feat: adds function/method enhancements, demo samples (#122)

* feat: adds function/method enhancements

Author: telpirion

.github/CODEOWNERS

@@ -9,3 +9,6 @@
 
 # The python-samples-owners team is the default owner for samples
 /samples/**/*.py @dizcology @googleapis/python-samples-owners
+
+# The enhanced client library tests are owned by @telpirion
+/tests/unit/enhanced_library/*.py @telpirion

google/cloud/aiplatform/helpers/__init__.py

@@ -0,0 +1,3 @@
+from google.cloud.aiplatform.helpers import value_converter
+
+__all__ = (value_converter,)

google/cloud/aiplatform/helpers/_decorators.py

@@ -0,0 +1,70 @@
+# Copyright 2020 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+from __future__ import absolute_import
+from google.cloud.aiplatform.helpers import value_converter
+
+from proto.marshal import Marshal
+from proto.marshal.rules.struct import ValueRule
+from google.protobuf.struct_pb2 import Value
+
+
+class ConversionValueRule(ValueRule):
+ def to_python(self, value, *, absent: bool = None):
+ return super().to_python(value, absent=absent)
+
+ def to_proto(self, value):
+
+ # Need to check whether value is an instance
+ # of an enhanced type
+ if callable(getattr(value, "to_value", None)):
+ return value.to_value()
+ else:
+ return super().to_proto(value)
+
+
+def _add_methods_to_classes_in_package(pkg):
+ classes = dict(
+ [(name, cls) for name, cls in pkg.__dict__.items() if isinstance(cls, type)]
+ )
+
+ for class_name, cls in classes.items():
+ # Add to_value() method to class with docstring
+ setattr(cls, "to_value", value_converter.to_value)
+ cls.to_value.__doc__ = value_converter.to_value.__doc__
+
+ # Add from_value() method to class with docstring
+ setattr(cls, "from_value", _add_from_value_to_class(cls))
+ cls.from_value.__doc__ = value_converter.from_value.__doc__
+
+ # Add from_map() method to class with docstring
+ setattr(cls, "from_map", _add_from_map_to_class(cls))
+ cls.from_map.__doc__ = value_converter.from_map.__doc__
+
+
+def _add_from_value_to_class(cls):
+ def _from_value(value):
+ return value_converter.from_value(cls, value)
+
+ return _from_value
+
+
+def _add_from_map_to_class(cls):
+ def _from_map(map_):
+ return value_converter.from_map(cls, map_)
+
+ return _from_map
+
+
+marshal = Marshal(name="google.cloud.aiplatform.v1beta1")
+marshal.register(Value, ConversionValueRule(marshal=marshal))

google/cloud/aiplatform/helpers/value_converter.py

@@ -0,0 +1,60 @@
+# Copyright 2020 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# https://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+from __future__ import absolute_import
+from google.protobuf.struct_pb2 import Value
+from google.protobuf import json_format
+from proto.marshal.collections.maps import MapComposite
+from proto.marshal import Marshal
+from proto import Message
+from proto.message import MessageMeta
+
+
+def to_value(self: Message) -> Value:
+ """Converts a message type to a :class:`~google.protobuf.struct_pb2.Value` object.
+
+ Args:
+ message: the message to convert
+
+ Returns:
+ the message as a :class:`~google.protobuf.struct_pb2.Value` object
+ """
+ tmp_dict = json_format.MessageToDict(self._pb)
+ return json_format.ParseDict(tmp_dict, Value())
+
+
+def from_value(cls: MessageMeta, value: Value) -> Message:
+ """Creates instance of class from a :class:`~google.protobuf.struct_pb2.Value` object.
+
+ Args:
+ value: a :class:`~google.protobuf.struct_pb2.Value` object
+
+ Returns:
+ Instance of class
+ """
+ value_dict = json_format.MessageToDict(value)
+ return json_format.ParseDict(value_dict, cls()._pb)
+
+
+def from_map(cls: MessageMeta, map_: MapComposite) -> Message:
+ """Creates instance of class from a :class:`~proto.marshal.collections.maps.MapComposite` object.
+
+ Args:
+ map_: a :class:`~proto.marshal.collections.maps.MapComposite` object
+
+ Returns:
+ Instance of class
+ """
+ marshal = Marshal(name="marshal")
+ pb = marshal.to_proto(Value, map_)
+ return from_value(cls, pb)

google/cloud/aiplatform/v1beta1/schema/predict/instance/__init__.py

@@ -14,6 +14,8 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 #
+from google.cloud.aiplatform.helpers import _decorators
+import google.cloud.aiplatform.v1beta1.schema.predict.instance_v1beta1.types as pkg
 
 from google.cloud.aiplatform.v1beta1.schema.predict.instance_v1beta1.types.image_classification import (
  ImageClassificationPredictionInstance,
@@ -54,3 +56,4 @@
  "VideoClassificationPredictionInstance",
  "VideoObjectTrackingPredictionInstance",
 )
+_decorators._add_methods_to_classes_in_package(pkg)

google/cloud/aiplatform/v1beta1/schema/predict/params/__init__.py

@@ -14,6 +14,8 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 #
+from google.cloud.aiplatform.helpers import _decorators
+import google.cloud.aiplatform.v1beta1.schema.predict.params_v1beta1.types as pkg
 
 from google.cloud.aiplatform.v1beta1.schema.predict.params_v1beta1.types.image_classification import (
  ImageClassificationPredictionParams,
@@ -42,3 +44,4 @@
  "VideoClassificationPredictionParams",
  "VideoObjectTrackingPredictionParams",
 )
+_decorators._add_methods_to_classes_in_package(pkg)

google/cloud/aiplatform/v1beta1/schema/predict/prediction/__init__.py

@@ -14,6 +14,8 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 #
+from google.cloud.aiplatform.helpers import _decorators
+import google.cloud.aiplatform.v1beta1.schema.predict.prediction_v1beta1.types as pkg
 
 from google.cloud.aiplatform.v1beta1.schema.predict.prediction_v1beta1.types.classification import (
  ClassificationPredictionResult,
@@ -62,3 +64,4 @@
  "VideoClassificationPredictionResult",
  "VideoObjectTrackingPredictionResult",
 )
+_decorators._add_methods_to_classes_in_package(pkg)

google/cloud/aiplatform/v1beta1/schema/predict/prediction_v1beta1/types/text_sentiment.py

@@ -17,8 +17,10 @@
 
 import proto # type: ignore
 
-
-from google.cloud.aiplatform.v1beta1.schema.predict.instance import text_sentiment_pb2 as gcaspi_text_sentiment # type: ignore
+# DO NOT OVERWRITE FOLLOWING LINE: it was manually edited.
+from google.cloud.aiplatform.v1beta1.schema.predict.instance import (
+ TextSentimentPredictionInstance,
+)
 
 
 __protobuf__ = proto.module(
@@ -57,9 +59,7 @@ class Prediction(proto.Message):
  sentiment = proto.Field(proto.INT32, number=1)
 
  instance = proto.Field(
- proto.MESSAGE,
- number=1,
- message=gcaspi_text_sentiment.TextSentimentPredictionInstance,
+ proto.MESSAGE, number=1, message=TextSentimentPredictionInstance,
  )
 
  prediction = proto.Field(proto.MESSAGE, number=2, message=Prediction,)

google/cloud/aiplatform/v1beta1/schema/trainingjob/definition/__init__.py

@@ -14,6 +14,8 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 #
+from google.cloud.aiplatform.helpers import _decorators
+import google.cloud.aiplatform.v1beta1.schema.trainingjob.definition_v1beta1.types as pkg
 
 from google.cloud.aiplatform.v1beta1.schema.trainingjob.definition_v1beta1.types.automl_forecasting import (
  AutoMlForecasting,
@@ -130,3 +132,4 @@
  "AutoMlVideoObjectTrackingInputs",
  "ExportEvaluatedDataItemsConfig",
 )
+_decorators._add_methods_to_classes_in_package(pkg)

google/cloud/aiplatform/v1beta1/schema/trainingjob/definition_v1beta1/types/automl_forecasting.py

@@ -78,14 +78,14 @@ class AutoMlForecastingInputs(proto.Message):
  function over the validation set.
 
  The supported optimization objectives:
-  "minimize-rmse" (default) - Minimize root-
+ "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-rmspe" - Minimize root-
  mean-squared percentage error (RMSPE).
  "minimize-wape-mae" - Minimize the combination
- of weighted absolute  percentage error (WAPE)
+ of weighted absolute percentage error (WAPE)
  and mean-absolute-error (MAE).
  train_budget_milli_node_hours (int):
  Required. The train budget of creating this
@@ -418,11 +418,11 @@ class Period(proto.Message):
  unit (str):
  The time granularity unit of this time
  period. The supported unit are:
-  "hour"
-  "day"
-  "week"
-  "month"
-  "year".
+ "hour"
+ "day"
+ "week"
+ "month"
+ "year".
  quantity (int):
  The number of units per period, e.g. 3 weeks
  or 2 months.