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.

AutoMl

class google.cloud.automl_v1beta1.services.auto_ml.AutoMlAsyncClient(*, credentials: google.auth.credentials.Credentials = None, transport: Union[str, google.cloud.automl_v1beta1.services.auto_ml.transports.base.AutoMlTransport] = 'grpc_asyncio', client_options: <module 'google.api_core.client_options' from '/workspace/.nox/docs/lib/python3.8/site-packages/google/api_core/client_options.py'> = None, client_info: google.api_core.gapic_v1.client_info.ClientInfo = <google.api_core.gapic_v1.client_info.ClientInfo object>)[source]

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.

Instantiates the auto ml client.

Parameters
  • credentials (Optional[google.auth.credentials.Credentials]) – The authorization credentials to attach to requests. These credentials identify the application to the service; if none are specified, the client will attempt to ascertain the credentials from the environment.

  • transport (Union[str, AutoMlTransport]) – The transport to use. If set to None, a transport is chosen automatically.

  • client_options (ClientOptions) – Custom options for the client. It won’t take effect if a transport instance is provided. (1) The api_endpoint property can be used to override the default endpoint provided by the client. GOOGLE_API_USE_MTLS_ENDPOINT environment variable can also be used to override the endpoint: “always” (always use the default mTLS endpoint), “never” (always use the default regular endpoint) and “auto” (auto switch to the default mTLS endpoint if client certificate is present, this is the default value). However, the api_endpoint property takes precedence if provided. (2) If GOOGLE_API_USE_CLIENT_CERTIFICATE environment variable is “true”, then the client_cert_source property can be used to provide client certificate for mutual TLS transport. If not provided, the default SSL client certificate will be used if present. If GOOGLE_API_USE_CLIENT_CERTIFICATE is “false” or not set, no client certificate will be used.

Raises

google.auth.exceptions.MutualTlsChannelError – If mutual TLS transport creation failed for any reason.

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

Returns a fully-qualified annotation_spec string.

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

Returns a fully-qualified column_spec string.

static common_billing_account_path(billing_account: str)str

Returns a fully-qualified billing_account string.

static common_folder_path(folder: str)str

Returns a fully-qualified folder string.

static common_location_path(project: str, location: str)str

Returns a fully-qualified location string.

static common_organization_path(organization: str)str

Returns a fully-qualified organization string.

static common_project_path(project: str)str

Returns a fully-qualified project string.

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

Creates a dataset.

Parameters
  • request (google.cloud.automl_v1beta1.types.CreateDatasetRequest) – The request object. Request message for [AutoMl.CreateDataset][google.cloud.automl.v1beta1.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 (google.cloud.automl_v1beta1.types.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

A workspace for solving a single, particular machine learning (ML) problem. A workspace contains examples that may be annotated.

Return type

google.cloud.automl_v1beta1.types.Dataset

async create_model(request: Optional[google.cloud.automl_v1beta1.types.service.CreateModelRequest] = None, *, parent: Optional[str] = None, model: Optional[google.cloud.automl_v1beta1.types.model.Model] = None, retry: google.api_core.retry.Retry = <object object>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())google.api_core.operation_async.AsyncOperation[source]

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
  • request (google.cloud.automl_v1beta1.types.CreateModelRequest) – The request object. Request message for [AutoMl.CreateModel][google.cloud.automl.v1beta1.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 (google.cloud.automl_v1beta1.types.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

An object representing a long-running operation.

The result type for the operation will be google.cloud.automl_v1beta1.types.Model API proto representing a trained machine learning model.

Return type

google.api_core.operation_async.AsyncOperation

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

Returns a fully-qualified dataset string.

async delete_dataset(request: Optional[google.cloud.automl_v1beta1.types.service.DeleteDatasetRequest] = None, *, name: Optional[str] = None, retry: google.api_core.retry.Retry = <object object>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())google.api_core.operation_async.AsyncOperation[source]

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
  • request (google.cloud.automl_v1beta1.types.DeleteDatasetRequest) – The request object. Request message for [AutoMl.DeleteDataset][google.cloud.automl.v1beta1.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

An 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 {}.

Return type

google.api_core.operation_async.AsyncOperation

async delete_model(request: Optional[google.cloud.automl_v1beta1.types.service.DeleteModelRequest] = None, *, name: Optional[str] = None, retry: google.api_core.retry.Retry = <object object>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())google.api_core.operation_async.AsyncOperation[source]

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
  • request (google.cloud.automl_v1beta1.types.DeleteModelRequest) – The request object. Request message for [AutoMl.DeleteModel][google.cloud.automl.v1beta1.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

An 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 {}.

Return type

google.api_core.operation_async.AsyncOperation

async deploy_model(request: Optional[google.cloud.automl_v1beta1.types.service.DeployModelRequest] = None, *, name: Optional[str] = None, retry: google.api_core.retry.Retry = <object object>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())google.api_core.operation_async.AsyncOperation[source]

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

[node_number][google.cloud.automl.v1beta1.ImageObjectDetectionModelDeploymentMetadata.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
  • request (google.cloud.automl_v1beta1.types.DeployModelRequest) – The request object. Request message for [AutoMl.DeployModel][google.cloud.automl.v1beta1.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

An 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 {}.

Return type

google.api_core.operation_async.AsyncOperation

async export_data(request: Optional[google.cloud.automl_v1beta1.types.service.ExportDataRequest] = None, *, name: Optional[str] = None, output_config: Optional[google.cloud.automl_v1beta1.types.io.OutputConfig] = None, retry: google.api_core.retry.Retry = <object object>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())google.api_core.operation_async.AsyncOperation[source]

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
  • request (google.cloud.automl_v1beta1.types.ExportDataRequest) – The request object. Request message for [AutoMl.ExportData][google.cloud.automl.v1beta1.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 (google.cloud.automl_v1beta1.types.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

An 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 {}.

Return type

google.api_core.operation_async.AsyncOperation

async export_evaluated_examples(request: Optional[google.cloud.automl_v1beta1.types.service.ExportEvaluatedExamplesRequest] = None, *, name: Optional[str] = None, output_config: Optional[google.cloud.automl_v1beta1.types.io.ExportEvaluatedExamplesOutputConfig] = None, retry: google.api_core.retry.Retry = <object object>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())google.api_core.operation_async.AsyncOperation[source]

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
  • request (google.cloud.automl_v1beta1.types.ExportEvaluatedExamplesRequest) – The request object. Request message for [AutoMl.ExportEvaluatedExamples][google.cloud.automl.v1beta1.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 (google.cloud.automl_v1beta1.types.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

An 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 {}.

Return type

google.api_core.operation_async.AsyncOperation

async export_model(request: Optional[google.cloud.automl_v1beta1.types.service.ExportModelRequest] = None, *, name: Optional[str] = None, output_config: Optional[google.cloud.automl_v1beta1.types.io.ModelExportOutputConfig] = None, retry: google.api_core.retry.Retry = <object object>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())google.api_core.operation_async.AsyncOperation[source]

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

[ModelExportOutputConfig][google.cloud.automl.v1beta1.ModelExportOutputConfig].

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

Parameters
  • request (google.cloud.automl_v1beta1.types.ExportModelRequest) – The request object. Request message for [AutoMl.ExportModel][google.cloud.automl.v1beta1.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 (google.cloud.automl_v1beta1.types.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

An 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 {}.

Return type

google.api_core.operation_async.AsyncOperation

classmethod from_service_account_file(filename: str, *args, **kwargs)[source]
Creates an instance of this client using the provided credentials

file.

Parameters
  • 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

The constructed client.

Return type

AutoMlAsyncClient

classmethod from_service_account_info(info: dict, *args, **kwargs)[source]
Creates an instance of this client using the provided credentials

info.

Parameters
  • 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

The constructed client.

Return type

AutoMlAsyncClient

classmethod from_service_account_json(filename: str, *args, **kwargs)
Creates an instance of this client using the provided credentials

file.

Parameters
  • 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

The constructed client.

Return type

AutoMlAsyncClient

async get_annotation_spec(request: Optional[google.cloud.automl_v1beta1.types.service.GetAnnotationSpecRequest] = None, *, name: Optional[str] = None, retry: google.api_core.retry.Retry = <object object>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())google.cloud.automl_v1beta1.types.annotation_spec.AnnotationSpec[source]

Gets an annotation spec.

Parameters
  • request (google.cloud.automl_v1beta1.types.GetAnnotationSpecRequest) – The request object. Request message for [AutoMl.GetAnnotationSpec][google.cloud.automl.v1beta1.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

A definition of an annotation spec.

Return type

google.cloud.automl_v1beta1.types.AnnotationSpec

async get_column_spec(request: Optional[google.cloud.automl_v1beta1.types.service.GetColumnSpecRequest] = None, *, name: Optional[str] = None, retry: google.api_core.retry.Retry = <object object>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())google.cloud.automl_v1beta1.types.column_spec.ColumnSpec[source]

Gets a column spec.

Parameters
  • request (google.cloud.automl_v1beta1.types.GetColumnSpecRequest) – The request object. Request message for [AutoMl.GetColumnSpec][google.cloud.automl.v1beta1.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

A 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

Return type

google.cloud.automl_v1beta1.types.ColumnSpec

async get_dataset(request: Optional[google.cloud.automl_v1beta1.types.service.GetDatasetRequest] = None, *, name: Optional[str] = None, retry: google.api_core.retry.Retry = <object object>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())google.cloud.automl_v1beta1.types.dataset.Dataset[source]

Gets a dataset.

Parameters
  • request (google.cloud.automl_v1beta1.types.GetDatasetRequest) – The request object. Request message for [AutoMl.GetDataset][google.cloud.automl.v1beta1.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

A workspace for solving a single, particular machine learning (ML) problem. A workspace contains examples that may be annotated.

Return type

google.cloud.automl_v1beta1.types.Dataset

async get_model(request: Optional[google.cloud.automl_v1beta1.types.service.GetModelRequest] = None, *, name: Optional[str] = None, retry: google.api_core.retry.Retry = <object object>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())google.cloud.automl_v1beta1.types.model.Model[source]

Gets a model.

Parameters
  • request (google.cloud.automl_v1beta1.types.GetModelRequest) – The request object. Request message for [AutoMl.GetModel][google.cloud.automl.v1beta1.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

API proto representing a trained machine learning model.

Return type

google.cloud.automl_v1beta1.types.Model

async get_model_evaluation(request: Optional[google.cloud.automl_v1beta1.types.service.GetModelEvaluationRequest] = None, *, name: Optional[str] = None, retry: google.api_core.retry.Retry = <object object>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())google.cloud.automl_v1beta1.types.model_evaluation.ModelEvaluation[source]

Gets a model evaluation.

Parameters
  • request (google.cloud.automl_v1beta1.types.GetModelEvaluationRequest) – The request object. Request message for [AutoMl.GetModelEvaluation][google.cloud.automl.v1beta1.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

Evaluation results of a model.

Return type

google.cloud.automl_v1beta1.types.ModelEvaluation

async get_table_spec(request: Optional[google.cloud.automl_v1beta1.types.service.GetTableSpecRequest] = None, *, name: Optional[str] = None, retry: google.api_core.retry.Retry = <object object>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())google.cloud.automl_v1beta1.types.table_spec.TableSpec[source]

Gets a table spec.

Parameters
  • request (google.cloud.automl_v1beta1.types.GetTableSpecRequest) – The request object. Request message for [AutoMl.GetTableSpec][google.cloud.automl.v1beta1.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

A 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

Return type

google.cloud.automl_v1beta1.types.TableSpec

get_transport_class()Type[google.cloud.automl_v1beta1.services.auto_ml.transports.base.AutoMlTransport]

Returns an appropriate transport class.

Parameters

label – The name of the desired transport. If none is provided, then the first transport in the registry is used.

Returns

The transport class to use.

async import_data(request: Optional[google.cloud.automl_v1beta1.types.service.ImportDataRequest] = None, *, name: Optional[str] = None, input_config: Optional[google.cloud.automl_v1beta1.types.io.InputConfig] = None, retry: google.api_core.retry.Retry = <object object>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())google.api_core.operation_async.AsyncOperation[source]

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

For Tables:

  • A [schema_inference_version][google.cloud.automl.v1beta1.InputConfig.params] parameter must be explicitly set. Returns an empty response in the [response][google.longrunning.Operation.response] field when it completes.

Parameters
  • request (google.cloud.automl_v1beta1.types.ImportDataRequest) – The request object. Request message for [AutoMl.ImportData][google.cloud.automl.v1beta1.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 (google.cloud.automl_v1beta1.types.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

An 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 {}.

Return type

google.api_core.operation_async.AsyncOperation

async list_column_specs(request: Optional[google.cloud.automl_v1beta1.types.service.ListColumnSpecsRequest] = None, *, parent: Optional[str] = None, retry: google.api_core.retry.Retry = <object object>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())google.cloud.automl_v1beta1.services.auto_ml.pagers.ListColumnSpecsAsyncPager[source]

Lists column specs in a table spec.

Parameters
  • request (google.cloud.automl_v1beta1.types.ListColumnSpecsRequest) – The request object. Request message for [AutoMl.ListColumnSpecs][google.cloud.automl.v1beta1.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

Response message for [AutoMl.ListColumnSpecs][google.cloud.automl.v1beta1.AutoMl.ListColumnSpecs].

Iterating over this object will yield results and resolve additional pages automatically.

Return type

google.cloud.automl_v1beta1.services.auto_ml.pagers.ListColumnSpecsAsyncPager

async list_datasets(request: Optional[google.cloud.automl_v1beta1.types.service.ListDatasetsRequest] = None, *, parent: Optional[str] = None, retry: google.api_core.retry.Retry = <object object>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())google.cloud.automl_v1beta1.services.auto_ml.pagers.ListDatasetsAsyncPager[source]

Lists datasets in a project.

Parameters
  • request (google.cloud.automl_v1beta1.types.ListDatasetsRequest) – The request object. Request message for [AutoMl.ListDatasets][google.cloud.automl.v1beta1.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

Response message for [AutoMl.ListDatasets][google.cloud.automl.v1beta1.AutoMl.ListDatasets].

Iterating over this object will yield results and resolve additional pages automatically.

Return type

google.cloud.automl_v1beta1.services.auto_ml.pagers.ListDatasetsAsyncPager

async list_model_evaluations(request: Optional[google.cloud.automl_v1beta1.types.service.ListModelEvaluationsRequest] = None, *, parent: Optional[str] = None, retry: google.api_core.retry.Retry = <object object>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())google.cloud.automl_v1beta1.services.auto_ml.pagers.ListModelEvaluationsAsyncPager[source]

Lists model evaluations.

Parameters
  • request (google.cloud.automl_v1beta1.types.ListModelEvaluationsRequest) – The request object. Request message for [AutoMl.ListModelEvaluations][google.cloud.automl.v1beta1.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

Response message for [AutoMl.ListModelEvaluations][google.cloud.automl.v1beta1.AutoMl.ListModelEvaluations].

Iterating over this object will yield results and resolve additional pages automatically.

Return type

google.cloud.automl_v1beta1.services.auto_ml.pagers.ListModelEvaluationsAsyncPager

async list_models(request: Optional[google.cloud.automl_v1beta1.types.service.ListModelsRequest] = None, *, parent: Optional[str] = None, retry: google.api_core.retry.Retry = <object object>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())google.cloud.automl_v1beta1.services.auto_ml.pagers.ListModelsAsyncPager[source]

Lists models.

Parameters
  • request (google.cloud.automl_v1beta1.types.ListModelsRequest) – The request object. Request message for [AutoMl.ListModels][google.cloud.automl.v1beta1.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

Response message for [AutoMl.ListModels][google.cloud.automl.v1beta1.AutoMl.ListModels].

Iterating over this object will yield results and resolve additional pages automatically.

Return type

google.cloud.automl_v1beta1.services.auto_ml.pagers.ListModelsAsyncPager

async list_table_specs(request: Optional[google.cloud.automl_v1beta1.types.service.ListTableSpecsRequest] = None, *, parent: Optional[str] = None, retry: google.api_core.retry.Retry = <object object>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())google.cloud.automl_v1beta1.services.auto_ml.pagers.ListTableSpecsAsyncPager[source]

Lists table specs in a dataset.

Parameters
  • request (google.cloud.automl_v1beta1.types.ListTableSpecsRequest) – The request object. Request message for [AutoMl.ListTableSpecs][google.cloud.automl.v1beta1.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

Response message for [AutoMl.ListTableSpecs][google.cloud.automl.v1beta1.AutoMl.ListTableSpecs].

Iterating over this object will yield results and resolve additional pages automatically.

Return type

google.cloud.automl_v1beta1.services.auto_ml.pagers.ListTableSpecsAsyncPager

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

Returns a fully-qualified model_evaluation string.

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

Returns a fully-qualified model string.

static parse_annotation_spec_path(path: str)Dict[str, str]

Parses a annotation_spec path into its component segments.

static parse_column_spec_path(path: str)Dict[str, str]

Parses a column_spec path into its component segments.

static parse_common_billing_account_path(path: str)Dict[str, str]

Parse a billing_account path into its component segments.

static parse_common_folder_path(path: str)Dict[str, str]

Parse a folder path into its component segments.

static parse_common_location_path(path: str)Dict[str, str]

Parse a location path into its component segments.

static parse_common_organization_path(path: str)Dict[str, str]

Parse a organization path into its component segments.

static parse_common_project_path(path: str)Dict[str, str]

Parse a project path into its component segments.

static parse_dataset_path(path: str)Dict[str, str]

Parses a dataset path into its component segments.

static parse_model_evaluation_path(path: str)Dict[str, str]

Parses a model_evaluation path into its component segments.

static parse_model_path(path: str)Dict[str, str]

Parses a model path into its component segments.

static parse_table_spec_path(path: str)Dict[str, str]

Parses a table_spec path into its component segments.

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

Returns a fully-qualified table_spec string.

property transport: google.cloud.automl_v1beta1.services.auto_ml.transports.base.AutoMlTransport

Returns the transport used by the client instance.

Returns

The transport used by the client instance.

Return type

AutoMlTransport

async undeploy_model(request: Optional[google.cloud.automl_v1beta1.types.service.UndeployModelRequest] = None, *, name: Optional[str] = None, retry: google.api_core.retry.Retry = <object object>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())google.api_core.operation_async.AsyncOperation[source]

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
  • request (google.cloud.automl_v1beta1.types.UndeployModelRequest) – The request object. Request message for [AutoMl.UndeployModel][google.cloud.automl.v1beta1.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

An 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 {}.

Return type

google.api_core.operation_async.AsyncOperation

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

Updates a column spec.

Parameters
Returns

A 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

Return type

google.cloud.automl_v1beta1.types.ColumnSpec

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

Updates a dataset.

Parameters
  • request (google.cloud.automl_v1beta1.types.UpdateDatasetRequest) – The request object. Request message for [AutoMl.UpdateDataset][google.cloud.automl.v1beta1.AutoMl.UpdateDataset]

  • dataset (google.cloud.automl_v1beta1.types.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

A workspace for solving a single, particular machine learning (ML) problem. A workspace contains examples that may be annotated.

Return type

google.cloud.automl_v1beta1.types.Dataset

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

Updates a table spec.

Parameters
Returns

A 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

Return type

google.cloud.automl_v1beta1.types.TableSpec

class google.cloud.automl_v1beta1.services.auto_ml.AutoMlClient(*, credentials: Optional[google.auth.credentials.Credentials] = None, transport: Optional[Union[str, google.cloud.automl_v1beta1.services.auto_ml.transports.base.AutoMlTransport]] = None, client_options: Optional[google.api_core.client_options.ClientOptions] = None, client_info: google.api_core.gapic_v1.client_info.ClientInfo = <google.api_core.gapic_v1.client_info.ClientInfo object>)[source]

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.

Instantiates the auto ml client.

Parameters
  • credentials (Optional[google.auth.credentials.Credentials]) – The authorization credentials to attach to requests. These credentials identify the application to the service; if none are specified, the client will attempt to ascertain the credentials from the environment.

  • transport (Union[str, AutoMlTransport]) – The transport to use. If set to None, a transport is chosen automatically.

  • client_options (google.api_core.client_options.ClientOptions) – Custom options for the client. It won’t take effect if a transport instance is provided. (1) The api_endpoint property can be used to override the default endpoint provided by the client. GOOGLE_API_USE_MTLS_ENDPOINT environment variable can also be used to override the endpoint: “always” (always use the default mTLS endpoint), “never” (always use the default regular endpoint) and “auto” (auto switch to the default mTLS endpoint if client certificate is present, this is the default value). However, the api_endpoint property takes precedence if provided. (2) If GOOGLE_API_USE_CLIENT_CERTIFICATE environment variable is “true”, then the client_cert_source property can be used to provide client certificate for mutual TLS transport. If not provided, the default SSL client certificate will be used if present. If GOOGLE_API_USE_CLIENT_CERTIFICATE is “false” or not set, no client certificate will be used.

  • client_info (google.api_core.gapic_v1.client_info.ClientInfo) – The client info used to send a user-agent string along with API requests. If None, then default info will be used. Generally, you only need to set this if you’re developing your own client library.

Raises

google.auth.exceptions.MutualTLSChannelError – If mutual TLS transport creation failed for any reason.

__exit__(type, value, traceback)[source]

Releases underlying transport’s resources.

Warning

ONLY use as a context manager if the transport is NOT shared with other clients! Exiting the with block will CLOSE the transport and may cause errors in other clients!

static annotation_spec_path(project: str, location: str, dataset: str, annotation_spec: str)str[source]

Returns a fully-qualified annotation_spec string.

static column_spec_path(project: str, location: str, dataset: str, table_spec: str, column_spec: str)str[source]

Returns a fully-qualified column_spec string.

static common_billing_account_path(billing_account: str)str[source]

Returns a fully-qualified billing_account string.

static common_folder_path(folder: str)str[source]

Returns a fully-qualified folder string.

static common_location_path(project: str, location: str)str[source]

Returns a fully-qualified location string.

static common_organization_path(organization: str)str[source]

Returns a fully-qualified organization string.

static common_project_path(project: str)str[source]

Returns a fully-qualified project string.

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: google.api_core.retry.Retry = <object object>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())google.cloud.automl_v1beta1.types.dataset.Dataset[source]

Creates a dataset.

Parameters
  • request (Union[google.cloud.automl_v1beta1.types.CreateDatasetRequest, dict]) – The request object. Request message for [AutoMl.CreateDataset][google.cloud.automl.v1beta1.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 (google.cloud.automl_v1beta1.types.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

A workspace for solving a single, particular machine learning (ML) problem. A workspace contains examples that may be annotated.

Return type

google.cloud.automl_v1beta1.types.Dataset

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: google.api_core.retry.Retry = <object object>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())google.api_core.operation.Operation[source]

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
  • request (Union[google.cloud.automl_v1beta1.types.CreateModelRequest, dict]) – The request object. Request message for [AutoMl.CreateModel][google.cloud.automl.v1beta1.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 (google.cloud.automl_v1beta1.types.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

An object representing a long-running operation.

The result type for the operation will be google.cloud.automl_v1beta1.types.Model API proto representing a trained machine learning model.

Return type

google.api_core.operation.Operation

static dataset_path(project: str, location: str, dataset: str)str[source]

Returns a fully-qualified dataset string.

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

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
  • request (Union[google.cloud.automl_v1beta1.types.DeleteDatasetRequest, dict]) – The request object. Request message for [AutoMl.DeleteDataset][google.cloud.automl.v1beta1.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

An 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 {}.

Return type

google.api_core.operation.Operation

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

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
  • request (Union[google.cloud.automl_v1beta1.types.DeleteModelRequest, dict]) – The request object. Request message for [AutoMl.DeleteModel][google.cloud.automl.v1beta1.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

An 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 {}.

Return type

google.api_core.operation.Operation

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

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

[node_number][google.cloud.automl.v1beta1.ImageObjectDetectionModelDeploymentMetadata.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
  • request (Union[google.cloud.automl_v1beta1.types.DeployModelRequest, dict]) – The request object. Request message for [AutoMl.DeployModel][google.cloud.automl.v1beta1.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

An 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 {}.

Return type

google.api_core.operation.Operation

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: google.api_core.retry.Retry = <object object>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())google.api_core.operation.Operation[source]

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
  • request (Union[google.cloud.automl_v1beta1.types.ExportDataRequest, dict]) – The request object. Request message for [AutoMl.ExportData][google.cloud.automl.v1beta1.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 (google.cloud.automl_v1beta1.types.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

An 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 {}.

Return type

google.api_core.operation.Operation

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: google.api_core.retry.Retry = <object object>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())google.api_core.operation.Operation[source]

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
  • request (Union[google.cloud.automl_v1beta1.types.ExportEvaluatedExamplesRequest, dict]) – The request object. Request message for [AutoMl.ExportEvaluatedExamples][google.cloud.automl.v1beta1.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 (google.cloud.automl_v1beta1.types.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

An 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 {}.

Return type

google.api_core.operation.Operation

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: google.api_core.retry.Retry = <object object>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())google.api_core.operation.Operation[source]

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

[ModelExportOutputConfig][google.cloud.automl.v1beta1.ModelExportOutputConfig].

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

Parameters
  • request (Union[google.cloud.automl_v1beta1.types.ExportModelRequest, dict]) – The request object. Request message for [AutoMl.ExportModel][google.cloud.automl.v1beta1.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 (google.cloud.automl_v1beta1.types.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

An 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 {}.

Return type

google.api_core.operation.Operation

classmethod from_service_account_file(filename: str, *args, **kwargs)[source]
Creates an instance of this client using the provided credentials

file.

Parameters
  • 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

The constructed client.

Return type

AutoMlClient

classmethod from_service_account_info(info: dict, *args, **kwargs)[source]
Creates an instance of this client using the provided credentials

info.

Parameters
  • 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

The constructed client.

Return type

AutoMlClient

classmethod from_service_account_json(filename: str, *args, **kwargs)
Creates an instance of this client using the provided credentials

file.

Parameters
  • 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

The constructed client.

Return type

AutoMlClient

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

Gets an annotation spec.

Parameters
  • request (Union[google.cloud.automl_v1beta1.types.GetAnnotationSpecRequest, dict]) – The request object. Request message for [AutoMl.GetAnnotationSpec][google.cloud.automl.v1beta1.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

A definition of an annotation spec.

Return type

google.cloud.automl_v1beta1.types.AnnotationSpec

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

Gets a column spec.

Parameters
  • request (Union[google.cloud.automl_v1beta1.types.GetColumnSpecRequest, dict]) – The request object. Request message for [AutoMl.GetColumnSpec][google.cloud.automl.v1beta1.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

A 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

Return type

google.cloud.automl_v1beta1.types.ColumnSpec

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

Gets a dataset.

Parameters
  • request (Union[google.cloud.automl_v1beta1.types.GetDatasetRequest, dict]) – The request object. Request message for [AutoMl.GetDataset][google.cloud.automl.v1beta1.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

A workspace for solving a single, particular machine learning (ML) problem. A workspace contains examples that may be annotated.

Return type

google.cloud.automl_v1beta1.types.Dataset

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

Gets a model.

Parameters
  • request (Union[google.cloud.automl_v1beta1.types.GetModelRequest, dict]) – The request object. Request message for [AutoMl.GetModel][google.cloud.automl.v1beta1.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

API proto representing a trained machine learning model.

Return type

google.cloud.automl_v1beta1.types.Model

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

Gets a model evaluation.

Parameters
  • request (Union[google.cloud.automl_v1beta1.types.GetModelEvaluationRequest, dict]) – The request object. Request message for [AutoMl.GetModelEvaluation][google.cloud.automl.v1beta1.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

Evaluation results of a model.

Return type

google.cloud.automl_v1beta1.types.ModelEvaluation

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

Gets a table spec.

Parameters
  • request (Union[google.cloud.automl_v1beta1.types.GetTableSpecRequest, dict]) – The request object. Request message for [AutoMl.GetTableSpec][google.cloud.automl.v1beta1.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

A 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

Return type

google.cloud.automl_v1beta1.types.TableSpec

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: google.api_core.retry.Retry = <object object>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())google.api_core.operation.Operation[source]

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

For Tables:

  • A [schema_inference_version][google.cloud.automl.v1beta1.InputConfig.params] parameter must be explicitly set. Returns an empty response in the [response][google.longrunning.Operation.response] field when it completes.

Parameters
  • request (Union[google.cloud.automl_v1beta1.types.ImportDataRequest, dict]) – The request object. Request message for [AutoMl.ImportData][google.cloud.automl.v1beta1.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 (google.cloud.automl_v1beta1.types.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

An 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 {}.

Return type

google.api_core.operation.Operation

list_column_specs(request: Optional[Union[google.cloud.automl_v1beta1.types.service.ListColumnSpecsRequest, dict]] = None, *, parent: Optional[str] = None, retry: google.api_core.retry.Retry = <object object>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())google.cloud.automl_v1beta1.services.auto_ml.pagers.ListColumnSpecsPager[source]

Lists column specs in a table spec.

Parameters
  • request (Union[google.cloud.automl_v1beta1.types.ListColumnSpecsRequest, dict]) – The request object. Request message for [AutoMl.ListColumnSpecs][google.cloud.automl.v1beta1.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

Response message for [AutoMl.ListColumnSpecs][google.cloud.automl.v1beta1.AutoMl.ListColumnSpecs].

Iterating over this object will yield results and resolve additional pages automatically.

Return type

google.cloud.automl_v1beta1.services.auto_ml.pagers.ListColumnSpecsPager

list_datasets(request: Optional[Union[google.cloud.automl_v1beta1.types.service.ListDatasetsRequest, dict]] = None, *, parent: Optional[str] = None, retry: google.api_core.retry.Retry = <object object>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())google.cloud.automl_v1beta1.services.auto_ml.pagers.ListDatasetsPager[source]

Lists datasets in a project.

Parameters
  • request (Union[google.cloud.automl_v1beta1.types.ListDatasetsRequest, dict]) – The request object. Request message for [AutoMl.ListDatasets][google.cloud.automl.v1beta1.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

Response message for [AutoMl.ListDatasets][google.cloud.automl.v1beta1.AutoMl.ListDatasets].

Iterating over this object will yield results and resolve additional pages automatically.

Return type

google.cloud.automl_v1beta1.services.auto_ml.pagers.ListDatasetsPager

list_model_evaluations(request: Optional[Union[google.cloud.automl_v1beta1.types.service.ListModelEvaluationsRequest, dict]] = None, *, parent: Optional[str] = None, retry: google.api_core.retry.Retry = <object object>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())google.cloud.automl_v1beta1.services.auto_ml.pagers.ListModelEvaluationsPager[source]

Lists model evaluations.

Parameters
  • request (Union[google.cloud.automl_v1beta1.types.ListModelEvaluationsRequest, dict]) – The request object. Request message for [AutoMl.ListModelEvaluations][google.cloud.automl.v1beta1.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

Response message for [AutoMl.ListModelEvaluations][google.cloud.automl.v1beta1.AutoMl.ListModelEvaluations].

Iterating over this object will yield results and resolve additional pages automatically.

Return type

google.cloud.automl_v1beta1.services.auto_ml.pagers.ListModelEvaluationsPager

list_models(request: Optional[Union[google.cloud.automl_v1beta1.types.service.ListModelsRequest, dict]] = None, *, parent: Optional[str] = None, retry: google.api_core.retry.Retry = <object object>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())google.cloud.automl_v1beta1.services.auto_ml.pagers.ListModelsPager[source]

Lists models.

Parameters
  • request (Union[google.cloud.automl_v1beta1.types.ListModelsRequest, dict]) – The request object. Request message for [AutoMl.ListModels][google.cloud.automl.v1beta1.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

Response message for [AutoMl.ListModels][google.cloud.automl.v1beta1.AutoMl.ListModels].

Iterating over this object will yield results and resolve additional pages automatically.

Return type

google.cloud.automl_v1beta1.services.auto_ml.pagers.ListModelsPager

list_table_specs(request: Optional[Union[google.cloud.automl_v1beta1.types.service.ListTableSpecsRequest, dict]] = None, *, parent: Optional[str] = None, retry: google.api_core.retry.Retry = <object object>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())google.cloud.automl_v1beta1.services.auto_ml.pagers.ListTableSpecsPager[source]

Lists table specs in a dataset.

Parameters
  • request (Union[google.cloud.automl_v1beta1.types.ListTableSpecsRequest, dict]) – The request object. Request message for [AutoMl.ListTableSpecs][google.cloud.automl.v1beta1.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

Response message for [AutoMl.ListTableSpecs][google.cloud.automl.v1beta1.AutoMl.ListTableSpecs].

Iterating over this object will yield results and resolve additional pages automatically.

Return type

google.cloud.automl_v1beta1.services.auto_ml.pagers.ListTableSpecsPager

static model_evaluation_path(project: str, location: str, model: str, model_evaluation: str)str[source]

Returns a fully-qualified model_evaluation string.

static model_path(project: str, location: str, model: str)str[source]

Returns a fully-qualified model string.

static parse_annotation_spec_path(path: str)Dict[str, str][source]

Parses a annotation_spec path into its component segments.

static parse_column_spec_path(path: str)Dict[str, str][source]

Parses a column_spec path into its component segments.

static parse_common_billing_account_path(path: str)Dict[str, str][source]

Parse a billing_account path into its component segments.

static parse_common_folder_path(path: str)Dict[str, str][source]

Parse a folder path into its component segments.

static parse_common_location_path(path: str)Dict[str, str][source]

Parse a location path into its component segments.

static parse_common_organization_path(path: str)Dict[str, str][source]

Parse a organization path into its component segments.

static parse_common_project_path(path: str)Dict[str, str][source]

Parse a project path into its component segments.

static parse_dataset_path(path: str)Dict[str, str][source]

Parses a dataset path into its component segments.

static parse_model_evaluation_path(path: str)Dict[str, str][source]

Parses a model_evaluation path into its component segments.

static parse_model_path(path: str)Dict[str, str][source]

Parses a model path into its component segments.

static parse_table_spec_path(path: str)Dict[str, str][source]

Parses a table_spec path into its component segments.

static table_spec_path(project: str, location: str, dataset: str, table_spec: str)str[source]

Returns a fully-qualified table_spec string.

property transport: google.cloud.automl_v1beta1.services.auto_ml.transports.base.AutoMlTransport

Returns the transport used by the client instance.

Returns

The transport used by the client

instance.

Return type

AutoMlTransport

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

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
  • request (Union[google.cloud.automl_v1beta1.types.UndeployModelRequest, dict]) – The request object. Request message for [AutoMl.UndeployModel][google.cloud.automl.v1beta1.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

An 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 {}.

Return type

google.api_core.operation.Operation

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: google.api_core.retry.Retry = <object object>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())google.cloud.automl_v1beta1.types.column_spec.ColumnSpec[source]

Updates a column spec.

Parameters
Returns

A 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

Return type

google.cloud.automl_v1beta1.types.ColumnSpec

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: google.api_core.retry.Retry = <object object>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())google.cloud.automl_v1beta1.types.dataset.Dataset[source]

Updates a dataset.

Parameters
Returns

A workspace for solving a single, particular machine learning (ML) problem. A workspace contains examples that may be annotated.

Return type

google.cloud.automl_v1beta1.types.Dataset

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: google.api_core.retry.Retry = <object object>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())google.cloud.automl_v1beta1.types.table_spec.TableSpec[source]

Updates a table spec.

Parameters
Returns

A 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

Return type

google.cloud.automl_v1beta1.types.TableSpec

class google.cloud.automl_v1beta1.services.auto_ml.pagers.ListColumnSpecsAsyncPager(method: Callable[[...], Awaitable[google.cloud.automl_v1beta1.types.service.ListColumnSpecsResponse]], request: google.cloud.automl_v1beta1.types.service.ListColumnSpecsRequest, response: google.cloud.automl_v1beta1.types.service.ListColumnSpecsResponse, *, metadata: Sequence[Tuple[str, str]] = ())[source]

A pager for iterating through list_column_specs requests.

This class thinly wraps an initial google.cloud.automl_v1beta1.types.ListColumnSpecsResponse object, and provides an __aiter__ method to iterate through its column_specs field.

If there are more pages, the __aiter__ method will make additional ListColumnSpecs requests and continue to iterate through the column_specs field on the corresponding responses.

All the usual google.cloud.automl_v1beta1.types.ListColumnSpecsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.

Instantiates the pager.

Parameters
class google.cloud.automl_v1beta1.services.auto_ml.pagers.ListColumnSpecsPager(method: Callable[[...], google.cloud.automl_v1beta1.types.service.ListColumnSpecsResponse], request: google.cloud.automl_v1beta1.types.service.ListColumnSpecsRequest, response: google.cloud.automl_v1beta1.types.service.ListColumnSpecsResponse, *, metadata: Sequence[Tuple[str, str]] = ())[source]

A pager for iterating through list_column_specs requests.

This class thinly wraps an initial google.cloud.automl_v1beta1.types.ListColumnSpecsResponse object, and provides an __iter__ method to iterate through its column_specs field.

If there are more pages, the __iter__ method will make additional ListColumnSpecs requests and continue to iterate through the column_specs field on the corresponding responses.

All the usual google.cloud.automl_v1beta1.types.ListColumnSpecsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.

Instantiate the pager.

Parameters
class google.cloud.automl_v1beta1.services.auto_ml.pagers.ListDatasetsAsyncPager(method: Callable[[...], Awaitable[google.cloud.automl_v1beta1.types.service.ListDatasetsResponse]], request: google.cloud.automl_v1beta1.types.service.ListDatasetsRequest, response: google.cloud.automl_v1beta1.types.service.ListDatasetsResponse, *, metadata: Sequence[Tuple[str, str]] = ())[source]

A pager for iterating through list_datasets requests.

This class thinly wraps an initial google.cloud.automl_v1beta1.types.ListDatasetsResponse object, and provides an __aiter__ method to iterate through its datasets field.

If there are more pages, the __aiter__ method will make additional ListDatasets requests and continue to iterate through the datasets field on the corresponding responses.

All the usual google.cloud.automl_v1beta1.types.ListDatasetsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.

Instantiates the pager.

Parameters
class google.cloud.automl_v1beta1.services.auto_ml.pagers.ListDatasetsPager(method: Callable[[...], google.cloud.automl_v1beta1.types.service.ListDatasetsResponse], request: google.cloud.automl_v1beta1.types.service.ListDatasetsRequest, response: google.cloud.automl_v1beta1.types.service.ListDatasetsResponse, *, metadata: Sequence[Tuple[str, str]] = ())[source]

A pager for iterating through list_datasets requests.

This class thinly wraps an initial google.cloud.automl_v1beta1.types.ListDatasetsResponse object, and provides an __iter__ method to iterate through its datasets field.

If there are more pages, the __iter__ method will make additional ListDatasets requests and continue to iterate through the datasets field on the corresponding responses.

All the usual google.cloud.automl_v1beta1.types.ListDatasetsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.

Instantiate the pager.

Parameters
class google.cloud.automl_v1beta1.services.auto_ml.pagers.ListModelEvaluationsAsyncPager(method: Callable[[...], Awaitable[google.cloud.automl_v1beta1.types.service.ListModelEvaluationsResponse]], request: google.cloud.automl_v1beta1.types.service.ListModelEvaluationsRequest, response: google.cloud.automl_v1beta1.types.service.ListModelEvaluationsResponse, *, metadata: Sequence[Tuple[str, str]] = ())[source]

A pager for iterating through list_model_evaluations requests.

This class thinly wraps an initial google.cloud.automl_v1beta1.types.ListModelEvaluationsResponse object, and provides an __aiter__ method to iterate through its model_evaluation field.

If there are more pages, the __aiter__ method will make additional ListModelEvaluations requests and continue to iterate through the model_evaluation field on the corresponding responses.

All the usual google.cloud.automl_v1beta1.types.ListModelEvaluationsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.

Instantiates the pager.

Parameters
class google.cloud.automl_v1beta1.services.auto_ml.pagers.ListModelEvaluationsPager(method: Callable[[...], google.cloud.automl_v1beta1.types.service.ListModelEvaluationsResponse], request: google.cloud.automl_v1beta1.types.service.ListModelEvaluationsRequest, response: google.cloud.automl_v1beta1.types.service.ListModelEvaluationsResponse, *, metadata: Sequence[Tuple[str, str]] = ())[source]

A pager for iterating through list_model_evaluations requests.

This class thinly wraps an initial google.cloud.automl_v1beta1.types.ListModelEvaluationsResponse object, and provides an __iter__ method to iterate through its model_evaluation field.

If there are more pages, the __iter__ method will make additional ListModelEvaluations requests and continue to iterate through the model_evaluation field on the corresponding responses.

All the usual google.cloud.automl_v1beta1.types.ListModelEvaluationsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.

Instantiate the pager.

Parameters
class google.cloud.automl_v1beta1.services.auto_ml.pagers.ListModelsAsyncPager(method: Callable[[...], Awaitable[google.cloud.automl_v1beta1.types.service.ListModelsResponse]], request: google.cloud.automl_v1beta1.types.service.ListModelsRequest, response: google.cloud.automl_v1beta1.types.service.ListModelsResponse, *, metadata: Sequence[Tuple[str, str]] = ())[source]

A pager for iterating through list_models requests.

This class thinly wraps an initial google.cloud.automl_v1beta1.types.ListModelsResponse object, and provides an __aiter__ method to iterate through its model field.

If there are more pages, the __aiter__ method will make additional ListModels requests and continue to iterate through the model field on the corresponding responses.

All the usual google.cloud.automl_v1beta1.types.ListModelsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.

Instantiates the pager.

Parameters
class google.cloud.automl_v1beta1.services.auto_ml.pagers.ListModelsPager(method: Callable[[...], google.cloud.automl_v1beta1.types.service.ListModelsResponse], request: google.cloud.automl_v1beta1.types.service.ListModelsRequest, response: google.cloud.automl_v1beta1.types.service.ListModelsResponse, *, metadata: Sequence[Tuple[str, str]] = ())[source]

A pager for iterating through list_models requests.

This class thinly wraps an initial google.cloud.automl_v1beta1.types.ListModelsResponse object, and provides an __iter__ method to iterate through its model field.

If there are more pages, the __iter__ method will make additional ListModels requests and continue to iterate through the model field on the corresponding responses.

All the usual google.cloud.automl_v1beta1.types.ListModelsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.

Instantiate the pager.

Parameters
class google.cloud.automl_v1beta1.services.auto_ml.pagers.ListTableSpecsAsyncPager(method: Callable[[...], Awaitable[google.cloud.automl_v1beta1.types.service.ListTableSpecsResponse]], request: google.cloud.automl_v1beta1.types.service.ListTableSpecsRequest, response: google.cloud.automl_v1beta1.types.service.ListTableSpecsResponse, *, metadata: Sequence[Tuple[str, str]] = ())[source]

A pager for iterating through list_table_specs requests.

This class thinly wraps an initial google.cloud.automl_v1beta1.types.ListTableSpecsResponse object, and provides an __aiter__ method to iterate through its table_specs field.

If there are more pages, the __aiter__ method will make additional ListTableSpecs requests and continue to iterate through the table_specs field on the corresponding responses.

All the usual google.cloud.automl_v1beta1.types.ListTableSpecsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.

Instantiates the pager.

Parameters
class google.cloud.automl_v1beta1.services.auto_ml.pagers.ListTableSpecsPager(method: Callable[[...], google.cloud.automl_v1beta1.types.service.ListTableSpecsResponse], request: google.cloud.automl_v1beta1.types.service.ListTableSpecsRequest, response: google.cloud.automl_v1beta1.types.service.ListTableSpecsResponse, *, metadata: Sequence[Tuple[str, str]] = ())[source]

A pager for iterating through list_table_specs requests.

This class thinly wraps an initial google.cloud.automl_v1beta1.types.ListTableSpecsResponse object, and provides an __iter__ method to iterate through its table_specs field.

If there are more pages, the __iter__ method will make additional ListTableSpecs requests and continue to iterate through the table_specs field on the corresponding responses.

All the usual google.cloud.automl_v1beta1.types.ListTableSpecsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.

Instantiate the pager.

Parameters