ModelServiceClient(*, credentials: typing.Optional[google.auth.credentials.Credentials] = None, transport: typing.Optional[typing.Union[str, google.cloud.retail_v2beta.services.model_service.transports.base.ModelServiceTransport, typing.Callable[[...], google.cloud.retail_v2beta.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_v2beta.services.model_service.transports.base.ModelServiceTransport, typing.Callable[[...], google.cloud.retail_v2beta.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 |
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 |
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_v2beta.types.model_service.CreateModelRequest, dict
]
] = None,
*,
parent: typing.Optional[str] = None,
model: typing.Optional[google.cloud.retail_v2beta.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, typing.Union[str, bytes]]] = ()
) -> 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_v2beta
def sample_create_model():
# Create a client
client = retail_v2beta.ModelServiceClient()
# Initialize request argument(s)
model = retail_v2beta.Model()
model.name = "name_value"
model.display_name = "display_name_value"
model.type_ = "type__value"
request = retail_v2beta.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_v2beta.types.CreateModelRequest, dict]
The request object. Request for creating a model. |
parent |
str
Required. The parent resource under which to create the model. Format: |
model |
google.cloud.retail_v2beta.types.Model
Required. The payload of the Model to create. This corresponds to the |
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, Union[str, bytes]]]
Key/value pairs which should be sent along with the request as metadata. Normally, each value must be of type |
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_v2beta.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, typing.Union[str, bytes]]] = ()
) -> 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_v2beta
def sample_delete_model():
# Create a client
client = retail_v2beta.ModelServiceClient()
# Initialize request argument(s)
request = retail_v2beta.DeleteModelRequest(
name="name_value",
)
# Make the request
client.delete_model(request=request)
Parameters | |
---|---|
Name | Description |
request |
Union[google.cloud.retail_v2beta.types.DeleteModelRequest, dict]
The request object. Request for deleting a model. |
name |
str
Required. The resource name of the Model to delete. Format: |
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, Union[str, bytes]]]
Key/value pairs which should be sent along with the request as metadata. Normally, each value must be of type |
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_v2beta.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, typing.Union[str, bytes]]] = ()
) -> google.cloud.retail_v2beta.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_v2beta
def sample_get_model():
# Create a client
client = retail_v2beta.ModelServiceClient()
# Initialize request argument(s)
request = retail_v2beta.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_v2beta.types.GetModelRequest, dict]
The request object. Request for getting a model. |
name |
str
Required. The resource name of the Model to get. Format: |
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, Union[str, bytes]]]
Key/value pairs which should be sent along with the request as metadata. Normally, each value must be of type |
Returns | |
---|---|
Type | Description |
google.cloud.retail_v2beta.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 |
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, typing.Union[str, bytes]]] = ()
) -> google.longrunning.operations_pb2.Operation
Gets the latest state of a long-running operation.
Parameters | |
---|---|
Name | Description |
request |
The request object. Request message for |
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, Union[str, bytes]]]
Key/value pairs which should be sent along with the request as metadata. Normally, each value must be of type |
Returns | |
---|---|
Type | Description |
|
An Operation object. |
list_models
list_models(
request: typing.Optional[
typing.Union[
google.cloud.retail_v2beta.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, typing.Union[str, bytes]]] = ()
) -> google.cloud.retail_v2beta.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_v2beta
def sample_list_models():
# Create a client
client = retail_v2beta.ModelServiceClient()
# Initialize request argument(s)
request = retail_v2beta.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_v2beta.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: |
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, Union[str, bytes]]]
Key/value pairs which should be sent along with the request as metadata. Normally, each value must be of type |
Returns | |
---|---|
Type | Description |
google.cloud.retail_v2beta.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, typing.Union[str, bytes]]] = ()
) -> google.longrunning.operations_pb2.ListOperationsResponse
Lists operations that match the specified filter in the request.
Parameters | |
---|---|
Name | Description |
request |
The request object. Request message for |
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, Union[str, bytes]]]
Key/value pairs which should be sent along with the request as metadata. Normally, each value must be of type |
Returns | |
---|---|
Type | Description |
|
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_v2beta.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, typing.Union[str, bytes]]] = ()
) -> google.cloud.retail_v2beta.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_v2beta
def sample_pause_model():
# Create a client
client = retail_v2beta.ModelServiceClient()
# Initialize request argument(s)
request = retail_v2beta.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_v2beta.types.PauseModelRequest, dict]
The request object. Request for pausing training of a model. |
name |
str
Required. The name of the model to pause. Format: |
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, Union[str, bytes]]]
Key/value pairs which should be sent along with the request as metadata. Normally, each value must be of type |
Returns | |
---|---|
Type | Description |
google.cloud.retail_v2beta.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_v2beta.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, typing.Union[str, bytes]]] = ()
) -> google.cloud.retail_v2beta.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_v2beta
def sample_resume_model():
# Create a client
client = retail_v2beta.ModelServiceClient()
# Initialize request argument(s)
request = retail_v2beta.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_v2beta.types.ResumeModelRequest, dict]
The request object. Request for resuming training of a model. |
name |
str
Required. The name of the model to resume. Format: |
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, Union[str, bytes]]]
Key/value pairs which should be sent along with the request as metadata. Normally, each value must be of type |
Returns | |
---|---|
Type | Description |
google.cloud.retail_v2beta.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_v2beta.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, typing.Union[str, bytes]]] = ()
) -> 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_v2beta
def sample_tune_model():
# Create a client
client = retail_v2beta.ModelServiceClient()
# Initialize request argument(s)
request = retail_v2beta.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_v2beta.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: |
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, Union[str, bytes]]]
Key/value pairs which should be sent along with the request as metadata. Normally, each value must be of type |
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_v2beta.types.model_service.UpdateModelRequest, dict
]
] = None,
*,
model: typing.Optional[google.cloud.retail_v2beta.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, typing.Union[str, bytes]]] = ()
) -> google.cloud.retail_v2beta.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_v2beta
def sample_update_model():
# Create a client
client = retail_v2beta.ModelServiceClient()
# Initialize request argument(s)
model = retail_v2beta.Model()
model.name = "name_value"
model.display_name = "display_name_value"
model.type_ = "type__value"
request = retail_v2beta.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_v2beta.types.UpdateModelRequest, dict]
The request object. Request for updating an existing model. |
model |
google.cloud.retail_v2beta.types.Model
Required. The body of the updated Model. This corresponds to the |
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 |
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, Union[str, bytes]]]
Key/value pairs which should be sent along with the request as metadata. Normally, each value must be of type |
Returns | |
---|---|
Type | Description |
google.cloud.retail_v2beta.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. |