feat: add dedicated_resources to DeployedIndex message in aiplatform …

…v1 index_endpoint.proto chore: sort imports (#990) * feat: add dedicated_resources to DeployedIndex message in aiplatform v1 index_endpoint.proto chore: sort imports PiperOrigin-RevId: 425394497 Source-Link: googleapis/googleapis@bd97e46 Source-Link: googleapis/googleapis-gen@13eed11 Copy-Tag: eyJwIjoiLmdpdGh1Yi8uT3dsQm90LnlhbWwiLCJoIjoiMTNlZWQxMTA1MWUxY2Y5ZjlhYjQzZDE3NGYyM2QzNWZmYjMyOTQxYyJ9 * 🦉 Updates from OwlBot See https://github.com/googleapis/repo-automation-bots/blob/main/packages/owl-bot/README.md Co-authored-by: Owl Bot <gcf-owl-bot[bot]@users.noreply.github.com>
googleapis · Jan 31, 2022 · a814923 · a814923
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diff --git a/google/cloud/aiplatform/v1/schema/trainingjob/definition_v1/types/automl_tables.py b/google/cloud/aiplatform/v1/schema/trainingjob/definition_v1/types/automl_tables.py
@@ -99,21 +99,21 @@ class AutoMlTablesInputs(proto.Message):
             operating characteristic (ROC) curve.
             "minimize-log-loss" - Minimize log loss.
               "maximize-au-prc" - Maximize the area under
-            the precision-recall curve.   "maximize-
-            precision-at-recall" - Maximize precision for a
-            specified
+            the precision-recall curve.
+            "maximize-precision-at-recall" - Maximize
+            precision for a specified
             recall value.   "maximize-recall-at-precision" -
             Maximize recall for a specified
             precision value.
             classification (multi-class):
               "minimize-log-loss" (default) - Minimize log
             loss.
             regression:
-              "minimize-rmse" (default) - Minimize root-
-            mean-squared error (RMSE).   "minimize-mae" -
-            Minimize mean-absolute error (MAE).   "minimize-
-            rmsle" - Minimize root-mean-squared log error
-            (RMSLE).
+              "minimize-rmse" (default) - Minimize
+            root-mean-squared error (RMSE).   "minimize-mae"
+            - Minimize mean-absolute error (MAE).
+            "minimize-rmsle" - Minimize root-mean-squared
+            log error (RMSLE).
         train_budget_milli_node_hours (int):
             Required. The train budget of creating this
             model, expressed in milli node hours i.e. 1,000

diff --git a/google/cloud/aiplatform/v1beta1/schema/trainingjob/definition_v1beta1/types/automl_tables.py b/google/cloud/aiplatform/v1beta1/schema/trainingjob/definition_v1beta1/types/automl_tables.py
@@ -99,21 +99,21 @@ class AutoMlTablesInputs(proto.Message):
             operating characteristic (ROC) curve.
             "minimize-log-loss" - Minimize log loss.
               "maximize-au-prc" - Maximize the area under
-            the precision-recall curve.   "maximize-
-            precision-at-recall" - Maximize precision for a
-            specified
+            the precision-recall curve.
+            "maximize-precision-at-recall" - Maximize
+            precision for a specified
             recall value.   "maximize-recall-at-precision" -
             Maximize recall for a specified
             precision value.
             classification (multi-class):
               "minimize-log-loss" (default) - Minimize log
             loss.
             regression:
-              "minimize-rmse" (default) - Minimize root-
-            mean-squared error (RMSE).   "minimize-mae" -
-            Minimize mean-absolute error (MAE).   "minimize-
-            rmsle" - Minimize root-mean-squared log error
-            (RMSLE).
+              "minimize-rmse" (default) - Minimize
+            root-mean-squared error (RMSE).   "minimize-mae"
+            - Minimize mean-absolute error (MAE).
+            "minimize-rmsle" - Minimize root-mean-squared
+            log error (RMSLE).
         train_budget_milli_node_hours (int):
             Required. The train budget of creating this
             model, expressed in milli node hours i.e. 1,000

diff --git a/google/cloud/aiplatform_v1/services/dataset_service/async_client.py b/google/cloud/aiplatform_v1/services/dataset_service/async_client.py
@@ -16,7 +16,7 @@
 from collections import OrderedDict
 import functools
 import re
-from typing import Dict, Sequence, Tuple, Type, Union
+from typing import Dict, Optional, Sequence, Tuple, Type, Union
 import pkg_resources
 
 from google.api_core.client_options import ClientOptions
@@ -129,6 +129,42 @@ def from_service_account_file(cls, filename: str, *args, **kwargs):
 
     from_service_account_json = from_service_account_file
 
+    @classmethod
+    def get_mtls_endpoint_and_cert_source(
+        cls, client_options: Optional[ClientOptions] = None
+    ):
+        """Return the API endpoint and client cert source for mutual TLS.
+
+        The client cert source is determined in the following order:
+        (1) if `GOOGLE_API_USE_CLIENT_CERTIFICATE` environment variable is not "true", the
+        client cert source is None.
+        (2) if `client_options.client_cert_source` is provided, use the provided one; if the
+        default client cert source exists, use the default one; otherwise the client cert
+        source is None.
+
+        The API endpoint is determined in the following order:
+        (1) if `client_options.api_endpoint` if provided, use the provided one.
+        (2) if `GOOGLE_API_USE_CLIENT_CERTIFICATE` environment variable is "always", use the
+        default mTLS endpoint; if the environment variabel is "never", use the default API
+        endpoint; otherwise if client cert source exists, use the default mTLS endpoint, otherwise
+        use the default API endpoint.
+
+        More details can be found at https://google.aip.dev/auth/4114.
+
+        Args:
+            client_options (google.api_core.client_options.ClientOptions): Custom options for the
+                client. Only the `api_endpoint` and `client_cert_source` properties may be used
+                in this method.
+
+        Returns:
+            Tuple[str, Callable[[], Tuple[bytes, bytes]]]: returns the API endpoint and the
+                client cert source to use.
+
+        Raises:
+            google.auth.exceptions.MutualTLSChannelError: If any errors happen.
+        """
+        return DatasetServiceClient.get_mtls_endpoint_and_cert_source(client_options)  # type: ignore
+
     @property
     def transport(self) -> DatasetServiceTransport:
         """Returns the transport used by the client instance.
@@ -234,7 +270,7 @@ async def create_dataset(
 
         """
         # Create or coerce a protobuf request object.
-        # Sanity check: If we got a request object, we should *not* have
+        # Quick check: If we got a request object, we should *not* have
         # gotten any keyword arguments that map to the request.
         has_flattened_params = any([parent, dataset])
         if request is not None and has_flattened_params:
@@ -315,7 +351,7 @@ async def get_dataset(
 
         """
         # Create or coerce a protobuf request object.
-        # Sanity check: If we got a request object, we should *not* have
+        # Quick check: If we got a request object, we should *not* have
         # gotten any keyword arguments that map to the request.
         has_flattened_params = any([name])
         if request is not None and has_flattened_params:
@@ -400,7 +436,7 @@ async def update_dataset(
 
         """
         # Create or coerce a protobuf request object.
-        # Sanity check: If we got a request object, we should *not* have
+        # Quick check: If we got a request object, we should *not* have
         # gotten any keyword arguments that map to the request.
         has_flattened_params = any([dataset, update_mask])
         if request is not None and has_flattened_params:
@@ -478,7 +514,7 @@ async def list_datasets(
 
         """
         # Create or coerce a protobuf request object.
-        # Sanity check: If we got a request object, we should *not* have
+        # Quick check: If we got a request object, we should *not* have
         # gotten any keyword arguments that map to the request.
         has_flattened_params = any([parent])
         if request is not None and has_flattened_params:
@@ -569,7 +605,7 @@ async def delete_dataset(
 
         """
         # Create or coerce a protobuf request object.
-        # Sanity check: If we got a request object, we should *not* have
+        # Quick check: If we got a request object, we should *not* have
         # gotten any keyword arguments that map to the request.
         has_flattened_params = any([name])
         if request is not None and has_flattened_params:
@@ -661,7 +697,7 @@ async def import_data(
 
         """
         # Create or coerce a protobuf request object.
-        # Sanity check: If we got a request object, we should *not* have
+        # Quick check: If we got a request object, we should *not* have
         # gotten any keyword arguments that map to the request.
         has_flattened_params = any([name, import_configs])
         if request is not None and has_flattened_params:
@@ -754,7 +790,7 @@ async def export_data(
 
         """
         # Create or coerce a protobuf request object.
-        # Sanity check: If we got a request object, we should *not* have
+        # Quick check: If we got a request object, we should *not* have
         # gotten any keyword arguments that map to the request.
         has_flattened_params = any([name, export_config])
         if request is not None and has_flattened_params:
@@ -839,7 +875,7 @@ async def list_data_items(
 
         """
         # Create or coerce a protobuf request object.
-        # Sanity check: If we got a request object, we should *not* have
+        # Quick check: If we got a request object, we should *not* have
         # gotten any keyword arguments that map to the request.
         has_flattened_params = any([parent])
         if request is not None and has_flattened_params:
@@ -917,7 +953,7 @@ async def get_annotation_spec(
 
         """
         # Create or coerce a protobuf request object.
-        # Sanity check: If we got a request object, we should *not* have
+        # Quick check: If we got a request object, we should *not* have
         # gotten any keyword arguments that map to the request.
         has_flattened_params = any([name])
         if request is not None and has_flattened_params:
@@ -992,7 +1028,7 @@ async def list_annotations(
 
         """
         # Create or coerce a protobuf request object.
-        # Sanity check: If we got a request object, we should *not* have
+        # Quick check: If we got a request object, we should *not* have
         # gotten any keyword arguments that map to the request.
         has_flattened_params = any([parent])
         if request is not None and has_flattened_params: