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))