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 '/usr/lib/python3.10/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) Theapi_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, theapi_endpoint
property takes precedence if provided. (2) If GOOGLE_API_USE_CLIENT_CERTIFICATE environment variable is “true”, then theclient_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 therequest
instance; ifrequest
is provided, this should not be set.dataset (
google.cloud.automl_v1beta1.types.Dataset
) – Required. The dataset to create. This corresponds to thedataset
field on therequest
instance; ifrequest
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
- 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 therequest
instance; ifrequest
is provided, this should not be set.model (
google.cloud.automl_v1beta1.types.Model
) – Required. The model to create. This corresponds to themodel
field on therequest
instance; ifrequest
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 therequest
instance; ifrequest
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 {}.
- The result type for the operation will be
- 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, anddelete_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 therequest
instance; ifrequest
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 {}.
- The result type for the operation will be
- 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 therequest
instance; ifrequest
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 {}.
- The result type for the operation will be
- 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 therequest
instance; ifrequest
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 therequest
instance; ifrequest
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 {}.
- The result type for the operation will be
- 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 therequest
instance; ifrequest
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 therequest
instance; ifrequest
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 {}.
- The result type for the operation will be
- 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 therequest
instance; ifrequest
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 therequest
instance; ifrequest
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 {}.
- The result type for the operation will be
- 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
- 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
- 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
- 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 therequest
instance; ifrequest
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
- 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 therequest
instance; ifrequest
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
- 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 therequest
instance; ifrequest
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
- 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 thename
field on therequest
instance; ifrequest
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
- 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 therequest
instance; ifrequest
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
- 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 therequest
instance; ifrequest
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
- 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 therequest
instance; ifrequest
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 therequest
instance; ifrequest
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 {}.
- The result type for the operation will be
- 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 therequest
instance; ifrequest
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 therequest
instance; ifrequest
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 therequest
instance; ifrequest
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 therequest
instance; ifrequest
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 therequest
instance; ifrequest
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 therequest
instance; ifrequest
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 {}.
- The result type for the operation will be
- 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
request (
google.cloud.automl_v1beta1.types.UpdateColumnSpecRequest
) – The request object. Request message for [AutoMl.UpdateColumnSpec][google.cloud.automl.v1beta1.AutoMl.UpdateColumnSpec]column_spec (
google.cloud.automl_v1beta1.types.ColumnSpec
) –Required. The column spec which replaces the resource on the server.
This corresponds to the
column_spec
field on therequest
instance; ifrequest
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
- 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 therequest
instance; ifrequest
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
- 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
request (
google.cloud.automl_v1beta1.types.UpdateTableSpecRequest
) – The request object. Request message for [AutoMl.UpdateTableSpec][google.cloud.automl.v1beta1.AutoMl.UpdateTableSpec]table_spec (
google.cloud.automl_v1beta1.types.TableSpec
) –Required. The table spec which replaces the resource on the server.
This corresponds to the
table_spec
field on therequest
instance; ifrequest
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
- 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) Theapi_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, theapi_endpoint
property takes precedence if provided. (2) If GOOGLE_API_USE_CLIENT_CERTIFICATE environment variable is “true”, then theclient_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.
- 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_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.
- 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 therequest
instance; ifrequest
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 therequest
instance; ifrequest
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
- 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.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 (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 therequest
instance; ifrequest
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 therequest
instance; ifrequest
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[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.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 (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 therequest
instance; ifrequest
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 {}.
- The result type for the operation will be
- Return type
google.api_core.operation.Operation
- 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.Operation [source]¶
Deletes a model. Returns
google.protobuf.Empty
in the [response][google.longrunning.Operation.response] field when it completes, anddelete_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 therequest
instance; ifrequest
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 {}.
- The result type for the operation will be
- Return type
google.api_core.operation.Operation
- 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.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 (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 therequest
instance; ifrequest
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 {}.
- The result type for the operation will be
- Return type
google.api_core.operation.Operation
- 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.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 (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 therequest
instance; ifrequest
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 therequest
instance; ifrequest
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 {}.
- The result type for the operation will be
- Return type
google.api_core.operation.Operation
- 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.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 (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 therequest
instance; ifrequest
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 therequest
instance; ifrequest
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 {}.
- The result type for the operation will be
- Return type
google.api_core.operation.Operation
- 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.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 (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 therequest
instance; ifrequest
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 therequest
instance; ifrequest
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 {}.
- The result type for the operation will be
- 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
- 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
- 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
- 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 therequest
instance; ifrequest
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
- 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 therequest
instance; ifrequest
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
- 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 therequest
instance; ifrequest
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
- 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 therequest
instance; ifrequest
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
- 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 therequest
instance; ifrequest
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
- 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 therequest
instance; ifrequest
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
- 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.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 (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 therequest
instance; ifrequest
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 therequest
instance; ifrequest
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 {}.
- The result type for the operation will be
- Return type
google.api_core.operation.Operation
- 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.ListColumnSpecsPager [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 therequest
instance; ifrequest
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[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.ListDatasetsPager [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 therequest
instance; ifrequest
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[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.ListModelEvaluationsPager [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 therequest
instance; ifrequest
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[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.ListModelsPager [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 therequest
instance; ifrequest
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[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.ListTableSpecsPager [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 therequest
instance; ifrequest
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[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.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 (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 therequest
instance; ifrequest
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 {}.
- The result type for the operation will be
- Return type
google.api_core.operation.Operation
- 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
request (google.cloud.automl_v1beta1.types.UpdateColumnSpecRequest) – The request object. Request message for [AutoMl.UpdateColumnSpec][google.cloud.automl.v1beta1.AutoMl.UpdateColumnSpec]
column_spec (google.cloud.automl_v1beta1.types.ColumnSpec) –
Required. The column spec which replaces the resource on the server.
This corresponds to the
column_spec
field on therequest
instance; ifrequest
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
- 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 therequest
instance; ifrequest
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
- 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
request (google.cloud.automl_v1beta1.types.UpdateTableSpecRequest) – The request object. Request message for [AutoMl.UpdateTableSpec][google.cloud.automl.v1beta1.AutoMl.UpdateTableSpec]
table_spec (google.cloud.automl_v1beta1.types.TableSpec) –
Required. The table spec which replaces the resource on the server.
This corresponds to the
table_spec
field on therequest
instance; ifrequest
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
- 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 itscolumn_specs
field.If there are more pages, the
__aiter__
method will make additionalListColumnSpecs
requests and continue to iterate through thecolumn_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
method (Callable) – The method that was originally called, and which instantiated this pager.
request (google.cloud.automl_v1beta1.types.ListColumnSpecsRequest) – The initial request object.
response (google.cloud.automl_v1beta1.types.ListColumnSpecsResponse) – The initial response object.
metadata (Sequence[Tuple[str, str]]) – Strings which should be sent along with the request as metadata.
- 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 itscolumn_specs
field.If there are more pages, the
__iter__
method will make additionalListColumnSpecs
requests and continue to iterate through thecolumn_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
method (Callable) – The method that was originally called, and which instantiated this pager.
request (google.cloud.automl_v1beta1.types.ListColumnSpecsRequest) – The initial request object.
response (google.cloud.automl_v1beta1.types.ListColumnSpecsResponse) – The initial response object.
metadata (Sequence[Tuple[str, str]]) – Strings which should be sent along with the request as metadata.
- 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 itsdatasets
field.If there are more pages, the
__aiter__
method will make additionalListDatasets
requests and continue to iterate through thedatasets
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
method (Callable) – The method that was originally called, and which instantiated this pager.
request (google.cloud.automl_v1beta1.types.ListDatasetsRequest) – The initial request object.
response (google.cloud.automl_v1beta1.types.ListDatasetsResponse) – The initial response object.
metadata (Sequence[Tuple[str, str]]) – Strings which should be sent along with the request as metadata.
- 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 itsdatasets
field.If there are more pages, the
__iter__
method will make additionalListDatasets
requests and continue to iterate through thedatasets
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
method (Callable) – The method that was originally called, and which instantiated this pager.
request (google.cloud.automl_v1beta1.types.ListDatasetsRequest) – The initial request object.
response (google.cloud.automl_v1beta1.types.ListDatasetsResponse) – The initial response object.
metadata (Sequence[Tuple[str, str]]) – Strings which should be sent along with the request as metadata.
- 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 itsmodel_evaluation
field.If there are more pages, the
__aiter__
method will make additionalListModelEvaluations
requests and continue to iterate through themodel_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
method (Callable) – The method that was originally called, and which instantiated this pager.
request (google.cloud.automl_v1beta1.types.ListModelEvaluationsRequest) – The initial request object.
response (google.cloud.automl_v1beta1.types.ListModelEvaluationsResponse) – The initial response object.
metadata (Sequence[Tuple[str, str]]) – Strings which should be sent along with the request as metadata.
- 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 itsmodel_evaluation
field.If there are more pages, the
__iter__
method will make additionalListModelEvaluations
requests and continue to iterate through themodel_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
method (Callable) – The method that was originally called, and which instantiated this pager.
request (google.cloud.automl_v1beta1.types.ListModelEvaluationsRequest) – The initial request object.
response (google.cloud.automl_v1beta1.types.ListModelEvaluationsResponse) – The initial response object.
metadata (Sequence[Tuple[str, str]]) – Strings which should be sent along with the request as metadata.
- 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 itsmodel
field.If there are more pages, the
__aiter__
method will make additionalListModels
requests and continue to iterate through themodel
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
method (Callable) – The method that was originally called, and which instantiated this pager.
request (google.cloud.automl_v1beta1.types.ListModelsRequest) – The initial request object.
response (google.cloud.automl_v1beta1.types.ListModelsResponse) – The initial response object.
metadata (Sequence[Tuple[str, str]]) – Strings which should be sent along with the request as metadata.
- 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 itsmodel
field.If there are more pages, the
__iter__
method will make additionalListModels
requests and continue to iterate through themodel
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
method (Callable) – The method that was originally called, and which instantiated this pager.
request (google.cloud.automl_v1beta1.types.ListModelsRequest) – The initial request object.
response (google.cloud.automl_v1beta1.types.ListModelsResponse) – The initial response object.
metadata (Sequence[Tuple[str, str]]) – Strings which should be sent along with the request as metadata.
- 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 itstable_specs
field.If there are more pages, the
__aiter__
method will make additionalListTableSpecs
requests and continue to iterate through thetable_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
method (Callable) – The method that was originally called, and which instantiated this pager.
request (google.cloud.automl_v1beta1.types.ListTableSpecsRequest) – The initial request object.
response (google.cloud.automl_v1beta1.types.ListTableSpecsResponse) – The initial response object.
metadata (Sequence[Tuple[str, str]]) – Strings which should be sent along with the request as metadata.
- 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 itstable_specs
field.If there are more pages, the
__iter__
method will make additionalListTableSpecs
requests and continue to iterate through thetable_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
method (Callable) – The method that was originally called, and which instantiated this pager.
request (google.cloud.automl_v1beta1.types.ListTableSpecsRequest) – The initial request object.
response (google.cloud.automl_v1beta1.types.ListTableSpecsResponse) – The initial response object.
metadata (Sequence[Tuple[str, str]]) – Strings which should be sent along with the request as metadata.