chore: Upgrade black version to 25.1.0 for Vertex SDK

PiperOrigin-RevId: 789752562

Author: sararob

google/cloud/aiplatform/_streaming_prediction.py

@@ -130,7 +130,9 @@ async def predict_stream_of_tensor_lists_from_single_tensor_list_async(
         inputs=tensor_list,
         parameters=parameters_tensor,
     )
-    async for response in await prediction_service_async_client.server_streaming_predict(
+    async for (
+        response
+    ) in await prediction_service_async_client.server_streaming_predict(
         request=request
     ):
         yield response.outputs
@@ -183,7 +185,9 @@ async def predict_stream_of_dict_lists_from_single_dict_list_async(
     """
     tensor_list = [value_to_tensor(d) for d in dict_list]
     parameters_tensor = value_to_tensor(parameters) if parameters else None
-    async for tensor_list in predict_stream_of_tensor_lists_from_single_tensor_list_async(
+    async for (
+        tensor_list
+    ) in predict_stream_of_tensor_lists_from_single_tensor_list_async(
         prediction_service_async_client=prediction_service_async_client,
         endpoint_name=endpoint_name,
         tensor_list=tensor_list,

google/cloud/aiplatform/base.py

@@ -639,7 +639,6 @@ def _get_and_validate_project_location(
         project: Optional[str] = None,
         location: Optional[str] = None,
     ) -> Tuple[str, str]:
-
         """Validate the project and location for the resource.
 
         Args:

google/cloud/aiplatform/datasets/__init__.py

@@ -16,9 +16,13 @@
 #
 
 from google.cloud.aiplatform.datasets.dataset import _Dataset
-from google.cloud.aiplatform.datasets.column_names_dataset import _ColumnNamesDataset
+from google.cloud.aiplatform.datasets.column_names_dataset import (
+    _ColumnNamesDataset,
+)
 from google.cloud.aiplatform.datasets.tabular_dataset import TabularDataset
-from google.cloud.aiplatform.datasets.time_series_dataset import TimeSeriesDataset
+from google.cloud.aiplatform.datasets.time_series_dataset import (
+    TimeSeriesDataset,
+)
 from google.cloud.aiplatform.datasets.image_dataset import ImageDataset
 from google.cloud.aiplatform.datasets.text_dataset import TextDataset
 from google.cloud.aiplatform.datasets.video_dataset import VideoDataset

google/cloud/aiplatform/docker_utils/build.py

@@ -223,7 +223,7 @@ def _prepare_exposed_ports(exposed_ports: Optional[List[int]] = None) -> str:
 
 
 def _prepare_environment_variables(
-    environment_variables: Optional[Dict[str, str]] = None
+    environment_variables: Optional[Dict[str, str]] = None,
 ) -> str:
     """Returns the Dockerfile entries required to set environment variables in containers.
 

google/cloud/aiplatform/docker_utils/run.py

@@ -30,7 +30,9 @@
     )
 
 from google.cloud.aiplatform.constants import prediction
-from google.cloud.aiplatform.docker_utils.utils import DEFAULT_MOUNTED_MODEL_DIRECTORY
+from google.cloud.aiplatform.docker_utils.utils import (
+    DEFAULT_MOUNTED_MODEL_DIRECTORY,
+)
 from google.cloud.aiplatform.utils import prediction_utils
 
 _logger = logging.getLogger(__name__)

google/cloud/aiplatform/explain/metadata/tf/v1/saved_model_metadata_builder.py

@@ -126,7 +126,7 @@ def get_metadata_protobuf(self) -> explanation_metadata.ExplanationMetadata:
 
 
 def _create_input_metadata_from_signature(
-    signature_inputs: Dict[str, "tf.Tensor"]  # noqa: F821
+    signature_inputs: Dict[str, "tf.Tensor"],  # noqa: F821
 ) -> Dict[str, explanation_metadata.ExplanationMetadata.InputMetadata]:
     """Creates InputMetadata from signature inputs.
 

google/cloud/aiplatform/explain/metadata/tf/v2/saved_model_metadata_builder.py

@@ -75,9 +75,7 @@ def __init__(
             signature_name
         )
 
-    def _infer_metadata_entries_from_model(
-        self, signature_name: str
-    ) -> Tuple[
+    def _infer_metadata_entries_from_model(self, signature_name: str) -> Tuple[
         Dict[str, explanation_metadata.ExplanationMetadata.InputMetadata],
         Dict[str, explanation_metadata.ExplanationMetadata.OutputMetadata],
     ]:
@@ -107,10 +105,10 @@ def _infer_metadata_entries_from_model(
         output_mds = {}
         for name in output_sig:
             if not self._explain_output or self._explain_output[0] == name:
-                output_mds[
-                    name
-                ] = explanation_metadata.ExplanationMetadata.OutputMetadata(
-                    output_tensor_name=name,
+                output_mds[name] = (
+                    explanation_metadata.ExplanationMetadata.OutputMetadata(
+                        output_tensor_name=name,
+                    )
                 )
                 break
         else:

google/cloud/aiplatform/featurestore/_entity_type.py

@@ -116,11 +116,11 @@ def __init__(
         )
         self._gca_resource = self._get_gca_resource(
             resource_name=entity_type_name,
-            parent_resource_name_fields={
-                featurestore.Featurestore._resource_noun: featurestore_id
-            }
-            if featurestore_id
-            else featurestore_id,
+            parent_resource_name_fields=(
+                {featurestore.Featurestore._resource_noun: featurestore_id}
+                if featurestore_id
+                else featurestore_id
+            ),
         )
 
         self._featurestore_online_client = self._instantiate_featurestore_online_client(
@@ -1842,7 +1842,7 @@ def _apply_feature_timestamp(
 
     @staticmethod
     def _is_timestamp(
-        timestamp: Union[datetime.datetime, timestamp_pb2.Timestamp]
+        timestamp: Union[datetime.datetime, timestamp_pb2.Timestamp],
     ) -> bool:
         return isinstance(timestamp, datetime.datetime) or isinstance(
             timestamp, timestamp_pb2.Timestamp

google/cloud/aiplatform/featurestore/feature.py

@@ -114,12 +114,14 @@ def __init__(
         )
         self._gca_resource = self._get_gca_resource(
             resource_name=feature_name,
-            parent_resource_name_fields={
-                featurestore.Featurestore._resource_noun: featurestore_id,
-                featurestore.EntityType._resource_noun: entity_type_id,
-            }
-            if featurestore_id
-            else featurestore_id,
+            parent_resource_name_fields=(
+                {
+                    featurestore.Featurestore._resource_noun: featurestore_id,
+                    featurestore.EntityType._resource_noun: entity_type_id,
+                }
+                if featurestore_id
+                else featurestore_id
+            ),
         )
 
     def _get_featurestore_name(self) -> str:
@@ -338,11 +340,11 @@ def list(
                 resource_noun=featurestore.EntityType._resource_noun,
                 parse_resource_name_method=featurestore.EntityType._parse_resource_name,
                 format_resource_name_method=featurestore.EntityType._format_resource_name,
-                parent_resource_name_fields={
-                    featurestore.Featurestore._resource_noun: featurestore_id
-                }
-                if featurestore_id
-                else featurestore_id,
+                parent_resource_name_fields=(
+                    {featurestore.Featurestore._resource_noun: featurestore_id}
+                    if featurestore_id
+                    else featurestore_id
+                ),
                 project=project,
                 location=location,
                 resource_id_validator=featurestore.EntityType._resource_id_validator,
@@ -585,11 +587,11 @@ def create(
             resource_noun=featurestore.EntityType._resource_noun,
             parse_resource_name_method=featurestore.EntityType._parse_resource_name,
             format_resource_name_method=featurestore.EntityType._format_resource_name,
-            parent_resource_name_fields={
-                featurestore.Featurestore._resource_noun: featurestore_id
-            }
-            if featurestore_id
-            else featurestore_id,
+            parent_resource_name_fields=(
+                {featurestore.Featurestore._resource_noun: featurestore_id}
+                if featurestore_id
+                else featurestore_id
+            ),
             project=project,
             location=location,
             resource_id_validator=featurestore.EntityType._resource_id_validator,

google/cloud/aiplatform/gapic/schema/__init__.py

@@ -18,12 +18,20 @@
 from google.cloud.aiplatform.v1.schema import predict
 from google.cloud.aiplatform.v1.schema import trainingjob
 from google.cloud.aiplatform.v1beta1.schema import predict as predict_v1beta1
-from google.cloud.aiplatform.v1beta1.schema import predict as trainingjob_v1beta1
+from google.cloud.aiplatform.v1beta1.schema import (
+    predict as trainingjob_v1beta1,
+)
 
 # import the v1 submodules for enhancement
-from google.cloud.aiplatform.v1.schema.predict.instance_v1 import types as instance
-from google.cloud.aiplatform.v1.schema.predict.params_v1 import types as params
-from google.cloud.aiplatform.v1.schema.predict.prediction_v1 import types as prediction
+from google.cloud.aiplatform.v1.schema.predict.instance_v1 import (
+    types as instance,
+)
+from google.cloud.aiplatform.v1.schema.predict.params_v1 import (
+    types as params,
+)
+from google.cloud.aiplatform.v1.schema.predict.prediction_v1 import (
+    types as prediction,
+)
 from google.cloud.aiplatform.v1.schema.trainingjob.definition_v1 import (
     types as definition,
 )