PipelineService¶

async batch_delete_pipeline_jobs(request: Optional[Union[BatchDeletePipelineJobsRequest, dict]] = None, *, parent: Optional[str] = None, names: Optional[MutableSequence[str]] = None, retry: Optional[Union[AsyncRetry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → AsyncOperation[source]¶

Batch deletes PipelineJobs The Operation is atomic. If it fails, none of the PipelineJobs are deleted. If it succeeds, all of the PipelineJobs are deleted.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1

async def sample_batch_delete_pipeline_jobs():
    # Create a client
    client = aiplatform_v1.PipelineServiceAsyncClient()

    # Initialize request argument(s)
    request = aiplatform_v1.BatchDeletePipelineJobsRequest(
        parent="parent_value",
        names=['names_value1', 'names_value2'],
    )

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

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

    response = (await operation).result()

    # Handle the response
    print(response)

Parameters:

request (Optional[Union[google.cloud.aiplatform_v1.types.BatchDeletePipelineJobsRequest, dict]]) – The request object. Request message for [PipelineService.BatchDeletePipelineJobs][google.cloud.aiplatform.v1.PipelineService.BatchDeletePipelineJobs].
parent (str) –
Required. The name of the PipelineJobs’ parent resource. Format: projects/{project}/locations/{location}

This corresponds to the parent field on the request instance; if request is provided, this should not be set.
names (MutableSequence[str]) –
Required. The names of the PipelineJobs to delete. A maximum of 32 PipelineJobs can be deleted in a batch. Format: projects/{project}/locations/{location}/pipelineJobs/{pipelineJob}

This corresponds to the names field on the request instance; if request is provided, this should not be set.
retry (google.api_core.retry_async.AsyncRetry) – 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:

An object representing a long-running operation.

The result type for the operation will be google.cloud.aiplatform_v1.types.BatchDeletePipelineJobsResponse Response message for: [PipelineService.BatchDeletePipelineJobs][google.cloud.aiplatform.v1.PipelineService.BatchDeletePipelineJobs].

Return type:

async cancel_operation(request: Optional[CancelOperationRequest] = None, *, retry: Optional[Union[AsyncRetry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → None[source]¶

Starts asynchronous cancellation on a long-running operation.

The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn’t support this method, it returns google.rpc.Code.UNIMPLEMENTED.

Parameters:

request (CancelOperationRequest) – The request object. Request message for CancelOperation method.
retry (google.api_core.retry_async.AsyncRetry) – 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:

None

async cancel_pipeline_job(request: Optional[Union[CancelPipelineJobRequest, dict]] = None, *, name: Optional[str] = None, retry: Optional[Union[AsyncRetry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → None[source]¶

Cancels a PipelineJob. Starts asynchronous cancellation on the PipelineJob. The server makes a best effort to cancel the pipeline, but success is not guaranteed. Clients can use [PipelineService.GetPipelineJob][google.cloud.aiplatform.v1.PipelineService.GetPipelineJob] or other methods to check whether the cancellation succeeded or whether the pipeline completed despite cancellation. On successful cancellation, the PipelineJob is not deleted; instead it becomes a pipeline with a [PipelineJob.error][google.cloud.aiplatform.v1.PipelineJob.error] value with a [google.rpc.Status.code][google.rpc.Status.code] of 1, corresponding to Code.CANCELLED, and [PipelineJob.state][google.cloud.aiplatform.v1.PipelineJob.state] is set to CANCELLED.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1

async def sample_cancel_pipeline_job():
    # Create a client
    client = aiplatform_v1.PipelineServiceAsyncClient()

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

    # Make the request
    await client.cancel_pipeline_job(request=request)

Parameters:

request (Optional[Union[google.cloud.aiplatform_v1.types.CancelPipelineJobRequest, dict]]) – The request object. Request message for [PipelineService.CancelPipelineJob][google.cloud.aiplatform.v1.PipelineService.CancelPipelineJob].
name (str) –
Required. The name of the PipelineJob to cancel. Format: projects/{project}/locations/{location}/pipelineJobs/{pipeline_job}

This corresponds to the name field on the request instance; if request is provided, this should not be set.
retry (google.api_core.retry_async.AsyncRetry) – 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.

async cancel_training_pipeline(request: Optional[Union[CancelTrainingPipelineRequest, dict]] = None, *, name: Optional[str] = None, retry: Optional[Union[AsyncRetry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → None[source]¶

Cancels a TrainingPipeline. Starts asynchronous cancellation on the TrainingPipeline. The server makes a best effort to cancel the pipeline, but success is not guaranteed. Clients can use [PipelineService.GetTrainingPipeline][google.cloud.aiplatform.v1.PipelineService.GetTrainingPipeline] or other methods to check whether the cancellation succeeded or whether the pipeline completed despite cancellation. On successful cancellation, the TrainingPipeline is not deleted; instead it becomes a pipeline with a [TrainingPipeline.error][google.cloud.aiplatform.v1.TrainingPipeline.error] value with a [google.rpc.Status.code][google.rpc.Status.code] of 1, corresponding to Code.CANCELLED, and [TrainingPipeline.state][google.cloud.aiplatform.v1.TrainingPipeline.state] is set to CANCELLED.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1

async def sample_cancel_training_pipeline():
    # Create a client
    client = aiplatform_v1.PipelineServiceAsyncClient()

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

    # Make the request
    await client.cancel_training_pipeline(request=request)

Parameters:

request (Optional[Union[google.cloud.aiplatform_v1.types.CancelTrainingPipelineRequest, dict]]) – The request object. Request message for [PipelineService.CancelTrainingPipeline][google.cloud.aiplatform.v1.PipelineService.CancelTrainingPipeline].
name (str) –
Required. The name of the TrainingPipeline to cancel. Format: projects/{project}/locations/{location}/trainingPipelines/{training_pipeline}

This corresponds to the name field on the request instance; if request is provided, this should not be set.
retry (google.api_core.retry_async.AsyncRetry) – 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.

static common_billing_account_path(billing_account: str) → str¶: Returns a fully-qualified billing_account string.

static common_folder_path(folder: str) → str¶: Returns a fully-qualified folder string.

static common_location_path(project: str, location: str) → str¶: Returns a fully-qualified location string.

static common_organization_path(organization: str) → str¶: Returns a fully-qualified organization string.

static common_project_path(project: str) → str¶: Returns a fully-qualified project string.

static context_path(project: str, location: str, metadata_store: str, context: str) → str¶: Returns a fully-qualified context string.

async create_pipeline_job(request: Optional[Union[CreatePipelineJobRequest, dict]] = None, *, parent: Optional[str] = None, pipeline_job: Optional[PipelineJob] = None, pipeline_job_id: Optional[str] = None, retry: Optional[Union[AsyncRetry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → PipelineJob[source]¶

Creates a PipelineJob. A PipelineJob will run immediately when created.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1

async def sample_create_pipeline_job():
    # Create a client
    client = aiplatform_v1.PipelineServiceAsyncClient()

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

    # Make the request
    response = await client.create_pipeline_job(request=request)

    # Handle the response
    print(response)

Parameters:

request (Optional[Union[google.cloud.aiplatform_v1.types.CreatePipelineJobRequest, dict]]) – The request object. Request message for [PipelineService.CreatePipelineJob][google.cloud.aiplatform.v1.PipelineService.CreatePipelineJob].
parent (str) –
Required. The resource name of the Location to create the PipelineJob 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.
pipeline_job (google.cloud.aiplatform_v1.types.PipelineJob) – Required. The PipelineJob to create. This corresponds to the pipeline_job field on the request instance; if request is provided, this should not be set.
pipeline_job_id (str) –
The ID to use for the PipelineJob, which will become the final component of the PipelineJob name. If not provided, an ID will be automatically generated.

This value should be less than 128 characters, and valid characters are /[a-z][0-9]-/.

This corresponds to the pipeline_job_id field on the request instance; if request is provided, this should not be set.
retry (google.api_core.retry_async.AsyncRetry) – 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:

An instance of a machine learning PipelineJob.

Return type:

async create_training_pipeline(request: Optional[Union[CreateTrainingPipelineRequest, dict]] = None, *, parent: Optional[str] = None, training_pipeline: Optional[TrainingPipeline] = None, retry: Optional[Union[AsyncRetry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → TrainingPipeline[source]¶

Creates a TrainingPipeline. A created TrainingPipeline right away will be attempted to be run.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1

async def sample_create_training_pipeline():
    # Create a client
    client = aiplatform_v1.PipelineServiceAsyncClient()

    # Initialize request argument(s)
    training_pipeline = aiplatform_v1.TrainingPipeline()
    training_pipeline.display_name = "display_name_value"
    training_pipeline.training_task_definition = "training_task_definition_value"
    training_pipeline.training_task_inputs.null_value = "NULL_VALUE"

    request = aiplatform_v1.CreateTrainingPipelineRequest(
        parent="parent_value",
        training_pipeline=training_pipeline,
    )

    # Make the request
    response = await client.create_training_pipeline(request=request)

    # Handle the response
    print(response)

Parameters:

request (Optional[Union[google.cloud.aiplatform_v1.types.CreateTrainingPipelineRequest, dict]]) – The request object. Request message for [PipelineService.CreateTrainingPipeline][google.cloud.aiplatform.v1.PipelineService.CreateTrainingPipeline].
parent (str) –
Required. The resource name of the Location to create the TrainingPipeline 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.
training_pipeline (google.cloud.aiplatform_v1.types.TrainingPipeline) –
Required. The TrainingPipeline to create.

This corresponds to the training_pipeline field on the request instance; if request is provided, this should not be set.
retry (google.api_core.retry_async.AsyncRetry) – 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:

The TrainingPipeline orchestrates tasks associated with training a Model. It: always executes the training task, and optionally may also export data from Vertex AI’s Dataset which becomes the training input, [upload][google.cloud.aiplatform.v1.ModelService.UploadModel] the Model to Vertex AI, and evaluate the Model.

Return type:

static custom_job_path(project: str, location: str, custom_job: str) → str¶: Returns a fully-qualified custom_job string.

async delete_operation(request: Optional[DeleteOperationRequest] = None, *, retry: Optional[Union[AsyncRetry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → None[source]¶

Deletes a long-running operation.

This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn’t support this method, it returns google.rpc.Code.UNIMPLEMENTED.

Parameters:

request (DeleteOperationRequest) – The request object. Request message for DeleteOperation method.
retry (google.api_core.retry_async.AsyncRetry) – 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:

None

async delete_pipeline_job(request: Optional[Union[DeletePipelineJobRequest, dict]] = None, *, name: Optional[str] = None, retry: Optional[Union[AsyncRetry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → AsyncOperation[source]¶

Deletes a PipelineJob.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1

async def sample_delete_pipeline_job():
    # Create a client
    client = aiplatform_v1.PipelineServiceAsyncClient()

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

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

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

    response = (await operation).result()

    # Handle the response
    print(response)

Parameters:

request (Optional[Union[google.cloud.aiplatform_v1.types.DeletePipelineJobRequest, dict]]) – The request object. Request message for [PipelineService.DeletePipelineJob][google.cloud.aiplatform.v1.PipelineService.DeletePipelineJob].
name (str) –
Required. The name of the PipelineJob resource to be deleted. Format: projects/{project}/locations/{location}/pipelineJobs/{pipeline_job}

This corresponds to the name field on the request instance; if request is provided, this should not be set.
retry (google.api_core.retry_async.AsyncRetry) – 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:

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);

}

Return type:

async delete_training_pipeline(request: Optional[Union[DeleteTrainingPipelineRequest, dict]] = None, *, name: Optional[str] = None, retry: Optional[Union[AsyncRetry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → AsyncOperation[source]¶

Deletes a TrainingPipeline.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1

async def sample_delete_training_pipeline():
    # Create a client
    client = aiplatform_v1.PipelineServiceAsyncClient()

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

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

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

    response = (await operation).result()

    # Handle the response
    print(response)

Parameters:

request (Optional[Union[google.cloud.aiplatform_v1.types.DeleteTrainingPipelineRequest, dict]]) – The request object. Request message for [PipelineService.DeleteTrainingPipeline][google.cloud.aiplatform.v1.PipelineService.DeleteTrainingPipeline].
name (str) –
Required. The name of the TrainingPipeline resource to be deleted. Format: projects/{project}/locations/{location}/trainingPipelines/{training_pipeline}

This corresponds to the name field on the request instance; if request is provided, this should not be set.
retry (google.api_core.retry_async.AsyncRetry) – 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:

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);

}

Return type:

PipelineServiceAsyncClient

static endpoint_path(project: str, location: str, endpoint: str) → str¶: Returns a fully-qualified endpoint string.

static execution_path(project: str, location: str, metadata_store: str, execution: str) → str¶: Returns a fully-qualified execution string.

classmethod from_service_account_file(filename: str, *args, **kwargs)[source]¶

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

Parameters:

filename (str) – The path to the service account private key json file.
args – Additional arguments to pass to the constructor.
kwargs – Additional arguments to pass to the constructor.

Returns:

The constructed client.

Return type:

classmethod from_service_account_info(info: dict, *args, **kwargs)[source]¶

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

Parameters:

info (dict) – The service account private key info.
args – Additional arguments to pass to the constructor.
kwargs – Additional arguments to pass to the constructor.

Returns:

The constructed client.

Return type:

PipelineServiceAsyncClient

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

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

Parameters:

filename (str) – The path to the service account private key json file.
args – Additional arguments to pass to the constructor.
kwargs – Additional arguments to pass to the constructor.

Returns:

The constructed client.

Return type:

PipelineServiceAsyncClient

async get_iam_policy(request: Optional[GetIamPolicyRequest] = None, *, retry: Optional[Union[AsyncRetry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → Policy[source]¶

Gets the IAM access control policy for a function.

Returns an empty policy if the function exists and does not have a policy set.

Parameters:

request (GetIamPolicyRequest) – The request object. Request message for GetIamPolicy method.
retry (google.api_core.retry_async.AsyncRetry) – 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:

Defines an Identity and Access Management (IAM) policy. It is used to specify access control policies for Cloud Platform resources. A Policy is a collection of bindings. A binding binds one or more members to a single role. Members can be user accounts, service accounts, Google groups, and domains (such as G Suite). A role is a named list of permissions (defined by IAM or configured by users). A binding can optionally specify a condition, which is a logic expression that further constrains the role binding based on attributes about the request and/or target resource.

JSON Example

{
  "bindings": [
    {
      "role": "roles/resourcemanager.organizationAdmin",
      "members": [
        "user:mike@example.com",
        "group:admins@example.com",
        "domain:google.com",
        "serviceAccount:my-project-id@appspot.gserviceaccount.com"
      ]
    },
    {
      "role": "roles/resourcemanager.organizationViewer",
      "members": ["user:eve@example.com"],
      "condition": {
        "title": "expirable access",
        "description": "Does not grant access after Sep 2020",
        "expression": "request.time <
        timestamp('2020-10-01T00:00:00.000Z')",
      }
    }
  ]
}

YAML Example

bindings:
- members:
  - user:mike@example.com
  - group:admins@example.com
  - domain:google.com
  - serviceAccount:my-project-id@appspot.gserviceaccount.com
  role: roles/resourcemanager.organizationAdmin
- members:
  - user:eve@example.com
  role: roles/resourcemanager.organizationViewer
  condition:
    title: expirable access
    description: Does not grant access after Sep 2020
    expression: request.time < timestamp('2020-10-01T00:00:00.000Z')

For a description of IAM and its features, see the IAM developer’s guide.

Return type:

Policy

async get_location(request: Optional[GetLocationRequest] = None, *, retry: Optional[Union[AsyncRetry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → Location[source]¶

Gets information about a location.

Parameters:

request (GetLocationRequest) – The request object. Request message for GetLocation method.
retry (google.api_core.retry_async.AsyncRetry) – 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:

Location object.

Return type:

Location

classmethod get_mtls_endpoint_and_cert_source(client_options: Optional[ClientOptions] = None)[source]¶

Return the API endpoint and client cert source for mutual TLS.

The client cert source is determined in the following order: (1) if GOOGLE_API_USE_CLIENT_CERTIFICATE environment variable is not “true”, the client cert source is None. (2) if client_options.client_cert_source is provided, use the provided one; if the default client cert source exists, use the default one; otherwise the client cert source is None.

The API endpoint is determined in the following order: (1) if client_options.api_endpoint if provided, use the provided one. (2) if GOOGLE_API_USE_CLIENT_CERTIFICATE environment variable is “always”, use the default mTLS endpoint; if the environment variable is “never”, use the default API endpoint; otherwise if client cert source exists, use the default mTLS endpoint, otherwise use the default API endpoint.

More details can be found at https://google.aip.dev/auth/4114.

Parameters:

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.

Returns:

returns the API endpoint and the: client cert source to use.

Return type:

Tuple[str, Callable[[], Tuple[bytes, bytes]]]

Raises:

google.auth.exceptions.MutualTLSChannelError – If any errors happen.

async get_operation(request: Optional[GetOperationRequest] = None, *, retry: Optional[Union[AsyncRetry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → Operation[source]¶

Gets the latest state of a long-running operation.

Parameters:

request (GetOperationRequest) – The request object. Request message for GetOperation method.
retry (google.api_core.retry_async.AsyncRetry) – 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:

An Operation object.

Return type:

Operation

async get_pipeline_job(request: Optional[Union[GetPipelineJobRequest, dict]] = None, *, name: Optional[str] = None, retry: Optional[Union[AsyncRetry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → PipelineJob[source]¶

Gets a PipelineJob.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1

async def sample_get_pipeline_job():
    # Create a client
    client = aiplatform_v1.PipelineServiceAsyncClient()

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

    # Make the request
    response = await client.get_pipeline_job(request=request)

    # Handle the response
    print(response)

Parameters:

request (Optional[Union[google.cloud.aiplatform_v1.types.GetPipelineJobRequest, dict]]) – The request object. Request message for [PipelineService.GetPipelineJob][google.cloud.aiplatform.v1.PipelineService.GetPipelineJob].
name (str) –
Required. The name of the PipelineJob resource. Format: projects/{project}/locations/{location}/pipelineJobs/{pipeline_job}

This corresponds to the name field on the request instance; if request is provided, this should not be set.
retry (google.api_core.retry_async.AsyncRetry) – 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:

An instance of a machine learning PipelineJob.

Return type:

async get_training_pipeline(request: Optional[Union[GetTrainingPipelineRequest, dict]] = None, *, name: Optional[str] = None, retry: Optional[Union[AsyncRetry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → TrainingPipeline[source]¶

Gets a TrainingPipeline.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1

async def sample_get_training_pipeline():
    # Create a client
    client = aiplatform_v1.PipelineServiceAsyncClient()

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

    # Make the request
    response = await client.get_training_pipeline(request=request)

    # Handle the response
    print(response)

Parameters:

request (Optional[Union[google.cloud.aiplatform_v1.types.GetTrainingPipelineRequest, dict]]) – The request object. Request message for [PipelineService.GetTrainingPipeline][google.cloud.aiplatform.v1.PipelineService.GetTrainingPipeline].
name (str) –
Required. The name of the TrainingPipeline resource. Format: projects/{project}/locations/{location}/trainingPipelines/{training_pipeline}

This corresponds to the name field on the request instance; if request is provided, this should not be set.
retry (google.api_core.retry_async.AsyncRetry) – 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:

The TrainingPipeline orchestrates tasks associated with training a Model. It: always executes the training task, and optionally may also export data from Vertex AI’s Dataset which becomes the training input, [upload][google.cloud.aiplatform.v1.ModelService.UploadModel] the Model to Vertex AI, and evaluate the Model.

Return type:

google.cloud.aiplatform_v1.services.pipeline_service.pagers.ListPipelineJobsAsyncPager

classmethod get_transport_class(label: Optional[str] = None) → Type[PipelineServiceTransport]¶

Returns an appropriate transport class.

Parameters:: label – The name of the desired transport. If none is provided, then the first transport in the registry is used.
Returns:: The transport class to use.

async list_locations(request: Optional[ListLocationsRequest] = None, *, retry: Optional[Union[AsyncRetry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → ListLocationsResponse[source]¶

Lists information about the supported locations for this service.

Parameters:

request (ListLocationsRequest) – The request object. Request message for ListLocations method.
retry (google.api_core.retry_async.AsyncRetry) – 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:

Response message for ListLocations method.

Return type:

ListLocationsResponse

async list_operations(request: Optional[ListOperationsRequest] = None, *, retry: Optional[Union[AsyncRetry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → ListOperationsResponse[source]¶

Lists operations that match the specified filter in the request.

Parameters:

request (ListOperationsRequest) – The request object. Request message for ListOperations method.
retry (google.api_core.retry_async.AsyncRetry) – 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:

Response message for ListOperations method.

Return type:

ListOperationsResponse

async list_pipeline_jobs(request: Optional[Union[ListPipelineJobsRequest, dict]] = None, *, parent: Optional[str] = None, retry: Optional[Union[AsyncRetry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → ListPipelineJobsAsyncPager[source]¶

Lists PipelineJobs in a Location.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1

async def sample_list_pipeline_jobs():
    # Create a client
    client = aiplatform_v1.PipelineServiceAsyncClient()

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

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

    # Handle the response
    async for response in page_result:
        print(response)

Parameters:

request (Optional[Union[google.cloud.aiplatform_v1.types.ListPipelineJobsRequest, dict]]) – The request object. Request message for [PipelineService.ListPipelineJobs][google.cloud.aiplatform.v1.PipelineService.ListPipelineJobs].
parent (str) –
Required. The resource name of the Location to list the PipelineJobs 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_async.AsyncRetry) – 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:

Response message for: [PipelineService.ListPipelineJobs][google.cloud.aiplatform.v1.PipelineService.ListPipelineJobs]

Iterating over this object will yield results and resolve additional pages automatically.

Return type:

async list_training_pipelines(request: Optional[Union[ListTrainingPipelinesRequest, dict]] = None, *, parent: Optional[str] = None, retry: Optional[Union[AsyncRetry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → ListTrainingPipelinesAsyncPager[source]¶

Lists TrainingPipelines in a Location.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1

async def sample_list_training_pipelines():
    # Create a client
    client = aiplatform_v1.PipelineServiceAsyncClient()

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

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

    # Handle the response
    async for response in page_result:
        print(response)

Parameters:

request (Optional[Union[google.cloud.aiplatform_v1.types.ListTrainingPipelinesRequest, dict]]) – The request object. Request message for [PipelineService.ListTrainingPipelines][google.cloud.aiplatform.v1.PipelineService.ListTrainingPipelines].
parent (str) –
Required. The resource name of the Location to list the TrainingPipelines 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_async.AsyncRetry) – 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:

Response message for: [PipelineService.ListTrainingPipelines][google.cloud.aiplatform.v1.PipelineService.ListTrainingPipelines]

Iterating over this object will yield results and resolve additional pages automatically.

Return type:

google.cloud.aiplatform_v1.services.pipeline_service.pagers.ListTrainingPipelinesAsyncPager

static model_path(project: str, location: str, model: str) → str¶: Returns a fully-qualified model string.

static network_path(project: str, network: str) → str¶: Returns a fully-qualified network string.

static parse_artifact_path(path: str) → Dict[str, str]¶: Parses a artifact path into its component segments.

static parse_common_billing_account_path(path: str) → Dict[str, str]¶: Parse a billing_account path into its component segments.

static parse_common_folder_path(path: str) → Dict[str, str]¶: Parse a folder path into its component segments.

static parse_common_location_path(path: str) → Dict[str, str]¶: Parse a location path into its component segments.

static parse_common_organization_path(path: str) → Dict[str, str]¶: Parse a organization path into its component segments.

static parse_common_project_path(path: str) → Dict[str, str]¶: Parse a project path into its component segments.

static parse_context_path(path: str) → Dict[str, str]¶: Parses a context path into its component segments.

static parse_custom_job_path(path: str) → Dict[str, str]¶: Parses a custom_job path into its component segments.

static parse_endpoint_path(path: str) → Dict[str, str]¶: Parses a endpoint path into its component segments.

static parse_execution_path(path: str) → Dict[str, str]¶: Parses a execution path into its component segments.

static parse_model_path(path: str) → Dict[str, str]¶: Parses a model path into its component segments.

static parse_network_path(path: str) → Dict[str, str]¶: Parses a network path into its component segments.

static parse_pipeline_job_path(path: str) → Dict[str, str]¶: Parses a pipeline_job path into its component segments.

static parse_training_pipeline_path(path: str) → Dict[str, str]¶: Parses a training_pipeline path into its component segments.

static pipeline_job_path(project: str, location: str, pipeline_job: str) → str¶: Returns a fully-qualified pipeline_job string.

async set_iam_policy(request: Optional[SetIamPolicyRequest] = None, *, retry: Optional[Union[AsyncRetry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → Policy[source]¶

Sets the IAM access control policy on the specified function.

Replaces any existing policy.

Parameters:

request (SetIamPolicyRequest) – The request object. Request message for SetIamPolicy method.
retry (google.api_core.retry_async.AsyncRetry) – 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:

Defines an Identity and Access Management (IAM) policy. It is used to specify access control policies for Cloud Platform resources. A Policy is a collection of bindings. A binding binds one or more members to a single role. Members can be user accounts, service accounts, Google groups, and domains (such as G Suite). A role is a named list of permissions (defined by IAM or configured by users). A binding can optionally specify a condition, which is a logic expression that further constrains the role binding based on attributes about the request and/or target resource.

JSON Example

{
  "bindings": [
    {
      "role": "roles/resourcemanager.organizationAdmin",
      "members": [
        "user:mike@example.com",
        "group:admins@example.com",
        "domain:google.com",
        "serviceAccount:my-project-id@appspot.gserviceaccount.com"
      ]
    },
    {
      "role": "roles/resourcemanager.organizationViewer",
      "members": ["user:eve@example.com"],
      "condition": {
        "title": "expirable access",
        "description": "Does not grant access after Sep 2020",
        "expression": "request.time <
        timestamp('2020-10-01T00:00:00.000Z')",
      }
    }
  ]
}

YAML Example

bindings:
- members:
  - user:mike@example.com
  - group:admins@example.com
  - domain:google.com
  - serviceAccount:my-project-id@appspot.gserviceaccount.com
  role: roles/resourcemanager.organizationAdmin
- members:
  - user:eve@example.com
  role: roles/resourcemanager.organizationViewer
  condition:
    title: expirable access
    description: Does not grant access after Sep 2020
    expression: request.time < timestamp('2020-10-01T00:00:00.000Z')

For a description of IAM and its features, see the IAM developer’s guide.

Return type:

Policy

async test_iam_permissions(request: Optional[TestIamPermissionsRequest] = None, *, retry: Optional[Union[AsyncRetry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → TestIamPermissionsResponse[source]¶

Tests the specified IAM permissions against the IAM access control: policy for a function.

If the function does not exist, this will return an empty set of permissions, not a NOT_FOUND error.

Parameters:

request (TestIamPermissionsRequest) – The request object. Request message for TestIamPermissions method.
retry (google.api_core.retry_async.AsyncRetry) – 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:

Response message for TestIamPermissions method.

Return type:

TestIamPermissionsResponse

static training_pipeline_path(project: str, location: str, training_pipeline: str) → str¶: Returns a fully-qualified training_pipeline string.

property transport: PipelineServiceTransport¶

Returns the transport used by the client instance.

Returns:: The transport used by the client instance.
Return type:: PipelineServiceTransport

property universe_domain: str¶

Return the universe domain used by the client instance.

Returns:

The universe domain used: by the client instance.

Return type:

str

async wait_operation(request: Optional[WaitOperationRequest] = None, *, retry: Optional[Union[AsyncRetry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → Operation[source]¶

Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state.

If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns google.rpc.Code.UNIMPLEMENTED.

Parameters:

request (WaitOperationRequest) – The request object. Request message for WaitOperation method.
retry (google.api_core.retry_async.AsyncRetry) – 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:

An Operation object.

Return type:

Operation

class google.cloud.aiplatform_v1.services.pipeline_service.PipelineServiceClient(*, credentials: ~typing.Optional[~google.auth.credentials.Credentials] = None, transport: ~typing.Optional[~typing.Union[str, ~google.cloud.aiplatform_v1.services.pipeline_service.transports.base.PipelineServiceTransport, ~typing.Callable[[...], ~google.cloud.aiplatform_v1.services.pipeline_service.transports.base.PipelineServiceTransport]]] = None, client_options: ~typing.Optional[~typing.Union[~google.api_core.client_options.ClientOptions, dict]] = None, client_info: ~google.api_core.gapic_v1.client_info.ClientInfo = <google.api_core.gapic_v1.client_info.ClientInfo object>)[source]¶

A service for creating and managing Vertex AI’s pipelines. This includes both TrainingPipeline resources (used for AutoML and custom training) and PipelineJob resources (used for Vertex AI Pipelines).

Instantiates the pipeline service client.

Parameters:

credentials (Optional[google.auth.credentials.Credentials]) – The authorization credentials to attach to requests. These credentials identify the application to the service; if none are specified, the client will attempt to ascertain the credentials from the environment.
transport (Optional[Union[str,PipelineServiceTransport,Callable[..., PipelineServiceTransport]]]) – The transport to use, or a Callable that constructs and returns a new transport. If a Callable is given, it will be called with the same set of initialization arguments as used in the PipelineServiceTransport constructor. If set to None, a transport is chosen automatically.
client_options (Optional[Union[google.api_core.client_options.ClientOptions, dict]]) –
Custom options for the client.

1. The api_endpoint property can be used to override the default endpoint provided by the client when transport is not explicitly provided. Only if this property is not set and transport was not explicitly provided, the endpoint is determined by the GOOGLE_API_USE_MTLS_ENDPOINT environment variable, which have one of the following values: “always” (always use the default mTLS endpoint), “never” (always use the default regular endpoint) and “auto” (auto-switch to the default mTLS endpoint if client certificate is present; this is the default value).

2. If the GOOGLE_API_USE_CLIENT_CERTIFICATE environment variable is “true”, then the client_cert_source property can be used to provide a client certificate for mTLS transport. If not provided, the default SSL client certificate will be used if present. If GOOGLE_API_USE_CLIENT_CERTIFICATE is “false” or not set, no client certificate will be used.

3. The universe_domain property can be used to override the default “googleapis.com” universe. Note that the api_endpoint property still takes precedence; and universe_domain is currently not supported for mTLS.
client_info (google.api_core.gapic_v1.client_info.ClientInfo) – The client info used to send a user-agent string along with API requests. If None, then default info will be used. Generally, you only need to set this if you’re developing your own client library.

Raises:

google.auth.exceptions.MutualTLSChannelError – If mutual TLS transport creation failed for any reason.

__exit__(type, value, traceback)[source]¶: Releases underlying transport’s resources.

Warning

ONLY use as a context manager if the transport is NOT shared with other clients! Exiting the with block will CLOSE the transport and may cause errors in other clients!

property api_endpoint¶

Return the API endpoint used by the client instance.

Returns:: The API endpoint used by the client instance.
Return type:: str

static artifact_path(project: str, location: str, metadata_store: str, artifact: str) → str[source]¶: Returns a fully-qualified artifact string.

batch_cancel_pipeline_jobs(request: Optional[Union[BatchCancelPipelineJobsRequest, dict]] = None, *, parent: Optional[str] = None, names: Optional[MutableSequence[str]] = None, retry: Optional[Union[Retry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → Operation[source]¶

Batch cancel PipelineJobs. Firstly the server will check if all the jobs are in non-terminal states, and skip the jobs that are already terminated. If the operation failed, none of the pipeline jobs are cancelled. The server will poll the states of all the pipeline jobs periodically to check the cancellation status. This operation will return an LRO.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1

def sample_batch_cancel_pipeline_jobs():
    # Create a client
    client = aiplatform_v1.PipelineServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1.BatchCancelPipelineJobsRequest(
        parent="parent_value",
        names=['names_value1', 'names_value2'],
    )

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

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

    response = operation.result()

    # Handle the response
    print(response)

Parameters:

request (Union[google.cloud.aiplatform_v1.types.BatchCancelPipelineJobsRequest, dict]) – The request object. Request message for [PipelineService.BatchCancelPipelineJobs][google.cloud.aiplatform.v1.PipelineService.BatchCancelPipelineJobs].
parent (str) –
Required. The name of the PipelineJobs’ parent resource. Format: projects/{project}/locations/{location}

This corresponds to the parent field on the request instance; if request is provided, this should not be set.
names (MutableSequence[str]) –
Required. The names of the PipelineJobs to cancel. A maximum of 32 PipelineJobs can be cancelled in a batch. Format: projects/{project}/locations/{location}/pipelineJobs/{pipelineJob}

This corresponds to the names 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:

An object representing a long-running operation.

The result type for the operation will be google.cloud.aiplatform_v1.types.BatchCancelPipelineJobsResponse Response message for: [PipelineService.BatchCancelPipelineJobs][google.cloud.aiplatform.v1.PipelineService.BatchCancelPipelineJobs].

Return type:

batch_delete_pipeline_jobs(request: Optional[Union[BatchDeletePipelineJobsRequest, dict]] = None, *, parent: Optional[str] = None, names: Optional[MutableSequence[str]] = None, retry: Optional[Union[Retry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → Operation[source]¶

Batch deletes PipelineJobs The Operation is atomic. If it fails, none of the PipelineJobs are deleted. If it succeeds, all of the PipelineJobs are deleted.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1

def sample_batch_delete_pipeline_jobs():
    # Create a client
    client = aiplatform_v1.PipelineServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1.BatchDeletePipelineJobsRequest(
        parent="parent_value",
        names=['names_value1', 'names_value2'],
    )

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

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

    response = operation.result()

    # Handle the response
    print(response)

Parameters:

request (Union[google.cloud.aiplatform_v1.types.BatchDeletePipelineJobsRequest, dict]) – The request object. Request message for [PipelineService.BatchDeletePipelineJobs][google.cloud.aiplatform.v1.PipelineService.BatchDeletePipelineJobs].
parent (str) –
Required. The name of the PipelineJobs’ parent resource. Format: projects/{project}/locations/{location}

This corresponds to the parent field on the request instance; if request is provided, this should not be set.
names (MutableSequence[str]) –
Required. The names of the PipelineJobs to delete. A maximum of 32 PipelineJobs can be deleted in a batch. Format: projects/{project}/locations/{location}/pipelineJobs/{pipelineJob}

This corresponds to the names 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:

An object representing a long-running operation.

The result type for the operation will be google.cloud.aiplatform_v1.types.BatchDeletePipelineJobsResponse Response message for: [PipelineService.BatchDeletePipelineJobs][google.cloud.aiplatform.v1.PipelineService.BatchDeletePipelineJobs].

Return type:

cancel_operation(request: Optional[CancelOperationRequest] = None, *, retry: Optional[Union[Retry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → None[source]¶

Starts asynchronous cancellation on a long-running operation.

The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn’t support this method, it returns google.rpc.Code.UNIMPLEMENTED.

Parameters:

request (CancelOperationRequest) – The request object. Request message for CancelOperation method.
retry (google.api_core.retry.Retry) – Designation of what errors, if any, should be retried.
timeout (float) – The timeout for this request.
metadata (Sequence[Tuple[str, str]]) – Strings which should be sent along with the request as metadata.

Returns:

None

cancel_pipeline_job(request: Optional[Union[CancelPipelineJobRequest, dict]] = None, *, name: Optional[str] = None, retry: Optional[Union[Retry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → None[source]¶

Cancels a PipelineJob. Starts asynchronous cancellation on the PipelineJob. The server makes a best effort to cancel the pipeline, but success is not guaranteed. Clients can use [PipelineService.GetPipelineJob][google.cloud.aiplatform.v1.PipelineService.GetPipelineJob] or other methods to check whether the cancellation succeeded or whether the pipeline completed despite cancellation. On successful cancellation, the PipelineJob is not deleted; instead it becomes a pipeline with a [PipelineJob.error][google.cloud.aiplatform.v1.PipelineJob.error] value with a [google.rpc.Status.code][google.rpc.Status.code] of 1, corresponding to Code.CANCELLED, and [PipelineJob.state][google.cloud.aiplatform.v1.PipelineJob.state] is set to CANCELLED.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1

def sample_cancel_pipeline_job():
    # Create a client
    client = aiplatform_v1.PipelineServiceClient()

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

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

Parameters:

request (Union[google.cloud.aiplatform_v1.types.CancelPipelineJobRequest, dict]) – The request object. Request message for [PipelineService.CancelPipelineJob][google.cloud.aiplatform.v1.PipelineService.CancelPipelineJob].
name (str) –
Required. The name of the PipelineJob to cancel. Format: projects/{project}/locations/{location}/pipelineJobs/{pipeline_job}

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.

cancel_training_pipeline(request: Optional[Union[CancelTrainingPipelineRequest, dict]] = None, *, name: Optional[str] = None, retry: Optional[Union[Retry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → None[source]¶

Cancels a TrainingPipeline. Starts asynchronous cancellation on the TrainingPipeline. The server makes a best effort to cancel the pipeline, but success is not guaranteed. Clients can use [PipelineService.GetTrainingPipeline][google.cloud.aiplatform.v1.PipelineService.GetTrainingPipeline] or other methods to check whether the cancellation succeeded or whether the pipeline completed despite cancellation. On successful cancellation, the TrainingPipeline is not deleted; instead it becomes a pipeline with a [TrainingPipeline.error][google.cloud.aiplatform.v1.TrainingPipeline.error] value with a [google.rpc.Status.code][google.rpc.Status.code] of 1, corresponding to Code.CANCELLED, and [TrainingPipeline.state][google.cloud.aiplatform.v1.TrainingPipeline.state] is set to CANCELLED.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1

def sample_cancel_training_pipeline():
    # Create a client
    client = aiplatform_v1.PipelineServiceClient()

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

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

Parameters:

request (Union[google.cloud.aiplatform_v1.types.CancelTrainingPipelineRequest, dict]) – The request object. Request message for [PipelineService.CancelTrainingPipeline][google.cloud.aiplatform.v1.PipelineService.CancelTrainingPipeline].
name (str) –
Required. The name of the TrainingPipeline to cancel. Format: projects/{project}/locations/{location}/trainingPipelines/{training_pipeline}

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.

static common_billing_account_path(billing_account: str) → str[source]¶: Returns a fully-qualified billing_account string.

static common_folder_path(folder: str) → str[source]¶: Returns a fully-qualified folder string.

static common_location_path(project: str, location: str) → str[source]¶: Returns a fully-qualified location string.

static common_organization_path(organization: str) → str[source]¶: Returns a fully-qualified organization string.

static common_project_path(project: str) → str[source]¶: Returns a fully-qualified project string.

static context_path(project: str, location: str, metadata_store: str, context: str) → str[source]¶: Returns a fully-qualified context string.

create_pipeline_job(request: Optional[Union[CreatePipelineJobRequest, dict]] = None, *, parent: Optional[str] = None, pipeline_job: Optional[PipelineJob] = None, pipeline_job_id: Optional[str] = None, retry: Optional[Union[Retry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → PipelineJob[source]¶

Creates a PipelineJob. A PipelineJob will run immediately when created.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1

def sample_create_pipeline_job():
    # Create a client
    client = aiplatform_v1.PipelineServiceClient()

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

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

    # Handle the response
    print(response)

Parameters:

request (Union[google.cloud.aiplatform_v1.types.CreatePipelineJobRequest, dict]) – The request object. Request message for [PipelineService.CreatePipelineJob][google.cloud.aiplatform.v1.PipelineService.CreatePipelineJob].
parent (str) –
Required. The resource name of the Location to create the PipelineJob 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.
pipeline_job (google.cloud.aiplatform_v1.types.PipelineJob) – Required. The PipelineJob to create. This corresponds to the pipeline_job field on the request instance; if request is provided, this should not be set.
pipeline_job_id (str) –
The ID to use for the PipelineJob, which will become the final component of the PipelineJob name. If not provided, an ID will be automatically generated.

This value should be less than 128 characters, and valid characters are /[a-z][0-9]-/.

This corresponds to the pipeline_job_id 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:

An instance of a machine learning PipelineJob.

Return type:

create_training_pipeline(request: Optional[Union[CreateTrainingPipelineRequest, dict]] = None, *, parent: Optional[str] = None, training_pipeline: Optional[TrainingPipeline] = None, retry: Optional[Union[Retry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → TrainingPipeline[source]¶

Creates a TrainingPipeline. A created TrainingPipeline right away will be attempted to be run.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1

def sample_create_training_pipeline():
    # Create a client
    client = aiplatform_v1.PipelineServiceClient()

    # Initialize request argument(s)
    training_pipeline = aiplatform_v1.TrainingPipeline()
    training_pipeline.display_name = "display_name_value"
    training_pipeline.training_task_definition = "training_task_definition_value"
    training_pipeline.training_task_inputs.null_value = "NULL_VALUE"

    request = aiplatform_v1.CreateTrainingPipelineRequest(
        parent="parent_value",
        training_pipeline=training_pipeline,
    )

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

    # Handle the response
    print(response)

Parameters:

request (Union[google.cloud.aiplatform_v1.types.CreateTrainingPipelineRequest, dict]) – The request object. Request message for [PipelineService.CreateTrainingPipeline][google.cloud.aiplatform.v1.PipelineService.CreateTrainingPipeline].
parent (str) –
Required. The resource name of the Location to create the TrainingPipeline 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.
training_pipeline (google.cloud.aiplatform_v1.types.TrainingPipeline) –
Required. The TrainingPipeline to create.

This corresponds to the training_pipeline 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:

The TrainingPipeline orchestrates tasks associated with training a Model. It: always executes the training task, and optionally may also export data from Vertex AI’s Dataset which becomes the training input, [upload][google.cloud.aiplatform.v1.ModelService.UploadModel] the Model to Vertex AI, and evaluate the Model.

Return type:

static custom_job_path(project: str, location: str, custom_job: str) → str[source]¶: Returns a fully-qualified custom_job string.

delete_operation(request: Optional[DeleteOperationRequest] = None, *, retry: Optional[Union[Retry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → None[source]¶

Deletes a long-running operation.

This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn’t support this method, it returns google.rpc.Code.UNIMPLEMENTED.

Parameters:

request (DeleteOperationRequest) – The request object. Request message for DeleteOperation method.
retry (google.api_core.retry.Retry) – Designation of what errors, if any, should be retried.
timeout (float) – The timeout for this request.
metadata (Sequence[Tuple[str, str]]) – Strings which should be sent along with the request as metadata.

Returns:

None

delete_pipeline_job(request: Optional[Union[DeletePipelineJobRequest, dict]] = None, *, name: Optional[str] = None, retry: Optional[Union[Retry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → Operation[source]¶

Deletes a PipelineJob.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1

def sample_delete_pipeline_job():
    # Create a client
    client = aiplatform_v1.PipelineServiceClient()

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

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

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

    response = operation.result()

    # Handle the response
    print(response)

Parameters:

request (Union[google.cloud.aiplatform_v1.types.DeletePipelineJobRequest, dict]) – The request object. Request message for [PipelineService.DeletePipelineJob][google.cloud.aiplatform.v1.PipelineService.DeletePipelineJob].
name (str) –
Required. The name of the PipelineJob resource to be deleted. Format: projects/{project}/locations/{location}/pipelineJobs/{pipeline_job}

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:

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);

}

Return type:

delete_training_pipeline(request: Optional[Union[DeleteTrainingPipelineRequest, dict]] = None, *, name: Optional[str] = None, retry: Optional[Union[Retry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → Operation[source]¶

Deletes a TrainingPipeline.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1

def sample_delete_training_pipeline():
    # Create a client
    client = aiplatform_v1.PipelineServiceClient()

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

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

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

    response = operation.result()

    # Handle the response
    print(response)

Parameters:

request (Union[google.cloud.aiplatform_v1.types.DeleteTrainingPipelineRequest, dict]) – The request object. Request message for [PipelineService.DeleteTrainingPipeline][google.cloud.aiplatform.v1.PipelineService.DeleteTrainingPipeline].
name (str) –
Required. The name of the TrainingPipeline resource to be deleted. Format: projects/{project}/locations/{location}/trainingPipelines/{training_pipeline}

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:

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);

}

Return type:

static endpoint_path(project: str, location: str, endpoint: str) → str[source]¶: Returns a fully-qualified endpoint string.

static execution_path(project: str, location: str, metadata_store: str, execution: str) → str[source]¶: Returns a fully-qualified execution string.

classmethod from_service_account_file(filename: str, *args, **kwargs)[source]¶

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

Parameters:

filename (str) – The path to the service account private key json file.
args – Additional arguments to pass to the constructor.
kwargs – Additional arguments to pass to the constructor.

Returns:

The constructed client.

Return type:

PipelineServiceClient

classmethod from_service_account_info(info: dict, *args, **kwargs)[source]¶

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

Parameters:

info (dict) – The service account private key info.
args – Additional arguments to pass to the constructor.
kwargs – Additional arguments to pass to the constructor.

Returns:

The constructed client.

Return type:

PipelineServiceClient

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

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

Parameters:

filename (str) – The path to the service account private key json file.
args – Additional arguments to pass to the constructor.
kwargs – Additional arguments to pass to the constructor.

Returns:

The constructed client.

Return type:

PipelineServiceClient

get_iam_policy(request: Optional[GetIamPolicyRequest] = None, *, retry: Optional[Union[Retry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → Policy[source]¶

Gets the IAM access control policy for a function.

Returns an empty policy if the function exists and does not have a policy set.

Parameters:

request (GetIamPolicyRequest) – The request object. Request message for GetIamPolicy method.
retry (google.api_core.retry.Retry) – Designation of what errors, if any, should be retried.
timeout (float) – The timeout for this request.
metadata (Sequence[Tuple[str, str]]) – Strings which should be sent along with the request as metadata.

Returns:

Defines an Identity and Access Management (IAM) policy. It is used to specify access control policies for Cloud Platform resources. A Policy is a collection of bindings. A binding binds one or more members to a single role. Members can be user accounts, service accounts, Google groups, and domains (such as G Suite). A role is a named list of permissions (defined by IAM or configured by users). A binding can optionally specify a condition, which is a logic expression that further constrains the role binding based on attributes about the request and/or target resource.

JSON Example

{
  "bindings": [
    {
      "role": "roles/resourcemanager.organizationAdmin",
      "members": [
        "user:mike@example.com",
        "group:admins@example.com",
        "domain:google.com",
        "serviceAccount:my-project-id@appspot.gserviceaccount.com"
      ]
    },
    {
      "role": "roles/resourcemanager.organizationViewer",
      "members": ["user:eve@example.com"],
      "condition": {
        "title": "expirable access",
        "description": "Does not grant access after Sep 2020",
        "expression": "request.time <
        timestamp('2020-10-01T00:00:00.000Z')",
      }
    }
  ]
}

YAML Example

bindings:
- members:
  - user:mike@example.com
  - group:admins@example.com
  - domain:google.com
  - serviceAccount:my-project-id@appspot.gserviceaccount.com
  role: roles/resourcemanager.organizationAdmin
- members:
  - user:eve@example.com
  role: roles/resourcemanager.organizationViewer
  condition:
    title: expirable access
    description: Does not grant access after Sep 2020
    expression: request.time < timestamp('2020-10-01T00:00:00.000Z')

For a description of IAM and its features, see the IAM developer’s guide.

Return type:

Policy

get_location(request: Optional[GetLocationRequest] = None, *, retry: Optional[Union[Retry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → Location[source]¶

Gets information about a location.

Parameters:

request (GetLocationRequest) – The request object. Request message for GetLocation method.
retry (google.api_core.retry.Retry) – Designation of what errors, if any, should be retried.
timeout (float) – The timeout for this request.
metadata (Sequence[Tuple[str, str]]) – Strings which should be sent along with the request as metadata.

Returns:

Location object.

Return type:

Location

classmethod get_mtls_endpoint_and_cert_source(client_options: Optional[ClientOptions] = None)[source]¶

Deprecated. Return the API endpoint and client cert source for mutual TLS.

The client cert source is determined in the following order: (1) if GOOGLE_API_USE_CLIENT_CERTIFICATE environment variable is not “true”, the client cert source is None. (2) if client_options.client_cert_source is provided, use the provided one; if the default client cert source exists, use the default one; otherwise the client cert source is None.

The API endpoint is determined in the following order: (1) if client_options.api_endpoint if provided, use the provided one. (2) if GOOGLE_API_USE_CLIENT_CERTIFICATE environment variable is “always”, use the default mTLS endpoint; if the environment variable is “never”, use the default API endpoint; otherwise if client cert source exists, use the default mTLS endpoint, otherwise use the default API endpoint.

More details can be found at https://google.aip.dev/auth/4114.

Parameters:

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.

Returns:

returns the API endpoint and the: client cert source to use.

Return type:

Tuple[str, Callable[[], Tuple[bytes, bytes]]]

Raises:

google.auth.exceptions.MutualTLSChannelError – If any errors happen.

get_operation(request: Optional[GetOperationRequest] = None, *, retry: Optional[Union[Retry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → Operation[source]¶

Gets the latest state of a long-running operation.

Parameters:

request (GetOperationRequest) – The request object. Request message for GetOperation method.
retry (google.api_core.retry.Retry) – Designation of what errors, if any, should be retried.
timeout (float) – The timeout for this request.
metadata (Sequence[Tuple[str, str]]) – Strings which should be sent along with the request as metadata.

Returns:

An Operation object.

Return type:

Operation

get_pipeline_job(request: Optional[Union[GetPipelineJobRequest, dict]] = None, *, name: Optional[str] = None, retry: Optional[Union[Retry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → PipelineJob[source]¶

Gets a PipelineJob.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1

def sample_get_pipeline_job():
    # Create a client
    client = aiplatform_v1.PipelineServiceClient()

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

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

    # Handle the response
    print(response)

Parameters:

request (Union[google.cloud.aiplatform_v1.types.GetPipelineJobRequest, dict]) – The request object. Request message for [PipelineService.GetPipelineJob][google.cloud.aiplatform.v1.PipelineService.GetPipelineJob].
name (str) –
Required. The name of the PipelineJob resource. Format: projects/{project}/locations/{location}/pipelineJobs/{pipeline_job}

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:

An instance of a machine learning PipelineJob.

Return type:

get_training_pipeline(request: Optional[Union[GetTrainingPipelineRequest, dict]] = None, *, name: Optional[str] = None, retry: Optional[Union[Retry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → TrainingPipeline[source]¶

Gets a TrainingPipeline.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1

def sample_get_training_pipeline():
    # Create a client
    client = aiplatform_v1.PipelineServiceClient()

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

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

    # Handle the response
    print(response)

Parameters:

request (Union[google.cloud.aiplatform_v1.types.GetTrainingPipelineRequest, dict]) – The request object. Request message for [PipelineService.GetTrainingPipeline][google.cloud.aiplatform.v1.PipelineService.GetTrainingPipeline].
name (str) –
Required. The name of the TrainingPipeline resource. Format: projects/{project}/locations/{location}/trainingPipelines/{training_pipeline}

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:

The TrainingPipeline orchestrates tasks associated with training a Model. It: always executes the training task, and optionally may also export data from Vertex AI’s Dataset which becomes the training input, [upload][google.cloud.aiplatform.v1.ModelService.UploadModel] the Model to Vertex AI, and evaluate the Model.

Return type: