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TensorboardServiceAsyncClient(*, credentials: Optional[google.auth.credentials.Credentials] = None, transport: Union[str, google.cloud.aiplatform_v1beta1.services.tensorboard_service.transports.base.TensorboardServiceTransport] = '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>)
TensorboardService
Inheritance
builtins.object > TensorboardServiceAsyncClientProperties
transport
Returns the transport used by the client instance.
Type | Description |
TensorboardServiceTransport | The transport used by the client instance. |
Methods
TensorboardServiceAsyncClient
TensorboardServiceAsyncClient(*, credentials: Optional[google.auth.credentials.Credentials] = None, transport: Union[str, google.cloud.aiplatform_v1beta1.services.tensorboard_service.transports.base.TensorboardServiceTransport] = '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 tensorboard 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, `.TensorboardServiceTransport`]
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. |
batch_create_tensorboard_runs
batch_create_tensorboard_runs(request: Optional[Union[google.cloud.aiplatform_v1beta1.types.tensorboard_service.BatchCreateTensorboardRunsRequest, dict]] = None, *, parent: Optional[str] = None, requests: Optional[Sequence[google.cloud.aiplatform_v1beta1.types.tensorboard_service.CreateTensorboardRunRequest]] = None, retry: Union[google.api_core.retry.Retry, object] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())
Batch create TensorboardRuns.
Name | Description |
request |
Union[google.cloud.aiplatform_v1beta1.types.BatchCreateTensorboardRunsRequest, dict]
The request object. Request message for TensorboardService.BatchCreateTensorboardRuns. |
parent |
`str`
Required. The resource name of the TensorboardExperiment to create the TensorboardRuns in. Format: |
requests |
:class:`Sequence[google.cloud.aiplatform_v1beta1.types.CreateTensorboardRunRequest]`
Required. The request message specifying the TensorboardRuns to create. A maximum of 1000 TensorboardRuns can be created in a batch. 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_v1beta1.types.BatchCreateTensorboardRunsResponse | Response message for TensorboardService.BatchCreateTensorboardRuns. |
batch_create_tensorboard_time_series
batch_create_tensorboard_time_series(request: Optional[Union[google.cloud.aiplatform_v1beta1.types.tensorboard_service.BatchCreateTensorboardTimeSeriesRequest, dict]] = None, *, parent: Optional[str] = None, requests: Optional[Sequence[google.cloud.aiplatform_v1beta1.types.tensorboard_service.CreateTensorboardTimeSeriesRequest]] = None, retry: Union[google.api_core.retry.Retry, object] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())
Batch create TensorboardTimeSeries that belong to a TensorboardExperiment.
Name | Description |
request |
Union[google.cloud.aiplatform_v1beta1.types.BatchCreateTensorboardTimeSeriesRequest, dict]
The request object. Request message for TensorboardService.BatchCreateTensorboardTimeSeries. |
parent |
`str`
Required. The resource name of the TensorboardExperiment to create the TensorboardTimeSeries in. Format: |
requests |
:class:`Sequence[google.cloud.aiplatform_v1beta1.types.CreateTensorboardTimeSeriesRequest]`
Required. The request message specifying the TensorboardTimeSeries to create. A maximum of 1000 TensorboardTimeSeries can be created in a batch. 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_v1beta1.types.BatchCreateTensorboardTimeSeriesResponse | Response message for TensorboardService.BatchCreateTensorboardTimeSeries. |
batch_read_tensorboard_time_series_data
batch_read_tensorboard_time_series_data(request: Optional[Union[google.cloud.aiplatform_v1beta1.types.tensorboard_service.BatchReadTensorboardTimeSeriesDataRequest, dict]] = None, *, tensorboard: Optional[str] = None, retry: Union[google.api_core.retry.Retry, object] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())
Reads multiple TensorboardTimeSeries' data. The data point number limit is 1000 for scalars, 100 for tensors and blob references. If the number of data points stored is less than the limit, all data will be returned. Otherwise, that limit number of data points will be randomly selected from this time series and returned.
Name | Description |
request |
Union[google.cloud.aiplatform_v1beta1.types.BatchReadTensorboardTimeSeriesDataRequest, dict]
The request object. Request message for TensorboardService.BatchReadTensorboardTimeSeriesData. |
tensorboard |
`str`
Required. The resource name of the Tensorboard containing TensorboardTimeSeries to read data 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_v1beta1.types.BatchReadTensorboardTimeSeriesDataResponse | Response message for TensorboardService.BatchReadTensorboardTimeSeriesData. |
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.
create_tensorboard
create_tensorboard(request: Optional[Union[google.cloud.aiplatform_v1beta1.types.tensorboard_service.CreateTensorboardRequest, dict]] = None, *, parent: Optional[str] = None, tensorboard: Optional[google.cloud.aiplatform_v1beta1.types.tensorboard.Tensorboard] = None, retry: Union[google.api_core.retry.Retry, object] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())
Creates a Tensorboard.
Name | Description |
request |
Union[google.cloud.aiplatform_v1beta1.types.CreateTensorboardRequest, dict]
The request object. Request message for TensorboardService.CreateTensorboard. |
parent |
`str`
Required. The resource name of the Location to create the Tensorboard in. Format: |
tensorboard |
Tensorboard
Required. The Tensorboard 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.api_core.operation_async.AsyncOperation | An object representing a long-running operation. The result type for the operation will be Tensorboard Tensorboard is a physical database that stores users' training metrics. A default Tensorboard is provided in each region of a GCP project. If needed users can also create extra Tensorboards in their projects. |
create_tensorboard_experiment
create_tensorboard_experiment(request: Optional[Union[google.cloud.aiplatform_v1beta1.types.tensorboard_service.CreateTensorboardExperimentRequest, dict]] = None, *, parent: Optional[str] = None, tensorboard_experiment: Optional[google.cloud.aiplatform_v1beta1.types.tensorboard_experiment.TensorboardExperiment] = None, tensorboard_experiment_id: Optional[str] = None, retry: Union[google.api_core.retry.Retry, object] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())
Creates a TensorboardExperiment.
Name | Description |
request |
Union[google.cloud.aiplatform_v1beta1.types.CreateTensorboardExperimentRequest, dict]
The request object. Request message for TensorboardService.CreateTensorboardExperiment. |
parent |
`str`
Required. The resource name of the Tensorboard to create the TensorboardExperiment in. Format: |
tensorboard_experiment |
TensorboardExperiment
The TensorboardExperiment to create. This corresponds to the |
tensorboard_experiment_id |
`str`
Required. The ID to use for the Tensorboard experiment, which will become the final component of the Tensorboard experiment's resource name. This value should be 1-128 characters, and valid characters are / |
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_v1beta1.types.TensorboardExperiment | A TensorboardExperiment is a group of TensorboardRuns, that are typically the results of a training job run, in a Tensorboard. |
create_tensorboard_run
create_tensorboard_run(request: Optional[Union[google.cloud.aiplatform_v1beta1.types.tensorboard_service.CreateTensorboardRunRequest, dict]] = None, *, parent: Optional[str] = None, tensorboard_run: Optional[google.cloud.aiplatform_v1beta1.types.tensorboard_run.TensorboardRun] = None, tensorboard_run_id: Optional[str] = None, retry: Union[google.api_core.retry.Retry, object] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())
Creates a TensorboardRun.
Name | Description |
request |
Union[google.cloud.aiplatform_v1beta1.types.CreateTensorboardRunRequest, dict]
The request object. Request message for TensorboardService.CreateTensorboardRun. |
parent |
`str`
Required. The resource name of the TensorboardExperiment to create the TensorboardRun in. Format: |
tensorboard_run |
TensorboardRun
Required. The TensorboardRun to create. This corresponds to the |
tensorboard_run_id |
`str`
Required. The ID to use for the Tensorboard run, which will become the final component of the Tensorboard run's resource name. This value should be 1-128 characters, and valid characters are / |
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_v1beta1.types.TensorboardRun | TensorboardRun maps to a specific execution of a training job with a given set of hyperparameter values, model definition, dataset, etc |
create_tensorboard_time_series
create_tensorboard_time_series(request: Optional[Union[google.cloud.aiplatform_v1beta1.types.tensorboard_service.CreateTensorboardTimeSeriesRequest, dict]] = None, *, parent: Optional[str] = None, tensorboard_time_series: Optional[google.cloud.aiplatform_v1beta1.types.tensorboard_time_series.TensorboardTimeSeries] = None, retry: Union[google.api_core.retry.Retry, object] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())
Creates a TensorboardTimeSeries.
Name | Description |
request |
Union[google.cloud.aiplatform_v1beta1.types.CreateTensorboardTimeSeriesRequest, dict]
The request object. Request message for TensorboardService.CreateTensorboardTimeSeries. |
parent |
`str`
Required. The resource name of the TensorboardRun to create the TensorboardTimeSeries in. Format: |
tensorboard_time_series |
TensorboardTimeSeries
Required. The TensorboardTimeSeries 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_v1beta1.types.TensorboardTimeSeries | TensorboardTimeSeries maps to times series produced in training runs |
delete_tensorboard
delete_tensorboard(request: Optional[Union[google.cloud.aiplatform_v1beta1.types.tensorboard_service.DeleteTensorboardRequest, dict]] = None, *, name: Optional[str] = None, retry: Union[google.api_core.retry.Retry, object] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())
Deletes a Tensorboard.
Name | Description |
request |
Union[google.cloud.aiplatform_v1beta1.types.DeleteTensorboardRequest, dict]
The request object. Request message for TensorboardService.DeleteTensorboard. |
name |
`str`
Required. The name of the Tensorboard 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. |
Type | Description |
google.api_core.operation_async.AsyncOperation | An object representing a long-running operation. The result type for the operation will be `google.protobuf.empty_pb2.Empty` A generic empty message that you can re-use to avoid defining duplicated empty messages in your APIs. A typical example is to use it as the request or the response type of an API method. For instance: service Foo { rpc Bar(google.protobuf.Empty) returns (google.protobuf.Empty); } The JSON representation for Empty is empty JSON object {}. |
delete_tensorboard_experiment
delete_tensorboard_experiment(request: Optional[Union[google.cloud.aiplatform_v1beta1.types.tensorboard_service.DeleteTensorboardExperimentRequest, dict]] = None, *, name: Optional[str] = None, retry: Union[google.api_core.retry.Retry, object] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())
Deletes a TensorboardExperiment.
Name | Description |
request |
Union[google.cloud.aiplatform_v1beta1.types.DeleteTensorboardExperimentRequest, dict]
The request object. Request message for TensorboardService.DeleteTensorboardExperiment. |
name |
`str`
Required. The name of the TensorboardExperiment 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. |
Type | Description |
google.api_core.operation_async.AsyncOperation | An object representing a long-running operation. The result type for the operation will be `google.protobuf.empty_pb2.Empty` A generic empty message that you can re-use to avoid defining duplicated empty messages in your APIs. A typical example is to use it as the request or the response type of an API method. For instance: service Foo { rpc Bar(google.protobuf.Empty) returns (google.protobuf.Empty); } The JSON representation for Empty is empty JSON object {}. |
delete_tensorboard_run
delete_tensorboard_run(request: Optional[Union[google.cloud.aiplatform_v1beta1.types.tensorboard_service.DeleteTensorboardRunRequest, dict]] = None, *, name: Optional[str] = None, retry: Union[google.api_core.retry.Retry, object] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())
Deletes a TensorboardRun.
Name | Description |
request |
Union[google.cloud.aiplatform_v1beta1.types.DeleteTensorboardRunRequest, dict]
The request object. Request message for TensorboardService.DeleteTensorboardRun. |
name |
`str`
Required. The name of the TensorboardRun 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. |
Type | Description |
google.api_core.operation_async.AsyncOperation | An object representing a long-running operation. The result type for the operation will be `google.protobuf.empty_pb2.Empty` A generic empty message that you can re-use to avoid defining duplicated empty messages in your APIs. A typical example is to use it as the request or the response type of an API method. For instance: service Foo { rpc Bar(google.protobuf.Empty) returns (google.protobuf.Empty); } The JSON representation for Empty is empty JSON object {}. |
delete_tensorboard_time_series
delete_tensorboard_time_series(request: Optional[Union[google.cloud.aiplatform_v1beta1.types.tensorboard_service.DeleteTensorboardTimeSeriesRequest, dict]] = None, *, name: Optional[str] = None, retry: Union[google.api_core.retry.Retry, object] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())
Deletes a TensorboardTimeSeries.
Name | Description |
request |
Union[google.cloud.aiplatform_v1beta1.types.DeleteTensorboardTimeSeriesRequest, dict]
The request object. Request message for TensorboardService.DeleteTensorboardTimeSeries. |
name |
`str`
Required. The name of the TensorboardTimeSeries 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. |
Type | Description |
google.api_core.operation_async.AsyncOperation | An object representing a long-running operation. The result type for the operation will be `google.protobuf.empty_pb2.Empty` A generic empty message that you can re-use to avoid defining duplicated empty messages in your APIs. A typical example is to use it as the request or the response type of an API method. For instance: service Foo { rpc Bar(google.protobuf.Empty) returns (google.protobuf.Empty); } The JSON representation for Empty is empty JSON object {}. |
export_tensorboard_time_series_data
export_tensorboard_time_series_data(request: Optional[Union[google.cloud.aiplatform_v1beta1.types.tensorboard_service.ExportTensorboardTimeSeriesDataRequest, dict]] = None, *, tensorboard_time_series: Optional[str] = None, retry: Union[google.api_core.retry.Retry, object] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())
Exports a TensorboardTimeSeries' data. Data is returned in paginated responses.
Name | Description |
request |
Union[google.cloud.aiplatform_v1beta1.types.ExportTensorboardTimeSeriesDataRequest, dict]
The request object. Request message for TensorboardService.ExportTensorboardTimeSeriesData. |
tensorboard_time_series |
`str`
Required. The resource name of the TensorboardTimeSeries to export data 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_v1beta1.services.tensorboard_service.pagers.ExportTensorboardTimeSeriesDataAsyncPager | Response message for TensorboardService.ExportTensorboardTimeSeriesData. Iterating over this object will yield results and resolve additional pages automatically. |
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 |
TensorboardServiceAsyncClient | 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 |
TensorboardServiceAsyncClient | 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 |
TensorboardServiceAsyncClient | The constructed client. |
get_tensorboard
get_tensorboard(request: Optional[Union[google.cloud.aiplatform_v1beta1.types.tensorboard_service.GetTensorboardRequest, dict]] = None, *, name: Optional[str] = None, retry: Union[google.api_core.retry.Retry, object] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())
Gets a Tensorboard.
Name | Description |
request |
Union[google.cloud.aiplatform_v1beta1.types.GetTensorboardRequest, dict]
The request object. Request message for TensorboardService.GetTensorboard. |
name |
`str`
Required. The name of the Tensorboard 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_v1beta1.types.Tensorboard | Tensorboard is a physical database that stores users' training metrics. A default Tensorboard is provided in each region of a GCP project. If needed users can also create extra Tensorboards in their projects. |
get_tensorboard_experiment
get_tensorboard_experiment(request: Optional[Union[google.cloud.aiplatform_v1beta1.types.tensorboard_service.GetTensorboardExperimentRequest, dict]] = None, *, name: Optional[str] = None, retry: Union[google.api_core.retry.Retry, object] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())
Gets a TensorboardExperiment.
Name | Description |
request |
Union[google.cloud.aiplatform_v1beta1.types.GetTensorboardExperimentRequest, dict]
The request object. Request message for TensorboardService.GetTensorboardExperiment. |
name |
`str`
Required. The name of the TensorboardExperiment 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_v1beta1.types.TensorboardExperiment | A TensorboardExperiment is a group of TensorboardRuns, that are typically the results of a training job run, in a Tensorboard. |
get_tensorboard_run
get_tensorboard_run(request: Optional[Union[google.cloud.aiplatform_v1beta1.types.tensorboard_service.GetTensorboardRunRequest, dict]] = None, *, name: Optional[str] = None, retry: Union[google.api_core.retry.Retry, object] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())
Gets a TensorboardRun.
Name | Description |
request |
Union[google.cloud.aiplatform_v1beta1.types.GetTensorboardRunRequest, dict]
The request object. Request message for TensorboardService.GetTensorboardRun. |
name |
`str`
Required. The name of the TensorboardRun 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_v1beta1.types.TensorboardRun | TensorboardRun maps to a specific execution of a training job with a given set of hyperparameter values, model definition, dataset, etc |
get_tensorboard_time_series
get_tensorboard_time_series(request: Optional[Union[google.cloud.aiplatform_v1beta1.types.tensorboard_service.GetTensorboardTimeSeriesRequest, dict]] = None, *, name: Optional[str] = None, retry: Union[google.api_core.retry.Retry, object] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())
Gets a TensorboardTimeSeries.
Name | Description |
request |
Union[google.cloud.aiplatform_v1beta1.types.GetTensorboardTimeSeriesRequest, dict]
The request object. Request message for TensorboardService.GetTensorboardTimeSeries. |
name |
`str`
Required. The name of the TensorboardTimeSeries 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_v1beta1.types.TensorboardTimeSeries | TensorboardTimeSeries maps to times series produced in training runs |
get_transport_class
get_transport_class()
Returns an appropriate transport class.
list_tensorboard_experiments
list_tensorboard_experiments(request: Optional[Union[google.cloud.aiplatform_v1beta1.types.tensorboard_service.ListTensorboardExperimentsRequest, dict]] = None, *, parent: Optional[str] = None, retry: Union[google.api_core.retry.Retry, object] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())
Lists TensorboardExperiments in a Location.
Name | Description |
request |
Union[google.cloud.aiplatform_v1beta1.types.ListTensorboardExperimentsRequest, dict]
The request object. Request message for TensorboardService.ListTensorboardExperiments. |
parent |
`str`
Required. The resource name of the Tensorboard to list TensorboardExperiments. Format: 'projects/{project}/locations/{location}/tensorboards/{tensorboard}' 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_v1beta1.services.tensorboard_service.pagers.ListTensorboardExperimentsAsyncPager | Response message for TensorboardService.ListTensorboardExperiments. Iterating over this object will yield results and resolve additional pages automatically. |
list_tensorboard_runs
list_tensorboard_runs(request: Optional[Union[google.cloud.aiplatform_v1beta1.types.tensorboard_service.ListTensorboardRunsRequest, dict]] = None, *, parent: Optional[str] = None, retry: Union[google.api_core.retry.Retry, object] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())
Lists TensorboardRuns in a Location.
Name | Description |
request |
Union[google.cloud.aiplatform_v1beta1.types.ListTensorboardRunsRequest, dict]
The request object. Request message for TensorboardService.ListTensorboardRuns. |
parent |
`str`
Required. The resource name of the TensorboardExperiment to list TensorboardRuns. Format: 'projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}' 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_v1beta1.services.tensorboard_service.pagers.ListTensorboardRunsAsyncPager | Response message for TensorboardService.ListTensorboardRuns. Iterating over this object will yield results and resolve additional pages automatically. |
list_tensorboard_time_series
list_tensorboard_time_series(request: Optional[Union[google.cloud.aiplatform_v1beta1.types.tensorboard_service.ListTensorboardTimeSeriesRequest, dict]] = None, *, parent: Optional[str] = None, retry: Union[google.api_core.retry.Retry, object] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())
Lists TensorboardTimeSeries in a Location.
Name | Description |
request |
Union[google.cloud.aiplatform_v1beta1.types.ListTensorboardTimeSeriesRequest, dict]
The request object. Request message for TensorboardService.ListTensorboardTimeSeries. |
parent |
`str`
Required. The resource name of the TensorboardRun to list TensorboardTimeSeries. Format: 'projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}' 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_v1beta1.services.tensorboard_service.pagers.ListTensorboardTimeSeriesAsyncPager | Response message for TensorboardService.ListTensorboardTimeSeries. Iterating over this object will yield results and resolve additional pages automatically. |
list_tensorboards
list_tensorboards(request: Optional[Union[google.cloud.aiplatform_v1beta1.types.tensorboard_service.ListTensorboardsRequest, dict]] = None, *, parent: Optional[str] = None, retry: Union[google.api_core.retry.Retry, object] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())
Lists Tensorboards in a Location.
Name | Description |
request |
Union[google.cloud.aiplatform_v1beta1.types.ListTensorboardsRequest, dict]
The request object. Request message for TensorboardService.ListTensorboards. |
parent |
`str`
Required. The resource name of the Location to list Tensorboards. 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_v1beta1.services.tensorboard_service.pagers.ListTensorboardsAsyncPager | Response message for TensorboardService.ListTensorboards. Iterating over this object will yield results and resolve additional pages automatically. |
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_tensorboard_experiment_path
parse_tensorboard_experiment_path(path: str)
Parses a tensorboard_experiment path into its component segments.
parse_tensorboard_path
parse_tensorboard_path(path: str)
Parses a tensorboard path into its component segments.
parse_tensorboard_run_path
parse_tensorboard_run_path(path: str)
Parses a tensorboard_run path into its component segments.
parse_tensorboard_time_series_path
parse_tensorboard_time_series_path(path: str)
Parses a tensorboard_time_series path into its component segments.
read_tensorboard_blob_data
read_tensorboard_blob_data(request: Optional[Union[google.cloud.aiplatform_v1beta1.types.tensorboard_service.ReadTensorboardBlobDataRequest, dict]] = None, *, time_series: Optional[str] = None, retry: Union[google.api_core.retry.Retry, object] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())
Gets bytes of TensorboardBlobs. This is to allow reading blob data stored in consumer project's Cloud Storage bucket without users having to obtain Cloud Storage access permission.
Name | Description |
request |
Union[google.cloud.aiplatform_v1beta1.types.ReadTensorboardBlobDataRequest, dict]
The request object. Request message for TensorboardService.ReadTensorboardBlobData. |
time_series |
`str`
Required. The resource name of the TensorboardTimeSeries to list Blobs. Format: 'projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}/timeSeries/{time_series}' 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 |
AsyncIterable[google.cloud.aiplatform_v1beta1.types.ReadTensorboardBlobDataResponse] | Response message for TensorboardService.ReadTensorboardBlobData. |
read_tensorboard_time_series_data
read_tensorboard_time_series_data(request: Optional[Union[google.cloud.aiplatform_v1beta1.types.tensorboard_service.ReadTensorboardTimeSeriesDataRequest, dict]] = None, *, tensorboard_time_series: Optional[str] = None, retry: Union[google.api_core.retry.Retry, object] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())
Reads a TensorboardTimeSeries' data. By default, if the number of data points stored is less than 1000, all data will be returned. Otherwise, 1000 data points will be randomly selected from this time series and returned. This value can be changed by changing max_data_points, which can't be greater than 10k.
Name | Description |
request |
Union[google.cloud.aiplatform_v1beta1.types.ReadTensorboardTimeSeriesDataRequest, dict]
The request object. Request message for TensorboardService.ReadTensorboardTimeSeriesData. |
tensorboard_time_series |
`str`
Required. The resource name of the TensorboardTimeSeries to read data 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_v1beta1.types.ReadTensorboardTimeSeriesDataResponse | Response message for TensorboardService.ReadTensorboardTimeSeriesData. |
tensorboard_experiment_path
tensorboard_experiment_path(
project: str, location: str, tensorboard: str, experiment: str
)
Returns a fully-qualified tensorboard_experiment string.
tensorboard_path
tensorboard_path(project: str, location: str, tensorboard: str)
Returns a fully-qualified tensorboard string.
tensorboard_run_path
tensorboard_run_path(
project: str, location: str, tensorboard: str, experiment: str, run: str
)
Returns a fully-qualified tensorboard_run string.
tensorboard_time_series_path
tensorboard_time_series_path(
project: str,
location: str,
tensorboard: str,
experiment: str,
run: str,
time_series: str,
)
Returns a fully-qualified tensorboard_time_series string.
update_tensorboard
update_tensorboard(request: Optional[Union[google.cloud.aiplatform_v1beta1.types.tensorboard_service.UpdateTensorboardRequest, dict]] = None, *, tensorboard: Optional[google.cloud.aiplatform_v1beta1.types.tensorboard.Tensorboard] = None, update_mask: Optional[google.protobuf.field_mask_pb2.FieldMask] = None, retry: Union[google.api_core.retry.Retry, object] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())
Updates a Tensorboard.
Name | Description |
request |
Union[google.cloud.aiplatform_v1beta1.types.UpdateTensorboardRequest, dict]
The request object. Request message for TensorboardService.UpdateTensorboard. |
tensorboard |
Tensorboard
Required. The Tensorboard's |
update_mask |
`google.protobuf.field_mask_pb2.FieldMask`
Required. Field mask is used to specify the fields to be overwritten in the Tensorboard resource by the update. The fields specified in the update_mask are relative to the resource, not the full request. A field will be overwritten if it is in the mask. If the user does not provide a mask then all fields will be overwritten if new values are specified. 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.api_core.operation_async.AsyncOperation | An object representing a long-running operation. The result type for the operation will be Tensorboard Tensorboard is a physical database that stores users' training metrics. A default Tensorboard is provided in each region of a GCP project. If needed users can also create extra Tensorboards in their projects. |
update_tensorboard_experiment
update_tensorboard_experiment(request: Optional[Union[google.cloud.aiplatform_v1beta1.types.tensorboard_service.UpdateTensorboardExperimentRequest, dict]] = None, *, tensorboard_experiment: Optional[google.cloud.aiplatform_v1beta1.types.tensorboard_experiment.TensorboardExperiment] = None, update_mask: Optional[google.protobuf.field_mask_pb2.FieldMask] = None, retry: Union[google.api_core.retry.Retry, object] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())
Updates a TensorboardExperiment.
Name | Description |
request |
Union[google.cloud.aiplatform_v1beta1.types.UpdateTensorboardExperimentRequest, dict]
The request object. Request message for TensorboardService.UpdateTensorboardExperiment. |
tensorboard_experiment |
TensorboardExperiment
Required. The TensorboardExperiment's |
update_mask |
`google.protobuf.field_mask_pb2.FieldMask`
Required. Field mask is used to specify the fields to be overwritten in the TensorboardExperiment resource by the update. The fields specified in the update_mask are relative to the resource, not the full request. A field will be overwritten if it is in the mask. If the user does not provide a mask then all fields will be overwritten if new values are specified. 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_v1beta1.types.TensorboardExperiment | A TensorboardExperiment is a group of TensorboardRuns, that are typically the results of a training job run, in a Tensorboard. |
update_tensorboard_run
update_tensorboard_run(request: Optional[Union[google.cloud.aiplatform_v1beta1.types.tensorboard_service.UpdateTensorboardRunRequest, dict]] = None, *, tensorboard_run: Optional[google.cloud.aiplatform_v1beta1.types.tensorboard_run.TensorboardRun] = None, update_mask: Optional[google.protobuf.field_mask_pb2.FieldMask] = None, retry: Union[google.api_core.retry.Retry, object] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())
Updates a TensorboardRun.
Name | Description |
request |
Union[google.cloud.aiplatform_v1beta1.types.UpdateTensorboardRunRequest, dict]
The request object. Request message for TensorboardService.UpdateTensorboardRun. |
tensorboard_run |
TensorboardRun
Required. The TensorboardRun's |
update_mask |
`google.protobuf.field_mask_pb2.FieldMask`
Required. Field mask is used to specify the fields to be overwritten in the TensorboardRun resource by the update. The fields specified in the update_mask are relative to the resource, not the full request. A field will be overwritten if it is in the mask. If the user does not provide a mask then all fields will be overwritten if new values are specified. 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_v1beta1.types.TensorboardRun | TensorboardRun maps to a specific execution of a training job with a given set of hyperparameter values, model definition, dataset, etc |
update_tensorboard_time_series
update_tensorboard_time_series(request: Optional[Union[google.cloud.aiplatform_v1beta1.types.tensorboard_service.UpdateTensorboardTimeSeriesRequest, dict]] = None, *, tensorboard_time_series: Optional[google.cloud.aiplatform_v1beta1.types.tensorboard_time_series.TensorboardTimeSeries] = None, update_mask: Optional[google.protobuf.field_mask_pb2.FieldMask] = None, retry: Union[google.api_core.retry.Retry, object] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())
Updates a TensorboardTimeSeries.
Name | Description |
request |
Union[google.cloud.aiplatform_v1beta1.types.UpdateTensorboardTimeSeriesRequest, dict]
The request object. Request message for TensorboardService.UpdateTensorboardTimeSeries. |
tensorboard_time_series |
TensorboardTimeSeries
Required. The TensorboardTimeSeries' |
update_mask |
`google.protobuf.field_mask_pb2.FieldMask`
Required. Field mask is used to specify the fields to be overwritten in the TensorboardTimeSeries resource by the update. The fields specified in the update_mask are relative to the resource, not the full request. A field will be overwritten if it is in the mask. If the user does not provide a mask then all fields will be overwritten if new values are specified. 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_v1beta1.types.TensorboardTimeSeries | TensorboardTimeSeries maps to times series produced in training runs |
write_tensorboard_experiment_data
write_tensorboard_experiment_data(request: Optional[Union[google.cloud.aiplatform_v1beta1.types.tensorboard_service.WriteTensorboardExperimentDataRequest, dict]] = None, *, tensorboard_experiment: Optional[str] = None, write_run_data_requests: Optional[Sequence[google.cloud.aiplatform_v1beta1.types.tensorboard_service.WriteTensorboardRunDataRequest]] = None, retry: Union[google.api_core.retry.Retry, object] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())
Write time series data points of multiple TensorboardTimeSeries in multiple TensorboardRun's. If any data fail to be ingested, an error will be returned.
Name | Description |
request |
Union[google.cloud.aiplatform_v1beta1.types.WriteTensorboardExperimentDataRequest, dict]
The request object. Request message for TensorboardService.WriteTensorboardExperimentData. |
tensorboard_experiment |
`str`
Required. The resource name of the TensorboardExperiment to write data to. Format: |
write_run_data_requests |
:class:`Sequence[google.cloud.aiplatform_v1beta1.types.WriteTensorboardRunDataRequest]`
Required. Requests containing per-run TensorboardTimeSeries data to write. 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_v1beta1.types.WriteTensorboardExperimentDataResponse | Response message for TensorboardService.WriteTensorboardExperimentData. |
write_tensorboard_run_data
write_tensorboard_run_data(request: Optional[Union[google.cloud.aiplatform_v1beta1.types.tensorboard_service.WriteTensorboardRunDataRequest, dict]] = None, *, tensorboard_run: Optional[str] = None, time_series_data: Optional[Sequence[google.cloud.aiplatform_v1beta1.types.tensorboard_data.TimeSeriesData]] = None, retry: Union[google.api_core.retry.Retry, object] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())
Write time series data points into multiple TensorboardTimeSeries under a TensorboardRun. If any data fail to be ingested, an error will be returned.
Name | Description |
request |
Union[google.cloud.aiplatform_v1beta1.types.WriteTensorboardRunDataRequest, dict]
The request object. Request message for TensorboardService.WriteTensorboardRunData. |
tensorboard_run |
`str`
Required. The resource name of the TensorboardRun to write data to. Format: |
time_series_data |
:class:`Sequence[google.cloud.aiplatform_v1beta1.types.TimeSeriesData]`
Required. The TensorboardTimeSeries data to write. Values with in a time series are indexed by their step value. Repeated writes to the same step will overwrite the existing value for that step. The upper limit of data points per write request is 5000. 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_v1beta1.types.WriteTensorboardRunDataResponse | Response message for TensorboardService.WriteTensorboardRunData. |