async def batch_migrate_resources(
self,
request: migration_service.BatchMigrateResourcesRequest = None,
*,
parent: str = None,
migrate_resource_requests: Sequence[
migration_service.MigrateResourceRequest] = None,
retry: retries.Retry = gapic_v1.method.DEFAULT,
timeout: float = None,
metadata: Sequence[Tuple[str, str]] = (),
) -> operation_async.AsyncOperation:
r"""Batch migrates resources from ml.googleapis.com,
automl.googleapis.com, and datalabeling.googleapis.com
to AI Platform (Unified).
Args:
request (:class:`google.cloud.aiplatform_v1.types.BatchMigrateResourcesRequest`):
The request object. Request message for
[MigrationService.BatchMigrateResources][google.cloud.aiplatform.v1.MigrationService.BatchMigrateResources].
parent (:class:`str`):
Required. The location of the migrated resource will
live 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.
migrate_resource_requests (:class:`Sequence[google.cloud.aiplatform_v1.types.MigrateResourceRequest]`):
Required. The request messages
specifying the resources to migrate.
They must be in the same location as the
destination. Up to 50 resources can be
migrated in one batch.
This corresponds to the ``migrate_resource_requests`` 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:
google.api_core.operation_async.AsyncOperation:
An object representing a long-running operation.
The result type for the operation will be
:class:`google.cloud.aiplatform_v1.types.BatchMigrateResourcesResponse`
Response message for
[MigrationService.BatchMigrateResources][google.cloud.aiplatform.v1.MigrationService.BatchMigrateResources].
"""
# Create or coerce a protobuf request object.
# Sanity check: If we got a request object, we should *not* have
# gotten any keyword arguments that map to the request.
has_flattened_params = any([parent, migrate_resource_requests])
if request is not None and has_flattened_params:
raise ValueError("If the `request` argument is set, then none of "
"the individual field arguments should be set.")
request = migration_service.BatchMigrateResourcesRequest(request)
# If we have keyword arguments corresponding to fields on the
# request, apply these.
if parent is not None:
request.parent = parent
if migrate_resource_requests:
request.migrate_resource_requests.extend(migrate_resource_requests)
# Wrap the RPC method; this adds retry and timeout information,
# and friendly error handling.
rpc = gapic_v1.method_async.wrap_method(
self._client._transport.batch_migrate_resources,
default_timeout=None,
client_info=DEFAULT_CLIENT_INFO,
)
# Certain fields should be provided within the metadata header;
# add these here.
metadata = tuple(metadata) + (gapic_v1.routing_header.to_grpc_metadata(
(("parent", request.parent), )), )
# Send the request.
response = await rpc(
request,
retry=retry,
timeout=timeout,
metadata=metadata,
)
# Wrap the response in an operation future.
response = operation_async.from_gapic(
response,
self._client._transport.operations_client,
migration_service.BatchMigrateResourcesResponse,
metadata_type=migration_service.
BatchMigrateResourcesOperationMetadata,
)
# Done; return the response.
return response
def batch_migrate_resources(
self,
request: Union[migration_service.BatchMigrateResourcesRequest,
dict] = None,
*,
parent: str = None,
migrate_resource_requests: Sequence[
migration_service.MigrateResourceRequest] = None,
retry: OptionalRetry = gapic_v1.method.DEFAULT,
timeout: float = None,
metadata: Sequence[Tuple[str, str]] = (),
) -> operation.Operation:
r"""Batch migrates resources from ml.googleapis.com,
automl.googleapis.com, and datalabeling.googleapis.com
to Vertex AI.
.. code-block:: python
from google.cloud import aiplatform_v1
def sample_batch_migrate_resources():
# Create a client
client = aiplatform_v1.MigrationServiceClient()
# Initialize request argument(s)
migrate_resource_requests = aiplatform_v1.MigrateResourceRequest()
migrate_resource_requests.migrate_ml_engine_model_version_config.endpoint = "endpoint_value"
migrate_resource_requests.migrate_ml_engine_model_version_config.model_version = "model_version_value"
migrate_resource_requests.migrate_ml_engine_model_version_config.model_display_name = "model_display_name_value"
request = aiplatform_v1.BatchMigrateResourcesRequest(
parent="parent_value",
migrate_resource_requests=migrate_resource_requests,
)
# Make the request
operation = client.batch_migrate_resources(request=request)
print("Waiting for operation to complete...")
response = operation.result()
# Handle the response
print(response)
Args:
request (Union[google.cloud.aiplatform_v1.types.BatchMigrateResourcesRequest, dict]):
The request object. Request message for
[MigrationService.BatchMigrateResources][google.cloud.aiplatform.v1.MigrationService.BatchMigrateResources].
parent (str):
Required. The location of the migrated resource will
live 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.
migrate_resource_requests (Sequence[google.cloud.aiplatform_v1.types.MigrateResourceRequest]):
Required. The request messages
specifying the resources to migrate.
They must be in the same location as the
destination. Up to 50 resources can be
migrated in one batch.
This corresponds to the ``migrate_resource_requests`` 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:
google.api_core.operation.Operation:
An object representing a long-running operation.
The result type for the operation will be
:class:`google.cloud.aiplatform_v1.types.BatchMigrateResourcesResponse`
Response message for
[MigrationService.BatchMigrateResources][google.cloud.aiplatform.v1.MigrationService.BatchMigrateResources].
"""
# Create or coerce a protobuf request object.
# Quick check: If we got a request object, we should *not* have
# gotten any keyword arguments that map to the request.
has_flattened_params = any([parent, migrate_resource_requests])
if request is not None and has_flattened_params:
raise ValueError("If the `request` argument is set, then none of "
"the individual field arguments should be set.")
# Minor optimization to avoid making a copy if the user passes
# in a migration_service.BatchMigrateResourcesRequest.
# There's no risk of modifying the input as we've already verified
# there are no flattened fields.
if not isinstance(request,
migration_service.BatchMigrateResourcesRequest):
request = migration_service.BatchMigrateResourcesRequest(request)
# If we have keyword arguments corresponding to fields on the
# request, apply these.
if parent is not None:
request.parent = parent
if migrate_resource_requests is not None:
request.migrate_resource_requests = migrate_resource_requests
# Wrap the RPC method; this adds retry and timeout information,
# and friendly error handling.
rpc = self._transport._wrapped_methods[
self._transport.batch_migrate_resources]
# Certain fields should be provided within the metadata header;
# add these here.
metadata = tuple(metadata) + (gapic_v1.routing_header.to_grpc_metadata(
(("parent", request.parent), )), )
# Send the request.
response = rpc(
request,
retry=retry,
timeout=timeout,
metadata=metadata,
)
# Wrap the response in an operation future.
response = operation.from_gapic(
response,
self._transport.operations_client,
migration_service.BatchMigrateResourcesResponse,
metadata_type=migration_service.
BatchMigrateResourcesOperationMetadata,
)
# Done; return the response.
return response
