As of January 1, 2020 this library no longer supports Python 2 on the latest released version. Library versions released prior to that date will continue to be available. For more information please visit Python 2 support on Google Cloud.

Source code for google.cloud.automl_v1beta1.types.dataset

# -*- 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.automl_v1beta1.types import image
from google.cloud.automl_v1beta1.types import tables
from google.cloud.automl_v1beta1.types import text
from google.cloud.automl_v1beta1.types import translation
from google.cloud.automl_v1beta1.types import video
from google.protobuf import timestamp_pb2  # type: ignore


__protobuf__ = proto.module(
    package="google.cloud.automl.v1beta1", manifest={"Dataset",},
)


[docs]class Dataset(proto.Message): r"""A workspace for solving a single, particular machine learning (ML) problem. A workspace contains examples that may be annotated. Attributes: translation_dataset_metadata (google.cloud.automl_v1beta1.types.TranslationDatasetMetadata): Metadata for a dataset used for translation. image_classification_dataset_metadata (google.cloud.automl_v1beta1.types.ImageClassificationDatasetMetadata): Metadata for a dataset used for image classification. text_classification_dataset_metadata (google.cloud.automl_v1beta1.types.TextClassificationDatasetMetadata): Metadata for a dataset used for text classification. image_object_detection_dataset_metadata (google.cloud.automl_v1beta1.types.ImageObjectDetectionDatasetMetadata): Metadata for a dataset used for image object detection. video_classification_dataset_metadata (google.cloud.automl_v1beta1.types.VideoClassificationDatasetMetadata): Metadata for a dataset used for video classification. video_object_tracking_dataset_metadata (google.cloud.automl_v1beta1.types.VideoObjectTrackingDatasetMetadata): Metadata for a dataset used for video object tracking. text_extraction_dataset_metadata (google.cloud.automl_v1beta1.types.TextExtractionDatasetMetadata): Metadata for a dataset used for text extraction. text_sentiment_dataset_metadata (google.cloud.automl_v1beta1.types.TextSentimentDatasetMetadata): Metadata for a dataset used for text sentiment. tables_dataset_metadata (google.cloud.automl_v1beta1.types.TablesDatasetMetadata): Metadata for a dataset used for Tables. name (str): Output only. The resource name of the dataset. Form: ``projects/{project_id}/locations/{location_id}/datasets/{dataset_id}`` display_name (str): Required. The name of the dataset to show in the interface. The name can be up to 32 characters long and can consist only of ASCII Latin letters A-Z and a-z, underscores (_), and ASCII digits 0-9. description (str): User-provided description of the dataset. The description can be up to 25000 characters long. example_count (int): Output only. The number of examples in the dataset. create_time (google.protobuf.timestamp_pb2.Timestamp): Output only. Timestamp when this dataset was created. etag (str): Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens. """ translation_dataset_metadata = proto.Field( proto.MESSAGE, number=23, oneof="dataset_metadata", message=translation.TranslationDatasetMetadata, ) image_classification_dataset_metadata = proto.Field( proto.MESSAGE, number=24, oneof="dataset_metadata", message=image.ImageClassificationDatasetMetadata, ) text_classification_dataset_metadata = proto.Field( proto.MESSAGE, number=25, oneof="dataset_metadata", message=text.TextClassificationDatasetMetadata, ) image_object_detection_dataset_metadata = proto.Field( proto.MESSAGE, number=26, oneof="dataset_metadata", message=image.ImageObjectDetectionDatasetMetadata, ) video_classification_dataset_metadata = proto.Field( proto.MESSAGE, number=31, oneof="dataset_metadata", message=video.VideoClassificationDatasetMetadata, ) video_object_tracking_dataset_metadata = proto.Field( proto.MESSAGE, number=29, oneof="dataset_metadata", message=video.VideoObjectTrackingDatasetMetadata, ) text_extraction_dataset_metadata = proto.Field( proto.MESSAGE, number=28, oneof="dataset_metadata", message=text.TextExtractionDatasetMetadata, ) text_sentiment_dataset_metadata = proto.Field( proto.MESSAGE, number=30, oneof="dataset_metadata", message=text.TextSentimentDatasetMetadata, ) tables_dataset_metadata = proto.Field( proto.MESSAGE, number=33, oneof="dataset_metadata", message=tables.TablesDatasetMetadata, ) name = proto.Field(proto.STRING, number=1,) display_name = proto.Field(proto.STRING, number=2,) description = proto.Field(proto.STRING, number=3,) example_count = proto.Field(proto.INT32, number=21,) create_time = proto.Field( proto.MESSAGE, number=14, message=timestamp_pb2.Timestamp, ) etag = proto.Field(proto.STRING, number=17,)
__all__ = tuple(sorted(__protobuf__.manifest))