As of January 1, 2020 this library no longer supports Python 2 on the latest released version. Library versions released prior to that date will continue to be available. For more information please visit Python 2 support on Google Cloud.

ModelService

class google.cloud.retail_v2alpha.services.model_service.ModelServiceAsyncClient(*, credentials: typing.Optional[google.auth.credentials.Credentials] = None, transport: typing.Optional[typing.Union[str, google.cloud.retail_v2alpha.services.model_service.transports.base.ModelServiceTransport, typing.Callable[[...], google.cloud.retail_v2alpha.services.model_service.transports.base.ModelServiceTransport]]] = 'grpc_asyncio', client_options: typing.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]

Service for performing CRUD operations on models. Recommendation models contain all the metadata necessary to generate a set of models for the Predict() API. A model is queried indirectly via a ServingConfig, which associates a model with a given Placement (e.g. Frequently Bought Together on Home Page).

This service allows you to do the following:

  • Initiate training of a model.

  • Pause training of an existing model.

  • List all the available models along with their metadata.

  • Control their tuning schedule.

Instantiates the model service async 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 (Optional[Union[str,ModelServiceTransport,Callable[..., ModelServiceTransport]]]) – The transport to use, or a Callable that constructs and returns a new transport to use. If a Callable is given, it will be called with the same set of initialization arguments as used in the ModelServiceTransport constructor. If set to None, a transport is chosen automatically.

  • client_options (Optional[Union[google.api_core.client_options.ClientOptions, dict]]) –

    Custom options for the client.

    1. The api_endpoint property can be used to override the default endpoint provided by the client when transport is not explicitly provided. Only if this property is not set and transport was not explicitly provided, the endpoint is determined by the GOOGLE_API_USE_MTLS_ENDPOINT environment variable, which have one of the following values: “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).

    2. If the GOOGLE_API_USE_CLIENT_CERTIFICATE environment variable is “true”, then the client_cert_source property can be used to provide a client certificate for mTLS 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.

    3. The universe_domain property can be used to override the default “googleapis.com” universe. Note that api_endpoint property still takes precedence; and universe_domain is currently not supported for mTLS.

  • 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.

property api_endpoint

Return the API endpoint used by the client instance.

Returns

The API endpoint used by the client instance.

Return type

str

static catalog_path(project: str, location: str, catalog: str) → str

Returns a fully-qualified catalog 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_model(request: Optional[Union[google.cloud.retail_v2alpha.types.model_service.CreateModelRequest, dict]] = None, *, parent: Optional[str] = None, model: Optional[google.cloud.retail_v2alpha.types.model.Model] = None, retry: Optional[Union[google.api_core.retry.retry_unary_async.AsyncRetry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → google.api_core.operation_async.AsyncOperation[source]

Creates a new model.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import retail_v2alpha

async def sample_create_model():
    # Create a client
    client = retail_v2alpha.ModelServiceAsyncClient()

    # Initialize request argument(s)
    model = retail_v2alpha.Model()
    model.page_optimization_config.page_optimization_event_type = "page_optimization_event_type_value"
    model.page_optimization_config.panels.candidates.serving_config_id = "serving_config_id_value"
    model.page_optimization_config.panels.default_candidate.serving_config_id = "serving_config_id_value"
    model.name = "name_value"
    model.display_name = "display_name_value"
    model.type_ = "type__value"

    request = retail_v2alpha.CreateModelRequest(
        parent="parent_value",
        model=model,
    )

    # Make the request
    operation = client.create_model(request=request)

    print("Waiting for operation to complete...")

    response = (await operation).result()

    # Handle the response
    print(response)
Parameters

  • request (Optional[Union[google.cloud.retail_v2alpha.types.CreateModelRequest, dict]]) – The request object. Request for creating a model.

  • parent (str) –

    Required. The parent resource under which to create the model. Format: projects/{project_number}/locations/{location_id}/catalogs/{catalog_id}

    This corresponds to the parent field on the request instance; if request is provided, this should not be set.

  • model (google.cloud.retail_v2alpha.types.Model) –

    Required. The payload of the [Model][google.cloud.retail.v2alpha.Model] to create.

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

  • retry (google.api_core.retry_async.AsyncRetry) – 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.retail_v2alpha.types.Model Metadata that describes the training and serving parameters of a

[Model][google.cloud.retail.v2alpha.Model]. A [Model][google.cloud.retail.v2alpha.Model] can be associated with a [ServingConfig][google.cloud.retail.v2alpha.ServingConfig] and then queried through the Predict API.

Return type

google.api_core.operation_async.AsyncOperation

async delete_model(request: Optional[Union[google.cloud.retail_v2alpha.types.model_service.DeleteModelRequest, dict]] = None, *, name: Optional[str] = None, retry: Optional[Union[google.api_core.retry.retry_unary_async.AsyncRetry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → None[source]

Deletes an existing model.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import retail_v2alpha

async def sample_delete_model():
    # Create a client
    client = retail_v2alpha.ModelServiceAsyncClient()

    # Initialize request argument(s)
    request = retail_v2alpha.DeleteModelRequest(
        name="name_value",
    )

    # Make the request
    await client.delete_model(request=request)
Parameters

  • request (Optional[Union[google.cloud.retail_v2alpha.types.DeleteModelRequest, dict]]) – The request object. Request for deleting a model.

  • name (str) –

    Required. The resource name of the [Model][google.cloud.retail.v2alpha.Model] to delete. Format: projects/{project_number}/locations/{location_id}/catalogs/{catalog_id}/models/{model_id}

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

  • retry (google.api_core.retry_async.AsyncRetry) – 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.

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

ModelServiceAsyncClient

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

ModelServiceAsyncClient

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

ModelServiceAsyncClient

async get_model(request: Optional[Union[google.cloud.retail_v2alpha.types.model_service.GetModelRequest, dict]] = None, *, name: Optional[str] = None, retry: Optional[Union[google.api_core.retry.retry_unary_async.AsyncRetry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → google.cloud.retail_v2alpha.types.model.Model[source]

Gets a model.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import retail_v2alpha

async def sample_get_model():
    # Create a client
    client = retail_v2alpha.ModelServiceAsyncClient()

    # Initialize request argument(s)
    request = retail_v2alpha.GetModelRequest(
        name="name_value",
    )

    # Make the request
    response = await client.get_model(request=request)

    # Handle the response
    print(response)
Parameters

  • request (Optional[Union[google.cloud.retail_v2alpha.types.GetModelRequest, dict]]) – The request object. Request for getting a model.

  • name (str) –

    Required. The resource name of the [Model][google.cloud.retail.v2alpha.Model] to get. Format: projects/{project_number}/locations/{location_id}/catalogs/{catalog}/models/{model_id}

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

  • retry (google.api_core.retry_async.AsyncRetry) – 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

Metadata that describes the training and serving parameters of a

[Model][google.cloud.retail.v2alpha.Model]. A [Model][google.cloud.retail.v2alpha.Model] can be associated with a [ServingConfig][google.cloud.retail.v2alpha.ServingConfig] and then queried through the Predict API.

Return type

google.cloud.retail_v2alpha.types.Model

classmethod get_mtls_endpoint_and_cert_source(client_options: Optional[google.api_core.client_options.ClientOptions] = None)[source]

Return the API endpoint and client cert source for mutual TLS.

The client cert source is determined in the following order: (1) if GOOGLE_API_USE_CLIENT_CERTIFICATE environment variable is not “true”, the client cert source is None. (2) if client_options.client_cert_source is provided, use the provided one; if the default client cert source exists, use the default one; otherwise the client cert source is None.

The API endpoint is determined in the following order: (1) if client_options.api_endpoint if provided, use the provided one. (2) if GOOGLE_API_USE_CLIENT_CERTIFICATE environment variable is “always”, use the default mTLS endpoint; if the environment variable is “never”, use the default API endpoint; otherwise if client cert source exists, use the default mTLS endpoint, otherwise use the default API endpoint.

More details can be found at https://google.aip.dev/auth/4114.

Parameters

client_options (google.api_core.client_options.ClientOptions) – Custom options for the client. Only the api_endpoint and client_cert_source properties may be used in this method.

Returns

returns the API endpoint and the

client cert source to use.

Return type

Tuple[str, Callable[[], Tuple[bytes, bytes]]]

Raises

google.auth.exceptions.MutualTLSChannelError – If any errors happen.

async get_operation(request: Optional[google.longrunning.operations_pb2.GetOperationRequest] = None, *, retry: Optional[Union[google.api_core.retry.retry_unary_async.AsyncRetry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → google.longrunning.operations_pb2.Operation[source]

Gets the latest state of a long-running operation.

Parameters

  • request (GetOperationRequest) – The request object. Request message for GetOperation method.

  • retry (google.api_core.retry_async.AsyncRetry) – 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 Operation object.

Return type

Operation

classmethod get_transport_class(label: Optional[str] = None) → Type[google.cloud.retail_v2alpha.services.model_service.transports.base.ModelServiceTransport]

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 list_models(request: Optional[Union[google.cloud.retail_v2alpha.types.model_service.ListModelsRequest, dict]] = None, *, parent: Optional[str] = None, retry: Optional[Union[google.api_core.retry.retry_unary_async.AsyncRetry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → google.cloud.retail_v2alpha.services.model_service.pagers.ListModelsAsyncPager[source]

Lists all the models linked to this event store.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import retail_v2alpha

async def sample_list_models():
    # Create a client
    client = retail_v2alpha.ModelServiceAsyncClient()

    # Initialize request argument(s)
    request = retail_v2alpha.ListModelsRequest(
        parent="parent_value",
    )

    # Make the request
    page_result = client.list_models(request=request)

    # Handle the response
    async for response in page_result:
        print(response)
Parameters

  • request (Optional[Union[google.cloud.retail_v2alpha.types.ListModelsRequest, dict]]) – The request object. Request for listing models associated with a resource.

  • parent (str) –

    Required. The parent for which to list models. Format: projects/{project_number}/locations/{location_id}/catalogs/{catalog_id}

    This corresponds to the parent field on the request instance; if request is provided, this should not be set.

  • retry (google.api_core.retry_async.AsyncRetry) – 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 to a ListModelRequest.

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

Return type

google.cloud.retail_v2alpha.services.model_service.pagers.ListModelsAsyncPager

async list_operations(request: Optional[google.longrunning.operations_pb2.ListOperationsRequest] = None, *, retry: Optional[Union[google.api_core.retry.retry_unary_async.AsyncRetry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → google.longrunning.operations_pb2.ListOperationsResponse[source]

Lists operations that match the specified filter in the request.

Parameters

  • request (ListOperationsRequest) – The request object. Request message for ListOperations method.

  • retry (google.api_core.retry_async.AsyncRetry) – 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 ListOperations method.

Return type

ListOperationsResponse

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

Returns a fully-qualified model string.

static parse_catalog_path(path: str) → Dict[str, str]

Parses a catalog 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_model_path(path: str) → Dict[str, str]

Parses a model path into its component segments.

async pause_model(request: Optional[Union[google.cloud.retail_v2alpha.types.model_service.PauseModelRequest, dict]] = None, *, name: Optional[str] = None, retry: Optional[Union[google.api_core.retry.retry_unary_async.AsyncRetry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → google.cloud.retail_v2alpha.types.model.Model[source]

Pauses the training of an existing model.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import retail_v2alpha

async def sample_pause_model():
    # Create a client
    client = retail_v2alpha.ModelServiceAsyncClient()

    # Initialize request argument(s)
    request = retail_v2alpha.PauseModelRequest(
        name="name_value",
    )

    # Make the request
    response = await client.pause_model(request=request)

    # Handle the response
    print(response)
Parameters

  • request (Optional[Union[google.cloud.retail_v2alpha.types.PauseModelRequest, dict]]) – The request object. Request for pausing training of a model.

  • name (str) –

    Required. The name of the model to pause. Format: projects/{project_number}/locations/{location_id}/catalogs/{catalog_id}/models/{model_id}

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

  • retry (google.api_core.retry_async.AsyncRetry) – 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

Metadata that describes the training and serving parameters of a

[Model][google.cloud.retail.v2alpha.Model]. A [Model][google.cloud.retail.v2alpha.Model] can be associated with a [ServingConfig][google.cloud.retail.v2alpha.ServingConfig] and then queried through the Predict API.

Return type

google.cloud.retail_v2alpha.types.Model

async resume_model(request: Optional[Union[google.cloud.retail_v2alpha.types.model_service.ResumeModelRequest, dict]] = None, *, name: Optional[str] = None, retry: Optional[Union[google.api_core.retry.retry_unary_async.AsyncRetry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → google.cloud.retail_v2alpha.types.model.Model[source]

Resumes the training of an existing model.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import retail_v2alpha

async def sample_resume_model():
    # Create a client
    client = retail_v2alpha.ModelServiceAsyncClient()

    # Initialize request argument(s)
    request = retail_v2alpha.ResumeModelRequest(
        name="name_value",
    )

    # Make the request
    response = await client.resume_model(request=request)

    # Handle the response
    print(response)
Parameters

  • request (Optional[Union[google.cloud.retail_v2alpha.types.ResumeModelRequest, dict]]) – The request object. Request for resuming training of a model.

  • name (str) –

    Required. The name of the model to resume. Format: projects/{project_number}/locations/{location_id}/catalogs/{catalog_id}/models/{model_id}

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

  • retry (google.api_core.retry_async.AsyncRetry) – 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

Metadata that describes the training and serving parameters of a

[Model][google.cloud.retail.v2alpha.Model]. A [Model][google.cloud.retail.v2alpha.Model] can be associated with a [ServingConfig][google.cloud.retail.v2alpha.ServingConfig] and then queried through the Predict API.

Return type

google.cloud.retail_v2alpha.types.Model

property transport: google.cloud.retail_v2alpha.services.model_service.transports.base.ModelServiceTransport

Returns the transport used by the client instance.

Returns

The transport used by the client instance.

Return type

ModelServiceTransport

async tune_model(request: Optional[Union[google.cloud.retail_v2alpha.types.model_service.TuneModelRequest, dict]] = None, *, name: Optional[str] = None, retry: Optional[Union[google.api_core.retry.retry_unary_async.AsyncRetry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → google.api_core.operation_async.AsyncOperation[source]

Tunes an existing model.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import retail_v2alpha

async def sample_tune_model():
    # Create a client
    client = retail_v2alpha.ModelServiceAsyncClient()

    # Initialize request argument(s)
    request = retail_v2alpha.TuneModelRequest(
        name="name_value",
    )

    # Make the request
    operation = client.tune_model(request=request)

    print("Waiting for operation to complete...")

    response = (await operation).result()

    # Handle the response
    print(response)
Parameters

  • request (Optional[Union[google.cloud.retail_v2alpha.types.TuneModelRequest, dict]]) – The request object. Request to manually start a tuning process now (instead of waiting for the periodically scheduled tuning to happen).

  • name (str) –

    Required. The resource name of the model to tune. Format: projects/{project_number}/locations/{location_id}/catalogs/{catalog_id}/models/{model_id}

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

  • retry (google.api_core.retry_async.AsyncRetry) – 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.retail_v2alpha.types.TuneModelResponse Response associated with a tune operation.

Return type

google.api_core.operation_async.AsyncOperation

property universe_domain: str

Return the universe domain used by the client instance.

Returns

The universe domain used

by the client instance.

Return type

str

async update_model(request: Optional[Union[google.cloud.retail_v2alpha.types.model_service.UpdateModelRequest, dict]] = None, *, model: Optional[google.cloud.retail_v2alpha.types.model.Model] = None, update_mask: Optional[google.protobuf.field_mask_pb2.FieldMask] = None, retry: Optional[Union[google.api_core.retry.retry_unary_async.AsyncRetry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → google.cloud.retail_v2alpha.types.model.Model[source]

Update of model metadata. Only fields that currently can be updated are: filtering_option and periodic_tuning_state. If other values are provided, this API method ignores them.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import retail_v2alpha

async def sample_update_model():
    # Create a client
    client = retail_v2alpha.ModelServiceAsyncClient()

    # Initialize request argument(s)
    model = retail_v2alpha.Model()
    model.page_optimization_config.page_optimization_event_type = "page_optimization_event_type_value"
    model.page_optimization_config.panels.candidates.serving_config_id = "serving_config_id_value"
    model.page_optimization_config.panels.default_candidate.serving_config_id = "serving_config_id_value"
    model.name = "name_value"
    model.display_name = "display_name_value"
    model.type_ = "type__value"

    request = retail_v2alpha.UpdateModelRequest(
        model=model,
    )

    # Make the request
    response = await client.update_model(request=request)

    # Handle the response
    print(response)
Parameters

  • request (Optional[Union[google.cloud.retail_v2alpha.types.UpdateModelRequest, dict]]) – The request object. Request for updating an existing model.

  • model (google.cloud.retail_v2alpha.types.Model) –

    Required. The body of the updated [Model][google.cloud.retail.v2alpha.Model].

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

  • update_mask (google.protobuf.field_mask_pb2.FieldMask) –

    Optional. Indicates which fields in the provided ‘model’ to update. If not set, by default updates all fields.

    This corresponds to the update_mask field on the request instance; if request is provided, this should not be set.

  • retry (google.api_core.retry_async.AsyncRetry) – 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

Metadata that describes the training and serving parameters of a

[Model][google.cloud.retail.v2alpha.Model]. A [Model][google.cloud.retail.v2alpha.Model] can be associated with a [ServingConfig][google.cloud.retail.v2alpha.ServingConfig] and then queried through the Predict API.

Return type

google.cloud.retail_v2alpha.types.Model

class google.cloud.retail_v2alpha.services.model_service.ModelServiceClient(*, credentials: typing.Optional[google.auth.credentials.Credentials] = None, transport: typing.Optional[typing.Union[str, google.cloud.retail_v2alpha.services.model_service.transports.base.ModelServiceTransport, typing.Callable[[...], google.cloud.retail_v2alpha.services.model_service.transports.base.ModelServiceTransport]]] = None, client_options: typing.Optional[typing.Union[google.api_core.client_options.ClientOptions, dict]] = None, client_info: google.api_core.gapic_v1.client_info.ClientInfo = <google.api_core.gapic_v1.client_info.ClientInfo object>)[source]

Service for performing CRUD operations on models. Recommendation models contain all the metadata necessary to generate a set of models for the Predict() API. A model is queried indirectly via a ServingConfig, which associates a model with a given Placement (e.g. Frequently Bought Together on Home Page).

This service allows you to do the following:

  • Initiate training of a model.

  • Pause training of an existing model.

  • List all the available models along with their metadata.

  • Control their tuning schedule.

Instantiates the model service 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 (Optional[Union[str,ModelServiceTransport,Callable[..., ModelServiceTransport]]]) – The transport to use, or a Callable that constructs and returns a new transport. If a Callable is given, it will be called with the same set of initialization arguments as used in the ModelServiceTransport constructor. If set to None, a transport is chosen automatically.

  • client_options (Optional[Union[google.api_core.client_options.ClientOptions, dict]]) –

    Custom options for the client.

    1. The api_endpoint property can be used to override the default endpoint provided by the client when transport is not explicitly provided. Only if this property is not set and transport was not explicitly provided, the endpoint is determined by the GOOGLE_API_USE_MTLS_ENDPOINT environment variable, which have one of the following values: “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).

    2. If the GOOGLE_API_USE_CLIENT_CERTIFICATE environment variable is “true”, then the client_cert_source property can be used to provide a client certificate for mTLS 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.

    3. The universe_domain property can be used to override the default “googleapis.com” universe. Note that the api_endpoint property still takes precedence; and universe_domain is currently not supported for mTLS.

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

Raises

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

__exit__(type, value, traceback)[source]

Releases underlying transport’s resources.

Warning

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

property api_endpoint

Return the API endpoint used by the client instance.

Returns

The API endpoint used by the client instance.

Return type

str

static catalog_path(project: str, location: str, catalog: str) → str[source]

Returns a fully-qualified catalog string.

static common_billing_account_path(billing_account: str) → str[source]

Returns a fully-qualified billing_account string.

static common_folder_path(folder: str) → str[source]

Returns a fully-qualified folder string.

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

Returns a fully-qualified location string.

static common_organization_path(organization: str) → str[source]

Returns a fully-qualified organization string.

static common_project_path(project: str) → str[source]

Returns a fully-qualified project string.

create_model(request: Optional[Union[google.cloud.retail_v2alpha.types.model_service.CreateModelRequest, dict]] = None, *, parent: Optional[str] = None, model: Optional[google.cloud.retail_v2alpha.types.model.Model] = None, retry: Optional[Union[google.api_core.retry.retry_unary.Retry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → google.api_core.operation.Operation[source]

Creates a new model.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import retail_v2alpha

def sample_create_model():
    # Create a client
    client = retail_v2alpha.ModelServiceClient()

    # Initialize request argument(s)
    model = retail_v2alpha.Model()
    model.page_optimization_config.page_optimization_event_type = "page_optimization_event_type_value"
    model.page_optimization_config.panels.candidates.serving_config_id = "serving_config_id_value"
    model.page_optimization_config.panels.default_candidate.serving_config_id = "serving_config_id_value"
    model.name = "name_value"
    model.display_name = "display_name_value"
    model.type_ = "type__value"

    request = retail_v2alpha.CreateModelRequest(
        parent="parent_value",
        model=model,
    )

    # Make the request
    operation = client.create_model(request=request)

    print("Waiting for operation to complete...")

    response = operation.result()

    # Handle the response
    print(response)
Parameters

  • request (Union[google.cloud.retail_v2alpha.types.CreateModelRequest, dict]) – The request object. Request for creating a model.

  • parent (str) –

    Required. The parent resource under which to create the model. Format: projects/{project_number}/locations/{location_id}/catalogs/{catalog_id}

    This corresponds to the parent field on the request instance; if request is provided, this should not be set.

  • model (google.cloud.retail_v2alpha.types.Model) –

    Required. The payload of the [Model][google.cloud.retail.v2alpha.Model] to create.

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

  • retry (google.api_core.retry.Retry) – Designation of what errors, if any, should be retried.

  • timeout (float) – The timeout for this request.

  • metadata (Sequence[Tuple[str, str]]) – Strings which should be sent along with the request as metadata.

Returns

An object representing a long-running operation.

The result type for the operation will be google.cloud.retail_v2alpha.types.Model Metadata that describes the training and serving parameters of a

[Model][google.cloud.retail.v2alpha.Model]. A [Model][google.cloud.retail.v2alpha.Model] can be associated with a [ServingConfig][google.cloud.retail.v2alpha.ServingConfig] and then queried through the Predict API.

Return type

google.api_core.operation.Operation

delete_model(request: Optional[Union[google.cloud.retail_v2alpha.types.model_service.DeleteModelRequest, dict]] = None, *, name: Optional[str] = None, retry: Optional[Union[google.api_core.retry.retry_unary.Retry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → None[source]

Deletes an existing model.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import retail_v2alpha

def sample_delete_model():
    # Create a client
    client = retail_v2alpha.ModelServiceClient()

    # Initialize request argument(s)
    request = retail_v2alpha.DeleteModelRequest(
        name="name_value",
    )

    # Make the request
    client.delete_model(request=request)
Parameters

  • request (Union[google.cloud.retail_v2alpha.types.DeleteModelRequest, dict]) – The request object. Request for deleting a model.

  • name (str) –

    Required. The resource name of the [Model][google.cloud.retail.v2alpha.Model] to delete. Format: projects/{project_number}/locations/{location_id}/catalogs/{catalog_id}/models/{model_id}

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

  • retry (google.api_core.retry.Retry) – Designation of what errors, if any, should be retried.

  • timeout (float) – The timeout for this request.

  • metadata (Sequence[Tuple[str, str]]) – Strings which should be sent along with the request as metadata.

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

ModelServiceClient

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

ModelServiceClient

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

ModelServiceClient

get_model(request: Optional[Union[google.cloud.retail_v2alpha.types.model_service.GetModelRequest, dict]] = None, *, name: Optional[str] = None, retry: Optional[Union[google.api_core.retry.retry_unary.Retry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → google.cloud.retail_v2alpha.types.model.Model[source]

Gets a model.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import retail_v2alpha

def sample_get_model():
    # Create a client
    client = retail_v2alpha.ModelServiceClient()

    # Initialize request argument(s)
    request = retail_v2alpha.GetModelRequest(
        name="name_value",
    )

    # Make the request
    response = client.get_model(request=request)

    # Handle the response
    print(response)
Parameters

  • request (Union[google.cloud.retail_v2alpha.types.GetModelRequest, dict]) – The request object. Request for getting a model.

  • name (str) –

    Required. The resource name of the [Model][google.cloud.retail.v2alpha.Model] to get. Format: projects/{project_number}/locations/{location_id}/catalogs/{catalog}/models/{model_id}

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

  • retry (google.api_core.retry.Retry) – Designation of what errors, if any, should be retried.

  • timeout (float) – The timeout for this request.

  • metadata (Sequence[Tuple[str, str]]) – Strings which should be sent along with the request as metadata.

Returns

Metadata that describes the training and serving parameters of a

[Model][google.cloud.retail.v2alpha.Model]. A [Model][google.cloud.retail.v2alpha.Model] can be associated with a [ServingConfig][google.cloud.retail.v2alpha.ServingConfig] and then queried through the Predict API.

Return type

google.cloud.retail_v2alpha.types.Model

classmethod get_mtls_endpoint_and_cert_source(client_options: Optional[google.api_core.client_options.ClientOptions] = None)[source]

Deprecated. Return the API endpoint and client cert source for mutual TLS.

The client cert source is determined in the following order: (1) if GOOGLE_API_USE_CLIENT_CERTIFICATE environment variable is not “true”, the client cert source is None. (2) if client_options.client_cert_source is provided, use the provided one; if the default client cert source exists, use the default one; otherwise the client cert source is None.

The API endpoint is determined in the following order: (1) if client_options.api_endpoint if provided, use the provided one. (2) if GOOGLE_API_USE_CLIENT_CERTIFICATE environment variable is “always”, use the default mTLS endpoint; if the environment variable is “never”, use the default API endpoint; otherwise if client cert source exists, use the default mTLS endpoint, otherwise use the default API endpoint.

More details can be found at https://google.aip.dev/auth/4114.

Parameters

client_options (google.api_core.client_options.ClientOptions) – Custom options for the client. Only the api_endpoint and client_cert_source properties may be used in this method.

Returns

returns the API endpoint and the

client cert source to use.

Return type

Tuple[str, Callable[[], Tuple[bytes, bytes]]]

Raises

google.auth.exceptions.MutualTLSChannelError – If any errors happen.

get_operation(request: Optional[google.longrunning.operations_pb2.GetOperationRequest] = None, *, retry: Optional[Union[google.api_core.retry.retry_unary.Retry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → google.longrunning.operations_pb2.Operation[source]

Gets the latest state of a long-running operation.

Parameters

  • request (GetOperationRequest) – The request object. Request message for GetOperation method.

  • 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 Operation object.

Return type

Operation

list_models(request: Optional[Union[google.cloud.retail_v2alpha.types.model_service.ListModelsRequest, dict]] = None, *, parent: Optional[str] = None, retry: Optional[Union[google.api_core.retry.retry_unary.Retry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → google.cloud.retail_v2alpha.services.model_service.pagers.ListModelsPager[source]

Lists all the models linked to this event store.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import retail_v2alpha

def sample_list_models():
    # Create a client
    client = retail_v2alpha.ModelServiceClient()

    # Initialize request argument(s)
    request = retail_v2alpha.ListModelsRequest(
        parent="parent_value",
    )

    # Make the request
    page_result = client.list_models(request=request)

    # Handle the response
    for response in page_result:
        print(response)
Parameters

  • request (Union[google.cloud.retail_v2alpha.types.ListModelsRequest, dict]) – The request object. Request for listing models associated with a resource.

  • parent (str) –

    Required. The parent for which to list models. Format: projects/{project_number}/locations/{location_id}/catalogs/{catalog_id}

    This corresponds to the parent field on the request instance; if request is provided, this should not be set.

  • retry (google.api_core.retry.Retry) – Designation of what errors, if any, should be retried.

  • timeout (float) – The timeout for this request.

  • metadata (Sequence[Tuple[str, str]]) – Strings which should be sent along with the request as metadata.

Returns

Response to a ListModelRequest.

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

Return type

google.cloud.retail_v2alpha.services.model_service.pagers.ListModelsPager

list_operations(request: Optional[google.longrunning.operations_pb2.ListOperationsRequest] = None, *, retry: Optional[Union[google.api_core.retry.retry_unary.Retry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → google.longrunning.operations_pb2.ListOperationsResponse[source]

Lists operations that match the specified filter in the request.

Parameters

  • request (ListOperationsRequest) – The request object. Request message for ListOperations method.

  • 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 ListOperations method.

Return type

ListOperationsResponse

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

Returns a fully-qualified model string.

static parse_catalog_path(path: str) → Dict[str, str][source]

Parses a catalog 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_model_path(path: str) → Dict[str, str][source]

Parses a model path into its component segments.

pause_model(request: Optional[Union[google.cloud.retail_v2alpha.types.model_service.PauseModelRequest, dict]] = None, *, name: Optional[str] = None, retry: Optional[Union[google.api_core.retry.retry_unary.Retry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → google.cloud.retail_v2alpha.types.model.Model[source]

Pauses the training of an existing model.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import retail_v2alpha

def sample_pause_model():
    # Create a client
    client = retail_v2alpha.ModelServiceClient()

    # Initialize request argument(s)
    request = retail_v2alpha.PauseModelRequest(
        name="name_value",
    )

    # Make the request
    response = client.pause_model(request=request)

    # Handle the response
    print(response)
Parameters

  • request (Union[google.cloud.retail_v2alpha.types.PauseModelRequest, dict]) – The request object. Request for pausing training of a model.

  • name (str) –

    Required. The name of the model to pause. Format: projects/{project_number}/locations/{location_id}/catalogs/{catalog_id}/models/{model_id}

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

  • retry (google.api_core.retry.Retry) – Designation of what errors, if any, should be retried.

  • timeout (float) – The timeout for this request.

  • metadata (Sequence[Tuple[str, str]]) – Strings which should be sent along with the request as metadata.

Returns

Metadata that describes the training and serving parameters of a

[Model][google.cloud.retail.v2alpha.Model]. A [Model][google.cloud.retail.v2alpha.Model] can be associated with a [ServingConfig][google.cloud.retail.v2alpha.ServingConfig] and then queried through the Predict API.

Return type

google.cloud.retail_v2alpha.types.Model

resume_model(request: Optional[Union[google.cloud.retail_v2alpha.types.model_service.ResumeModelRequest, dict]] = None, *, name: Optional[str] = None, retry: Optional[Union[google.api_core.retry.retry_unary.Retry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → google.cloud.retail_v2alpha.types.model.Model[source]

Resumes the training of an existing model.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import retail_v2alpha

def sample_resume_model():
    # Create a client
    client = retail_v2alpha.ModelServiceClient()

    # Initialize request argument(s)
    request = retail_v2alpha.ResumeModelRequest(
        name="name_value",
    )

    # Make the request
    response = client.resume_model(request=request)

    # Handle the response
    print(response)
Parameters

  • request (Union[google.cloud.retail_v2alpha.types.ResumeModelRequest, dict]) – The request object. Request for resuming training of a model.

  • name (str) –

    Required. The name of the model to resume. Format: projects/{project_number}/locations/{location_id}/catalogs/{catalog_id}/models/{model_id}

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

  • retry (google.api_core.retry.Retry) – Designation of what errors, if any, should be retried.

  • timeout (float) – The timeout for this request.

  • metadata (Sequence[Tuple[str, str]]) – Strings which should be sent along with the request as metadata.

Returns

Metadata that describes the training and serving parameters of a

[Model][google.cloud.retail.v2alpha.Model]. A [Model][google.cloud.retail.v2alpha.Model] can be associated with a [ServingConfig][google.cloud.retail.v2alpha.ServingConfig] and then queried through the Predict API.

Return type

google.cloud.retail_v2alpha.types.Model

property transport: google.cloud.retail_v2alpha.services.model_service.transports.base.ModelServiceTransport

Returns the transport used by the client instance.

Returns

The transport used by the client

instance.

Return type

ModelServiceTransport

tune_model(request: Optional[Union[google.cloud.retail_v2alpha.types.model_service.TuneModelRequest, dict]] = None, *, name: Optional[str] = None, retry: Optional[Union[google.api_core.retry.retry_unary.Retry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → google.api_core.operation.Operation[source]

Tunes an existing model.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import retail_v2alpha

def sample_tune_model():
    # Create a client
    client = retail_v2alpha.ModelServiceClient()

    # Initialize request argument(s)
    request = retail_v2alpha.TuneModelRequest(
        name="name_value",
    )

    # Make the request
    operation = client.tune_model(request=request)

    print("Waiting for operation to complete...")

    response = operation.result()

    # Handle the response
    print(response)
Parameters

  • request (Union[google.cloud.retail_v2alpha.types.TuneModelRequest, dict]) – The request object. Request to manually start a tuning process now (instead of waiting for the periodically scheduled tuning to happen).

  • name (str) –

    Required. The resource name of the model to tune. Format: projects/{project_number}/locations/{location_id}/catalogs/{catalog_id}/models/{model_id}

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

  • retry (google.api_core.retry.Retry) – Designation of what errors, if any, should be retried.

  • timeout (float) – The timeout for this request.

  • metadata (Sequence[Tuple[str, str]]) – Strings which should be sent along with the request as metadata.

Returns

An object representing a long-running operation.

The result type for the operation will be google.cloud.retail_v2alpha.types.TuneModelResponse Response associated with a tune operation.

Return type

google.api_core.operation.Operation

property universe_domain: str

Return the universe domain used by the client instance.

Returns

The universe domain used by the client instance.

Return type

str

update_model(request: Optional[Union[google.cloud.retail_v2alpha.types.model_service.UpdateModelRequest, dict]] = None, *, model: Optional[google.cloud.retail_v2alpha.types.model.Model] = None, update_mask: Optional[google.protobuf.field_mask_pb2.FieldMask] = None, retry: Optional[Union[google.api_core.retry.retry_unary.Retry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → google.cloud.retail_v2alpha.types.model.Model[source]

Update of model metadata. Only fields that currently can be updated are: filtering_option and periodic_tuning_state. If other values are provided, this API method ignores them.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import retail_v2alpha

def sample_update_model():
    # Create a client
    client = retail_v2alpha.ModelServiceClient()

    # Initialize request argument(s)
    model = retail_v2alpha.Model()
    model.page_optimization_config.page_optimization_event_type = "page_optimization_event_type_value"
    model.page_optimization_config.panels.candidates.serving_config_id = "serving_config_id_value"
    model.page_optimization_config.panels.default_candidate.serving_config_id = "serving_config_id_value"
    model.name = "name_value"
    model.display_name = "display_name_value"
    model.type_ = "type__value"

    request = retail_v2alpha.UpdateModelRequest(
        model=model,
    )

    # Make the request
    response = client.update_model(request=request)

    # Handle the response
    print(response)
Parameters

  • request (Union[google.cloud.retail_v2alpha.types.UpdateModelRequest, dict]) – The request object. Request for updating an existing model.

  • model (google.cloud.retail_v2alpha.types.Model) –

    Required. The body of the updated [Model][google.cloud.retail.v2alpha.Model].

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

  • update_mask (google.protobuf.field_mask_pb2.FieldMask) –

    Optional. Indicates which fields in the provided ‘model’ to update. If not set, by default updates all fields.

    This corresponds to the update_mask field on the request instance; if request is provided, this should not be set.

  • retry (google.api_core.retry.Retry) – Designation of what errors, if any, should be retried.

  • timeout (float) – The timeout for this request.

  • metadata (Sequence[Tuple[str, str]]) – Strings which should be sent along with the request as metadata.

Returns

Metadata that describes the training and serving parameters of a

[Model][google.cloud.retail.v2alpha.Model]. A [Model][google.cloud.retail.v2alpha.Model] can be associated with a [ServingConfig][google.cloud.retail.v2alpha.ServingConfig] and then queried through the Predict API.

Return type

google.cloud.retail_v2alpha.types.Model

class google.cloud.retail_v2alpha.services.model_service.pagers.ListModelsAsyncPager(method: Callable[[...], Awaitable[google.cloud.retail_v2alpha.types.model_service.ListModelsResponse]], request: google.cloud.retail_v2alpha.types.model_service.ListModelsRequest, response: google.cloud.retail_v2alpha.types.model_service.ListModelsResponse, *, retry: Optional[Union[google.api_core.retry.retry_unary_async.AsyncRetry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ())[source]

A pager for iterating through list_models requests.

This class thinly wraps an initial google.cloud.retail_v2alpha.types.ListModelsResponse object, and provides an __aiter__ method to iterate through its models field.

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

All the usual google.cloud.retail_v2alpha.types.ListModelsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.

Instantiates the pager.

Parameters
class google.cloud.retail_v2alpha.services.model_service.pagers.ListModelsPager(method: Callable[[...], google.cloud.retail_v2alpha.types.model_service.ListModelsResponse], request: google.cloud.retail_v2alpha.types.model_service.ListModelsRequest, response: google.cloud.retail_v2alpha.types.model_service.ListModelsResponse, *, retry: Optional[Union[google.api_core.retry.retry_unary.Retry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ())[source]

A pager for iterating through list_models requests.

This class thinly wraps an initial google.cloud.retail_v2alpha.types.ListModelsResponse object, and provides an __iter__ method to iterate through its models field.

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

All the usual google.cloud.retail_v2alpha.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