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))