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[6/6] Arm(R) Ethos(TM)-U NPU codegen integration with tvmc (#8854)
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* Add Arm(R) Ethos(TM)-U codegen support on tvmc

* Include `ethos-u` as a new target for tvmc
* Adds testing for the new target

Co-authored-by: Manupa Karunaratne <[email protected]>

* Add Arm(R) Ethos(TM)-U codegen support on tvmc

* move partition_for_ethosu from tvm.relay.backend.contrib.ethosu
  to tvm.relay.op.contrib.ethosu

* lazy load ethos-u-vela dependencies and show an appropriate error
  message in case the dependency is not present

* Adjust test cases

Co-authored-by: Leandro Nunes <[email protected]>

* Add Arm(R) Ethos(TM)-U codegen support on tvmc

* add missing import

Change-Id: Ieefa0ee6e86bdc09ff93fcc632ed003b5f3f3a99

Co-authored-by: Manupa Karunaratne <[email protected]>
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leandron and manupak authored Sep 30, 2021
1 parent 3d64783 commit dda75fe
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Showing 9 changed files with 128 additions and 62 deletions.
5 changes: 5 additions & 0 deletions python/tvm/driver/tvmc/composite_target.py
Original file line number Diff line number Diff line change
Expand Up @@ -25,6 +25,7 @@
from tvm.relay.op.contrib.arm_compute_lib import partition_for_arm_compute_lib
from tvm.relay.op.contrib.ethosn import partition_for_ethosn
from tvm.relay.op.contrib.cmsisnn import partition_for_cmsisnn
from tvm.relay.op.contrib.ethosu import partition_for_ethosu
from tvm.relay.op.contrib.bnns import partition_for_bnns
from tvm.relay.op.contrib.vitis_ai import partition_for_vitis_ai

Expand Down Expand Up @@ -58,6 +59,10 @@
"config_key": "relay.ext.ethos-n.options",
"pass_pipeline": partition_for_ethosn,
},
"ethos-u": {
"config_key": "relay.ext.ethosu.options",
"pass_pipeline": partition_for_ethosu,
},
"bnns": {
"config_key": None,
"pass_pipeline": partition_for_bnns,
Expand Down
1 change: 0 additions & 1 deletion python/tvm/relay/backend/contrib/ethosu/__init__.py
Original file line number Diff line number Diff line change
Expand Up @@ -22,4 +22,3 @@
from . import codegen
from . import vela_api
from . import tir_to_cs_translator
from .util import partition_for_ethosu
39 changes: 1 addition & 38 deletions python/tvm/relay/backend/contrib/ethosu/util.py
Original file line number Diff line number Diff line change
Expand Up @@ -23,13 +23,11 @@

from inspect import signature
from enum import Enum
from typing import Union, Tuple, Dict, Optional
from typing import Union, Tuple
import numpy as np # type: ignore

import tvm # type: ignore
from tvm import relay
from tvm.relay.build_module import bind_params_by_name # type: ignore
from tvm.relay.backend.contrib.ethosu import preprocess # type: ignore


class QConv2DArgs(Enum):
Expand Down Expand Up @@ -145,41 +143,6 @@ def get_accelerator_config():
return compiler_attrs.accelerator_config


# pylint: disable=unused-argument
def partition_for_ethosu(
mod: tvm.ir.IRModule, params: Optional[Dict[str, tvm.runtime.NDArray]] = None, **opts
):
"""This helper function partition the relay graph as produced by the
relay frontend for a given model into external functions
to be presented to the codegen.
Parameters
----------
mod : tvm.ir.IRModule
The IRModule that gets generated from a relay frontend
params : Optional[Dict[str, tvm.runtime.NDArray]]
Constant input parameters.
Returns
-------
mod : IRModule
The partitioned IRModule with external global functions
"""
if params:
mod["main"] = bind_params_by_name(mod["main"], params)

pattern = relay.op.contrib.get_pattern_table("ethosu")
mod = relay.transform.InferType()(mod)
mod = relay.transform.MergeComposite(pattern)(mod)
mod = relay.transform.AnnotateTarget("ethosu")(mod)
mod = relay.transform.MergeCompilerRegions()(mod)
mod = relay.transform.InferType()(mod)
mod = relay.transform.PartitionGraph()(mod)
mod = relay.transform.InferType()(mod)
mod = preprocess.preprocess_ext_io()(mod)
return mod


def get_arg_count(func):
"""Helper function to get the number of
arguments in a python function"""
Expand Down
82 changes: 76 additions & 6 deletions python/tvm/relay/op/contrib/ethosu.py
Original file line number Diff line number Diff line change
Expand Up @@ -14,19 +14,51 @@
# KIND, either express or implied. See the License for the
# specific language governing permissions and limitations
# under the License.
# pylint: disable=ungrouped-imports
"""Arm(R) Ethos(TM)-U NPU supported operators."""
from typing import List, Tuple, Callable
import functools

from typing import Dict, List, Tuple, Callable, Optional
import numpy as np # type: ignore

import tvm # type: ignore
from tvm import relay
from tvm.relay.expr import Constant # type: ignore
from tvm.relay.op.contrib.register import register_pattern_table # type: ignore
from tvm.relay.dataflow_pattern import wildcard, is_op, is_constant # type: ignore
from tvm.relay.backend.contrib.ethosu.util import QConv2DArgs # type: ignore
from tvm.relay.backend.contrib.ethosu.util import BiasAddArgs
from tvm.relay.backend.contrib.ethosu.util import RequantArgs
from tvm.relay.backend.contrib.ethosu.util import get_dim_value
from ethosu.vela import api as vapi # type: ignore
from tvm.relay.build_module import bind_params_by_name # type: ignore

try:
# As ethos-u-vela package is an optional TVM dependency, we want to lazy load it
# and check whether it is installed or not.
#
# In order to show the appropriate error messages when we try to invoke code that
# rely on imports from ethos-u-vela, we protect them with the decorator @requires_vela
# implemented below.
from ethosu.vela import api as vapi # type: ignore
from tvm.relay.backend.contrib.ethosu import preprocess
from tvm.relay.backend.contrib.ethosu.util import QConv2DArgs # type: ignore
from tvm.relay.backend.contrib.ethosu.util import BiasAddArgs
from tvm.relay.backend.contrib.ethosu.util import RequantArgs
from tvm.relay.backend.contrib.ethosu.util import get_dim_value
except ImportError:
vapi = None


def requires_vela(func):
"""Decorator to check whether we have the required dependency ethos-u-vela
installed as a python package"""

@functools.wraps(func)
def wrapper(*args, **kwargs):
if not vapi:
raise ImportError(
"The 'ethos-u-vela' python package is required for the Arm(R) Ethos(TM)-U NPU "
"backend. Please install the dependency using your Python package manager."
) from None
return func(*args, **kwargs)

return wrapper


class TensorParams:
Expand All @@ -36,6 +68,7 @@ class TensorParams:
for the creation of tensors in Vela.
"""

@requires_vela
def __init__(self, tensor, layout=None, scale=None, zero_point=None):
self.tensor = tensor
if isinstance(tensor, Constant):
Expand Down Expand Up @@ -148,6 +181,7 @@ class QnnConv2DParams:
padding_bounds = [31, 31, 32, 32]
activation_map = {"clip": "CLIP"}

@requires_vela
def __init__(self, func_body: tvm.relay.Function):
activation = None
if str(func_body.op) in self.activation_map.keys():
Expand Down Expand Up @@ -247,3 +281,39 @@ def pattern_table() -> List[Tuple[str, tvm.relay.dataflow_pattern.DFPattern, Cal
lambda pat: QnnConv2DParams(pat).is_valid(),
)
]


# pylint: disable=unused-argument
@requires_vela
def partition_for_ethosu(
mod: tvm.ir.IRModule, params: Optional[Dict[str, tvm.runtime.NDArray]] = None, **opts
):
"""This helper function partition the relay graph as produced by the
relay frontend for a given model into external functions
to be presented to the codegen.
Parameters
----------
mod : tvm.ir.IRModule
The IRModule that gets generated from a relay frontend
params : Optional[Dict[str, tvm.runtime.NDArray]]
Constant input parameters.
Returns
-------
mod : IRModule
The partitioned IRModule with external global functions
"""
if params:
mod["main"] = bind_params_by_name(mod["main"], params)

pattern = relay.op.contrib.get_pattern_table("ethosu")
mod = relay.transform.InferType()(mod)
mod = relay.transform.MergeComposite(pattern)(mod)
mod = relay.transform.AnnotateTarget("ethosu")(mod)
mod = relay.transform.MergeCompilerRegions()(mod)
mod = relay.transform.InferType()(mod)
mod = relay.transform.PartitionGraph()(mod)
mod = relay.transform.InferType()(mod)
mod = preprocess.preprocess_ext_io()(mod)
return mod
3 changes: 2 additions & 1 deletion tests/python/contrib/test_ethosu/test_codegen.py
Original file line number Diff line number Diff line change
Expand Up @@ -27,6 +27,7 @@
from tvm import relay
from tvm.relay.backend.contrib import ethosu
from tvm.relay.backend.contrib.ethosu import util
from tvm.relay.op.contrib.ethosu import partition_for_ethosu
from tests.python.relay.aot.aot_test_utils import generate_ref_data

from . import relay_ir_builder
Expand Down Expand Up @@ -139,7 +140,7 @@ def create_graph_activation(input_tensor_name, input_tensor_shape, input_tensor_
for test_case in test_cases:
relay_module, conv_params = test_case[0](*test_case[1])
input_tensor, input_shape, input_dtype = test_case[1]
mod = ethosu.partition_for_ethosu(relay_module)
mod = partition_for_ethosu(relay_module)

# Generate reference data
in_min, in_max = util.get_range_for_dtype_str(input_dtype)
Expand Down
4 changes: 2 additions & 2 deletions tests/python/contrib/test_ethosu/test_legalize.py
Original file line number Diff line number Diff line change
Expand Up @@ -294,7 +294,7 @@ def verify_linear(ext_func, conv2d_params):
]
for test_case in test_cases:
mod, conv_params = test_case[0](*test_case[1])
mod = ethosu.partition_for_ethosu(mod)
mod = partition_for_ethosu(mod)
mod = legalize.LegalizeEthosUConv2D()(mod)
verify_linear(mod["tvmgen_default_ethosu_main_0"], conv_params)

Expand Down Expand Up @@ -327,7 +327,7 @@ def create_graph_single_unsupported_ifm_layout(

for test_case in test_cases:
mod, conv_params = test_case[0](*test_case[1])
mod = ethosu.partition_for_ethosu(mod)
mod = partition_for_ethosu(mod)
with pytest.raises(
tvm._ffi.base.TVMError, match="EthosUCodegenError: Unsupported Layout NCHW"
):
Expand Down
5 changes: 3 additions & 2 deletions tests/python/contrib/test_ethosu/test_networks.py
Original file line number Diff line number Diff line change
Expand Up @@ -27,8 +27,9 @@
import tvm
import tvm.micro as micro
from tvm import relay
from tvm.relay.backend.contrib import ethosu
from tvm.relay.backend.contrib.ethosu import util
from tvm.relay.op.contrib.ethosu import partition_for_ethosu

import tvm.relay.testing.tf as tf_testing

from . import infra
Expand Down Expand Up @@ -56,7 +57,7 @@ def test_forward_mobilenet_v1(accel_type="ethos-u55-256"):
input_data = {input_tensor: input_data}
output_data = generate_ref_data(relay_mod, input_data)

mod = ethosu.partition_for_ethosu(relay_mod, params)
mod = partition_for_ethosu(relay_mod, params)
compiled_models = infra.build_source(mod, input_data, output_data, accel_type)
infra.verify_source(compiled_models, accel_type)

Expand Down
16 changes: 4 additions & 12 deletions tests/python/contrib/test_ethosu/test_vela_api.py
Original file line number Diff line number Diff line change
Expand Up @@ -347,9 +347,7 @@ def verify(test_vec, mock_obj):
assert mock_obj.call_args[1]["block_traversal"] == test_vec["block_traversal"]

def create_mock(test_vec):
with patch(
"tvm.relay.backend.contrib.ethosu.vela_api.vapi.npu_encode_weights"
) as mock_npu_encode_weights:
with patch("ethosu.vela.api.npu_encode_weights") as mock_npu_encode_weights:
ifm_bitdepth = np.iinfo(test_vec["ifm_dtype"]).bits
ifm_dtype = test_vec["ifm_dtype"]
max = np.iinfo(ifm_dtype).max
Expand Down Expand Up @@ -427,9 +425,7 @@ def verify(test_vec, mock_obj, packed_biases):
assert test_vec["hw_shifts"][idx] == mock_obj.call_args_list[idx][0][2]

def create_mock(test_vec):
with patch(
"tvm.relay.backend.contrib.ethosu.vela_api.vapi.npu_encode_bias"
) as mock_npu_encode_bias:
with patch("ethosu.vela.api.npu_encode_bias") as mock_npu_encode_bias:
mock_npu_encode_bias.return_value = bytearray(10)
ifm_dtype = test_vec["ifm_dtype"]
max = np.iinfo(ifm_dtype).max
Expand Down Expand Up @@ -507,12 +503,8 @@ def test_encode_weights(accel):
]

def create_mock(test_vec):
with patch(
"tvm.relay.backend.contrib.ethosu.vela_api.vapi.npu_encode_weights"
) as mock_enc_w:
with patch(
"tvm.relay.backend.contrib.ethosu.vela_api.vapi.npu_find_block_configs"
) as mock_blk_cfg:
with patch("ethosu.vela.api.npu_encode_weights") as mock_enc_w:
with patch("ethosu.vela.api.npu_find_block_configs") as mock_blk_cfg:
mock_blk_cfg.return_value = [vapi.NpuShape3D(8, 8, 8)]
ethosu_conv2d_calls = extract_ethosu_conv2d_extern_calls(test_vec["tir_module"])
buffer_info = tirtocs.extract_buffer_info(
Expand Down
35 changes: 35 additions & 0 deletions tests/python/driver/tvmc/test_compiler.py
Original file line number Diff line number Diff line change
Expand Up @@ -361,6 +361,41 @@ def test_compile_tflite_module_with_external_codegen_vitis_ai(tflite_mobilenet_v
assert os.path.exists(dumps_path)


def test_compile_tflite_module_with_external_codegen_ethosu(
tmpdir_factory, tflite_mobilenet_v1_1_quant
):
pytest.importorskip("tflite")
pytest.importorskip("ethosu.vela")
ACCEL_TYPES = ["ethos-u55-256", "ethos-u55-128", "ethos-u55-64", "ethos-u55-32"]

output_dir = tmpdir_factory.mktemp("mlf")

tvmc_model = tvmc.load(tflite_mobilenet_v1_1_quant)

for accel_type in ACCEL_TYPES:
output_file_name = f"{output_dir}/file_{accel_type}.tar"

tvmc_package = tvmc.compiler.compile_model(
tvmc_model,
target=f"ethos-u -accelerator_config={accel_type}, c -runtime=c --system-lib --link-params -mcpu=cortex-m55 --executor=aot",
output_format="mlf",
package_path=output_file_name,
pass_context_configs=["tir.disable_vectorize=true"],
)

# check whether an MLF package was created
assert os.path.exists(output_file_name)

# check whether the expected number of C sources are in the tarfile
with tarfile.open(output_file_name) as mlf_package:
c_source_files = [
name
for name in mlf_package.getnames()
if re.match(r"\./codegen/host/src/\D+\d+\.c", name)
]
assert len(c_source_files) == 17


@mock.patch("tvm.relay.build")
@mock.patch("tvm.driver.tvmc.composite_target.get_codegen_by_target")
@mock.patch("tvm.driver.tvmc.load")
Expand Down

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