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.model

# -*- 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={"Model",},)


[docs]class Model(proto.Message): r"""API proto representing a trained machine learning model. Attributes: translation_model_metadata (google.cloud.automl_v1beta1.types.TranslationModelMetadata): Metadata for translation models. image_classification_model_metadata (google.cloud.automl_v1beta1.types.ImageClassificationModelMetadata): Metadata for image classification models. text_classification_model_metadata (google.cloud.automl_v1beta1.types.TextClassificationModelMetadata): Metadata for text classification models. image_object_detection_model_metadata (google.cloud.automl_v1beta1.types.ImageObjectDetectionModelMetadata): Metadata for image object detection models. video_classification_model_metadata (google.cloud.automl_v1beta1.types.VideoClassificationModelMetadata): Metadata for video classification models. video_object_tracking_model_metadata (google.cloud.automl_v1beta1.types.VideoObjectTrackingModelMetadata): Metadata for video object tracking models. text_extraction_model_metadata (google.cloud.automl_v1beta1.types.TextExtractionModelMetadata): Metadata for text extraction models. tables_model_metadata (google.cloud.automl_v1beta1.types.TablesModelMetadata): Metadata for Tables models. text_sentiment_model_metadata (google.cloud.automl_v1beta1.types.TextSentimentModelMetadata): Metadata for text sentiment models. name (str): Output only. Resource name of the model. Format: ``projects/{project_id}/locations/{location_id}/models/{model_id}`` display_name (str): Required. The name of the model 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. It must start with a letter. dataset_id (str): Required. The resource ID of the dataset used to create the model. The dataset must come from the same ancestor project and location. create_time (google.protobuf.timestamp_pb2.Timestamp): Output only. Timestamp when the model training finished and can be used for prediction. update_time (google.protobuf.timestamp_pb2.Timestamp): Output only. Timestamp when this model was last updated. deployment_state (google.cloud.automl_v1beta1.types.Model.DeploymentState): Output only. Deployment state of the model. A model can only serve prediction requests after it gets deployed. """
[docs] class DeploymentState(proto.Enum): r"""Deployment state of the model.""" DEPLOYMENT_STATE_UNSPECIFIED = 0 DEPLOYED = 1 UNDEPLOYED = 2
translation_model_metadata = proto.Field( proto.MESSAGE, number=15, oneof="model_metadata", message=translation.TranslationModelMetadata, ) image_classification_model_metadata = proto.Field( proto.MESSAGE, number=13, oneof="model_metadata", message=image.ImageClassificationModelMetadata, ) text_classification_model_metadata = proto.Field( proto.MESSAGE, number=14, oneof="model_metadata", message=text.TextClassificationModelMetadata, ) image_object_detection_model_metadata = proto.Field( proto.MESSAGE, number=20, oneof="model_metadata", message=image.ImageObjectDetectionModelMetadata, ) video_classification_model_metadata = proto.Field( proto.MESSAGE, number=23, oneof="model_metadata", message=video.VideoClassificationModelMetadata, ) video_object_tracking_model_metadata = proto.Field( proto.MESSAGE, number=21, oneof="model_metadata", message=video.VideoObjectTrackingModelMetadata, ) text_extraction_model_metadata = proto.Field( proto.MESSAGE, number=19, oneof="model_metadata", message=text.TextExtractionModelMetadata, ) tables_model_metadata = proto.Field( proto.MESSAGE, number=24, oneof="model_metadata", message=tables.TablesModelMetadata, ) text_sentiment_model_metadata = proto.Field( proto.MESSAGE, number=22, oneof="model_metadata", message=text.TextSentimentModelMetadata, ) name = proto.Field(proto.STRING, number=1,) display_name = proto.Field(proto.STRING, number=2,) dataset_id = proto.Field(proto.STRING, number=3,) create_time = proto.Field(proto.MESSAGE, number=7, message=timestamp_pb2.Timestamp,) update_time = proto.Field( proto.MESSAGE, number=11, message=timestamp_pb2.Timestamp, ) deployment_state = proto.Field(proto.ENUM, number=8, enum=DeploymentState,)
__all__ = tuple(sorted(__protobuf__.manifest))