Class ModelServiceClient (1.23.0)

ModelServiceClient(*, credentials: typing.Optional[google.auth.credentials.Credentials] = None, transport: typing.Optional[typing.Union[str, google.cloud.retail_v2.services.model_service.transports.base.ModelServiceTransport, typing.Callable[[...], google.cloud.retail_v2.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>)

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.

Properties

api_endpoint

Return the API endpoint used by the client instance.

Returns
Type	Description
`str`	The API endpoint used by the client instance.

transport

Returns the transport used by the client instance.

Returns
Type	Description
`ModelServiceTransport`	The transport used by the client instance.

universe_domain

Return the universe domain used by the client instance.

Returns
Type	Description
`str`	The universe domain used by the client instance.

Methods

ModelServiceClient

ModelServiceClient(*, credentials: typing.Optional[google.auth.credentials.Credentials] = None, transport: typing.Optional[typing.Union[str, google.cloud.retail_v2.services.model_service.transports.base.ModelServiceTransport, typing.Callable[[...], google.cloud.retail_v2.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>)

Instantiates the model service client.

Parameters
Name	Description
`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.

Exceptions
Type	Description
`google.auth.exceptions.MutualTLSChannelError`	If mutual TLS transport creation failed for any reason.

exit

__exit__(type, value, traceback)

Releases underlying transport's resources.

catalog_path

catalog_path(project: str, location: str, catalog: str) -> str

Returns a fully-qualified catalog string.

common_billing_account_path

common_billing_account_path(billing_account: str) -> str

Returns a fully-qualified billing_account string.

common_folder_path

common_folder_path(folder: str) -> str

Returns a fully-qualified folder string.

common_location_path

common_location_path(project: str, location: str) -> str

Returns a fully-qualified location string.

common_organization_path

common_organization_path(organization: str) -> str

Returns a fully-qualified organization string.

common_project_path

common_project_path(project: str) -> str

Returns a fully-qualified project string.

create_model

create_model(
    request: typing.Optional[
        typing.Union[
            google.cloud.retail_v2.types.model_service.CreateModelRequest, dict
        ]
    ] = None,
    *,
    parent: typing.Optional[str] = None,
    model: typing.Optional[google.cloud.retail_v2.types.model.Model] = None,
    retry: typing.Optional[
        typing.Union[
            google.api_core.retry.retry_unary.Retry,
            google.api_core.gapic_v1.method._MethodDefault,
        ]
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.api_core.operation.Operation

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_v2

def sample_create_model():
    # Create a client
    client = retail_v2.ModelServiceClient()

    # Initialize request argument(s)
    model = retail_v2.Model()
    model.name = "name_value"
    model.display_name = "display_name_value"
    model.type_ = "type__value"

    request = retail_v2.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
Name	Description
`request`	`Union[google.cloud.retail_v2.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_v2.types.Model` Required. The payload of the Model to create. This corresponds to the `model` field on the `request` instance; if `request` is provided, this should not be set.
`retry`	`google.api_core.retry.Retry` Designation of what errors, if any, should be retried.
`timeout`	`float` The timeout for this request.
`metadata`	`Sequence[Tuple[str, str]]` Strings which should be sent along with the request as metadata.

Returns
Type	Description
`google.api_core.operation.Operation`	An object representing a long-running operation. The result type for the operation will be Model Metadata that describes the training and serving parameters of a Model. A Model can be associated with a ServingConfig and then queried through the Predict API.

delete_model

delete_model(
    request: typing.Optional[
        typing.Union[
            google.cloud.retail_v2.types.model_service.DeleteModelRequest, dict
        ]
    ] = None,
    *,
    name: typing.Optional[str] = None,
    retry: typing.Optional[
        typing.Union[
            google.api_core.retry.retry_unary.Retry,
            google.api_core.gapic_v1.method._MethodDefault,
        ]
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> None

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_v2

def sample_delete_model():
    # Create a client
    client = retail_v2.ModelServiceClient()

    # Initialize request argument(s)
    request = retail_v2.DeleteModelRequest(
        name="name_value",
    )

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

Parameters
Name	Description
`request`	`Union[google.cloud.retail_v2.types.DeleteModelRequest, dict]` The request object. Request for deleting a model.
`name`	`str` Required. The resource name of the 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.

from_service_account_file

from_service_account_file(filename: str, *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
`ModelServiceClient`	The constructed client.

from_service_account_info

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

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

Parameter
Name	Description
`info`	`dict` The service account private key info.

Returns
Type	Description
`ModelServiceClient`	The constructed client.

from_service_account_json

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

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

Parameter
Name	Description
`filename`	`str` The path to the service account private key json file.

Returns
Type	Description
`ModelServiceClient`	The constructed client.

get_model

get_model(
    request: typing.Optional[
        typing.Union[google.cloud.retail_v2.types.model_service.GetModelRequest, dict]
    ] = None,
    *,
    name: typing.Optional[str] = None,
    retry: typing.Optional[
        typing.Union[
            google.api_core.retry.retry_unary.Retry,
            google.api_core.gapic_v1.method._MethodDefault,
        ]
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.cloud.retail_v2.types.model.Model

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_v2

def sample_get_model():
    # Create a client
    client = retail_v2.ModelServiceClient()

    # Initialize request argument(s)
    request = retail_v2.GetModelRequest(
        name="name_value",
    )

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

    # Handle the response
    print(response)

Parameters
Name	Description
`request`	`Union[google.cloud.retail_v2.types.GetModelRequest, dict]` The request object. Request for getting a model.
`name`	`str` Required. The resource name of the 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
Type	Description
`google.cloud.retail_v2.types.Model`	Metadata that describes the training and serving parameters of a Model. A Model can be associated with a ServingConfig and then queried through the Predict API.

get_mtls_endpoint_and_cert_source

get_mtls_endpoint_and_cert_source(
    client_options: typing.Optional[
        google.api_core.client_options.ClientOptions
    ] = None,
)

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.

Parameter
Name	Description
`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.

Exceptions
Type	Description
`google.auth.exceptions.MutualTLSChannelError`	If any errors happen.

Returns
Type	Description
`Tuple[str, Callable[[], Tuple[bytes, bytes]]]`	returns the API endpoint and the client cert source to use.

get_operation

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

Gets the latest state of a long-running operation.

Parameters
Name	Description
`request`	`.operations_pb2.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
Type	Description
`.operations_pb2.Operation`	An `Operation` object.

list_models

list_models(
    request: typing.Optional[
        typing.Union[google.cloud.retail_v2.types.model_service.ListModelsRequest, dict]
    ] = None,
    *,
    parent: typing.Optional[str] = None,
    retry: typing.Optional[
        typing.Union[
            google.api_core.retry.retry_unary.Retry,
            google.api_core.gapic_v1.method._MethodDefault,
        ]
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.cloud.retail_v2.services.model_service.pagers.ListModelsPager

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_v2

def sample_list_models():
    # Create a client
    client = retail_v2.ModelServiceClient()

    # Initialize request argument(s)
    request = retail_v2.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
Name	Description
`request`	`Union[google.cloud.retail_v2.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
Type	Description
`google.cloud.retail_v2.services.model_service.pagers.ListModelsPager`	Response to a ListModelRequest. Iterating over this object will yield results and resolve additional pages automatically.

list_operations

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

Lists operations that match the specified filter in the request.

Parameters
Name	Description
`request`	`.operations_pb2.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
Type	Description
`.operations_pb2.ListOperationsResponse`	Response message for `ListOperations` method.

model_path

model_path(project: str, location: str, catalog: str, model: str) -> str

Returns a fully-qualified model string.

parse_catalog_path

parse_catalog_path(path: str) -> typing.Dict[str, str]

Parses a catalog path into its component segments.

parse_common_billing_account_path

parse_common_billing_account_path(path: str) -> typing.Dict[str, str]

Parse a billing_account path into its component segments.

parse_common_folder_path

parse_common_folder_path(path: str) -> typing.Dict[str, str]

Parse a folder path into its component segments.

parse_common_location_path

parse_common_location_path(path: str) -> typing.Dict[str, str]

Parse a location path into its component segments.

parse_common_organization_path

parse_common_organization_path(path: str) -> typing.Dict[str, str]

Parse a organization path into its component segments.

parse_common_project_path

parse_common_project_path(path: str) -> typing.Dict[str, str]

Parse a project path into its component segments.

parse_model_path

parse_model_path(path: str) -> typing.Dict[str, str]

Parses a model path into its component segments.

pause_model

pause_model(
    request: typing.Optional[
        typing.Union[google.cloud.retail_v2.types.model_service.PauseModelRequest, dict]
    ] = None,
    *,
    name: typing.Optional[str] = None,
    retry: typing.Optional[
        typing.Union[
            google.api_core.retry.retry_unary.Retry,
            google.api_core.gapic_v1.method._MethodDefault,
        ]
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.cloud.retail_v2.types.model.Model

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_v2

def sample_pause_model():
    # Create a client
    client = retail_v2.ModelServiceClient()

    # Initialize request argument(s)
    request = retail_v2.PauseModelRequest(
        name="name_value",
    )

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

    # Handle the response
    print(response)

Parameters
Name	Description
`request`	`Union[google.cloud.retail_v2.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
Type	Description
`google.cloud.retail_v2.types.Model`	Metadata that describes the training and serving parameters of a Model. A Model can be associated with a ServingConfig and then queried through the Predict API.

resume_model

resume_model(
    request: typing.Optional[
        typing.Union[
            google.cloud.retail_v2.types.model_service.ResumeModelRequest, dict
        ]
    ] = None,
    *,
    name: typing.Optional[str] = None,
    retry: typing.Optional[
        typing.Union[
            google.api_core.retry.retry_unary.Retry,
            google.api_core.gapic_v1.method._MethodDefault,
        ]
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.cloud.retail_v2.types.model.Model

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_v2

def sample_resume_model():
    # Create a client
    client = retail_v2.ModelServiceClient()

    # Initialize request argument(s)
    request = retail_v2.ResumeModelRequest(
        name="name_value",
    )

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

    # Handle the response
    print(response)

Parameters
Name	Description
`request`	`Union[google.cloud.retail_v2.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
Type	Description
`google.cloud.retail_v2.types.Model`	Metadata that describes the training and serving parameters of a Model. A Model can be associated with a ServingConfig and then queried through the Predict API.

tune_model

tune_model(
    request: typing.Optional[
        typing.Union[google.cloud.retail_v2.types.model_service.TuneModelRequest, dict]
    ] = None,
    *,
    name: typing.Optional[str] = None,
    retry: typing.Optional[
        typing.Union[
            google.api_core.retry.retry_unary.Retry,
            google.api_core.gapic_v1.method._MethodDefault,
        ]
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.api_core.operation.Operation

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_v2

def sample_tune_model():
    # Create a client
    client = retail_v2.ModelServiceClient()

    # Initialize request argument(s)
    request = retail_v2.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
Name	Description
`request`	`Union[google.cloud.retail_v2.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
Type	Description
`google.api_core.operation.Operation`	An object representing a long-running operation. The result type for the operation will be TuneModelResponse Response associated with a tune operation.

update_model

update_model(
    request: typing.Optional[
        typing.Union[
            google.cloud.retail_v2.types.model_service.UpdateModelRequest, dict
        ]
    ] = None,
    *,
    model: typing.Optional[google.cloud.retail_v2.types.model.Model] = None,
    update_mask: typing.Optional[google.protobuf.field_mask_pb2.FieldMask] = None,
    retry: typing.Optional[
        typing.Union[
            google.api_core.retry.retry_unary.Retry,
            google.api_core.gapic_v1.method._MethodDefault,
        ]
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.cloud.retail_v2.types.model.Model

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_v2

def sample_update_model():
    # Create a client
    client = retail_v2.ModelServiceClient()

    # Initialize request argument(s)
    model = retail_v2.Model()
    model.name = "name_value"
    model.display_name = "display_name_value"
    model.type_ = "type__value"

    request = retail_v2.UpdateModelRequest(
        model=model,
    )

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

    # Handle the response
    print(response)

Parameters
Name	Description
`request`	`Union[google.cloud.retail_v2.types.UpdateModelRequest, dict]` The request object. Request for updating an existing model.
`model`	`google.cloud.retail_v2.types.Model` Required. The body of the updated 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
Type	Description
`google.cloud.retail_v2.types.Model`	Metadata that describes the training and serving parameters of a Model. A Model can be associated with a ServingConfig and then queried through the Predict API.