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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 > VizierServiceAsyncClientProperties
transport
Returns the transport used by the client instance.
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.
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 |
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
async def sample_add_trial_measurement():
# Create a client
client = aiplatform_v1.VizierServiceAsyncClient()
# Initialize request argument(s)
request = aiplatform_v1.AddTrialMeasurementRequest(
trial_name="trial_name_value",
)
# Make the request
response = await client.add_trial_measurement(request=request)
# Handle the response
print(response)
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. |
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
async def sample_check_trial_early_stopping_state():
# Create a client
client = aiplatform_v1.VizierServiceAsyncClient()
# 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 = await operation.result()
# Handle the response
print(response)
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. |
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
async def sample_complete_trial():
# Create a client
client = aiplatform_v1.VizierServiceAsyncClient()
# Initialize request argument(s)
request = aiplatform_v1.CompleteTrialRequest(
name="name_value",
)
# Make the request
response = await client.complete_trial(request=request)
# Handle the response
print(response)
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. |
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
async def sample_create_study():
# Create a client
client = aiplatform_v1.VizierServiceAsyncClient()
# 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 = await client.create_study(request=request)
# Handle the response
print(response)
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: |
study |
Study
Required. The Study configuration used to create the Study. 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, str]]
Strings which should be sent along with the request as metadata. |
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
async def sample_create_trial():
# Create a client
client = aiplatform_v1.VizierServiceAsyncClient()
# Initialize request argument(s)
request = aiplatform_v1.CreateTrialRequest(
parent="parent_value",
)
# Make the request
response = await client.create_trial(request=request)
# Handle the response
print(response)
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: |
trial |
Trial
Required. The Trial 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, str]]
Strings which should be sent along with the request as metadata. |
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
async def sample_delete_study():
# Create a client
client = aiplatform_v1.VizierServiceAsyncClient()
# Initialize request argument(s)
request = aiplatform_v1.DeleteStudyRequest(
name="name_value",
)
# Make the request
await client.delete_study(request=request)
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: |
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
async def sample_delete_trial():
# Create a client
client = aiplatform_v1.VizierServiceAsyncClient()
# Initialize request argument(s)
request = aiplatform_v1.DeleteTrialRequest(
name="name_value",
)
# Make the request
await client.delete_trial(request=request)
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: |
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.
Name | Description |
filename |
str
The path to the service account private key json file. |
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.
Name | Description |
info |
dict
The service account private key info. |
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.
Name | Description |
filename |
str
The path to the service account private key json file. |
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.
Name | Description |
client_options |
google.api_core.client_options.ClientOptions
Custom options for the client. Only the |
Type | Description |
google.auth.exceptions.MutualTLSChannelError | If any errors happen. |
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
async def sample_get_study():
# Create a client
client = aiplatform_v1.VizierServiceAsyncClient()
# Initialize request argument(s)
request = aiplatform_v1.GetStudyRequest(
name="name_value",
)
# Make the request
response = await client.get_study(request=request)
# Handle the response
print(response)
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: |
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. |
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
async def sample_get_trial():
# Create a client
client = aiplatform_v1.VizierServiceAsyncClient()
# Initialize request argument(s)
request = aiplatform_v1.GetTrialRequest(
name="name_value",
)
# Make the request
response = await client.get_trial(request=request)
# Handle the response
print(response)
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: |
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. |
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
async def sample_list_optimal_trials():
# Create a client
client = aiplatform_v1.VizierServiceAsyncClient()
# Initialize request argument(s)
request = aiplatform_v1.ListOptimalTrialsRequest(
parent="parent_value",
)
# Make the request
response = await client.list_optimal_trials(request=request)
# Handle the response
print(response)
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 |
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. |
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
async def sample_list_studies():
# Create a client
client = aiplatform_v1.VizierServiceAsyncClient()
# Initialize request argument(s)
request = aiplatform_v1.ListStudiesRequest(
parent="parent_value",
)
# Make the request
page_result = client.list_studies(request=request)
# Handle the response
async for response in page_result:
print(response)
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: |
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. |
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
async def sample_list_trials():
# Create a client
client = aiplatform_v1.VizierServiceAsyncClient()
# Initialize request argument(s)
request = aiplatform_v1.ListTrialsRequest(
parent="parent_value",
)
# Make the request
page_result = client.list_trials(request=request)
# Handle the response
async for response in page_result:
print(response)
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: |
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. |
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
async def sample_lookup_study():
# Create a client
client = aiplatform_v1.VizierServiceAsyncClient()
# Initialize request argument(s)
request = aiplatform_v1.LookupStudyRequest(
parent="parent_value",
display_name="display_name_value",
)
# Make the request
response = await client.lookup_study(request=request)
# Handle the response
print(response)
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: |
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. |
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
async def sample_stop_trial():
# Create a client
client = aiplatform_v1.VizierServiceAsyncClient()
# Initialize request argument(s)
request = aiplatform_v1.StopTrialRequest(
name="name_value",
)
# Make the request
response = await client.stop_trial(request=request)
# Handle the response
print(response)
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. |
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
async def sample_suggest_trials():
# Create a client
client = aiplatform_v1.VizierServiceAsyncClient()
# 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 = await operation.result()
# Handle the response
print(response)
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. |
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.