Console
    Contact Us Start free

    Class AutoMlClient (0.4.0) 

      AutoMlClient 
 ( 
 transport 
 = 
 None 
 , 
 channel 
 = 
 None 
 , 
 credentials 
 = 
 None 
 , 
 client_config 
 = 
 None 
 , 
 client_info 
 = 
 None 
 , 
 client_options 
 = 
 None 
 , 
 )

    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.

    Methods

    AutoMlClient

      AutoMlClient 
 ( 
 transport 
 = 
 None 
 , 
 channel 
 = 
 None 
 , 
 credentials 
 = 
 None 
 , 
 client_config 
 = 
 None 
 , 
 client_info 
 = 
 None 
 , 
 client_options 
 = 
 None 
 , 
 )

    Constructor.

    Parameters
    Name Description
    channel grpc.Channel

    DEPRECATED. A Channel instance through which to make calls. This argument is mutually exclusive with credentials ; providing both will raise an exception.
    credentials google.auth.credentials.Credentials

    The authorization credentials to attach to requests. These credentials identify this application to the service. If none are specified, the client will attempt to ascertain the credentials from the environment. This argument is mutually exclusive with providing a transport instance to transport ; doing so will raise an exception.
    client_config dict

    DEPRECATED. A dictionary of call options for each method. If not specified, the default configuration is 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.
    client_options Union[dict, google.api_core.client_options.ClientOptions]

    Client options used to set user options on the client. API Endpoint should be set through client_options.

    annotation_spec_path

      annotation_spec_path 
 ( 
 project 
 , 
 location 
 , 
 dataset 
 , 
 annotation_spec 
 )

    Return a fully-qualified annotation_spec string.

    column_spec_path

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

    Return a fully-qualified column_spec string.

    create_dataset

      create_dataset 
 ( 
 parent 
 , 
 dataset 
 , 
 retry 
 = 
< _MethodDefault 
 . 
 _DEFAULT_VALUE 
 : 
< object 
 object 
>> , 
 timeout 
 = 
< _MethodDefault 
 . 
 _DEFAULT_VALUE 
 : 
< object 
 object 
>> , 
 metadata 
 = 
 None 
 )

    Creates a dataset.

    .. rubric:: Example

    from google.cloud import automl_v1beta1

    client = automl_v1beta1.AutoMlClient()

    parent = client.location_path('[PROJECT]', '[LOCATION]')

    TODO: Initialize dataset :

    dataset = {}

    response = client.create_dataset(parent, dataset)

    Parameters
    Name Description
    parent str

    The resource name of the project to create the dataset for.
    dataset Union[dict, Dataset ]

    The dataset to create. If a dict is provided, it must be of the same form as the protobuf message Dataset

    retry Optional[google.api_core.retry.Retry]

    A retry object used to retry requests. If None is specified, requests will not be retried.
    timeout Optional[float]

    The amount of time, in seconds, to wait for the request to complete. Note that if retry is specified, the timeout applies to each individual attempt.
    metadata Optional[Sequence[Tuple[str, str]]]

    Additional metadata that is provided to the method.
    Exceptions
    Type Description
    google.api_core.exceptions.GoogleAPICallError If the request failed for any reason.
    google.api_core.exceptions.RetryError If the request failed due to a retryable error and retry attempts failed.
    ValueError If the parameters are invalid.

    create_model

      create_model 
 ( 
 parent 
 , 
 model 
 , 
 retry 
 = 
< _MethodDefault 
 . 
 _DEFAULT_VALUE 
 : 
< object 
 object 
>> , 
 timeout 
 = 
< _MethodDefault 
 . 
 _DEFAULT_VALUE 
 : 
< object 
 object 
>> , 
 metadata 
 = 
 None 
 )

    Creates a model. Returns a Model in the 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.

    .. rubric:: Example

    from google.cloud import automl_v1beta1

    client = automl_v1beta1.AutoMlClient()

    parent = client.location_path('[PROJECT]', '[LOCATION]')

    TODO: Initialize model :

    model = {}

    response = client.create_model(parent, model)

    def callback(operation_future): ... # Handle result. ... result = operation_future.result()

    response.add_done_callback(callback)

    Handle metadata.

    metadata = response.metadata()

    Parameters
    Name Description
    parent str

    Resource name of the parent project where the model is being created.
    model Union[dict, Model ]

    The model to create. If a dict is provided, it must be of the same form as the protobuf message Model

    retry Optional[google.api_core.retry.Retry]

    A retry object used to retry requests. If None is specified, requests will not be retried.
    timeout Optional[float]

    The amount of time, in seconds, to wait for the request to complete. Note that if retry is specified, the timeout applies to each individual attempt.
    metadata Optional[Sequence[Tuple[str, str]]]

    Additional metadata that is provided to the method.
    Exceptions
    Type Description
    google.api_core.exceptions.GoogleAPICallError If the request failed for any reason.
    google.api_core.exceptions.RetryError If the request failed due to a retryable error and retry attempts failed.
    ValueError If the parameters are invalid.

    dataset_path

      dataset_path 
 ( 
 project 
 , 
 location 
 , 
 dataset 
 )

    Return a fully-qualified dataset string.

    delete_dataset

      delete_dataset 
 ( 
 name 
 , 
 retry 
 = 
< _MethodDefault 
 . 
 _DEFAULT_VALUE 
 : 
< object 
 object 
>> , 
 timeout 
 = 
< _MethodDefault 
 . 
 _DEFAULT_VALUE 
 : 
< object 
 object 
>> , 
 metadata 
 = 
 None 
 )

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

    .. rubric:: Example

    from google.cloud import automl_v1beta1

    client = automl_v1beta1.AutoMlClient()

    name = client.dataset_path('[PROJECT]', '[LOCATION]', '[DATASET]')

    response = client.delete_dataset(name)

    def callback(operation_future): ... # Handle result. ... result = operation_future.result()

    response.add_done_callback(callback)

    Handle metadata.

    metadata = response.metadata()

    Parameters
    Name Description
    name str

    The resource name of the dataset to delete.
    retry Optional[google.api_core.retry.Retry]

    A retry object used to retry requests. If None is specified, requests will not be retried.
    timeout Optional[float]

    The amount of time, in seconds, to wait for the request to complete. Note that if retry is specified, the timeout applies to each individual attempt.
    metadata Optional[Sequence[Tuple[str, str]]]

    Additional metadata that is provided to the method.
    Exceptions
    Type Description
    google.api_core.exceptions.GoogleAPICallError If the request failed for any reason.
    google.api_core.exceptions.RetryError If the request failed due to a retryable error and retry attempts failed.
    ValueError If the parameters are invalid.

    delete_model

      delete_model 
 ( 
 name 
 , 
 retry 
 = 
< _MethodDefault 
 . 
 _DEFAULT_VALUE 
 : 
< object 
 object 
>> , 
 timeout 
 = 
< _MethodDefault 
 . 
 _DEFAULT_VALUE 
 : 
< object 
 object 
>> , 
 metadata 
 = 
 None 
 )

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

    .. rubric:: Example

    from google.cloud import automl_v1beta1

    client = automl_v1beta1.AutoMlClient()

    name = client.model_path('[PROJECT]', '[LOCATION]', '[MODEL]')

    response = client.delete_model(name)

    def callback(operation_future): ... # Handle result. ... result = operation_future.result()

    response.add_done_callback(callback)

    Handle metadata.

    metadata = response.metadata()

    Parameters
    Name Description
    name str

    Resource name of the model being deleted.
    retry Optional[google.api_core.retry.Retry]

    A retry object used to retry requests. If None is specified, requests will not be retried.
    timeout Optional[float]

    The amount of time, in seconds, to wait for the request to complete. Note that if retry is specified, the timeout applies to each individual attempt.
    metadata Optional[Sequence[Tuple[str, str]]]

    Additional metadata that is provided to the method.
    Exceptions
    Type Description
    google.api_core.exceptions.GoogleAPICallError If the request failed for any reason.
    google.api_core.exceptions.RetryError If the request failed due to a retryable error and retry attempts failed.
    ValueError If the parameters are invalid.

    deploy_model

      deploy_model 
 ( 
 name 
 , 
 image_object_detection_model_deployment_metadata 
 = 
 None 
 , 
 retry 
 = 
< _MethodDefault 
 . 
 _DEFAULT_VALUE 
 : 
< object 
 object 
>> , 
 timeout 
 = 
< _MethodDefault 
 . 
 _DEFAULT_VALUE 
 : 
< object 
 object 
>> , 
 metadata 
 = 
 None 
 )

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

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

    Returns an empty response in the response field when it completes.

    .. rubric:: Example

    from google.cloud import automl_v1beta1

    client = automl_v1beta1.AutoMlClient()

    name = client.model_path('[PROJECT]', '[LOCATION]', '[MODEL]')

    response = client.deploy_model(name)

    def callback(operation_future): ... # Handle result. ... result = operation_future.result()

    response.add_done_callback(callback)

    Handle metadata.

    metadata = response.metadata()

    Parameters
    Name Description
    name str

    Resource name of the model to deploy.
    image_object_detection_model_deployment_metadata Union[dict, ImageObjectDetectionModelDeploymentMetadata ]

    Model deployment metadata specific to Image Object Detection. If a dict is provided, it must be of the same form as the protobuf message ImageObjectDetectionModelDeploymentMetadata

    retry Optional[google.api_core.retry.Retry]

    A retry object used to retry requests. If None is specified, requests will not be retried.
    timeout Optional[float]

    The amount of time, in seconds, to wait for the request to complete. Note that if retry is specified, the timeout applies to each individual attempt.
    metadata Optional[Sequence[Tuple[str, str]]]

    Additional metadata that is provided to the method.
    Exceptions
    Type Description
    google.api_core.exceptions.GoogleAPICallError If the request failed for any reason.
    google.api_core.exceptions.RetryError If the request failed due to a retryable error and retry attempts failed.
    ValueError If the parameters are invalid.

    export_data

      export_data 
 ( 
 name 
 , 
 output_config 
 , 
 retry 
 = 
< _MethodDefault 
 . 
 _DEFAULT_VALUE 
 : 
< object 
 object 
>> , 
 timeout 
 = 
< _MethodDefault 
 . 
 _DEFAULT_VALUE 
 : 
< object 
 object 
>> , 
 metadata 
 = 
 None 
 )

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

    .. rubric:: Example

    from google.cloud import automl_v1beta1

    client = automl_v1beta1.AutoMlClient()

    name = client.dataset_path('[PROJECT]', '[LOCATION]', '[DATASET]')

    TODO: Initialize output_config :

    output_config = {}

    response = client.export_data(name, output_config)

    def callback(operation_future): ... # Handle result. ... result = operation_future.result()

    response.add_done_callback(callback)

    Handle metadata.

    metadata = response.metadata()

    Parameters
    Name Description
    name str

    Required. The resource name of the dataset.
    output_config Union[dict, OutputConfig ]

    Required. The desired output location. If a dict is provided, it must be of the same form as the protobuf message OutputConfig

    retry Optional[google.api_core.retry.Retry]

    A retry object used to retry requests. If None is specified, requests will not be retried.
    timeout Optional[float]

    The amount of time, in seconds, to wait for the request to complete. Note that if retry is specified, the timeout applies to each individual attempt.
    metadata Optional[Sequence[Tuple[str, str]]]

    Additional metadata that is provided to the method.
    Exceptions
    Type Description
    google.api_core.exceptions.GoogleAPICallError If the request failed for any reason.
    google.api_core.exceptions.RetryError If the request failed due to a retryable error and retry attempts failed.
    ValueError If the parameters are invalid.

    export_evaluated_examples

      export_evaluated_examples 
 ( 
 name 
 , 
 output_config 
 , 
 retry 
 = 
< _MethodDefault 
 . 
 _DEFAULT_VALUE 
 : 
< object 
 object 
>> , 
 timeout 
 = 
< _MethodDefault 
 . 
 _DEFAULT_VALUE 
 : 
< object 
 object 
>> , 
 metadata 
 = 
 None 
 )

    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 field when it completes.

    .. rubric:: Example

    from google.cloud import automl_v1beta1

    client = automl_v1beta1.AutoMlClient()

    name = client.model_path('[PROJECT]', '[LOCATION]', '[MODEL]')

    TODO: Initialize output_config :

    output_config = {}

    response = client.export_evaluated_examples(name, output_config)

    def callback(operation_future): ... # Handle result. ... result = operation_future.result()

    response.add_done_callback(callback)

    Handle metadata.

    metadata = response.metadata()

    Parameters
    Name Description
    name str

    Required. The resource name of the model whose evaluated examples are to be exported.
    output_config Union[dict, ExportEvaluatedExamplesOutputConfig ]

    Required. The desired output location and configuration. If a dict is provided, it must be of the same form as the protobuf message ExportEvaluatedExamplesOutputConfig

    retry Optional[google.api_core.retry.Retry]

    A retry object used to retry requests. If None is specified, requests will not be retried.
    timeout Optional[float]

    The amount of time, in seconds, to wait for the request to complete. Note that if retry is specified, the timeout applies to each individual attempt.
    metadata Optional[Sequence[Tuple[str, str]]]

    Additional metadata that is provided to the method.
    Exceptions
    Type Description
    google.api_core.exceptions.GoogleAPICallError If the request failed for any reason.
    google.api_core.exceptions.RetryError If the request failed due to a retryable error and retry attempts failed.
    ValueError If the parameters are invalid.

    export_model

      export_model 
 ( 
 name 
 , 
 output_config 
 , 
 retry 
 = 
< _MethodDefault 
 . 
 _DEFAULT_VALUE 
 : 
< object 
 object 
>> , 
 timeout 
 = 
< _MethodDefault 
 . 
 _DEFAULT_VALUE 
 : 
< object 
 object 
>> , 
 metadata 
 = 
 None 
 )

    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 .

    Returns an empty response in the response field when it completes.

    .. rubric:: Example

    from google.cloud import automl_v1beta1

    client = automl_v1beta1.AutoMlClient()

    name = client.model_path('[PROJECT]', '[LOCATION]', '[MODEL]')

    TODO: Initialize output_config :

    output_config = {}

    response = client.export_model(name, output_config)

    def callback(operation_future): ... # Handle result. ... result = operation_future.result()

    response.add_done_callback(callback)

    Handle metadata.

    metadata = response.metadata()

    Parameters
    Name Description
    name str

    Required. The resource name of the model to export.
    output_config Union[dict, ModelExportOutputConfig ]

    Required. The desired output location and configuration. If a dict is provided, it must be of the same form as the protobuf message ModelExportOutputConfig

    retry Optional[google.api_core.retry.Retry]

    A retry object used to retry requests. If None is specified, requests will not be retried.
    timeout Optional[float]

    The amount of time, in seconds, to wait for the request to complete. Note that if retry is specified, the timeout applies to each individual attempt.
    metadata Optional[Sequence[Tuple[str, str]]]

    Additional metadata that is provided to the method.
    Exceptions
    Type Description
    google.api_core.exceptions.GoogleAPICallError If the request failed for any reason.
    google.api_core.exceptions.RetryError If the request failed due to a retryable error and retry attempts failed.
    ValueError If the parameters are invalid. 
      from_service_account_file 
 ( 
 filename 
 , 
 * 
 args 
 , 
 ** 
 kwargs 
 )

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

    Parameter
    Name Description
    filename str

    The path to the service account private key json file.
    Returns
    Type Description
    AutoMlClient The constructed client. 
      from_service_account_json 
 ( 
 filename 
 , 
 * 
 args 
 , 
 ** 
 kwargs 
 )

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

    Parameter
    Name Description
    filename str

    The path to the service account private key json file.
    Returns
    Type Description
    AutoMlClient The constructed client.

    get_annotation_spec

      get_annotation_spec 
 ( 
 name 
 , 
 retry 
 = 
< _MethodDefault 
 . 
 _DEFAULT_VALUE 
 : 
< object 
 object 
>> , 
 timeout 
 = 
< _MethodDefault 
 . 
 _DEFAULT_VALUE 
 : 
< object 
 object 
>> , 
 metadata 
 = 
 None 
 )

    Gets an annotation spec.

    .. rubric:: Example

    from google.cloud import automl_v1beta1

    client = automl_v1beta1.AutoMlClient()

    name = client.annotation_spec_path('[PROJECT]', '[LOCATION]', '[DATASET]', '[ANNOTATION_SPEC]')

    response = client.get_annotation_spec(name)

    Parameters
    Name Description
    name str

    The resource name of the annotation spec to retrieve.
    retry Optional[google.api_core.retry.Retry]

    A retry object used to retry requests. If None is specified, requests will not be retried.
    timeout Optional[float]

    The amount of time, in seconds, to wait for the request to complete. Note that if retry is specified, the timeout applies to each individual attempt.
    metadata Optional[Sequence[Tuple[str, str]]]

    Additional metadata that is provided to the method.
    Exceptions
    Type Description
    google.api_core.exceptions.GoogleAPICallError If the request failed for any reason.
    google.api_core.exceptions.RetryError If the request failed due to a retryable error and retry attempts failed.
    ValueError If the parameters are invalid.

    get_column_spec

      get_column_spec 
 ( 
 name 
 , 
 field_mask 
 = 
 None 
 , 
 retry 
 = 
< _MethodDefault 
 . 
 _DEFAULT_VALUE 
 : 
< object 
 object 
>> , 
 timeout 
 = 
< _MethodDefault 
 . 
 _DEFAULT_VALUE 
 : 
< object 
 object 
>> , 
 metadata 
 = 
 None 
 )

    Gets a column spec.

    .. rubric:: Example

    from google.cloud import automl_v1beta1

    client = automl_v1beta1.AutoMlClient()

    name = client.column_spec_path('[PROJECT]', '[LOCATION]', '[DATASET]', '[TABLE_SPEC]', '[COLUMN_SPEC]')

    response = client.get_column_spec(name)

    Parameters
    Name Description
    name str

    The resource name of the column spec to retrieve.
    field_mask Union[dict, FieldMask ]

    Mask specifying which fields to read. If a dict is provided, it must be of the same form as the protobuf message FieldMask

    retry Optional[google.api_core.retry.Retry]

    A retry object used to retry requests. If None is specified, requests will not be retried.
    timeout Optional[float]

    The amount of time, in seconds, to wait for the request to complete. Note that if retry is specified, the timeout applies to each individual attempt.
    metadata Optional[Sequence[Tuple[str, str]]]

    Additional metadata that is provided to the method.
    Exceptions
    Type Description
    google.api_core.exceptions.GoogleAPICallError If the request failed for any reason.
    google.api_core.exceptions.RetryError If the request failed due to a retryable error and retry attempts failed.
    ValueError If the parameters are invalid.

    get_dataset

      get_dataset 
 ( 
 name 
 , 
 retry 
 = 
< _MethodDefault 
 . 
 _DEFAULT_VALUE 
 : 
< object 
 object 
>> , 
 timeout 
 = 
< _MethodDefault 
 . 
 _DEFAULT_VALUE 
 : 
< object 
 object 
>> , 
 metadata 
 = 
 None 
 )

    Gets a dataset.

    .. rubric:: Example

    from google.cloud import automl_v1beta1

    client = automl_v1beta1.AutoMlClient()

    name = client.dataset_path('[PROJECT]', '[LOCATION]', '[DATASET]')

    response = client.get_dataset(name)

    Parameters
    Name Description
    name str

    The resource name of the dataset to retrieve.
    retry Optional[google.api_core.retry.Retry]

    A retry object used to retry requests. If None is specified, requests will not be retried.
    timeout Optional[float]

    The amount of time, in seconds, to wait for the request to complete. Note that if retry is specified, the timeout applies to each individual attempt.
    metadata Optional[Sequence[Tuple[str, str]]]

    Additional metadata that is provided to the method.
    Exceptions
    Type Description
    google.api_core.exceptions.GoogleAPICallError If the request failed for any reason.
    google.api_core.exceptions.RetryError If the request failed due to a retryable error and retry attempts failed.
    ValueError If the parameters are invalid.

    get_model

      get_model 
 ( 
 name 
 , 
 retry 
 = 
< _MethodDefault 
 . 
 _DEFAULT_VALUE 
 : 
< object 
 object 
>> , 
 timeout 
 = 
< _MethodDefault 
 . 
 _DEFAULT_VALUE 
 : 
< object 
 object 
>> , 
 metadata 
 = 
 None 
 )

    Gets a model.

    .. rubric:: Example

    from google.cloud import automl_v1beta1

    client = automl_v1beta1.AutoMlClient()

    name = client.model_path('[PROJECT]', '[LOCATION]', '[MODEL]')

    response = client.get_model(name)

    Parameters
    Name Description
    name str

    Resource name of the model.
    retry Optional[google.api_core.retry.Retry]

    A retry object used to retry requests. If None is specified, requests will not be retried.
    timeout Optional[float]

    The amount of time, in seconds, to wait for the request to complete. Note that if retry is specified, the timeout applies to each individual attempt.
    metadata Optional[Sequence[Tuple[str, str]]]

    Additional metadata that is provided to the method.
    Exceptions
    Type Description
    google.api_core.exceptions.GoogleAPICallError If the request failed for any reason.
    google.api_core.exceptions.RetryError If the request failed due to a retryable error and retry attempts failed.
    ValueError If the parameters are invalid.

    get_model_evaluation

      get_model_evaluation 
 ( 
 name 
 , 
 retry 
 = 
< _MethodDefault 
 . 
 _DEFAULT_VALUE 
 : 
< object 
 object 
>> , 
 timeout 
 = 
< _MethodDefault 
 . 
 _DEFAULT_VALUE 
 : 
< object 
 object 
>> , 
 metadata 
 = 
 None 
 )

    Gets a model evaluation.

    .. rubric:: Example

    from google.cloud import automl_v1beta1

    client = automl_v1beta1.AutoMlClient()

    name = client.model_evaluation_path('[PROJECT]', '[LOCATION]', '[MODEL]', '[MODEL_EVALUATION]')

    response = client.get_model_evaluation(name)

    Parameters
    Name Description
    name str

    Resource name for the model evaluation.
    retry Optional[google.api_core.retry.Retry]

    A retry object used to retry requests. If None is specified, requests will not be retried.
    timeout Optional[float]

    The amount of time, in seconds, to wait for the request to complete. Note that if retry is specified, the timeout applies to each individual attempt.
    metadata Optional[Sequence[Tuple[str, str]]]

    Additional metadata that is provided to the method.
    Exceptions
    Type Description
    google.api_core.exceptions.GoogleAPICallError If the request failed for any reason.
    google.api_core.exceptions.RetryError If the request failed due to a retryable error and retry attempts failed.
    ValueError If the parameters are invalid.

    get_table_spec

      get_table_spec 
 ( 
 name 
 , 
 field_mask 
 = 
 None 
 , 
 retry 
 = 
< _MethodDefault 
 . 
 _DEFAULT_VALUE 
 : 
< object 
 object 
>> , 
 timeout 
 = 
< _MethodDefault 
 . 
 _DEFAULT_VALUE 
 : 
< object 
 object 
>> , 
 metadata 
 = 
 None 
 )

    Gets a table spec.

    .. rubric:: Example

    from google.cloud import automl_v1beta1

    client = automl_v1beta1.AutoMlClient()

    name = client.table_spec_path('[PROJECT]', '[LOCATION]', '[DATASET]', '[TABLE_SPEC]')

    response = client.get_table_spec(name)

    Parameters
    Name Description
    name str

    The resource name of the table spec to retrieve.
    field_mask Union[dict, FieldMask ]

    Mask specifying which fields to read. If a dict is provided, it must be of the same form as the protobuf message FieldMask

    retry Optional[google.api_core.retry.Retry]

    A retry object used to retry requests. If None is specified, requests will not be retried.
    timeout Optional[float]

    The amount of time, in seconds, to wait for the request to complete. Note that if retry is specified, the timeout applies to each individual attempt.
    metadata Optional[Sequence[Tuple[str, str]]]

    Additional metadata that is provided to the method.
    Exceptions
    Type Description
    google.api_core.exceptions.GoogleAPICallError If the request failed for any reason.
    google.api_core.exceptions.RetryError If the request failed due to a retryable error and retry attempts failed.
    ValueError If the parameters are invalid.

    import_data

      import_data 
 ( 
 name 
 , 
 input_config 
 , 
 retry 
 = 
< _MethodDefault 
 . 
 _DEFAULT_VALUE 
 : 
< object 
 object 
>> , 
 timeout 
 = 
< _MethodDefault 
 . 
 _DEFAULT_VALUE 
 : 
< object 
 object 
>> , 
 metadata 
 = 
 None 
 )

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

    For Tables:

    • A schema_inference_version parameter must be explicitly set. Returns an empty response in the response field when it completes.

    .. rubric:: Example

    from google.cloud import automl_v1beta1

    client = automl_v1beta1.AutoMlClient()

    name = client.dataset_path('[PROJECT]', '[LOCATION]', '[DATASET]')

    TODO: Initialize input_config :

    input_config = {}

    response = client.import_data(name, input_config)

    def callback(operation_future): ... # Handle result. ... result = operation_future.result()

    response.add_done_callback(callback)

    Handle metadata.

    metadata = response.metadata()

    Parameters
    Name Description
    name str

    Required. Dataset name. Dataset must already exist. All imported annotations and examples will be added.
    input_config Union[dict, InputConfig ]

    Required. The desired input location and its domain specific semantics, if any. If a dict is provided, it must be of the same form as the protobuf message InputConfig

    retry Optional[google.api_core.retry.Retry]

    A retry object used to retry requests. If None is specified, requests will not be retried.
    timeout Optional[float]

    The amount of time, in seconds, to wait for the request to complete. Note that if retry is specified, the timeout applies to each individual attempt.
    metadata Optional[Sequence[Tuple[str, str]]]

    Additional metadata that is provided to the method.
    Exceptions
    Type Description
    google.api_core.exceptions.GoogleAPICallError If the request failed for any reason.
    google.api_core.exceptions.RetryError If the request failed due to a retryable error and retry attempts failed.
    ValueError If the parameters are invalid.

    list_column_specs

      list_column_specs 
 ( 
 parent 
 , 
 field_mask 
 = 
 None 
 , 
 filter_ 
 = 
 None 
 , 
 page_size 
 = 
 None 
 , 
 retry 
 = 
< _MethodDefault 
 . 
 _DEFAULT_VALUE 
 : 
< object 
 object 
>> , 
 timeout 
 = 
< _MethodDefault 
 . 
 _DEFAULT_VALUE 
 : 
< object 
 object 
>> , 
 metadata 
 = 
 None 
 )

    Lists column specs in a table spec.

    .. rubric:: Example

    from google.cloud import automl_v1beta1

    client = automl_v1beta1.AutoMlClient()

    parent = client.table_spec_path('[PROJECT]', '[LOCATION]', '[DATASET]', '[TABLE_SPEC]')

    Iterate over all results

    for element in client.list_column_specs(parent): ... # process element ... pass

    Alternatively:

    Iterate over results one page at a time

    for page in client.list_column_specs(parent).pages: ... for element in page: ... # process element ... pass

    Parameters
    Name Description
    parent str

    The resource name of the table spec to list column specs from.
    field_mask Union[dict, FieldMask ]

    Mask specifying which fields to read. If a dict is provided, it must be of the same form as the protobuf message FieldMask

    filter_ str

    Filter expression, see go/filtering.
    page_size int

    The maximum number of resources contained in the underlying API response. If page streaming is performed per- resource, this parameter does not affect the return value. If page streaming is performed per-page, this determines the maximum number of resources in a page.
    retry Optional[google.api_core.retry.Retry]

    A retry object used to retry requests. If None is specified, requests will not be retried.
    timeout Optional[float]

    The amount of time, in seconds, to wait for the request to complete. Note that if retry is specified, the timeout applies to each individual attempt.
    metadata Optional[Sequence[Tuple[str, str]]]

    Additional metadata that is provided to the method.
    Exceptions
    Type Description
    google.api_core.exceptions.GoogleAPICallError If the request failed for any reason.
    google.api_core.exceptions.RetryError If the request failed due to a retryable error and retry attempts failed.
    ValueError If the parameters are invalid.

    list_datasets

      list_datasets 
 ( 
 parent 
 , 
 filter_ 
 = 
 None 
 , 
 page_size 
 = 
 None 
 , 
 retry 
 = 
< _MethodDefault 
 . 
 _DEFAULT_VALUE 
 : 
< object 
 object 
>> , 
 timeout 
 = 
< _MethodDefault 
 . 
 _DEFAULT_VALUE 
 : 
< object 
 object 
>> , 
 metadata 
 = 
 None 
 )

    Lists datasets in a project.

    .. rubric:: Example

    from google.cloud import automl_v1beta1

    client = automl_v1beta1.AutoMlClient()

    parent = client.location_path('[PROJECT]', '[LOCATION]')

    Iterate over all results

    for element in client.list_datasets(parent): ... # process element ... pass

    Alternatively:

    Iterate over results one page at a time

    for page in client.list_datasets(parent).pages: ... for element in page: ... # process element ... pass

    Parameters
    Name Description
    parent str

    The resource name of the project from which to list datasets.
    filter_ str

    An expression for filtering the results of the request. - dataset_metadata - for existence of the case (e.g. image_classification_dataset_metadata:*). Some examples of using the filter are: - translation_dataset_metadata:* --> The dataset has translation_dataset_metadata.
    page_size int

    The maximum number of resources contained in the underlying API response. If page streaming is performed per- resource, this parameter does not affect the return value. If page streaming is performed per-page, this determines the maximum number of resources in a page.
    retry Optional[google.api_core.retry.Retry]

    A retry object used to retry requests. If None is specified, requests will not be retried.
    timeout Optional[float]

    The amount of time, in seconds, to wait for the request to complete. Note that if retry is specified, the timeout applies to each individual attempt.
    metadata Optional[Sequence[Tuple[str, str]]]

    Additional metadata that is provided to the method.
    Exceptions
    Type Description
    google.api_core.exceptions.GoogleAPICallError If the request failed for any reason.
    google.api_core.exceptions.RetryError If the request failed due to a retryable error and retry attempts failed.
    ValueError If the parameters are invalid.

    list_model_evaluations

      list_model_evaluations 
 ( 
 parent 
 , 
 filter_ 
 = 
 None 
 , 
 page_size 
 = 
 None 
 , 
 retry 
 = 
< _MethodDefault 
 . 
 _DEFAULT_VALUE 
 : 
< object 
 object 
>> , 
 timeout 
 = 
< _MethodDefault 
 . 
 _DEFAULT_VALUE 
 : 
< object 
 object 
>> , 
 metadata 
 = 
 None 
 )

    Lists model evaluations.

    .. rubric:: Example

    from google.cloud import automl_v1beta1

    client = automl_v1beta1.AutoMlClient()

    parent = client.model_path('[PROJECT]', '[LOCATION]', '[MODEL]')

    Iterate over all results

    for element in client.list_model_evaluations(parent): ... # process element ... pass

    Alternatively:

    Iterate over results one page at a time

    for page in client.list_model_evaluations(parent).pages: ... for element in page: ... # process element ... pass

    Parameters
    Name Description
    parent str

    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.
    filter_ str

    An expression for filtering the results of the request. - annotation_spec_id - for =, != or existence. See example below for the last. Some examples of using the filter are: - annotation_spec_id!=4 --> The model evaluation was done for annotation spec with ID different than 4. - NOT annotation_spec_id:* --> The model evaluation was done for aggregate of all annotation specs.
    page_size int

    The maximum number of resources contained in the underlying API response. If page streaming is performed per- resource, this parameter does not affect the return value. If page streaming is performed per-page, this determines the maximum number of resources in a page.
    retry Optional[google.api_core.retry.Retry]

    A retry object used to retry requests. If None is specified, requests will not be retried.
    timeout Optional[float]

    The amount of time, in seconds, to wait for the request to complete. Note that if retry is specified, the timeout applies to each individual attempt.
    metadata Optional[Sequence[Tuple[str, str]]]

    Additional metadata that is provided to the method.
    Exceptions
    Type Description
    google.api_core.exceptions.GoogleAPICallError If the request failed for any reason.
    google.api_core.exceptions.RetryError If the request failed due to a retryable error and retry attempts failed.
    ValueError If the parameters are invalid.

    list_models

      list_models 
 ( 
 parent 
 , 
 filter_ 
 = 
 None 
 , 
 page_size 
 = 
 None 
 , 
 retry 
 = 
< _MethodDefault 
 . 
 _DEFAULT_VALUE 
 : 
< object 
 object 
>> , 
 timeout 
 = 
< _MethodDefault 
 . 
 _DEFAULT_VALUE 
 : 
< object 
 object 
>> , 
 metadata 
 = 
 None 
 )

    Lists models.

    .. rubric:: Example

    from google.cloud import automl_v1beta1

    client = automl_v1beta1.AutoMlClient()

    parent = client.location_path('[PROJECT]', '[LOCATION]')

    Iterate over all results

    for element in client.list_models(parent): ... # process element ... pass

    Alternatively:

    Iterate over results one page at a time

    for page in client.list_models(parent).pages: ... for element in page: ... # process element ... pass

    Parameters
    Name Description
    parent str

    Resource name of the project, from which to list the models.
    filter_ str

    An expression for filtering the results of the request. - model_metadata - for existence of the case (e.g. video_classification_model_metadata:*). - dataset_id - for = or !=. Some examples of using the filter are: - image_classification_model_metadata:* --> The model has image_classification_model_metadata. - dataset_id=5 --> The model was created from a dataset with ID 5.
    page_size int

    The maximum number of resources contained in the underlying API response. If page streaming is performed per- resource, this parameter does not affect the return value. If page streaming is performed per-page, this determines the maximum number of resources in a page.
    retry Optional[google.api_core.retry.Retry]

    A retry object used to retry requests. If None is specified, requests will not be retried.
    timeout Optional[float]

    The amount of time, in seconds, to wait for the request to complete. Note that if retry is specified, the timeout applies to each individual attempt.
    metadata Optional[Sequence[Tuple[str, str]]]

    Additional metadata that is provided to the method.
    Exceptions
    Type Description
    google.api_core.exceptions.GoogleAPICallError If the request failed for any reason.
    google.api_core.exceptions.RetryError If the request failed due to a retryable error and retry attempts failed.
    ValueError If the parameters are invalid.

    list_table_specs

      list_table_specs 
 ( 
 parent 
 , 
 field_mask 
 = 
 None 
 , 
 filter_ 
 = 
 None 
 , 
 page_size 
 = 
 None 
 , 
 retry 
 = 
< _MethodDefault 
 . 
 _DEFAULT_VALUE 
 : 
< object 
 object 
>> , 
 timeout 
 = 
< _MethodDefault 
 . 
 _DEFAULT_VALUE 
 : 
< object 
 object 
>> , 
 metadata 
 = 
 None 
 )

    Lists table specs in a dataset.

    .. rubric:: Example

    from google.cloud import automl_v1beta1

    client = automl_v1beta1.AutoMlClient()

    parent = client.dataset_path('[PROJECT]', '[LOCATION]', '[DATASET]')

    Iterate over all results

    for element in client.list_table_specs(parent): ... # process element ... pass

    Alternatively:

    Iterate over results one page at a time

    for page in client.list_table_specs(parent).pages: ... for element in page: ... # process element ... pass

    Parameters
    Name Description
    parent str

    The resource name of the dataset to list table specs from.
    field_mask Union[dict, FieldMask ]

    Mask specifying which fields to read. If a dict is provided, it must be of the same form as the protobuf message FieldMask

    filter_ str

    Filter expression, see go/filtering.
    page_size int

    The maximum number of resources contained in the underlying API response. If page streaming is performed per- resource, this parameter does not affect the return value. If page streaming is performed per-page, this determines the maximum number of resources in a page.
    retry Optional[google.api_core.retry.Retry]

    A retry object used to retry requests. If None is specified, requests will not be retried.
    timeout Optional[float]

    The amount of time, in seconds, to wait for the request to complete. Note that if retry is specified, the timeout applies to each individual attempt.
    metadata Optional[Sequence[Tuple[str, str]]]

    Additional metadata that is provided to the method.
    Exceptions
    Type Description
    google.api_core.exceptions.GoogleAPICallError If the request failed for any reason.
    google.api_core.exceptions.RetryError If the request failed due to a retryable error and retry attempts failed.
    ValueError If the parameters are invalid.

    location_path

      location_path 
 ( 
 project 
 , 
 location 
 )

    Return a fully-qualified location string.

    model_evaluation_path

      model_evaluation_path 
 ( 
 project 
 , 
 location 
 , 
 model 
 , 
 model_evaluation 
 )

    Return a fully-qualified model_evaluation string.

    model_path

      model_path 
 ( 
 project 
 , 
 location 
 , 
 model 
 )

    Return a fully-qualified model string.

    table_spec_path

      table_spec_path 
 ( 
 project 
 , 
 location 
 , 
 dataset 
 , 
 table_spec 
 )

    Return a fully-qualified table_spec string.

    undeploy_model

      undeploy_model 
 ( 
 name 
 , 
 retry 
 = 
< _MethodDefault 
 . 
 _DEFAULT_VALUE 
 : 
< object 
 object 
>> , 
 timeout 
 = 
< _MethodDefault 
 . 
 _DEFAULT_VALUE 
 : 
< object 
 object 
>> , 
 metadata 
 = 
 None 
 )

    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 field when it completes.

    .. rubric:: Example

    from google.cloud import automl_v1beta1

    client = automl_v1beta1.AutoMlClient()

    name = client.model_path('[PROJECT]', '[LOCATION]', '[MODEL]')

    response = client.undeploy_model(name)

    def callback(operation_future): ... # Handle result. ... result = operation_future.result()

    response.add_done_callback(callback)

    Handle metadata.

    metadata = response.metadata()

    Parameters
    Name Description
    name str

    Resource name of the model to undeploy.
    retry Optional[google.api_core.retry.Retry]

    A retry object used to retry requests. If None is specified, requests will not be retried.
    timeout Optional[float]

    The amount of time, in seconds, to wait for the request to complete. Note that if retry is specified, the timeout applies to each individual attempt.
    metadata Optional[Sequence[Tuple[str, str]]]

    Additional metadata that is provided to the method.
    Exceptions
    Type Description
    google.api_core.exceptions.GoogleAPICallError If the request failed for any reason.
    google.api_core.exceptions.RetryError If the request failed due to a retryable error and retry attempts failed.
    ValueError If the parameters are invalid.

    update_column_spec

      update_column_spec 
 ( 
 column_spec 
 , 
 update_mask 
 = 
 None 
 , 
 retry 
 = 
< _MethodDefault 
 . 
 _DEFAULT_VALUE 
 : 
< object 
 object 
>> , 
 timeout 
 = 
< _MethodDefault 
 . 
 _DEFAULT_VALUE 
 : 
< object 
 object 
>> , 
 metadata 
 = 
 None 
 )

    Updates a column spec.

    .. rubric:: Example

    from google.cloud import automl_v1beta1

    client = automl_v1beta1.AutoMlClient()

    TODO: Initialize column_spec :

    column_spec = {}

    response = client.update_column_spec(column_spec)

    Parameters
    Name Description
    column_spec Union[dict, ColumnSpec ]

    The column spec which replaces the resource on the server. If a dict is provided, it must be of the same form as the protobuf message ColumnSpec

    update_mask Union[dict, FieldMask ]

    The update mask applies to the resource. For the FieldMask definition, see https: //developers.google.com/protocol-buffers // /docs/reference/google.protobuf#fieldmask If a dict is provided, it must be of the same form as the protobuf message FieldMask

    retry Optional[google.api_core.retry.Retry]

    A retry object used to retry requests. If None is specified, requests will not be retried.
    timeout Optional[float]

    The amount of time, in seconds, to wait for the request to complete. Note that if retry is specified, the timeout applies to each individual attempt.
    metadata Optional[Sequence[Tuple[str, str]]]

    Additional metadata that is provided to the method.
    Exceptions
    Type Description
    google.api_core.exceptions.GoogleAPICallError If the request failed for any reason.
    google.api_core.exceptions.RetryError If the request failed due to a retryable error and retry attempts failed.
    ValueError If the parameters are invalid.

    update_dataset

      update_dataset 
 ( 
 dataset 
 , 
 update_mask 
 = 
 None 
 , 
 retry 
 = 
< _MethodDefault 
 . 
 _DEFAULT_VALUE 
 : 
< object 
 object 
>> , 
 timeout 
 = 
< _MethodDefault 
 . 
 _DEFAULT_VALUE 
 : 
< object 
 object 
>> , 
 metadata 
 = 
 None 
 )

    Updates a dataset.

    .. rubric:: Example

    from google.cloud import automl_v1beta1

    client = automl_v1beta1.AutoMlClient()

    TODO: Initialize dataset :

    dataset = {}

    response = client.update_dataset(dataset)

    Parameters
    Name Description
    dataset Union[dict, Dataset ]

    The dataset which replaces the resource on the server. If a dict is provided, it must be of the same form as the protobuf message Dataset

    update_mask Union[dict, FieldMask ]

    The update mask applies to the resource. For the FieldMask definition, see https: //developers.google.com/protocol-buffers // /docs/reference/google.protobuf#fieldmask If a dict is provided, it must be of the same form as the protobuf message FieldMask

    retry Optional[google.api_core.retry.Retry]

    A retry object used to retry requests. If None is specified, requests will not be retried.
    timeout Optional[float]

    The amount of time, in seconds, to wait for the request to complete. Note that if retry is specified, the timeout applies to each individual attempt.
    metadata Optional[Sequence[Tuple[str, str]]]

    Additional metadata that is provided to the method.
    Exceptions
    Type Description
    google.api_core.exceptions.GoogleAPICallError If the request failed for any reason.
    google.api_core.exceptions.RetryError If the request failed due to a retryable error and retry attempts failed.
    ValueError If the parameters are invalid.

    update_table_spec

      update_table_spec 
 ( 
 table_spec 
 , 
 update_mask 
 = 
 None 
 , 
 retry 
 = 
< _MethodDefault 
 . 
 _DEFAULT_VALUE 
 : 
< object 
 object 
>> , 
 timeout 
 = 
< _MethodDefault 
 . 
 _DEFAULT_VALUE 
 : 
< object 
 object 
>> , 
 metadata 
 = 
 None 
 )

    Updates a table spec.

    .. rubric:: Example

    from google.cloud import automl_v1beta1

    client = automl_v1beta1.AutoMlClient()

    TODO: Initialize table_spec :

    table_spec = {}

    response = client.update_table_spec(table_spec)

    Parameters
    Name Description
    table_spec Union[dict, TableSpec ]

    The table spec which replaces the resource on the server. If a dict is provided, it must be of the same form as the protobuf message TableSpec

    update_mask Union[dict, FieldMask ]

    The update mask applies to the resource. For the FieldMask definition, see https: //developers.google.com/protocol-buffers // /docs/reference/google.protobuf#fieldmask If a dict is provided, it must be of the same form as the protobuf message FieldMask

    retry Optional[google.api_core.retry.Retry]

    A retry object used to retry requests. If None is specified, requests will not be retried.
    timeout Optional[float]

    The amount of time, in seconds, to wait for the request to complete. Note that if retry is specified, the timeout applies to each individual attempt.
    metadata Optional[Sequence[Tuple[str, str]]]

    Additional metadata that is provided to the method.
    Exceptions
    Type Description
    google.api_core.exceptions.GoogleAPICallError If the request failed for any reason.
    google.api_core.exceptions.RetryError If the request failed due to a retryable error and retry attempts failed.
    ValueError If the parameters are invalid.
    Create a Mobile Website
    View Site in Mobile | Classic
    Share by: