Class AutoMlAsyncClient

AutoML Server API.

The resource names are assigned by the server. The server never reuses names that it has created after the resources with those names are deleted.

An ID of a resource is the last element of the item's resource name. For projects/{project_id}/locations/{location_id}/datasets/{dataset_id}, then the id for the item is {dataset_id}.

Currently the only supported location_id is "us-central1".

On any input that is documented to expect a string parameter in snake_case or kebab-case, either of those cases is accepted.

Inheritance

builtins.object > AutoMlAsyncClient

Properties

transport

Returns the transport used by the client instance.

Returns
TypeDescription
AutoMlTransportThe transport used by the client instance.

Methods

annotation_spec_path

annotation_spec_path(
    project: str, location: str, dataset: str, annotation_spec: str
)

Returns a fully-qualified annotation_spec string.

Parameters
NameDescription
project str
location str
dataset str
annotation_spec str

column_spec_path

column_spec_path(
    project: str, location: str, dataset: str, table_spec: str, column_spec: str
)

Returns a fully-qualified column_spec string.

Parameters
NameDescription
project str
location str
dataset str
table_spec str
column_spec str

common_billing_account_path

common_billing_account_path(billing_account: str)

Returns a fully-qualified billing_account string.

Parameter
NameDescription
billing_account str

common_folder_path

common_folder_path(folder: str)

Returns a fully-qualified folder string.

Parameter
NameDescription
folder str

common_location_path

common_location_path(project: str, location: str)

Returns a fully-qualified location string.

Parameters
NameDescription
project str
location str

common_organization_path

common_organization_path(organization: str)

Returns a fully-qualified organization string.

Parameter
NameDescription
organization str

common_project_path

common_project_path(project: str)

Returns a fully-qualified project string.

Parameter
NameDescription
project str

create_dataset

create_dataset(request: Optional[Union[google.cloud.automl_v1beta1.types.service.CreateDatasetRequest, dict]] = None, *, parent: Optional[str] = None, dataset: Optional[google.cloud.automl_v1beta1.types.dataset.Dataset] = None, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())

Creates a dataset.

Parameters
NameDescription
request Union[google.cloud.automl_v1beta1.types.CreateDatasetRequest, dict]

The request object. Request message for AutoMl.CreateDataset.

parent `str`

Required. The resource name of the project to create the dataset for. This corresponds to the parent field on the request instance; if request is provided, this should not be set.

dataset Dataset

Required. The dataset to create. This corresponds to the dataset field on the request instance; if request is provided, this should not be set.

retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.

timeout float

The timeout for this request.

metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.

Returns
TypeDescription
google.cloud.automl_v1beta1.types.DatasetA workspace for solving a single, particular machine learning (ML) problem. A workspace contains examples that may be annotated.

create_model

create_model(request: Optional[Union[google.cloud.automl_v1beta1.types.service.CreateModelRequest, dict]] = None, *, parent: Optional[str] = None, model: Optional[google.cloud.automl_v1beta1.types.model.Model] = None, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())

Creates a model. Returns a Model in the response][google.longrunning.Operation.response] field when it completes. When you create a model, several model evaluations are created for it: a global evaluation, and one evaluation for each annotation spec.

Parameters
NameDescription
request Union[google.cloud.automl_v1beta1.types.CreateModelRequest, dict]

The request object. Request message for AutoMl.CreateModel.

parent `str`

Required. Resource name of the parent project where the model is being created. This corresponds to the parent field on the request instance; if request is provided, this should not be set.

model Model

Required. The model to create. This corresponds to the model field on the request instance; if request is provided, this should not be set.

retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.

timeout float

The timeout for this request.

metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.

Returns
TypeDescription
google.api_core.operation_async.AsyncOperationAn object representing a long-running operation. The result type for the operation will be Model API proto representing a trained machine learning model.

dataset_path

dataset_path(project: str, location: str, dataset: str)

Returns a fully-qualified dataset string.

Parameters
NameDescription
project str
location str
dataset str

delete_dataset

delete_dataset(request: Optional[Union[google.cloud.automl_v1beta1.types.service.DeleteDatasetRequest, dict]] = None, *, name: Optional[str] = None, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())

Deletes a dataset and all of its contents. Returns empty response in the response][google.longrunning.Operation.response] field when it completes, and delete_details in the metadata][google.longrunning.Operation.metadata] field.

Parameters
NameDescription
request Union[google.cloud.automl_v1beta1.types.DeleteDatasetRequest, dict]

The request object. Request message for AutoMl.DeleteDataset.

name `str`

Required. The resource name of the dataset to delete. This corresponds to the name field on the request instance; if request is provided, this should not be set.

retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.

timeout float

The timeout for this request.

metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.

Returns
TypeDescription
google.api_core.operation_async.AsyncOperationAn object representing a long-running operation. The result type for the operation will be `google.protobuf.empty_pb2.Empty` A generic empty message that you can re-use to avoid defining duplicated empty messages in your APIs. A typical example is to use it as the request or the response type of an API method. For instance: service Foo { rpc Bar(google.protobuf.Empty) returns (google.protobuf.Empty); } The JSON representation for Empty is empty JSON object {}.

delete_model

delete_model(request: Optional[Union[google.cloud.automl_v1beta1.types.service.DeleteModelRequest, dict]] = None, *, name: Optional[str] = None, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())

Deletes a model. Returns google.protobuf.Empty in the response][google.longrunning.Operation.response] field when it completes, and delete_details in the metadata][google.longrunning.Operation.metadata] field.

Parameters
NameDescription
request Union[google.cloud.automl_v1beta1.types.DeleteModelRequest, dict]

The request object. Request message for AutoMl.DeleteModel.

name `str`

Required. Resource name of the model being deleted. This corresponds to the name field on the request instance; if request is provided, this should not be set.

retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.

timeout float

The timeout for this request.

metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.

Returns
TypeDescription
google.api_core.operation_async.AsyncOperationAn object representing a long-running operation. The result type for the operation will be `google.protobuf.empty_pb2.Empty` A generic empty message that you can re-use to avoid defining duplicated empty messages in your APIs. A typical example is to use it as the request or the response type of an API method. For instance: service Foo { rpc Bar(google.protobuf.Empty) returns (google.protobuf.Empty); } The JSON representation for Empty is empty JSON object {}.

deploy_model

deploy_model(request: Optional[Union[google.cloud.automl_v1beta1.types.service.DeployModelRequest, dict]] = None, *, name: Optional[str] = None, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())

Deploys a model. If a model is already deployed, deploying it with the same parameters has no effect. Deploying with different parametrs (as e.g. changing

xref_node_number) will reset the deployment state without pausing the model's availability.

Only applicable for Text Classification, Image Object Detection , Tables, and Image Segmentation; all other domains manage deployment automatically.

Returns an empty response in the response][google.longrunning.Operation.response] field when it completes.

Parameters
NameDescription
request Union[google.cloud.automl_v1beta1.types.DeployModelRequest, dict]

The request object. Request message for AutoMl.DeployModel.

name `str`

Required. Resource name of the model to deploy. This corresponds to the name field on the request instance; if request is provided, this should not be set.

retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.

timeout float

The timeout for this request.

metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.

Returns
TypeDescription
google.api_core.operation_async.AsyncOperationAn object representing a long-running operation. The result type for the operation will be `google.protobuf.empty_pb2.Empty` A generic empty message that you can re-use to avoid defining duplicated empty messages in your APIs. A typical example is to use it as the request or the response type of an API method. For instance: service Foo { rpc Bar(google.protobuf.Empty) returns (google.protobuf.Empty); } The JSON representation for Empty is empty JSON object {}.

export_data

export_data(request: Optional[Union[google.cloud.automl_v1beta1.types.service.ExportDataRequest, dict]] = None, *, name: Optional[str] = None, output_config: Optional[google.cloud.automl_v1beta1.types.io.OutputConfig] = None, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())

Exports dataset's data to the provided output location. Returns an empty response in the response][google.longrunning.Operation.response] field when it completes.

Parameters
NameDescription
request Union[google.cloud.automl_v1beta1.types.ExportDataRequest, dict]

The request object. Request message for AutoMl.ExportData.

name `str`

Required. The resource name of the dataset. This corresponds to the name field on the request instance; if request is provided, this should not be set.

output_config OutputConfig

Required. The desired output location. This corresponds to the output_config field on the request instance; if request is provided, this should not be set.

retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.

timeout float

The timeout for this request.

metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.

Returns
TypeDescription
google.api_core.operation_async.AsyncOperationAn object representing a long-running operation. The result type for the operation will be `google.protobuf.empty_pb2.Empty` A generic empty message that you can re-use to avoid defining duplicated empty messages in your APIs. A typical example is to use it as the request or the response type of an API method. For instance: service Foo { rpc Bar(google.protobuf.Empty) returns (google.protobuf.Empty); } The JSON representation for Empty is empty JSON object {}.

export_evaluated_examples

export_evaluated_examples(request: Optional[Union[google.cloud.automl_v1beta1.types.service.ExportEvaluatedExamplesRequest, dict]] = None, *, name: Optional[str] = None, output_config: Optional[google.cloud.automl_v1beta1.types.io.ExportEvaluatedExamplesOutputConfig] = None, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())

Exports examples on which the model was evaluated (i.e. which were in the TEST set of the dataset the model was created from), together with their ground truth annotations and the annotations created (predicted) by the model. The examples, ground truth and predictions are exported in the state they were at the moment the model was evaluated.

This export is available only for 30 days since the model evaluation is created.

Currently only available for Tables.

Returns an empty response in the response][google.longrunning.Operation.response] field when it completes.

Parameters
NameDescription
request Union[google.cloud.automl_v1beta1.types.ExportEvaluatedExamplesRequest, dict]

The request object. Request message for AutoMl.ExportEvaluatedExamples.

name `str`

Required. The resource name of the model whose evaluated examples are to be exported. This corresponds to the name field on the request instance; if request is provided, this should not be set.

output_config ExportEvaluatedExamplesOutputConfig

Required. The desired output location and configuration. This corresponds to the output_config field on the request instance; if request is provided, this should not be set.

retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.

timeout float

The timeout for this request.

metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.

Returns
TypeDescription
google.api_core.operation_async.AsyncOperationAn object representing a long-running operation. The result type for the operation will be `google.protobuf.empty_pb2.Empty` A generic empty message that you can re-use to avoid defining duplicated empty messages in your APIs. A typical example is to use it as the request or the response type of an API method. For instance: service Foo { rpc Bar(google.protobuf.Empty) returns (google.protobuf.Empty); } The JSON representation for Empty is empty JSON object {}.

export_model

export_model(request: Optional[Union[google.cloud.automl_v1beta1.types.service.ExportModelRequest, dict]] = None, *, name: Optional[str] = None, output_config: Optional[google.cloud.automl_v1beta1.types.io.ModelExportOutputConfig] = None, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())

Exports a trained, "export-able", model to a user specified Google Cloud Storage location. A model is considered export-able if and only if it has an export format defined for it in

xref_ModelExportOutputConfig.

Returns an empty response in the response][google.longrunning.Operation.response] field when it completes.

Parameters
NameDescription
request Union[google.cloud.automl_v1beta1.types.ExportModelRequest, dict]

The request object. Request message for AutoMl.ExportModel. Models need to be enabled for exporting, otherwise an error code will be returned.

name `str`

Required. The resource name of the model to export. This corresponds to the name field on the request instance; if request is provided, this should not be set.

output_config ModelExportOutputConfig

Required. The desired output location and configuration. This corresponds to the output_config field on the request instance; if request is provided, this should not be set.

retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.

timeout float

The timeout for this request.

metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.

Returns
TypeDescription
google.api_core.operation_async.AsyncOperationAn object representing a long-running operation. The result type for the operation will be `google.protobuf.empty_pb2.Empty` A generic empty message that you can re-use to avoid defining duplicated empty messages in your APIs. A typical example is to use it as the request or the response type of an API method. For instance: service Foo { rpc Bar(google.protobuf.Empty) returns (google.protobuf.Empty); } The JSON representation for Empty is empty JSON object {}.

from_service_account_file

from_service_account_file(filename: str, *args, **kwargs)

Creates an instance of this client using the provided credentials file.

Parameters
NameDescription
filename str

The path to the service account private key json file.

args

Additional arguments to pass to the constructor.

kwargs

Additional arguments to pass to the constructor.

Returns
TypeDescription
AutoMlAsyncClientThe constructed client.

from_service_account_info

from_service_account_info(info: dict, *args, **kwargs)

Creates an instance of this client using the provided credentials info.

Parameters
NameDescription
info dict

The service account private key info.

args

Additional arguments to pass to the constructor.

kwargs

Additional arguments to pass to the constructor.

Returns
TypeDescription
AutoMlAsyncClientThe constructed client.

from_service_account_json

from_service_account_json(filename: str, *args, **kwargs)

Creates an instance of this client using the provided credentials file.

Parameters
NameDescription
filename str

The path to the service account private key json file.

args

Additional arguments to pass to the constructor.

kwargs

Additional arguments to pass to the constructor.

Returns
TypeDescription
AutoMlAsyncClientThe constructed client.

get_annotation_spec

get_annotation_spec(request: Optional[Union[google.cloud.automl_v1beta1.types.service.GetAnnotationSpecRequest, dict]] = None, *, name: Optional[str] = None, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())

Gets an annotation spec.

Parameters
NameDescription
request Union[google.cloud.automl_v1beta1.types.GetAnnotationSpecRequest, dict]

The request object. Request message for AutoMl.GetAnnotationSpec.

name `str`

Required. The resource name of the annotation spec to retrieve. This corresponds to the name field on the request instance; if request is provided, this should not be set.

retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.

timeout float

The timeout for this request.

metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.

Returns
TypeDescription
google.cloud.automl_v1beta1.types.AnnotationSpecA definition of an annotation spec.

get_column_spec

get_column_spec(request: Optional[Union[google.cloud.automl_v1beta1.types.service.GetColumnSpecRequest, dict]] = None, *, name: Optional[str] = None, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())

Gets a column spec.

Parameters
NameDescription
request Union[google.cloud.automl_v1beta1.types.GetColumnSpecRequest, dict]

The request object. Request message for AutoMl.GetColumnSpec.

name `str`

Required. The resource name of the column spec to retrieve. This corresponds to the name field on the request instance; if request is provided, this should not be set.

retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.

timeout float

The timeout for this request.

metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.

Returns
TypeDescription
google.cloud.automl_v1beta1.types.ColumnSpecA representation of a column in a relational table. When listing them, column specs are returned in the same order in which they were given on import . Used by: \* Tables

get_dataset

get_dataset(request: Optional[Union[google.cloud.automl_v1beta1.types.service.GetDatasetRequest, dict]] = None, *, name: Optional[str] = None, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())

Gets a dataset.

Parameters
NameDescription
request Union[google.cloud.automl_v1beta1.types.GetDatasetRequest, dict]

The request object. Request message for AutoMl.GetDataset.

name `str`

Required. The resource name of the dataset to retrieve. This corresponds to the name field on the request instance; if request is provided, this should not be set.

retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.

timeout float

The timeout for this request.

metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.

Returns
TypeDescription
google.cloud.automl_v1beta1.types.DatasetA workspace for solving a single, particular machine learning (ML) problem. A workspace contains examples that may be annotated.

get_model

get_model(request: Optional[Union[google.cloud.automl_v1beta1.types.service.GetModelRequest, dict]] = None, *, name: Optional[str] = None, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())

Gets a model.

Parameters
NameDescription
request Union[google.cloud.automl_v1beta1.types.GetModelRequest, dict]

The request object. Request message for AutoMl.GetModel.

name `str`

Required. Resource name of the model. This corresponds to the name field on the request instance; if request is provided, this should not be set.

retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.

timeout float

The timeout for this request.

metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.

Returns
TypeDescription
google.cloud.automl_v1beta1.types.ModelAPI proto representing a trained machine learning model.

get_model_evaluation

get_model_evaluation(request: Optional[Union[google.cloud.automl_v1beta1.types.service.GetModelEvaluationRequest, dict]] = None, *, name: Optional[str] = None, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())

Gets a model evaluation.

Parameters
NameDescription
request Union[google.cloud.automl_v1beta1.types.GetModelEvaluationRequest, dict]

The request object. Request message for AutoMl.GetModelEvaluation.

name `str`

Required. Resource name for the model evaluation. This corresponds to the name field on the request instance; if request is provided, this should not be set.

retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.

timeout float

The timeout for this request.

metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.

Returns
TypeDescription
google.cloud.automl_v1beta1.types.ModelEvaluationEvaluation results of a model.

get_table_spec

get_table_spec(request: Optional[Union[google.cloud.automl_v1beta1.types.service.GetTableSpecRequest, dict]] = None, *, name: Optional[str] = None, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())

Gets a table spec.

Parameters
NameDescription
request Union[google.cloud.automl_v1beta1.types.GetTableSpecRequest, dict]

The request object. Request message for AutoMl.GetTableSpec.

name `str`

Required. The resource name of the table spec to retrieve. This corresponds to the name field on the request instance; if request is provided, this should not be set.

retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.

timeout float

The timeout for this request.

metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.

Returns
TypeDescription
google.cloud.automl_v1beta1.types.TableSpecA specification of a relational table. The table's schema is represented via its child column specs. It is pre-populated as part of ImportData by schema inference algorithm, the version of which is a required parameter of ImportData InputConfig. Note: While working with a table, at times the schema may be inconsistent with the data in the table (e.g. string in a FLOAT64 column). The consistency validation is done upon creation of a model. Used by: \* Tables

get_transport_class

get_transport_class()

partial(func, *args, **keywords) - new function with partial application of the given arguments and keywords.

Parameter
NameDescription
label str

import_data

import_data(request: Optional[Union[google.cloud.automl_v1beta1.types.service.ImportDataRequest, dict]] = None, *, name: Optional[str] = None, input_config: Optional[google.cloud.automl_v1beta1.types.io.InputConfig] = None, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())

Imports data into a dataset. For Tables this method can only be called on an empty Dataset.

For Tables:

  • A xref_schema_inference_version parameter must be explicitly set. Returns an empty response in the response][google.longrunning.Operation.response] field when it completes.
Parameters
NameDescription
request Union[google.cloud.automl_v1beta1.types.ImportDataRequest, dict]

The request object. Request message for AutoMl.ImportData.

name `str`

Required. Dataset name. Dataset must already exist. All imported annotations and examples will be added. This corresponds to the name field on the request instance; if request is provided, this should not be set.

input_config InputConfig

Required. The desired input location and its domain specific semantics, if any. This corresponds to the input_config field on the request instance; if request is provided, this should not be set.

retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.

timeout float

The timeout for this request.

metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.

Returns
TypeDescription
google.api_core.operation_async.AsyncOperationAn object representing a long-running operation. The result type for the operation will be `google.protobuf.empty_pb2.Empty` A generic empty message that you can re-use to avoid defining duplicated empty messages in your APIs. A typical example is to use it as the request or the response type of an API method. For instance: service Foo { rpc Bar(google.protobuf.Empty) returns (google.protobuf.Empty); } The JSON representation for Empty is empty JSON object {}.

list_column_specs

list_column_specs(request: Optional[Union[google.cloud.automl_v1beta1.types.service.ListColumnSpecsRequest, dict]] = None, *, parent: Optional[str] = None, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())

Lists column specs in a table spec.

Parameters
NameDescription
request Union[google.cloud.automl_v1beta1.types.ListColumnSpecsRequest, dict]

The request object. Request message for AutoMl.ListColumnSpecs.

parent `str`

Required. The resource name of the table spec to list column specs from. This corresponds to the parent field on the request instance; if request is provided, this should not be set.

retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.

timeout float

The timeout for this request.

metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.

Returns
TypeDescription
google.cloud.automl_v1beta1.services.auto_ml.pagers.ListColumnSpecsAsyncPagerResponse message for AutoMl.ListColumnSpecs. Iterating over this object will yield results and resolve additional pages automatically.

list_datasets

list_datasets(request: Optional[Union[google.cloud.automl_v1beta1.types.service.ListDatasetsRequest, dict]] = None, *, parent: Optional[str] = None, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())

Lists datasets in a project.

Parameters
NameDescription
request Union[google.cloud.automl_v1beta1.types.ListDatasetsRequest, dict]

The request object. Request message for AutoMl.ListDatasets.

parent `str`

Required. The resource name of the project from which to list datasets. This corresponds to the parent field on the request instance; if request is provided, this should not be set.

retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.

timeout float

The timeout for this request.

metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.

Returns
TypeDescription
google.cloud.automl_v1beta1.services.auto_ml.pagers.ListDatasetsAsyncPagerResponse message for AutoMl.ListDatasets. Iterating over this object will yield results and resolve additional pages automatically.

list_model_evaluations

list_model_evaluations(request: Optional[Union[google.cloud.automl_v1beta1.types.service.ListModelEvaluationsRequest, dict]] = None, *, parent: Optional[str] = None, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())

Lists model evaluations.

Parameters
NameDescription
request Union[google.cloud.automl_v1beta1.types.ListModelEvaluationsRequest, dict]

The request object. Request message for AutoMl.ListModelEvaluations.

parent `str`

Required. Resource name of the model to list the model evaluations for. If modelId is set as "-", this will list model evaluations from across all models of the parent location. This corresponds to the parent field on the request instance; if request is provided, this should not be set.

retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.

timeout float

The timeout for this request.

metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.

Returns
TypeDescription
google.cloud.automl_v1beta1.services.auto_ml.pagers.ListModelEvaluationsAsyncPagerResponse message for AutoMl.ListModelEvaluations. Iterating over this object will yield results and resolve additional pages automatically.

list_models

list_models(request: Optional[Union[google.cloud.automl_v1beta1.types.service.ListModelsRequest, dict]] = None, *, parent: Optional[str] = None, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())

Lists models.

Parameters
NameDescription
request Union[google.cloud.automl_v1beta1.types.ListModelsRequest, dict]

The request object. Request message for AutoMl.ListModels.

parent `str`

Required. Resource name of the project, from which to list the models. This corresponds to the parent field on the request instance; if request is provided, this should not be set.

retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.

timeout float

The timeout for this request.

metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.

Returns
TypeDescription
google.cloud.automl_v1beta1.services.auto_ml.pagers.ListModelsAsyncPagerResponse message for AutoMl.ListModels. Iterating over this object will yield results and resolve additional pages automatically.

list_table_specs

list_table_specs(request: Optional[Union[google.cloud.automl_v1beta1.types.service.ListTableSpecsRequest, dict]] = None, *, parent: Optional[str] = None, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())

Lists table specs in a dataset.

Parameters
NameDescription
request Union[google.cloud.automl_v1beta1.types.ListTableSpecsRequest, dict]

The request object. Request message for AutoMl.ListTableSpecs.

parent `str`

Required. The resource name of the dataset to list table specs from. This corresponds to the parent field on the request instance; if request is provided, this should not be set.

retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.

timeout float

The timeout for this request.

metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.

Returns
TypeDescription
google.cloud.automl_v1beta1.services.auto_ml.pagers.ListTableSpecsAsyncPagerResponse message for AutoMl.ListTableSpecs. Iterating over this object will yield results and resolve additional pages automatically.

model_evaluation_path

model_evaluation_path(
    project: str, location: str, model: str, model_evaluation: str
)

Returns a fully-qualified model_evaluation string.

Parameters
NameDescription
project str
location str
model str
model_evaluation str

model_path

model_path(project: str, location: str, model: str)

Returns a fully-qualified model string.

Parameters
NameDescription
project str
location str
model str

parse_annotation_spec_path

parse_annotation_spec_path(path: str)

Parses a annotation_spec path into its component segments.

Parameter
NameDescription
path str

parse_column_spec_path

parse_column_spec_path(path: str)

Parses a column_spec path into its component segments.

Parameter
NameDescription
path str

parse_common_billing_account_path

parse_common_billing_account_path(path: str)

Parse a billing_account path into its component segments.

Parameter
NameDescription
path str

parse_common_folder_path

parse_common_folder_path(path: str)

Parse a folder path into its component segments.

Parameter
NameDescription
path str

parse_common_location_path

parse_common_location_path(path: str)

Parse a location path into its component segments.

Parameter
NameDescription
path str

parse_common_organization_path

parse_common_organization_path(path: str)

Parse a organization path into its component segments.

Parameter
NameDescription
path str

parse_common_project_path

parse_common_project_path(path: str)

Parse a project path into its component segments.

Parameter
NameDescription
path str

parse_dataset_path

parse_dataset_path(path: str)

Parses a dataset path into its component segments.

Parameter
NameDescription
path str

parse_model_evaluation_path

parse_model_evaluation_path(path: str)

Parses a model_evaluation path into its component segments.

Parameter
NameDescription
path str

parse_model_path

parse_model_path(path: str)

Parses a model path into its component segments.

Parameter
NameDescription
path str

parse_table_spec_path

parse_table_spec_path(path: str)

Parses a table_spec path into its component segments.

Parameter
NameDescription
path str

table_spec_path

table_spec_path(project: str, location: str, dataset: str, table_spec: str)

Returns a fully-qualified table_spec string.

Parameters
NameDescription
project str
location str
dataset str
table_spec str

undeploy_model

undeploy_model(request: Optional[Union[google.cloud.automl_v1beta1.types.service.UndeployModelRequest, dict]] = None, *, name: Optional[str] = None, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())

Undeploys a model. If the model is not deployed this method has no effect.

Only applicable for Text Classification, Image Object Detection and Tables; all other domains manage deployment automatically.

Returns an empty response in the response][google.longrunning.Operation.response] field when it completes.

Parameters
NameDescription
request Union[google.cloud.automl_v1beta1.types.UndeployModelRequest, dict]

The request object. Request message for AutoMl.UndeployModel.

name `str`

Required. Resource name of the model to undeploy. This corresponds to the name field on the request instance; if request is provided, this should not be set.

retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.

timeout float

The timeout for this request.

metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.

Returns
TypeDescription
google.api_core.operation_async.AsyncOperationAn object representing a long-running operation. The result type for the operation will be `google.protobuf.empty_pb2.Empty` A generic empty message that you can re-use to avoid defining duplicated empty messages in your APIs. A typical example is to use it as the request or the response type of an API method. For instance: service Foo { rpc Bar(google.protobuf.Empty) returns (google.protobuf.Empty); } The JSON representation for Empty is empty JSON object {}.

update_column_spec

update_column_spec(request: Optional[Union[google.cloud.automl_v1beta1.types.service.UpdateColumnSpecRequest, dict]] = None, *, column_spec: Optional[google.cloud.automl_v1beta1.types.column_spec.ColumnSpec] = None, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())

Updates a column spec.

Parameters
NameDescription
request Union[google.cloud.automl_v1beta1.types.UpdateColumnSpecRequest, dict]

The request object. Request message for AutoMl.UpdateColumnSpec

column_spec ColumnSpec

Required. The column spec which replaces the resource on the server. This corresponds to the column_spec field on the request instance; if request is provided, this should not be set.

retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.

timeout float

The timeout for this request.

metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.

Returns
TypeDescription
google.cloud.automl_v1beta1.types.ColumnSpecA representation of a column in a relational table. When listing them, column specs are returned in the same order in which they were given on import . Used by: \* Tables

update_dataset

update_dataset(request: Optional[Union[google.cloud.automl_v1beta1.types.service.UpdateDatasetRequest, dict]] = None, *, dataset: Optional[google.cloud.automl_v1beta1.types.dataset.Dataset] = None, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())

Updates a dataset.

Parameters
NameDescription
request Union[google.cloud.automl_v1beta1.types.UpdateDatasetRequest, dict]

The request object. Request message for AutoMl.UpdateDataset

dataset Dataset

Required. The dataset which replaces the resource on the server. This corresponds to the dataset field on the request instance; if request is provided, this should not be set.

retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.

timeout float

The timeout for this request.

metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.

Returns
TypeDescription
google.cloud.automl_v1beta1.types.DatasetA workspace for solving a single, particular machine learning (ML) problem. A workspace contains examples that may be annotated.

update_table_spec

update_table_spec(request: Optional[Union[google.cloud.automl_v1beta1.types.service.UpdateTableSpecRequest, dict]] = None, *, table_spec: Optional[google.cloud.automl_v1beta1.types.table_spec.TableSpec] = None, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())

Updates a table spec.

Parameters
NameDescription
request Union[google.cloud.automl_v1beta1.types.UpdateTableSpecRequest, dict]

The request object. Request message for AutoMl.UpdateTableSpec

table_spec TableSpec

Required. The table spec which replaces the resource on the server. This corresponds to the table_spec field on the request instance; if request is provided, this should not be set.

retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.

timeout float

The timeout for this request.

metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.

Returns
TypeDescription
google.cloud.automl_v1beta1.types.TableSpecA specification of a relational table. The table's schema is represented via its child column specs. It is pre-populated as part of ImportData by schema inference algorithm, the version of which is a required parameter of ImportData InputConfig. Note: While working with a table, at times the schema may be inconsistent with the data in the table (e.g. string in a FLOAT64 column). The consistency validation is done upon creation of a model. Used by: \* Tables