Class VizierServiceAsyncClient (1.11.0) 

VizierServiceAsyncClient(*, credentials: Optional[google.auth.credentials.Credentials] = None, transport: Union[str, google.cloud.aiplatform_v1.services.vizier_service.transports.base.VizierServiceTransport] = 'grpc_asyncio', client_options: Optional[google.api_core.client_options.ClientOptions] = None, client_info: google.api_core.gapic_v1.client_info.ClientInfo = <google.api_core.gapic_v1.client_info.ClientInfo object>)

Vertex AI Vizier API. Vertex AI Vizier is a service to solve blackbox optimization problems, such as tuning machine learning hyperparameters and searching over deep learning architectures.

Inheritance

builtins.object > VizierServiceAsyncClient

Properties

transport

Returns the transport used by the client instance.

Returns
Type Description
VizierServiceTransport The transport used by the client instance.

Methods

VizierServiceAsyncClient

VizierServiceAsyncClient(*, credentials: Optional[google.auth.credentials.Credentials] = None, transport: Union[str, google.cloud.aiplatform_v1.services.vizier_service.transports.base.VizierServiceTransport] = 'grpc_asyncio', client_options: Optional[google.api_core.client_options.ClientOptions] = None, client_info: google.api_core.gapic_v1.client_info.ClientInfo = <google.api_core.gapic_v1.client_info.ClientInfo object>)

Instantiates the vizier 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 Union[str, `.VizierServiceTransport`]

The transport to use. If set to None, a transport is chosen automatically.
client_options ClientOptions

Custom options for the client. It won't take effect if a transport instance is provided. (1) The api_endpoint property can be used to override the default endpoint provided by the client. GOOGLE_API_USE_MTLS_ENDPOINT environment variable can also be used to override the endpoint: "always" (always use the default mTLS endpoint), "never" (always use the default regular endpoint) and "auto" (auto switch to the default mTLS endpoint if client certificate is present, this is the default value). However, the api_endpoint property takes precedence if provided. (2) If GOOGLE_API_USE_CLIENT_CERTIFICATE environment variable is "true", then the client_cert_source property can be used to provide client certificate for mutual TLS transport. If not provided, the default SSL client certificate will be used if present. If GOOGLE_API_USE_CLIENT_CERTIFICATE is "false" or not set, no client certificate will be used.
Exceptions
Type Description
google.auth.exceptions.MutualTlsChannelError If mutual TLS transport creation failed for any reason.

add_trial_measurement

add_trial_measurement(request: Optional[Union[google.cloud.aiplatform_v1.types.vizier_service.AddTrialMeasurementRequest, dict]] = None, *, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())

Adds a measurement of the objective metrics to a Trial. This measurement is assumed to have been taken before the Trial is complete.

from google.cloud import aiplatform_v1

def sample_add_trial_measurement():
    # Create a client
    client = aiplatform_v1.VizierServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1.AddTrialMeasurementRequest(
        trial_name="trial_name_value",
    )

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

    # Handle the response
    print(response)
Parameters
Name Description
request Union[google.cloud.aiplatform_v1.types.AddTrialMeasurementRequest, dict]

The request object. Request message for VizierService.AddTrialMeasurement.
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.aiplatform_v1.types.Trial A message representing a Trial. A Trial contains a unique set of Parameters that has been or will be evaluated, along with the objective metrics got by running the Trial.

check_trial_early_stopping_state

check_trial_early_stopping_state(request: Optional[Union[google.cloud.aiplatform_v1.types.vizier_service.CheckTrialEarlyStoppingStateRequest, dict]] = None, *, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())

Checks whether a Trial should stop or not. Returns a long-running operation. When the operation is successful, it will contain a xref_CheckTrialEarlyStoppingStateResponse.

from google.cloud import aiplatform_v1

def sample_check_trial_early_stopping_state():
    # Create a client
    client = aiplatform_v1.VizierServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1.CheckTrialEarlyStoppingStateRequest(
        trial_name="trial_name_value",
    )

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

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

    response = operation.result()

    # Handle the response
    print(response)
Parameters
Name Description
request Union[google.cloud.aiplatform_v1.types.CheckTrialEarlyStoppingStateRequest, dict]

The request object. Request message for VizierService.CheckTrialEarlyStoppingState.
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_async.AsyncOperation An object representing a long-running operation. The result type for the operation will be CheckTrialEarlyStoppingStateResponse Response message for VizierService.CheckTrialEarlyStoppingState.

common_billing_account_path

common_billing_account_path(billing_account: str)

Returns a fully-qualified billing_account string.

common_folder_path

common_folder_path(folder: str)

Returns a fully-qualified folder string.

common_location_path

common_location_path(project: str, location: str)

Returns a fully-qualified location string.

common_organization_path

common_organization_path(organization: str)

Returns a fully-qualified organization string.

common_project_path

common_project_path(project: str)

Returns a fully-qualified project string.

complete_trial

complete_trial(request: Optional[Union[google.cloud.aiplatform_v1.types.vizier_service.CompleteTrialRequest, dict]] = None, *, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())

Marks a Trial as complete.

from google.cloud import aiplatform_v1

def sample_complete_trial():
    # Create a client
    client = aiplatform_v1.VizierServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1.CompleteTrialRequest(
        name="name_value",
    )

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

    # Handle the response
    print(response)
Parameters
Name Description
request Union[google.cloud.aiplatform_v1.types.CompleteTrialRequest, dict]

The request object. Request message for VizierService.CompleteTrial.
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.aiplatform_v1.types.Trial A message representing a Trial. A Trial contains a unique set of Parameters that has been or will be evaluated, along with the objective metrics got by running the Trial.

create_study

create_study(request: Optional[Union[google.cloud.aiplatform_v1.types.vizier_service.CreateStudyRequest, dict]] = None, *, parent: Optional[str] = None, study: Optional[google.cloud.aiplatform_v1.types.study.Study] = None, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())

Creates a Study. A resource name will be generated after creation of the Study.

from google.cloud import aiplatform_v1

def sample_create_study():
    # Create a client
    client = aiplatform_v1.VizierServiceClient()

    # Initialize request argument(s)
    study = aiplatform_v1.Study()
    study.display_name = "display_name_value"
    study.study_spec.metrics.metric_id = "metric_id_value"
    study.study_spec.metrics.goal = "MINIMIZE"
    study.study_spec.parameters.double_value_spec.min_value = 0.96
    study.study_spec.parameters.double_value_spec.max_value = 0.962
    study.study_spec.parameters.parameter_id = "parameter_id_value"

    request = aiplatform_v1.CreateStudyRequest(
        parent="parent_value",
        study=study,
    )

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

    # Handle the response
    print(response)
Parameters
Name Description
request Union[google.cloud.aiplatform_v1.types.CreateStudyRequest, dict]

The request object. Request message for VizierService.CreateStudy.
parent `str`

Required. The resource name of the Location to create the CustomJob in. Format: projects/{project}/locations/{location} This corresponds to the parent field on the request instance; if request is provided, this should not be set.
study Study

Required. The Study configuration used to create the Study. This corresponds to the study 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.aiplatform_v1.types.Study A message representing a Study.

create_trial

create_trial(request: Optional[Union[google.cloud.aiplatform_v1.types.vizier_service.CreateTrialRequest, dict]] = None, *, parent: Optional[str] = None, trial: Optional[google.cloud.aiplatform_v1.types.study.Trial] = None, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())

Adds a user provided Trial to a Study.

from google.cloud import aiplatform_v1

def sample_create_trial():
    # Create a client
    client = aiplatform_v1.VizierServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1.CreateTrialRequest(
        parent="parent_value",
    )

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

    # Handle the response
    print(response)
Parameters
Name Description
request Union[google.cloud.aiplatform_v1.types.CreateTrialRequest, dict]

The request object. Request message for VizierService.CreateTrial.
parent `str`

Required. The resource name of the Study to create the Trial in. Format: projects/{project}/locations/{location}/studies/{study} This corresponds to the parent field on the request instance; if request is provided, this should not be set.
trial Trial

Required. The Trial to create. This corresponds to the trial 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.aiplatform_v1.types.Trial A message representing a Trial. A Trial contains a unique set of Parameters that has been or will be evaluated, along with the objective metrics got by running the Trial.

custom_job_path

custom_job_path(project: str, location: str, custom_job: str)

Returns a fully-qualified custom_job string.

delete_study

delete_study(request: Optional[Union[google.cloud.aiplatform_v1.types.vizier_service.DeleteStudyRequest, dict]] = None, *, name: Optional[str] = None, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())

Deletes a Study.

from google.cloud import aiplatform_v1

def sample_delete_study():
    # Create a client
    client = aiplatform_v1.VizierServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1.DeleteStudyRequest(
        name="name_value",
    )

    # Make the request
    client.delete_study(request=request)
Parameters
Name Description
request Union[google.cloud.aiplatform_v1.types.DeleteStudyRequest, dict]

The request object. Request message for VizierService.DeleteStudy.
name `str`

Required. The name of the Study resource to be deleted. Format: projects/{project}/locations/{location}/studies/{study} 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.

delete_trial

delete_trial(request: Optional[Union[google.cloud.aiplatform_v1.types.vizier_service.DeleteTrialRequest, dict]] = None, *, name: Optional[str] = None, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())

Deletes a Trial.

from google.cloud import aiplatform_v1

def sample_delete_trial():
    # Create a client
    client = aiplatform_v1.VizierServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1.DeleteTrialRequest(
        name="name_value",
    )

    # Make the request
    client.delete_trial(request=request)
Parameters
Name Description
request Union[google.cloud.aiplatform_v1.types.DeleteTrialRequest, dict]

The request object. Request message for VizierService.DeleteTrial.
name `str`

Required. The Trial's name. Format: projects/{project}/locations/{location}/studies/{study}/trials/{trial} 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
VizierServiceAsyncClient 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
VizierServiceAsyncClient 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
VizierServiceAsyncClient The constructed client.

get_mtls_endpoint_and_cert_source

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

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 variabel 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_study

get_study(request: Optional[Union[google.cloud.aiplatform_v1.types.vizier_service.GetStudyRequest, dict]] = None, *, name: Optional[str] = None, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())

Gets a Study by name.

from google.cloud import aiplatform_v1

def sample_get_study():
    # Create a client
    client = aiplatform_v1.VizierServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1.GetStudyRequest(
        name="name_value",
    )

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

    # Handle the response
    print(response)
Parameters
Name Description
request Union[google.cloud.aiplatform_v1.types.GetStudyRequest, dict]

The request object. Request message for VizierService.GetStudy.
name `str`

Required. The name of the Study resource. Format: projects/{project}/locations/{location}/studies/{study} 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.aiplatform_v1.types.Study A message representing a Study.

get_transport_class

get_transport_class()

Returns an appropriate transport class.

get_trial

get_trial(request: Optional[Union[google.cloud.aiplatform_v1.types.vizier_service.GetTrialRequest, dict]] = None, *, name: Optional[str] = None, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())

Gets a Trial.

from google.cloud import aiplatform_v1

def sample_get_trial():
    # Create a client
    client = aiplatform_v1.VizierServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1.GetTrialRequest(
        name="name_value",
    )

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

    # Handle the response
    print(response)
Parameters
Name Description
request Union[google.cloud.aiplatform_v1.types.GetTrialRequest, dict]

The request object. Request message for VizierService.GetTrial.
name `str`

Required. The name of the Trial resource. Format: projects/{project}/locations/{location}/studies/{study}/trials/{trial} 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.aiplatform_v1.types.Trial A message representing a Trial. A Trial contains a unique set of Parameters that has been or will be evaluated, along with the objective metrics got by running the Trial.

list_optimal_trials

list_optimal_trials(request: Optional[Union[google.cloud.aiplatform_v1.types.vizier_service.ListOptimalTrialsRequest, dict]] = None, *, parent: Optional[str] = None, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())

Lists the pareto-optimal Trials for multi-objective Study or the optimal Trials for single-objective Study. The definition of pareto-optimal can be checked in wiki page. https://en.wikipedia.org/wiki/Pareto_efficiency

from google.cloud import aiplatform_v1

def sample_list_optimal_trials():
    # Create a client
    client = aiplatform_v1.VizierServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1.ListOptimalTrialsRequest(
        parent="parent_value",
    )

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

    # Handle the response
    print(response)
Parameters
Name Description
request Union[google.cloud.aiplatform_v1.types.ListOptimalTrialsRequest, dict]

The request object. Request message for VizierService.ListOptimalTrials.
parent `str`

Required. The name of the Study that the optimal Trial belongs to. 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.aiplatform_v1.types.ListOptimalTrialsResponse Response message for VizierService.ListOptimalTrials.

list_studies

list_studies(request: Optional[Union[google.cloud.aiplatform_v1.types.vizier_service.ListStudiesRequest, dict]] = None, *, parent: Optional[str] = None, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())

Lists all the studies in a region for an associated project.

from google.cloud import aiplatform_v1

def sample_list_studies():
    # Create a client
    client = aiplatform_v1.VizierServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1.ListStudiesRequest(
        parent="parent_value",
    )

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

    # Handle the response
    for response in page_result:
        print(response)
Parameters
Name Description
request Union[google.cloud.aiplatform_v1.types.ListStudiesRequest, dict]

The request object. Request message for VizierService.ListStudies.
parent `str`

Required. The resource name of the Location to list the Study from. Format: projects/{project}/locations/{location} 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.aiplatform_v1.services.vizier_service.pagers.ListStudiesAsyncPager Response message for VizierService.ListStudies. Iterating over this object will yield results and resolve additional pages automatically.

list_trials

list_trials(request: Optional[Union[google.cloud.aiplatform_v1.types.vizier_service.ListTrialsRequest, dict]] = None, *, parent: Optional[str] = None, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())

Lists the Trials associated with a Study.

from google.cloud import aiplatform_v1

def sample_list_trials():
    # Create a client
    client = aiplatform_v1.VizierServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1.ListTrialsRequest(
        parent="parent_value",
    )

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

    # Handle the response
    for response in page_result:
        print(response)
Parameters
Name Description
request Union[google.cloud.aiplatform_v1.types.ListTrialsRequest, dict]

The request object. Request message for VizierService.ListTrials.
parent `str`

Required. The resource name of the Study to list the Trial from. Format: projects/{project}/locations/{location}/studies/{study} 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.aiplatform_v1.services.vizier_service.pagers.ListTrialsAsyncPager Response message for VizierService.ListTrials. Iterating over this object will yield results and resolve additional pages automatically.

lookup_study

lookup_study(request: Optional[Union[google.cloud.aiplatform_v1.types.vizier_service.LookupStudyRequest, dict]] = None, *, parent: Optional[str] = None, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())

Looks a study up using the user-defined display_name field instead of the fully qualified resource name.

from google.cloud import aiplatform_v1

def sample_lookup_study():
    # Create a client
    client = aiplatform_v1.VizierServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1.LookupStudyRequest(
        parent="parent_value",
        display_name="display_name_value",
    )

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

    # Handle the response
    print(response)
Parameters
Name Description
request Union[google.cloud.aiplatform_v1.types.LookupStudyRequest, dict]

The request object. Request message for VizierService.LookupStudy.
parent `str`

Required. The resource name of the Location to get the Study from. Format: projects/{project}/locations/{location} 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.aiplatform_v1.types.Study A message representing a Study.

parse_common_billing_account_path

parse_common_billing_account_path(path: str)

Parse a billing_account path into its component segments.

parse_common_folder_path

parse_common_folder_path(path: str)

Parse a folder path into its component segments.

parse_common_location_path

parse_common_location_path(path: str)

Parse a location path into its component segments.

parse_common_organization_path

parse_common_organization_path(path: str)

Parse a organization path into its component segments.

parse_common_project_path

parse_common_project_path(path: str)

Parse a project path into its component segments.

parse_custom_job_path

parse_custom_job_path(path: str)

Parses a custom_job path into its component segments.

parse_study_path

parse_study_path(path: str)

Parses a study path into its component segments.

parse_trial_path

parse_trial_path(path: str)

Parses a trial path into its component segments.

stop_trial

stop_trial(request: Optional[Union[google.cloud.aiplatform_v1.types.vizier_service.StopTrialRequest, dict]] = None, *, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())

Stops a Trial.

from google.cloud import aiplatform_v1

def sample_stop_trial():
    # Create a client
    client = aiplatform_v1.VizierServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1.StopTrialRequest(
        name="name_value",
    )

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

    # Handle the response
    print(response)
Parameters
Name Description
request Union[google.cloud.aiplatform_v1.types.StopTrialRequest, dict]

The request object. Request message for VizierService.StopTrial.
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.aiplatform_v1.types.Trial A message representing a Trial. A Trial contains a unique set of Parameters that has been or will be evaluated, along with the objective metrics got by running the Trial.

study_path

study_path(project: str, location: str, study: str)

Returns a fully-qualified study string.

suggest_trials

suggest_trials(request: Optional[Union[google.cloud.aiplatform_v1.types.vizier_service.SuggestTrialsRequest, dict]] = None, *, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())

Adds one or more Trials to a Study, with parameter values suggested by Vertex AI Vizier. Returns a long-running operation associated with the generation of Trial suggestions. When this long-running operation succeeds, it will contain a xref_SuggestTrialsResponse.

from google.cloud import aiplatform_v1

def sample_suggest_trials():
    # Create a client
    client = aiplatform_v1.VizierServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1.SuggestTrialsRequest(
        parent="parent_value",
        suggestion_count=1744,
        client_id="client_id_value",
    )

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

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

    response = operation.result()

    # Handle the response
    print(response)
Parameters
Name Description
request Union[google.cloud.aiplatform_v1.types.SuggestTrialsRequest, dict]

The request object. Request message for VizierService.SuggestTrials.
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_async.AsyncOperation An object representing a long-running operation. The result type for the operation will be SuggestTrialsResponse Response message for VizierService.SuggestTrials.

trial_path

trial_path(project: str, location: str, study: str, trial: str)

Returns a fully-qualified trial string.