.coveragerc

@@ -21,15 +21,14 @@ branch = True
 [report]
 fail_under = 100
 show_missing = True
+omit = google/cloud/datalabeling/__init__.py
 exclude_lines =
     # Re-enable the standard pragma
     pragma: NO COVER
     # Ignore debug-only repr
     def __repr__
-    # Ignore abstract methods
-    raise NotImplementedError
-omit =
-  */gapic/*.py
-  */proto/*.py
-  */core/*.py
-  */site-packages/*.py
+    # Ignore pkg_resources exceptions.
+    # This is added at the module level as a safeguard for if someone
+    # generates the code and tries to run it without pip installing. This
+    # makes it virtually impossible to test properly.
+    except pkg_resources.DistributionNotFound

CHANGELOG.md

@@ -4,6 +4,17 @@
 
 [1]: https://pypi.org/project/google-cloud-datalabeling/#history
 
+## [1.0.0](https://www.github.com/googleapis/python-datalabeling/compare/v0.4.1...v1.0.0) (2020-08-12)
+
+
+### ⚠ BREAKING CHANGES
+
+* migrate to use microgen (#34)
+
+### Features
+
+* migrate to use microgen ([#34](https://www.github.com/googleapis/python-datalabeling/issues/34)) ([465eb36](https://www.github.com/googleapis/python-datalabeling/commit/465eb361d39d08029f30b36c769252c9f83e7949))
+
 ### [0.4.1](https://www.github.com/googleapis/python-datalabeling/compare/v0.4.0...v0.4.1) (2020-08-07)
 
 

README.rst

@@ -44,14 +44,13 @@ dependencies.
 
 Supported Python Versions
 ^^^^^^^^^^^^^^^^^^^^^^^^^
-
-Python >= 3.5
-
+Python >= 3.6
 
 Deprecated Python Versions
 ^^^^^^^^^^^^^^^^^^^^^^^^^^
+Python == 2.7.
 
-Python == 2.7. Python 2.7 support will be removed on January 1, 2020.
+The last version of this library compatible with Python 2.7 is google-cloud-datalabeling==0.4.1.
 
 
 Mac/Linux

UPGRADING.md

@@ -0,0 +1,169 @@
+# 1.0.0 Migration Guide
+
+The 1.0 release of the `google-cloud-datalabeling` client is a significant upgrade based on a [next-gen code generator](https://github.com/googleapis/gapic-generator-python), and includes substantial interface changes. Existing code written for earlier versions of this library will likely require updates to use this version. This document describes the changes that have been made, and what you need to do to update your usage.
+
+If you experience issues or have questions, please file an [issue](https://github.com/googleapis/python-datalabeling/issues).
+
+## Supported Python Versions
+
+> **WARNING**: Breaking change
+
+The 1.0.0 release requires Python 3.6+.
+
+
+## Method Calls
+
+> **WARNING**: Breaking change
+
+Methods expect request objects. We provide a script that will convert most common use cases.
+
+* Install the library
+
+```py
+python3 -m pip install google-cloud-datalabeling
+```
+
+* The script `fixup_datalabeling_v1_keywords.py` is shipped with the library. It expects an input directory (with the code to convert) and an empty destination directory.
+
+```sh
+$ fixup_datalabeling_v1_keywords.py --input-directory .samples/ --output-directory samples/
+```
+
+**Before:**
+```py
+from google.cloud import datalabeling
+
+client = datalabeling.DataLabelingServiceClient()
+
+datasets = client.list_datasets(parent="projects/project")
+```
+
+
+**After:**
+```py
+from google.cloud import datalabeling
+
+client = datalabeling.DataLabelingServiceClient()
+
+datasets = client.list_datasets(request={"parent": "projects/project"})
+```
+
+### More Details
+
+In `google-cloud-datalabeling<1.0.0`, parameters required by the API were positional parameters and optional parameters were keyword parameters.
+
+**Before:**
+```py
+    def create_dataset(
+        self,
+        parent,
+        dataset,
+        retry=google.api_core.gapic_v1.method.DEFAULT,
+        timeout=google.api_core.gapic_v1.method.DEFAULT,
+        metadata=None,
+    ):
+```
+
+In the 1.0.0 release, all methods have a single positional parameter `request`. Method docstrings indicate whether a parameter is required or optional.
+
+Some methods have additional keyword only parameters. The available parameters depend on the [`google.api.method_signature` annotation](https://github.com/googleapis/googleapis/blob/master/google/cloud/datalabeling/v1beta1/data_labeling_service.proto#L48) specified by the API producer.
+
+
+**After:**
+```py
+    def create_dataset(
+        self,
+        request: data_labeling_service.CreateDatasetRequest = None,
+        *,
+        parent: str = None,
+        dataset: gcd_dataset.Dataset = None,
+        retry: retries.Retry = gapic_v1.method.DEFAULT,
+        timeout: float = None,
+        metadata: Sequence[Tuple[str, str]] = (),
+    ) -> gcd_dataset.Dataset:
+```
+
+> **NOTE:** The `request` parameter and flattened keyword parameters for the API are mutually exclusive.
+> Passing both will result in an error.
+
+
+Both of these calls are valid:
+
+```py
+response = client.create_dataset(
+    request={
+        "parent": parent,
+        "dataset": dataset
+    }
+)
+```
+
+```py
+response = client.create_dataset(
+    parent=parent,
+    dataset=dataset
+)
+```
+
+This call is invalid because it mixes `request` with a keyword argument `dataset`. Executing this code
+will result in an error.
+
+```py
+response = client.create_dataset(
+    request={
+        "parent": parent
+    },
+    dataset=dataset
+)
+```
+
+
+
+## Enums and Types
+
+
+> **WARNING**: Breaking change
+
+The submodules `enums` and `types` have been removed.
+
+**Before:**
+```py
+from google.cloud import datalabeling
+
+data_type = datalabeling.enums.DataType.IMAGE
+dataset = datalabeling.types.Dataset(display_name="name")
+```
+
+
+**After:**
+```py
+from google.cloud import datalabeling
+
+data_type = datalabeling.DataType.IMAGE
+dataset = datalabeling.Dataset(display_name="name")
+```
+
+## Path Helper Methods
+The following path helper methods have been removed. Please construct the paths manually.
+
+```py
+project="project"
+dataset="dataset"
+annotated_dataset="annotated_dataset"
+annotation_spec_set="annotation_spec_set"
+data_item="data_item"
+evaluation="evaluation"
+evaluation_job="evaluation_job"
+example="example"
+instruction="instruction"
+
+annotated_dataset_path = f'projects/{project}/datasets/{dataset}/annotatedDatasets/{annotated_dataset}'
+annotation_spec_set_path = f'projects/{project}/annotationSpecSets/{annotation_spec_set}'
+data_item_path=f'projects/{project}/datasets/{dataset}/dataItems/{data_item}'
+dataset_path=f'projects/{project}/datasets/{dataset}'
+evaluation_path=f'projects/{project}/datasets/{dataset}/evaluations/{evaluation}'
+evaluation_job_path=f'projects/{project}/evaluationJobs/{evaluation_job}'
+example_path=f'projects/{project}/datasets/{dataset}/annotatedDatasets/{annotated_dataset}/examples/{example}'
+instruction_path=f'projects/{project}/instructions/{instruction}'
+project_path=f'projects/{project}'
+```

docs/UPGRADING.md

@@ -0,0 +1 @@
+../UPGRADING.md

docs/datalabeling_v1beta1/services.rst

@@ -0,0 +1,6 @@
+Services for Google Cloud Datalabeling v1beta1 API
+==================================================
+
+.. automodule:: google.cloud.datalabeling_v1beta1.services.data_labeling_service
+    :members:
+    :inherited-members:

docs/datalabeling_v1beta1/types.rst

@@ -0,0 +1,5 @@
+Types for Google Cloud Datalabeling v1beta1 API
+===============================================
+
+.. automodule:: google.cloud.datalabeling_v1beta1.types
+    :members:

docs/index.rst

@@ -7,9 +7,19 @@ Api Reference
 .. toctree::
     :maxdepth: 2
 
-    gapic/v1beta1/api
-    gapic/v1beta1/types
-
+    datalabeling_v1beta1/services
+    datalabeling_v1beta1/types
+
+Migration Guide
+---------------
+
+See the guide below for instructions on migrating to the 1.x release of this library.
+
+.. toctree::
+    :maxdepth: 2
+
+    UPGRADING
+
 Changelog
 ---------
 

google/cloud/datalabeling/py.typed

@@ -0,0 +1,2 @@
+# Marker file for PEP 561.
+# The google-cloud-datalabeling package uses inline types.

google/cloud/datalabeling_v1beta1/__init__.py

@@ -1,29 +1,293 @@
 # -*- coding: utf-8 -*-
-#
-# Copyright 2019 Google LLC
+
+# 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
+#     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.datalabeling_v1beta1 import types
-from google.cloud.datalabeling_v1beta1.gapic import data_labeling_service_client
-from google.cloud.datalabeling_v1beta1.gapic import enums
-
-
-class DataLabelingServiceClient(data_labeling_service_client.DataLabelingServiceClient):
-    __doc__ = data_labeling_service_client.DataLabelingServiceClient.__doc__
-    enums = enums
+from .services.data_labeling_service import DataLabelingServiceClient
+from .types.annotation import Annotation
+from .types.annotation import AnnotationMetadata
+from .types.annotation import AnnotationSentiment
+from .types.annotation import AnnotationSource
+from .types.annotation import AnnotationType
+from .types.annotation import AnnotationValue
+from .types.annotation import BoundingPoly
+from .types.annotation import ImageBoundingPolyAnnotation
+from .types.annotation import ImageClassificationAnnotation
+from .types.annotation import ImagePolylineAnnotation
+from .types.annotation import ImageSegmentationAnnotation
+from .types.annotation import NormalizedBoundingPoly
+from .types.annotation import NormalizedPolyline
+from .types.annotation import NormalizedVertex
+from .types.annotation import ObjectTrackingFrame
+from .types.annotation import OperatorMetadata
+from .types.annotation import Polyline
+from .types.annotation import SequentialSegment
+from .types.annotation import TextClassificationAnnotation
+from .types.annotation import TextEntityExtractionAnnotation
+from .types.annotation import TimeSegment
+from .types.annotation import Vertex
+from .types.annotation import VideoClassificationAnnotation
+from .types.annotation import VideoEventAnnotation
+from .types.annotation import VideoObjectTrackingAnnotation
+from .types.annotation_spec_set import AnnotationSpec
+from .types.annotation_spec_set import AnnotationSpecSet
+from .types.data_labeling_service import CreateAnnotationSpecSetRequest
+from .types.data_labeling_service import CreateDatasetRequest
+from .types.data_labeling_service import CreateEvaluationJobRequest
+from .types.data_labeling_service import CreateInstructionRequest
+from .types.data_labeling_service import DeleteAnnotatedDatasetRequest
+from .types.data_labeling_service import DeleteAnnotationSpecSetRequest
+from .types.data_labeling_service import DeleteDatasetRequest
+from .types.data_labeling_service import DeleteEvaluationJobRequest
+from .types.data_labeling_service import DeleteInstructionRequest
+from .types.data_labeling_service import ExportDataRequest
+from .types.data_labeling_service import GetAnnotatedDatasetRequest
+from .types.data_labeling_service import GetAnnotationSpecSetRequest
+from .types.data_labeling_service import GetDataItemRequest
+from .types.data_labeling_service import GetDatasetRequest
+from .types.data_labeling_service import GetEvaluationJobRequest
+from .types.data_labeling_service import GetEvaluationRequest
+from .types.data_labeling_service import GetExampleRequest
+from .types.data_labeling_service import GetInstructionRequest
+from .types.data_labeling_service import ImportDataRequest
+from .types.data_labeling_service import LabelImageRequest
+from .types.data_labeling_service import LabelTextRequest
+from .types.data_labeling_service import LabelVideoRequest
+from .types.data_labeling_service import ListAnnotatedDatasetsRequest
+from .types.data_labeling_service import ListAnnotatedDatasetsResponse
+from .types.data_labeling_service import ListAnnotationSpecSetsRequest
+from .types.data_labeling_service import ListAnnotationSpecSetsResponse
+from .types.data_labeling_service import ListDataItemsRequest
+from .types.data_labeling_service import ListDataItemsResponse
+from .types.data_labeling_service import ListDatasetsRequest
+from .types.data_labeling_service import ListDatasetsResponse
+from .types.data_labeling_service import ListEvaluationJobsRequest
+from .types.data_labeling_service import ListEvaluationJobsResponse
+from .types.data_labeling_service import ListExamplesRequest
+from .types.data_labeling_service import ListExamplesResponse
+from .types.data_labeling_service import ListInstructionsRequest
+from .types.data_labeling_service import ListInstructionsResponse
+from .types.data_labeling_service import PauseEvaluationJobRequest
+from .types.data_labeling_service import ResumeEvaluationJobRequest
+from .types.data_labeling_service import SearchEvaluationsRequest
+from .types.data_labeling_service import SearchEvaluationsResponse
+from .types.data_labeling_service import SearchExampleComparisonsRequest
+from .types.data_labeling_service import SearchExampleComparisonsResponse
+from .types.data_labeling_service import UpdateEvaluationJobRequest
+from .types.data_payloads import ImagePayload
+from .types.data_payloads import TextPayload
+from .types.data_payloads import VideoPayload
+from .types.data_payloads import VideoThumbnail
+from .types.dataset import AnnotatedDataset
+from .types.dataset import AnnotatedDatasetMetadata
+from .types.dataset import BigQuerySource
+from .types.dataset import ClassificationMetadata
+from .types.dataset import DataItem
+from .types.dataset import DataType
+from .types.dataset import Dataset
+from .types.dataset import Example
+from .types.dataset import GcsDestination
+from .types.dataset import GcsFolderDestination
+from .types.dataset import GcsSource
+from .types.dataset import InputConfig
+from .types.dataset import LabelStats
+from .types.dataset import OutputConfig
+from .types.dataset import TextMetadata
+from .types.evaluation import BoundingBoxEvaluationOptions
+from .types.evaluation import ClassificationMetrics
+from .types.evaluation import ConfusionMatrix
+from .types.evaluation import Evaluation
+from .types.evaluation import EvaluationConfig
+from .types.evaluation import EvaluationMetrics
+from .types.evaluation import ObjectDetectionMetrics
+from .types.evaluation import PrCurve
+from .types.evaluation_job import Attempt
+from .types.evaluation_job import EvaluationJob
+from .types.evaluation_job import EvaluationJobAlertConfig
+from .types.evaluation_job import EvaluationJobConfig
+from .types.human_annotation_config import BoundingPolyConfig
+from .types.human_annotation_config import EventConfig
+from .types.human_annotation_config import HumanAnnotationConfig
+from .types.human_annotation_config import ImageClassificationConfig
+from .types.human_annotation_config import ObjectDetectionConfig
+from .types.human_annotation_config import ObjectTrackingConfig
+from .types.human_annotation_config import PolylineConfig
+from .types.human_annotation_config import SegmentationConfig
+from .types.human_annotation_config import SentimentConfig
+from .types.human_annotation_config import StringAggregationType
+from .types.human_annotation_config import TextClassificationConfig
+from .types.human_annotation_config import TextEntityExtractionConfig
+from .types.human_annotation_config import VideoClassificationConfig
+from .types.instruction import CsvInstruction
+from .types.instruction import Instruction
+from .types.instruction import PdfInstruction
+from .types.operations import CreateInstructionMetadata
+from .types.operations import ExportDataOperationMetadata
+from .types.operations import ExportDataOperationResponse
+from .types.operations import ImportDataOperationMetadata
+from .types.operations import ImportDataOperationResponse
+from .types.operations import LabelImageBoundingBoxOperationMetadata
+from .types.operations import LabelImageBoundingPolyOperationMetadata
+from .types.operations import LabelImageClassificationOperationMetadata
+from .types.operations import LabelImageOrientedBoundingBoxOperationMetadata
+from .types.operations import LabelImagePolylineOperationMetadata
+from .types.operations import LabelImageSegmentationOperationMetadata
+from .types.operations import LabelOperationMetadata
+from .types.operations import LabelTextClassificationOperationMetadata
+from .types.operations import LabelTextEntityExtractionOperationMetadata
+from .types.operations import LabelVideoClassificationOperationMetadata
+from .types.operations import LabelVideoEventOperationMetadata
+from .types.operations import LabelVideoObjectDetectionOperationMetadata
+from .types.operations import LabelVideoObjectTrackingOperationMetadata
 
 
-__all__ = ("enums", "types", "DataLabelingServiceClient")
+__all__ = (
+    "AnnotatedDataset",
+    "AnnotatedDatasetMetadata",
+    "Annotation",
+    "AnnotationMetadata",
+    "AnnotationSentiment",
+    "AnnotationSource",
+    "AnnotationSpec",
+    "AnnotationSpecSet",
+    "AnnotationType",
+    "AnnotationValue",
+    "Attempt",
+    "BigQuerySource",
+    "BoundingBoxEvaluationOptions",
+    "BoundingPoly",
+    "BoundingPolyConfig",
+    "ClassificationMetadata",
+    "ClassificationMetrics",
+    "ConfusionMatrix",
+    "CreateAnnotationSpecSetRequest",
+    "CreateDatasetRequest",
+    "CreateEvaluationJobRequest",
+    "CreateInstructionMetadata",
+    "CreateInstructionRequest",
+    "CsvInstruction",
+    "DataItem",
+    "DataType",
+    "Dataset",
+    "DeleteAnnotatedDatasetRequest",
+    "DeleteAnnotationSpecSetRequest",
+    "DeleteDatasetRequest",
+    "DeleteEvaluationJobRequest",
+    "DeleteInstructionRequest",
+    "Evaluation",
+    "EvaluationConfig",
+    "EvaluationJob",
+    "EvaluationJobAlertConfig",
+    "EvaluationJobConfig",
+    "EvaluationMetrics",
+    "EventConfig",
+    "Example",
+    "ExportDataOperationMetadata",
+    "ExportDataOperationResponse",
+    "ExportDataRequest",
+    "GcsDestination",
+    "GcsFolderDestination",
+    "GcsSource",
+    "GetAnnotatedDatasetRequest",
+    "GetAnnotationSpecSetRequest",
+    "GetDataItemRequest",
+    "GetDatasetRequest",
+    "GetEvaluationJobRequest",
+    "GetEvaluationRequest",
+    "GetExampleRequest",
+    "GetInstructionRequest",
+    "HumanAnnotationConfig",
+    "ImageBoundingPolyAnnotation",
+    "ImageClassificationAnnotation",
+    "ImageClassificationConfig",
+    "ImagePayload",
+    "ImagePolylineAnnotation",
+    "ImageSegmentationAnnotation",
+    "ImportDataOperationMetadata",
+    "ImportDataOperationResponse",
+    "ImportDataRequest",
+    "InputConfig",
+    "Instruction",
+    "LabelImageBoundingBoxOperationMetadata",
+    "LabelImageBoundingPolyOperationMetadata",
+    "LabelImageClassificationOperationMetadata",
+    "LabelImageOrientedBoundingBoxOperationMetadata",
+    "LabelImagePolylineOperationMetadata",
+    "LabelImageRequest",
+    "LabelImageSegmentationOperationMetadata",
+    "LabelOperationMetadata",
+    "LabelStats",
+    "LabelTextClassificationOperationMetadata",
+    "LabelTextEntityExtractionOperationMetadata",
+    "LabelTextRequest",
+    "LabelVideoClassificationOperationMetadata",
+    "LabelVideoEventOperationMetadata",
+    "LabelVideoObjectDetectionOperationMetadata",
+    "LabelVideoObjectTrackingOperationMetadata",
+    "LabelVideoRequest",
+    "ListAnnotatedDatasetsRequest",
+    "ListAnnotatedDatasetsResponse",
+    "ListAnnotationSpecSetsRequest",
+    "ListAnnotationSpecSetsResponse",
+    "ListDataItemsRequest",
+    "ListDataItemsResponse",
+    "ListDatasetsRequest",
+    "ListDatasetsResponse",
+    "ListEvaluationJobsRequest",
+    "ListEvaluationJobsResponse",
+    "ListExamplesRequest",
+    "ListExamplesResponse",
+    "ListInstructionsRequest",
+    "ListInstructionsResponse",
+    "NormalizedBoundingPoly",
+    "NormalizedPolyline",
+    "NormalizedVertex",
+    "ObjectDetectionConfig",
+    "ObjectDetectionMetrics",
+    "ObjectTrackingConfig",
+    "ObjectTrackingFrame",
+    "OperatorMetadata",
+    "OutputConfig",
+    "PauseEvaluationJobRequest",
+    "PdfInstruction",
+    "Polyline",
+    "PolylineConfig",
+    "PrCurve",
+    "ResumeEvaluationJobRequest",
+    "SearchEvaluationsRequest",
+    "SearchEvaluationsResponse",
+    "SearchExampleComparisonsRequest",
+    "SearchExampleComparisonsResponse",
+    "SegmentationConfig",
+    "SentimentConfig",
+    "SequentialSegment",
+    "StringAggregationType",
+    "TextClassificationAnnotation",
+    "TextClassificationConfig",
+    "TextEntityExtractionAnnotation",
+    "TextEntityExtractionConfig",
+    "TextMetadata",
+    "TextPayload",
+    "TimeSegment",
+    "UpdateEvaluationJobRequest",
+    "Vertex",
+    "VideoClassificationAnnotation",
+    "VideoClassificationConfig",
+    "VideoEventAnnotation",
+    "VideoObjectTrackingAnnotation",
+    "VideoPayload",
+    "VideoThumbnail",
+    "DataLabelingServiceClient",
+)

google/cloud/datalabeling_v1beta1/py.typed

@@ -0,0 +1,2 @@
+# Marker file for PEP 561.
+# The google-cloud-datalabeling package uses inline types.

google/__init__.py → google/cloud/datalabeling_v1beta1/services/__init__.py

@@ -1,24 +1,16 @@
 # -*- coding: utf-8 -*-
-#
+
 # 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
+#     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.
-
-try:
-    import pkg_resources
-
-    pkg_resources.declare_namespace(__name__)
-except ImportError:
-    import pkgutil
-
-    __path__ = pkgutil.extend_path(__path__, __name__)
+#

google/cloud/__init__.py → google/cloud/datalabeling_v1beta1/services/data_labeling_service/__init__.py

@@ -1,24 +1,24 @@
 # -*- coding: utf-8 -*-
-#
+
 # 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
+#     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.
+#
 
-try:
-    import pkg_resources
-
-    pkg_resources.declare_namespace(__name__)
-except ImportError:
-    import pkgutil
+from .client import DataLabelingServiceClient
+from .async_client import DataLabelingServiceAsyncClient
 
-    __path__ = pkgutil.extend_path(__path__, __name__)
+__all__ = (
+    "DataLabelingServiceClient",
+    "DataLabelingServiceAsyncClient",
+)

google/cloud/datalabeling_v1beta1/services/data_labeling_service/transports/__init__.py

@@ -0,0 +1,38 @@
+# -*- coding: utf-8 -*-
+
+# 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 collections import OrderedDict
+from typing import Dict, Type
+
+from .base import DataLabelingServiceTransport
+from .grpc import DataLabelingServiceGrpcTransport
+from .grpc_asyncio import DataLabelingServiceGrpcAsyncIOTransport
+
+
+# Compile a registry of transports.
+_transport_registry = (
+    OrderedDict()
+)  # type: Dict[str, Type[DataLabelingServiceTransport]]
+_transport_registry["grpc"] = DataLabelingServiceGrpcTransport
+_transport_registry["grpc_asyncio"] = DataLabelingServiceGrpcAsyncIOTransport
+
+
+__all__ = (
+    "DataLabelingServiceTransport",
+    "DataLabelingServiceGrpcTransport",
+    "DataLabelingServiceGrpcAsyncIOTransport",
+)

google/cloud/datalabeling_v1beta1/types/__init__.py

@@ -0,0 +1,301 @@
+# -*- coding: utf-8 -*-
+
+# 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 .annotation_spec_set import (
+    AnnotationSpecSet,
+    AnnotationSpec,
+)
+from .annotation import (
+    Annotation,
+    AnnotationValue,
+    ImageClassificationAnnotation,
+    Vertex,
+    NormalizedVertex,
+    BoundingPoly,
+    NormalizedBoundingPoly,
+    ImageBoundingPolyAnnotation,
+    Polyline,
+    NormalizedPolyline,
+    ImagePolylineAnnotation,
+    ImageSegmentationAnnotation,
+    TextClassificationAnnotation,
+    TextEntityExtractionAnnotation,
+    SequentialSegment,
+    TimeSegment,
+    VideoClassificationAnnotation,
+    ObjectTrackingFrame,
+    VideoObjectTrackingAnnotation,
+    VideoEventAnnotation,
+    AnnotationMetadata,
+    OperatorMetadata,
+)
+from .data_payloads import (
+    ImagePayload,
+    TextPayload,
+    VideoThumbnail,
+    VideoPayload,
+)
+from .human_annotation_config import (
+    HumanAnnotationConfig,
+    ImageClassificationConfig,
+    BoundingPolyConfig,
+    PolylineConfig,
+    SegmentationConfig,
+    VideoClassificationConfig,
+    ObjectDetectionConfig,
+    ObjectTrackingConfig,
+    EventConfig,
+    TextClassificationConfig,
+    SentimentConfig,
+    TextEntityExtractionConfig,
+)
+from .dataset import (
+    Dataset,
+    InputConfig,
+    TextMetadata,
+    ClassificationMetadata,
+    GcsSource,
+    BigQuerySource,
+    OutputConfig,
+    GcsDestination,
+    GcsFolderDestination,
+    DataItem,
+    AnnotatedDataset,
+    LabelStats,
+    AnnotatedDatasetMetadata,
+    Example,
+)
+from .evaluation import (
+    Evaluation,
+    EvaluationConfig,
+    BoundingBoxEvaluationOptions,
+    EvaluationMetrics,
+    ClassificationMetrics,
+    ObjectDetectionMetrics,
+    PrCurve,
+    ConfusionMatrix,
+)
+from .evaluation_job import (
+    EvaluationJob,
+    EvaluationJobConfig,
+    EvaluationJobAlertConfig,
+    Attempt,
+)
+from .instruction import (
+    Instruction,
+    CsvInstruction,
+    PdfInstruction,
+)
+from .data_labeling_service import (
+    CreateDatasetRequest,
+    GetDatasetRequest,
+    ListDatasetsRequest,
+    ListDatasetsResponse,
+    DeleteDatasetRequest,
+    ImportDataRequest,
+    ExportDataRequest,
+    GetDataItemRequest,
+    ListDataItemsRequest,
+    ListDataItemsResponse,
+    GetAnnotatedDatasetRequest,
+    ListAnnotatedDatasetsRequest,
+    ListAnnotatedDatasetsResponse,
+    DeleteAnnotatedDatasetRequest,
+    LabelImageRequest,
+    LabelVideoRequest,
+    LabelTextRequest,
+    GetExampleRequest,
+    ListExamplesRequest,
+    ListExamplesResponse,
+    CreateAnnotationSpecSetRequest,
+    GetAnnotationSpecSetRequest,
+    ListAnnotationSpecSetsRequest,
+    ListAnnotationSpecSetsResponse,
+    DeleteAnnotationSpecSetRequest,
+    CreateInstructionRequest,
+    GetInstructionRequest,
+    DeleteInstructionRequest,
+    ListInstructionsRequest,
+    ListInstructionsResponse,
+    GetEvaluationRequest,
+    SearchEvaluationsRequest,
+    SearchEvaluationsResponse,
+    SearchExampleComparisonsRequest,
+    SearchExampleComparisonsResponse,
+    CreateEvaluationJobRequest,
+    UpdateEvaluationJobRequest,
+    GetEvaluationJobRequest,
+    PauseEvaluationJobRequest,
+    ResumeEvaluationJobRequest,
+    DeleteEvaluationJobRequest,
+    ListEvaluationJobsRequest,
+    ListEvaluationJobsResponse,
+)
+from .operations import (
+    ImportDataOperationResponse,
+    ExportDataOperationResponse,
+    ImportDataOperationMetadata,
+    ExportDataOperationMetadata,
+    LabelOperationMetadata,
+    LabelImageClassificationOperationMetadata,
+    LabelImageBoundingBoxOperationMetadata,
+    LabelImageOrientedBoundingBoxOperationMetadata,
+    LabelImageBoundingPolyOperationMetadata,
+    LabelImagePolylineOperationMetadata,
+    LabelImageSegmentationOperationMetadata,
+    LabelVideoClassificationOperationMetadata,
+    LabelVideoObjectDetectionOperationMetadata,
+    LabelVideoObjectTrackingOperationMetadata,
+    LabelVideoEventOperationMetadata,
+    LabelTextClassificationOperationMetadata,
+    LabelTextEntityExtractionOperationMetadata,
+    CreateInstructionMetadata,
+)
+
+
+__all__ = (
+    "AnnotationSpecSet",
+    "AnnotationSpec",
+    "Annotation",
+    "AnnotationValue",
+    "ImageClassificationAnnotation",
+    "Vertex",
+    "NormalizedVertex",
+    "BoundingPoly",
+    "NormalizedBoundingPoly",
+    "ImageBoundingPolyAnnotation",
+    "Polyline",
+    "NormalizedPolyline",
+    "ImagePolylineAnnotation",
+    "ImageSegmentationAnnotation",
+    "TextClassificationAnnotation",
+    "TextEntityExtractionAnnotation",
+    "SequentialSegment",
+    "TimeSegment",
+    "VideoClassificationAnnotation",
+    "ObjectTrackingFrame",
+    "VideoObjectTrackingAnnotation",
+    "VideoEventAnnotation",
+    "AnnotationMetadata",
+    "OperatorMetadata",
+    "ImagePayload",
+    "TextPayload",
+    "VideoThumbnail",
+    "VideoPayload",
+    "HumanAnnotationConfig",
+    "ImageClassificationConfig",
+    "BoundingPolyConfig",
+    "PolylineConfig",
+    "SegmentationConfig",
+    "VideoClassificationConfig",
+    "ObjectDetectionConfig",
+    "ObjectTrackingConfig",
+    "EventConfig",
+    "TextClassificationConfig",
+    "SentimentConfig",
+    "TextEntityExtractionConfig",
+    "Dataset",
+    "InputConfig",
+    "TextMetadata",
+    "ClassificationMetadata",
+    "GcsSource",
+    "BigQuerySource",
+    "OutputConfig",
+    "GcsDestination",
+    "GcsFolderDestination",
+    "DataItem",
+    "AnnotatedDataset",
+    "LabelStats",
+    "AnnotatedDatasetMetadata",
+    "Example",
+    "Evaluation",
+    "EvaluationConfig",
+    "BoundingBoxEvaluationOptions",
+    "EvaluationMetrics",
+    "ClassificationMetrics",
+    "ObjectDetectionMetrics",
+    "PrCurve",
+    "ConfusionMatrix",
+    "EvaluationJob",
+    "EvaluationJobConfig",
+    "EvaluationJobAlertConfig",
+    "Attempt",
+    "Instruction",
+    "CsvInstruction",
+    "PdfInstruction",
+    "CreateDatasetRequest",
+    "GetDatasetRequest",
+    "ListDatasetsRequest",
+    "ListDatasetsResponse",
+    "DeleteDatasetRequest",
+    "ImportDataRequest",
+    "ExportDataRequest",
+    "GetDataItemRequest",
+    "ListDataItemsRequest",
+    "ListDataItemsResponse",
+    "GetAnnotatedDatasetRequest",
+    "ListAnnotatedDatasetsRequest",
+    "ListAnnotatedDatasetsResponse",
+    "DeleteAnnotatedDatasetRequest",
+    "LabelImageRequest",
+    "LabelVideoRequest",
+    "LabelTextRequest",
+    "GetExampleRequest",
+    "ListExamplesRequest",
+    "ListExamplesResponse",
+    "CreateAnnotationSpecSetRequest",
+    "GetAnnotationSpecSetRequest",
+    "ListAnnotationSpecSetsRequest",
+    "ListAnnotationSpecSetsResponse",
+    "DeleteAnnotationSpecSetRequest",
+    "CreateInstructionRequest",
+    "GetInstructionRequest",
+    "DeleteInstructionRequest",
+    "ListInstructionsRequest",
+    "ListInstructionsResponse",
+    "GetEvaluationRequest",
+    "SearchEvaluationsRequest",
+    "SearchEvaluationsResponse",
+    "SearchExampleComparisonsRequest",
+    "SearchExampleComparisonsResponse",
+    "CreateEvaluationJobRequest",
+    "UpdateEvaluationJobRequest",
+    "GetEvaluationJobRequest",
+    "PauseEvaluationJobRequest",
+    "ResumeEvaluationJobRequest",
+    "DeleteEvaluationJobRequest",
+    "ListEvaluationJobsRequest",
+    "ListEvaluationJobsResponse",
+    "ImportDataOperationResponse",
+    "ExportDataOperationResponse",
+    "ImportDataOperationMetadata",
+    "ExportDataOperationMetadata",
+    "LabelOperationMetadata",
+    "LabelImageClassificationOperationMetadata",
+    "LabelImageBoundingBoxOperationMetadata",
+    "LabelImageOrientedBoundingBoxOperationMetadata",
+    "LabelImageBoundingPolyOperationMetadata",
+    "LabelImagePolylineOperationMetadata",
+    "LabelImageSegmentationOperationMetadata",
+    "LabelVideoClassificationOperationMetadata",
+    "LabelVideoObjectDetectionOperationMetadata",
+    "LabelVideoObjectTrackingOperationMetadata",
+    "LabelVideoEventOperationMetadata",
+    "LabelTextClassificationOperationMetadata",
+    "LabelTextEntityExtractionOperationMetadata",
+    "CreateInstructionMetadata",
+)

google/cloud/datalabeling_v1beta1/types/annotation_spec_set.py

@@ -0,0 +1,92 @@
+# -*- coding: utf-8 -*-
+
+# 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.
+#
+
+import proto  # type: ignore
+
+
+__protobuf__ = proto.module(
+    package="google.cloud.datalabeling.v1beta1",
+    manifest={"AnnotationSpecSet", "AnnotationSpec",},
+)
+
+
+class AnnotationSpecSet(proto.Message):
+    r"""An AnnotationSpecSet is a collection of label definitions.
+    For example, in image classification tasks, you define a set of
+    possible labels for images as an AnnotationSpecSet. An
+    AnnotationSpecSet is immutable upon creation.
+
+    Attributes:
+        name (str):
+            Output only. The AnnotationSpecSet resource name in the
+            following format:
+
+            "projects/{project_id}/annotationSpecSets/{annotation_spec_set_id}".
+        display_name (str):
+            Required. The display name for
+            AnnotationSpecSet that you define when you
+            create it. Maximum of 64 characters.
+        description (str):
+            Optional. User-provided description of the
+            annotation specification set. The description
+            can be up to 10,000 characters long.
+        annotation_specs (Sequence[~.annotation_spec_set.AnnotationSpec]):
+            Required. The array of AnnotationSpecs that
+            you define when you create the
+            AnnotationSpecSet. These are the possible labels
+            for the labeling task.
+        blocking_resources (Sequence[str]):
+            Output only. The names of any related
+            resources that are blocking changes to the
+            annotation spec set.
+    """
+
+    name = proto.Field(proto.STRING, number=1)
+
+    display_name = proto.Field(proto.STRING, number=2)
+
+    description = proto.Field(proto.STRING, number=3)
+
+    annotation_specs = proto.RepeatedField(
+        proto.MESSAGE, number=4, message="AnnotationSpec",
+    )
+
+    blocking_resources = proto.RepeatedField(proto.STRING, number=5)
+
+
+class AnnotationSpec(proto.Message):
+    r"""Container of information related to one possible annotation that can
+    be used in a labeling task. For example, an image classification
+    task where images are labeled as ``dog`` or ``cat`` must reference
+    an AnnotationSpec for ``dog`` and an AnnotationSpec for ``cat``.
+
+    Attributes:
+        display_name (str):
+            Required. The display name of the
+            AnnotationSpec. Maximum of 64 characters.
+        description (str):
+            Optional. User-provided description of the
+            annotation specification. The description can be
+            up to 10,000 characters long.
+    """
+
+    display_name = proto.Field(proto.STRING, number=1)
+
+    description = proto.Field(proto.STRING, number=2)
+
+
+__all__ = tuple(sorted(__protobuf__.manifest))

google/cloud/datalabeling_v1beta1/types/data_payloads.py

@@ -0,0 +1,112 @@
+# -*- coding: utf-8 -*-
+
+# 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.
+#
+
+import proto  # type: ignore
+
+
+from google.protobuf import duration_pb2 as duration  # type: ignore
+
+
+__protobuf__ = proto.module(
+    package="google.cloud.datalabeling.v1beta1",
+    manifest={"ImagePayload", "TextPayload", "VideoThumbnail", "VideoPayload",},
+)
+
+
+class ImagePayload(proto.Message):
+    r"""Container of information about an image.
+
+    Attributes:
+        mime_type (str):
+            Image format.
+        image_thumbnail (bytes):
+            A byte string of a thumbnail image.
+        image_uri (str):
+            Image uri from the user bucket.
+        signed_uri (str):
+            Signed uri of the image file in the service
+            bucket.
+    """
+
+    mime_type = proto.Field(proto.STRING, number=1)
+
+    image_thumbnail = proto.Field(proto.BYTES, number=2)
+
+    image_uri = proto.Field(proto.STRING, number=3)
+
+    signed_uri = proto.Field(proto.STRING, number=4)
+
+
+class TextPayload(proto.Message):
+    r"""Container of information about a piece of text.
+
+    Attributes:
+        text_content (str):
+            Text content.
+    """
+
+    text_content = proto.Field(proto.STRING, number=1)
+
+
+class VideoThumbnail(proto.Message):
+    r"""Container of information of a video thumbnail.
+
+    Attributes:
+        thumbnail (bytes):
+            A byte string of the video frame.
+        time_offset (~.duration.Duration):
+            Time offset relative to the beginning of the
+            video, corresponding to the video frame where
+            the thumbnail has been extracted from.
+    """
+
+    thumbnail = proto.Field(proto.BYTES, number=1)
+
+    time_offset = proto.Field(proto.MESSAGE, number=2, message=duration.Duration,)
+
+
+class VideoPayload(proto.Message):
+    r"""Container of information of a video.
+
+    Attributes:
+        mime_type (str):
+            Video format.
+        video_uri (str):
+            Video uri from the user bucket.
+        video_thumbnails (Sequence[~.data_payloads.VideoThumbnail]):
+            The list of video thumbnails.
+        frame_rate (float):
+            FPS of the video.
+        signed_uri (str):
+            Signed uri of the video file in the service
+            bucket.
+    """
+
+    mime_type = proto.Field(proto.STRING, number=1)
+
+    video_uri = proto.Field(proto.STRING, number=2)
+
+    video_thumbnails = proto.RepeatedField(
+        proto.MESSAGE, number=3, message=VideoThumbnail,
+    )
+
+    frame_rate = proto.Field(proto.FLOAT, number=4)
+
+    signed_uri = proto.Field(proto.STRING, number=5)
+
+
+__all__ = tuple(sorted(__protobuf__.manifest))

google/cloud/datalabeling_v1beta1/types/evaluation.py

@@ -0,0 +1,334 @@
+# -*- coding: utf-8 -*-
+
+# 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.
+#
+
+import proto  # type: ignore
+
+
+from google.cloud.datalabeling_v1beta1.types import annotation
+from google.cloud.datalabeling_v1beta1.types import annotation_spec_set
+from google.protobuf import timestamp_pb2 as timestamp  # type: ignore
+
+
+__protobuf__ = proto.module(
+    package="google.cloud.datalabeling.v1beta1",
+    manifest={
+        "Evaluation",
+        "EvaluationConfig",
+        "BoundingBoxEvaluationOptions",
+        "EvaluationMetrics",
+        "ClassificationMetrics",
+        "ObjectDetectionMetrics",
+        "PrCurve",
+        "ConfusionMatrix",
+    },
+)
+
+
+class Evaluation(proto.Message):
+    r"""Describes an evaluation between a machine learning model's
+    predictions and ground truth labels. Created when an
+    [EvaluationJob][google.cloud.datalabeling.v1beta1.EvaluationJob]
+    runs successfully.
+
+    Attributes:
+        name (str):
+            Output only. Resource name of an evaluation. The name has
+            the following format:
+
+            "projects/{project_id}/datasets/{dataset_id}/evaluations/{evaluation_id}'
+        config (~.evaluation.EvaluationConfig):
+            Output only. Options used in the evaluation
+            job that created this evaluation.
+        evaluation_job_run_time (~.timestamp.Timestamp):
+            Output only. Timestamp for when the
+            evaluation job that created this evaluation ran.
+        create_time (~.timestamp.Timestamp):
+            Output only. Timestamp for when this
+            evaluation was created.
+        evaluation_metrics (~.evaluation.EvaluationMetrics):
+            Output only. Metrics comparing predictions to
+            ground truth labels.
+        annotation_type (~.annotation.AnnotationType):
+            Output only. Type of task that the model version being
+            evaluated performs, as defined in the
+
+            [evaluationJobConfig.inputConfig.annotationType][google.cloud.datalabeling.v1beta1.EvaluationJobConfig.input_config]
+            field of the evaluation job that created this evaluation.
+        evaluated_item_count (int):
+            Output only. The number of items in the
+            ground truth dataset that were used for this
+            evaluation. Only populated when the evaulation
+            is for certain AnnotationTypes.
+    """
+
+    name = proto.Field(proto.STRING, number=1)
+
+    config = proto.Field(proto.MESSAGE, number=2, message="EvaluationConfig",)
+
+    evaluation_job_run_time = proto.Field(
+        proto.MESSAGE, number=3, message=timestamp.Timestamp,
+    )
+
+    create_time = proto.Field(proto.MESSAGE, number=4, message=timestamp.Timestamp,)
+
+    evaluation_metrics = proto.Field(
+        proto.MESSAGE, number=5, message="EvaluationMetrics",
+    )
+
+    annotation_type = proto.Field(proto.ENUM, number=6, enum=annotation.AnnotationType,)
+
+    evaluated_item_count = proto.Field(proto.INT64, number=7)
+
+
+class EvaluationConfig(proto.Message):
+    r"""Configuration details used for calculating evaluation metrics and
+    creating an
+    [Evaluation][google.cloud.datalabeling.v1beta1.Evaluation].
+
+    Attributes:
+        bounding_box_evaluation_options (~.evaluation.BoundingBoxEvaluationOptions):
+            Only specify this field if the related model performs image
+            object detection (``IMAGE_BOUNDING_BOX_ANNOTATION``).
+            Describes how to evaluate bounding boxes.
+    """
+
+    bounding_box_evaluation_options = proto.Field(
+        proto.MESSAGE,
+        number=1,
+        oneof="vertical_option",
+        message="BoundingBoxEvaluationOptions",
+    )
+
+
+class BoundingBoxEvaluationOptions(proto.Message):
+    r"""Options regarding evaluation between bounding boxes.
+
+    Attributes:
+        iou_threshold (float):
+            Minimum [intersection-over-union
+
+            (IOU)](/vision/automl/object-detection/docs/evaluate#intersection-over-union)
+            required for 2 bounding boxes to be considered a match. This
+            must be a number between 0 and 1.
+    """
+
+    iou_threshold = proto.Field(proto.FLOAT, number=1)
+
+
+class EvaluationMetrics(proto.Message):
+    r"""
+
+    Attributes:
+        classification_metrics (~.evaluation.ClassificationMetrics):
+
+        object_detection_metrics (~.evaluation.ObjectDetectionMetrics):
+
+    """
+
+    classification_metrics = proto.Field(
+        proto.MESSAGE, number=1, oneof="metrics", message="ClassificationMetrics",
+    )
+
+    object_detection_metrics = proto.Field(
+        proto.MESSAGE, number=2, oneof="metrics", message="ObjectDetectionMetrics",
+    )
+
+
+class ClassificationMetrics(proto.Message):
+    r"""Metrics calculated for a classification model.
+
+    Attributes:
+        pr_curve (~.evaluation.PrCurve):
+            Precision-recall curve based on ground truth
+            labels, predicted labels, and scores for the
+            predicted labels.
+        confusion_matrix (~.evaluation.ConfusionMatrix):
+            Confusion matrix of predicted labels vs.
+            ground truth labels.
+    """
+
+    pr_curve = proto.Field(proto.MESSAGE, number=1, message="PrCurve",)
+
+    confusion_matrix = proto.Field(proto.MESSAGE, number=2, message="ConfusionMatrix",)
+
+
+class ObjectDetectionMetrics(proto.Message):
+    r"""Metrics calculated for an image object detection (bounding
+    box) model.
+
+    Attributes:
+        pr_curve (~.evaluation.PrCurve):
+            Precision-recall curve.
+    """
+
+    pr_curve = proto.Field(proto.MESSAGE, number=1, message="PrCurve",)
+
+
+class PrCurve(proto.Message):
+    r"""
+
+    Attributes:
+        annotation_spec (~.annotation_spec_set.AnnotationSpec):
+            The annotation spec of the label for which
+            the precision-recall curve calculated. If this
+            field is empty, that means the precision-recall
+            curve is an aggregate curve for all labels.
+        area_under_curve (float):
+            Area under the precision-recall curve. Not to
+            be confused with area under a receiver operating
+            characteristic (ROC) curve.
+        confidence_metrics_entries (Sequence[~.evaluation.PrCurve.ConfidenceMetricsEntry]):
+            Entries that make up the precision-recall graph. Each entry
+            is a "point" on the graph drawn for a different
+            ``confidence_threshold``.
+        mean_average_precision (float):
+            Mean average prcision of this curve.
+    """
+
+    class ConfidenceMetricsEntry(proto.Message):
+        r"""
+
+        Attributes:
+            confidence_threshold (float):
+                Threshold used for this entry.
+
+                For classification tasks, this is a classification
+                threshold: a predicted label is categorized as positive or
+                negative (in the context of this point on the PR curve)
+                based on whether the label's score meets this threshold.
+
+                For image object detection (bounding box) tasks, this is the
+                [intersection-over-union
+
+                (IOU)](/vision/automl/object-detection/docs/evaluate#intersection-over-union)
+                threshold for the context of this point on the PR curve.
+            recall (float):
+                Recall value.
+            precision (float):
+                Precision value.
+            f1_score (float):
+                Harmonic mean of recall and precision.
+            recall_at1 (float):
+                Recall value for entries with label that has
+                highest score.
+            precision_at1 (float):
+                Precision value for entries with label that
+                has highest score.
+            f1_score_at1 (float):
+                The harmonic mean of
+                [recall_at1][google.cloud.datalabeling.v1beta1.PrCurve.ConfidenceMetricsEntry.recall_at1]
+                and
+                [precision_at1][google.cloud.datalabeling.v1beta1.PrCurve.ConfidenceMetricsEntry.precision_at1].
+            recall_at5 (float):
+                Recall value for entries with label that has
+                highest 5 scores.
+            precision_at5 (float):
+                Precision value for entries with label that
+                has highest 5 scores.
+            f1_score_at5 (float):
+                The harmonic mean of
+                [recall_at5][google.cloud.datalabeling.v1beta1.PrCurve.ConfidenceMetricsEntry.recall_at5]
+                and
+                [precision_at5][google.cloud.datalabeling.v1beta1.PrCurve.ConfidenceMetricsEntry.precision_at5].
+        """
+
+        confidence_threshold = proto.Field(proto.FLOAT, number=1)
+
+        recall = proto.Field(proto.FLOAT, number=2)
+
+        precision = proto.Field(proto.FLOAT, number=3)
+
+        f1_score = proto.Field(proto.FLOAT, number=4)
+
+        recall_at1 = proto.Field(proto.FLOAT, number=5)
+
+        precision_at1 = proto.Field(proto.FLOAT, number=6)
+
+        f1_score_at1 = proto.Field(proto.FLOAT, number=7)
+
+        recall_at5 = proto.Field(proto.FLOAT, number=8)
+
+        precision_at5 = proto.Field(proto.FLOAT, number=9)
+
+        f1_score_at5 = proto.Field(proto.FLOAT, number=10)
+
+    annotation_spec = proto.Field(
+        proto.MESSAGE, number=1, message=annotation_spec_set.AnnotationSpec,
+    )
+
+    area_under_curve = proto.Field(proto.FLOAT, number=2)
+
+    confidence_metrics_entries = proto.RepeatedField(
+        proto.MESSAGE, number=3, message=ConfidenceMetricsEntry,
+    )
+
+    mean_average_precision = proto.Field(proto.FLOAT, number=4)
+
+
+class ConfusionMatrix(proto.Message):
+    r"""Confusion matrix of the model running the classification.
+    Only applicable when the metrics entry aggregates multiple
+    labels. Not applicable when the entry is for a single label.
+
+    Attributes:
+        row (Sequence[~.evaluation.ConfusionMatrix.Row]):
+
+    """
+
+    class ConfusionMatrixEntry(proto.Message):
+        r"""
+
+        Attributes:
+            annotation_spec (~.annotation_spec_set.AnnotationSpec):
+                The annotation spec of a predicted label.
+            item_count (int):
+                Number of items predicted to have this label. (The ground
+                truth label for these items is the ``Row.annotationSpec`` of
+                this entry's parent.)
+        """
+
+        annotation_spec = proto.Field(
+            proto.MESSAGE, number=1, message=annotation_spec_set.AnnotationSpec,
+        )
+
+        item_count = proto.Field(proto.INT32, number=2)
+
+    class Row(proto.Message):
+        r"""A row in the confusion matrix. Each entry in this row has the
+        same ground truth label.
+
+        Attributes:
+            annotation_spec (~.annotation_spec_set.AnnotationSpec):
+                The annotation spec of the ground truth label
+                for this row.
+            entries (Sequence[~.evaluation.ConfusionMatrix.ConfusionMatrixEntry]):
+                A list of the confusion matrix entries. One
+                entry for each possible predicted label.
+        """
+
+        annotation_spec = proto.Field(
+            proto.MESSAGE, number=1, message=annotation_spec_set.AnnotationSpec,
+        )
+
+        entries = proto.RepeatedField(
+            proto.MESSAGE, number=2, message="ConfusionMatrix.ConfusionMatrixEntry",
+        )
+
+    row = proto.RepeatedField(proto.MESSAGE, number=1, message=Row,)
+
+
+__all__ = tuple(sorted(__protobuf__.manifest))

google/cloud/datalabeling_v1beta1/types/evaluation_job.py

@@ -0,0 +1,339 @@
+# -*- coding: utf-8 -*-
+
+# 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.
+#
+
+import proto  # type: ignore
+
+
+from google.cloud.datalabeling_v1beta1.types import dataset
+from google.cloud.datalabeling_v1beta1.types import evaluation
+from google.cloud.datalabeling_v1beta1.types import (
+    human_annotation_config as gcd_human_annotation_config,
+)
+from google.protobuf import timestamp_pb2 as timestamp  # type: ignore
+from google.rpc import status_pb2 as status  # type: ignore
+
+
+__protobuf__ = proto.module(
+    package="google.cloud.datalabeling.v1beta1",
+    manifest={
+        "EvaluationJob",
+        "EvaluationJobConfig",
+        "EvaluationJobAlertConfig",
+        "Attempt",
+    },
+)
+
+
+class EvaluationJob(proto.Message):
+    r"""Defines an evaluation job that runs periodically to generate
+    [Evaluations][google.cloud.datalabeling.v1beta1.Evaluation].
+    `Creating an evaluation
+    job </ml-engine/docs/continuous-evaluation/create-job>`__ is the
+    starting point for using continuous evaluation.
+
+    Attributes:
+        name (str):
+            Output only. After you create a job, Data Labeling Service
+            assigns a name to the job with the following format:
+
+            "projects/{project_id}/evaluationJobs/{evaluation_job_id}".
+        description (str):
+            Required. Description of the job. The
+            description can be up to 25,000 characters long.
+        state (~.evaluation_job.EvaluationJob.State):
+            Output only. Describes the current state of
+            the job.
+        schedule (str):
+            Required. Describes the interval at which the job runs. This
+            interval must be at least 1 day, and it is rounded to the
+            nearest day. For example, if you specify a 50-hour interval,
+            the job runs every 2 days.
+
+            You can provide the schedule in `crontab
+            format </scheduler/docs/configuring/cron-job-schedules>`__
+            or in an `English-like
+            format </appengine/docs/standard/python/config/cronref#schedule_format>`__.
+
+            Regardless of what you specify, the job will run at 10:00 AM
+            UTC. Only the interval from this schedule is used, not the
+            specific time of day.
+        model_version (str):
+            Required. The `AI Platform Prediction model
+            version </ml-engine/docs/prediction-overview>`__ to be
+            evaluated. Prediction input and output is sampled from this
+            model version. When creating an evaluation job, specify the
+            model version in the following format:
+
+            "projects/{project_id}/models/{model_name}/versions/{version_name}"
+
+            There can only be one evaluation job per model version.
+        evaluation_job_config (~.evaluation_job.EvaluationJobConfig):
+            Required. Configuration details for the
+            evaluation job.
+        annotation_spec_set (str):
+            Required. Name of the
+            [AnnotationSpecSet][google.cloud.datalabeling.v1beta1.AnnotationSpecSet]
+            describing all the labels that your machine learning model
+            outputs. You must create this resource before you create an
+            evaluation job and provide its name in the following format:
+
+            "projects/{project_id}/annotationSpecSets/{annotation_spec_set_id}".
+        label_missing_ground_truth (bool):
+            Required. Whether you want Data Labeling Service to provide
+            ground truth labels for prediction input. If you want the
+            service to assign human labelers to annotate your data, set
+            this to ``true``. If you want to provide your own ground
+            truth labels in the evaluation job's BigQuery table, set
+            this to ``false``.
+        attempts (Sequence[~.evaluation_job.Attempt]):
+            Output only. Every time the evaluation job
+            runs and an error occurs, the failed attempt is
+            appended to this array.
+        create_time (~.timestamp.Timestamp):
+            Output only. Timestamp of when this
+            evaluation job was created.
+    """
+
+    class State(proto.Enum):
+        r"""State of the job."""
+        STATE_UNSPECIFIED = 0
+        SCHEDULED = 1
+        RUNNING = 2
+        PAUSED = 3
+        STOPPED = 4
+
+    name = proto.Field(proto.STRING, number=1)
+
+    description = proto.Field(proto.STRING, number=2)
+
+    state = proto.Field(proto.ENUM, number=3, enum=State,)
+
+    schedule = proto.Field(proto.STRING, number=4)
+
+    model_version = proto.Field(proto.STRING, number=5)
+
+    evaluation_job_config = proto.Field(
+        proto.MESSAGE, number=6, message="EvaluationJobConfig",
+    )
+
+    annotation_spec_set = proto.Field(proto.STRING, number=7)
+
+    label_missing_ground_truth = proto.Field(proto.BOOL, number=8)
+
+    attempts = proto.RepeatedField(proto.MESSAGE, number=9, message="Attempt",)
+
+    create_time = proto.Field(proto.MESSAGE, number=10, message=timestamp.Timestamp,)
+
+
+class EvaluationJobConfig(proto.Message):
+    r"""Configures specific details of how a continuous evaluation
+    job works. Provide this configuration when you create an
+    EvaluationJob.
+
+    Attributes:
+        image_classification_config (~.gcd_human_annotation_config.ImageClassificationConfig):
+            Specify this field if your model version performs image
+            classification or general classification.
+
+            ``annotationSpecSet`` in this configuration must match
+            [EvaluationJob.annotationSpecSet][google.cloud.datalabeling.v1beta1.EvaluationJob.annotation_spec_set].
+            ``allowMultiLabel`` in this configuration must match
+            ``classificationMetadata.isMultiLabel`` in
+            [input_config][google.cloud.datalabeling.v1beta1.EvaluationJobConfig.input_config].
+        bounding_poly_config (~.gcd_human_annotation_config.BoundingPolyConfig):
+            Specify this field if your model version performs image
+            object detection (bounding box detection).
+
+            ``annotationSpecSet`` in this configuration must match
+            [EvaluationJob.annotationSpecSet][google.cloud.datalabeling.v1beta1.EvaluationJob.annotation_spec_set].
+        text_classification_config (~.gcd_human_annotation_config.TextClassificationConfig):
+            Specify this field if your model version performs text
+            classification.
+
+            ``annotationSpecSet`` in this configuration must match
+            [EvaluationJob.annotationSpecSet][google.cloud.datalabeling.v1beta1.EvaluationJob.annotation_spec_set].
+            ``allowMultiLabel`` in this configuration must match
+            ``classificationMetadata.isMultiLabel`` in
+            [input_config][google.cloud.datalabeling.v1beta1.EvaluationJobConfig.input_config].
+        input_config (~.dataset.InputConfig):
+            Rquired. Details for the sampled prediction input. Within
+            this configuration, there are requirements for several
+            fields:
+
+            -  ``dataType`` must be one of ``IMAGE``, ``TEXT``, or
+               ``GENERAL_DATA``.
+            -  ``annotationType`` must be one of
+               ``IMAGE_CLASSIFICATION_ANNOTATION``,
+               ``TEXT_CLASSIFICATION_ANNOTATION``,
+               ``GENERAL_CLASSIFICATION_ANNOTATION``, or
+               ``IMAGE_BOUNDING_BOX_ANNOTATION`` (image object
+               detection).
+            -  If your machine learning model performs classification,
+               you must specify ``classificationMetadata.isMultiLabel``.
+            -  You must specify ``bigquerySource`` (not ``gcsSource``).
+        evaluation_config (~.evaluation.EvaluationConfig):
+            Required. Details for calculating evaluation metrics and
+            creating
+            [Evaulations][google.cloud.datalabeling.v1beta1.Evaluation].
+            If your model version performs image object detection, you
+            must specify the ``boundingBoxEvaluationOptions`` field
+            within this configuration. Otherwise, provide an empty
+            object for this configuration.
+        human_annotation_config (~.gcd_human_annotation_config.HumanAnnotationConfig):
+            Optional. Details for human annotation of your data. If you
+            set
+            [labelMissingGroundTruth][google.cloud.datalabeling.v1beta1.EvaluationJob.label_missing_ground_truth]
+            to ``true`` for this evaluation job, then you must specify
+            this field. If you plan to provide your own ground truth
+            labels, then omit this field.
+
+            Note that you must create an
+            [Instruction][google.cloud.datalabeling.v1beta1.Instruction]
+            resource before you can specify this field. Provide the name
+            of the instruction resource in the ``instruction`` field
+            within this configuration.
+        bigquery_import_keys (Sequence[~.evaluation_job.EvaluationJobConfig.BigqueryImportKeysEntry]):
+            Required. Prediction keys that tell Data Labeling Service
+            where to find the data for evaluation in your BigQuery
+            table. When the service samples prediction input and output
+            from your model version and saves it to BigQuery, the data
+            gets stored as JSON strings in the BigQuery table. These
+            keys tell Data Labeling Service how to parse the JSON.
+
+            You can provide the following entries in this field:
+
+            -  ``data_json_key``: the data key for prediction input. You
+               must provide either this key or ``reference_json_key``.
+            -  ``reference_json_key``: the data reference key for
+               prediction input. You must provide either this key or
+               ``data_json_key``.
+            -  ``label_json_key``: the label key for prediction output.
+               Required.
+            -  ``label_score_json_key``: the score key for prediction
+               output. Required.
+            -  ``bounding_box_json_key``: the bounding box key for
+               prediction output. Required if your model version perform
+               image object detection.
+
+            Learn `how to configure prediction
+            keys </ml-engine/docs/continuous-evaluation/create-job#prediction-keys>`__.
+        example_count (int):
+            Required. The maximum number of predictions to sample and
+            save to BigQuery during each [evaluation
+            interval][google.cloud.datalabeling.v1beta1.EvaluationJob.schedule].
+            This limit overrides ``example_sample_percentage``: even if
+            the service has not sampled enough predictions to fulfill
+            ``example_sample_perecentage`` during an interval, it stops
+            sampling predictions when it meets this limit.
+        example_sample_percentage (float):
+            Required. Fraction of predictions to sample and save to
+            BigQuery during each [evaluation
+            interval][google.cloud.datalabeling.v1beta1.EvaluationJob.schedule].
+            For example, 0.1 means 10% of predictions served by your
+            model version get saved to BigQuery.
+        evaluation_job_alert_config (~.evaluation_job.EvaluationJobAlertConfig):
+            Optional. Configuration details for
+            evaluation job alerts. Specify this field if you
+            want to receive email alerts if the evaluation
+            job finds that your predictions have low mean
+            average precision during a run.
+    """
+
+    image_classification_config = proto.Field(
+        proto.MESSAGE,
+        number=4,
+        oneof="human_annotation_request_config",
+        message=gcd_human_annotation_config.ImageClassificationConfig,
+    )
+
+    bounding_poly_config = proto.Field(
+        proto.MESSAGE,
+        number=5,
+        oneof="human_annotation_request_config",
+        message=gcd_human_annotation_config.BoundingPolyConfig,
+    )
+
+    text_classification_config = proto.Field(
+        proto.MESSAGE,
+        number=8,
+        oneof="human_annotation_request_config",
+        message=gcd_human_annotation_config.TextClassificationConfig,
+    )
+
+    input_config = proto.Field(proto.MESSAGE, number=1, message=dataset.InputConfig,)
+
+    evaluation_config = proto.Field(
+        proto.MESSAGE, number=2, message=evaluation.EvaluationConfig,
+    )
+
+    human_annotation_config = proto.Field(
+        proto.MESSAGE,
+        number=3,
+        message=gcd_human_annotation_config.HumanAnnotationConfig,
+    )
+
+    bigquery_import_keys = proto.MapField(proto.STRING, proto.STRING, number=9)
+
+    example_count = proto.Field(proto.INT32, number=10)
+
+    example_sample_percentage = proto.Field(proto.DOUBLE, number=11)
+
+    evaluation_job_alert_config = proto.Field(
+        proto.MESSAGE, number=13, message="EvaluationJobAlertConfig",
+    )
+
+
+class EvaluationJobAlertConfig(proto.Message):
+    r"""Provides details for how an evaluation job sends email alerts
+    based on the results of a run.
+
+    Attributes:
+        email (str):
+            Required. An email address to send alerts to.
+        min_acceptable_mean_average_precision (float):
+            Required. A number between 0 and 1 that describes a minimum
+            mean average precision threshold. When the evaluation job
+            runs, if it calculates that your model version's predictions
+            from the recent interval have
+            [meanAveragePrecision][google.cloud.datalabeling.v1beta1.PrCurve.mean_average_precision]
+            below this threshold, then it sends an alert to your
+            specified email.
+    """
+
+    email = proto.Field(proto.STRING, number=1)
+
+    min_acceptable_mean_average_precision = proto.Field(proto.DOUBLE, number=2)
+
+
+class Attempt(proto.Message):
+    r"""Records a failed evaluation job run.
+
+    Attributes:
+        attempt_time (~.timestamp.Timestamp):
+
+        partial_failures (Sequence[~.status.Status]):
+            Details of errors that occurred.
+    """
+
+    attempt_time = proto.Field(proto.MESSAGE, number=1, message=timestamp.Timestamp,)
+
+    partial_failures = proto.RepeatedField(
+        proto.MESSAGE, number=2, message=status.Status,
+    )
+
+
+__all__ = tuple(sorted(__protobuf__.manifest))