"machine", "release", b"release", "system", b"system", "version", b"version"]) -> None: ... global___PlatformInfo = PlatformInfo -@typing_extensions.final +@typing.final class AvailableDeviceInfo(google.protobuf.message.Message): """Matches DeviceAttributes""" @@ -379,11 +387,11 @@ class AvailableDeviceInfo(google.protobuf.message.Message): memory_limit: builtins.int | None = ..., physical_description: builtins.str | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["memory_limit", b"memory_limit", "name", b"name", "physical_description", b"physical_description", "type", b"type"]) -> None: ... + def ClearField(self, field_name: typing.Literal["memory_limit", b"memory_limit", "name", b"name", "physical_description", b"physical_description", "type", b"type"]) -> None: ... global___AvailableDeviceInfo = AvailableDeviceInfo -@typing_extensions.final +@typing.final class MachineConfiguration(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -401,15 +409,19 @@ class MachineConfiguration(google.protobuf.message.Message): @property def platform_info(self) -> global___PlatformInfo: """Additional platform information.""" + @property def cpu_info(self) -> global___CPUInfo: """CPU Information.""" + @property def device_info(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[google.protobuf.any_pb2.Any]: """Other devices that are attached and relevant (e.g. GPUInfo).""" + @property def available_device_info(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___AvailableDeviceInfo]: """Devices accessible to the test (e.g. as given by list_local_devices).""" + @property def memory_info(self) -> global___MemoryInfo: ... def __init__( @@ -423,18 +435,18 @@ class MachineConfiguration(google.protobuf.message.Message): available_device_info: collections.abc.Iterable[global___AvailableDeviceInfo] | None = ..., memory_info: global___MemoryInfo | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["cpu_info", b"cpu_info", "memory_info", b"memory_info", "platform_info", b"platform_info"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["available_device_info", b"available_device_info", "cpu_info", b"cpu_info", "device_info", b"device_info", "hostname", b"hostname", "memory_info", b"memory_info", "platform_info", b"platform_info", "serial_identifier", b"serial_identifier"]) -> None: ... + def HasField(self, field_name: typing.Literal["cpu_info", b"cpu_info", "memory_info", b"memory_info", "platform_info", b"platform_info"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["available_device_info", b"available_device_info", "cpu_info", b"cpu_info", "device_info", b"device_info", "hostname", b"hostname", "memory_info", b"memory_info", "platform_info", b"platform_info", "serial_identifier", b"serial_identifier"]) -> None: ... global___MachineConfiguration = MachineConfiguration -@typing_extensions.final +@typing.final class RunConfiguration(google.protobuf.message.Message): """Run-specific items such as arguments to the test / benchmark.""" DESCRIPTOR: google.protobuf.descriptor.Descriptor - @typing_extensions.final + @typing.final class EnvVarsEntry(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @@ -448,7 +460,7 @@ class RunConfiguration(google.protobuf.message.Message): key: builtins.str | None = ..., value: builtins.str | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["key", b"key", "value", b"value"]) -> None: ... + def ClearField(self, field_name: typing.Literal["key", b"key", "value", b"value"]) -> None: ... ARGUMENT_FIELD_NUMBER: builtins.int ENV_VARS_FIELD_NUMBER: builtins.int @@ -457,17 +469,18 @@ class RunConfiguration(google.protobuf.message.Message): @property def env_vars(self) -> google.protobuf.internal.containers.ScalarMap[builtins.str, builtins.str]: """Environment variables used to run the test/benchmark.""" + def __init__( self, *, argument: collections.abc.Iterable[builtins.str] | None = ..., env_vars: collections.abc.Mapping[builtins.str, builtins.str] | None = ..., ) -> None: ... - def ClearField(self, field_name: typing_extensions.Literal["argument", b"argument", "env_vars", b"env_vars"]) -> None: ... + def ClearField(self, field_name: typing.Literal["argument", b"argument", "env_vars", b"env_vars"]) -> None: ... global___RunConfiguration = RunConfiguration -@typing_extensions.final +@typing.final class TestResults(google.protobuf.message.Message): """The output of one benchmark / test run. Each run contains a list of tests or benchmarks, stored as BenchmarkEntry messages. @@ -521,25 +534,10 @@ class TestResults(google.protobuf.message.Message): """The target of the run, e.g.: //tensorflow/core:kernels_adjust_contrast_op_benchmark_test """ - @property - def entries(self) -> global___BenchmarkEntries: - """The list of tests or benchmarks in this run.""" - @property - def build_configuration(self) -> global___BuildConfiguration: - """The configuration of the build (compiled opt? with cuda? any copts?)""" - @property - def commit_id(self) -> global___CommitId: - """The commit id (git hash or changelist)""" start_time: builtins.int """The time the run started (in seconds of UTC time since Unix epoch)""" run_time: builtins.float """The amount of time the total run took (wall time in seconds)""" - @property - def machine_configuration(self) -> global___MachineConfiguration: - """Machine-specific parameters (Platform and CPU info)""" - @property - def run_configuration(self) -> global___RunConfiguration: - """Run-specific parameters (arguments, etc)""" name: builtins.str """Benchmark target identifier.""" benchmark_type: global___TestResults.BenchmarkType.ValueType @@ -554,6 +552,26 @@ class TestResults(google.protobuf.message.Message): """TensorFlow version this benchmark runs against. This can be either set to full version or just the major version. """ + @property + def entries(self) -> global___BenchmarkEntries: + """The list of tests or benchmarks in this run.""" + + @property + def build_configuration(self) -> global___BuildConfiguration: + """The configuration of the build (compiled opt? with cuda? any copts?)""" + + @property + def commit_id(self) -> global___CommitId: + """The commit id (git hash or changelist)""" + + @property + def machine_configuration(self) -> global___MachineConfiguration: + """Machine-specific parameters (Platform and CPU info)""" + + @property + def run_configuration(self) -> global___RunConfiguration: + """Run-specific parameters (arguments, etc)""" + def __init__( self, *, @@ -570,7 +588,7 @@ class TestResults(google.protobuf.message.Message): run_mode: builtins.str | None = ..., tf_version: builtins.str | None = ..., ) -> None: ... - def HasField(self, field_name: typing_extensions.Literal["build_configuration", b"build_configuration", "commit_id", b"commit_id", "entries", b"entries", "machine_configuration", b"machine_configuration", "run_configuration", b"run_configuration"]) -> builtins.bool: ... - def ClearField(self, field_name: typing_extensions.Literal["benchmark_type", b"benchmark_type", "build_configuration", b"build_configuration", "commit_id", b"commit_id", "entries", b"entries", "machine_configuration", b"machine_configuration", "name", b"name", "run_configuration", b"run_configuration", "run_mode", b"run_mode", "run_time", b"run_time", "start_time", b"start_time", "target", b"target", "tf_version", b"tf_version"]) -> None: ... + def HasField(self, field_name: typing.Literal["build_configuration", b"build_configuration", "commit_id", b"commit_id", "entries", b"entries", "machine_configuration", b"machine_configuration", "run_configuration", b"run_configuration"]) -> builtins.bool: ... + def ClearField(self, field_name: typing.Literal["benchmark_type", b"benchmark_type", "build_configuration", b"build_configuration", "commit_id", b"commit_id", "entries", b"entries", "machine_configuration", b"machine_configuration", "name", b"name", "run_configuration", b"run_configuration", "run_mode", b"run_mode", "run_time", b"run_time", "start_time", b"start_time", "target", b"target", "tf_version", b"tf_version"]) -> None: ... global___TestResults = TestResults