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_v1.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_v1.types import image
from google.cloud.automl_v1.types import text
from google.cloud.automl_v1.types import translation
from google.protobuf import timestamp_pb2 # type: ignore
__protobuf__ = proto.module(package="google.cloud.automl.v1", 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_v1.types.TranslationDatasetMetadata):
Metadata for a dataset used for translation.
image_classification_dataset_metadata (google.cloud.automl_v1.types.ImageClassificationDatasetMetadata):
Metadata for a dataset used for image
classification.
text_classification_dataset_metadata (google.cloud.automl_v1.types.TextClassificationDatasetMetadata):
Metadata for a dataset used for text
classification.
image_object_detection_dataset_metadata (google.cloud.automl_v1.types.ImageObjectDetectionDatasetMetadata):
Metadata for a dataset used for image object
detection.
text_extraction_dataset_metadata (google.cloud.automl_v1.types.TextExtractionDatasetMetadata):
Metadata for a dataset used for text
extraction.
text_sentiment_dataset_metadata (google.cloud.automl_v1.types.TextSentimentDatasetMetadata):
Metadata for a dataset used for text
sentiment.
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.
labels (Sequence[google.cloud.automl_v1.types.Dataset.LabelsEntry]):
Optional. The labels with user-defined
metadata to organize your dataset.
Label keys and values can be no longer than 64
characters (Unicode codepoints), can only
contain lowercase letters, numeric characters,
underscores and dashes. International characters
are allowed. Label values are optional. Label
keys must start with a letter.
See https://goo.gl/xmQnxf for more information
on and examples of labels.
"""
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,
)
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,
)
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,)
labels = proto.MapField(proto.STRING, proto.STRING, number=39,)
__all__ = tuple(sorted(__protobuf__.manifest))