# -*- coding: utf-8 -*-
# Copyright 2025 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
import logging as std_logging
from collections import OrderedDict
import re
from typing import (
    Dict,
    Callable,
    Mapping,
    MutableMapping,
    MutableSequence,
    Optional,
    Sequence,
    Tuple,
    Type,
    Union,
)

from google.cloud.aiplatform_v1beta1 import gapic_version as package_version

from google.api_core.client_options import ClientOptions
from google.api_core import exceptions as core_exceptions
from google.api_core import gapic_v1
from google.api_core import retry_async as retries
from google.auth import credentials as ga_credentials  # type: ignore
from google.oauth2 import service_account  # type: ignore
import google.protobuf


try:
    OptionalRetry = Union[retries.AsyncRetry, gapic_v1.method._MethodDefault, None]
except AttributeError:  # pragma: NO COVER
    OptionalRetry = Union[retries.AsyncRetry, object, None]  # type: ignore

from google.api_core import operation as gac_operation  # type: ignore
from google.api_core import operation_async  # type: ignore
from google.cloud.aiplatform_v1beta1.services.pipeline_service import pagers
from google.cloud.aiplatform_v1beta1.types import encryption_spec
from google.cloud.aiplatform_v1beta1.types import model
from google.cloud.aiplatform_v1beta1.types import operation as gca_operation
from google.cloud.aiplatform_v1beta1.types import pipeline_job
from google.cloud.aiplatform_v1beta1.types import pipeline_job as gca_pipeline_job
from google.cloud.aiplatform_v1beta1.types import pipeline_service
from google.cloud.aiplatform_v1beta1.types import pipeline_state
from google.cloud.aiplatform_v1beta1.types import service_networking
from google.cloud.aiplatform_v1beta1.types import training_pipeline
from google.cloud.aiplatform_v1beta1.types import (
    training_pipeline as gca_training_pipeline,
)
from google.cloud.location import locations_pb2  # type: ignore
from google.iam.v1 import iam_policy_pb2  # type: ignore
from google.iam.v1 import policy_pb2  # type: ignore
from google.longrunning import operations_pb2  # type: ignore
from google.protobuf import empty_pb2  # type: ignore
from google.protobuf import struct_pb2  # type: ignore
from google.protobuf import timestamp_pb2  # type: ignore
from google.rpc import status_pb2  # type: ignore
from .transports.base import PipelineServiceTransport, DEFAULT_CLIENT_INFO
from .transports.grpc_asyncio import PipelineServiceGrpcAsyncIOTransport
from .client import PipelineServiceClient

try:
    from google.api_core import client_logging  # type: ignore

    CLIENT_LOGGING_SUPPORTED = True  # pragma: NO COVER
except ImportError:  # pragma: NO COVER
    CLIENT_LOGGING_SUPPORTED = False

_LOGGER = std_logging.getLogger(__name__)


class PipelineServiceAsyncClient:
    """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).
    """

    _client: PipelineServiceClient

    # Copy defaults from the synchronous client for use here.
    # Note: DEFAULT_ENDPOINT is deprecated. Use _DEFAULT_ENDPOINT_TEMPLATE instead.
    DEFAULT_ENDPOINT = PipelineServiceClient.DEFAULT_ENDPOINT
    DEFAULT_MTLS_ENDPOINT = PipelineServiceClient.DEFAULT_MTLS_ENDPOINT
    _DEFAULT_ENDPOINT_TEMPLATE = PipelineServiceClient._DEFAULT_ENDPOINT_TEMPLATE
    _DEFAULT_UNIVERSE = PipelineServiceClient._DEFAULT_UNIVERSE

    artifact_path = staticmethod(PipelineServiceClient.artifact_path)
    parse_artifact_path = staticmethod(PipelineServiceClient.parse_artifact_path)
    context_path = staticmethod(PipelineServiceClient.context_path)
    parse_context_path = staticmethod(PipelineServiceClient.parse_context_path)
    custom_job_path = staticmethod(PipelineServiceClient.custom_job_path)
    parse_custom_job_path = staticmethod(PipelineServiceClient.parse_custom_job_path)
    endpoint_path = staticmethod(PipelineServiceClient.endpoint_path)
    parse_endpoint_path = staticmethod(PipelineServiceClient.parse_endpoint_path)
    execution_path = staticmethod(PipelineServiceClient.execution_path)
    parse_execution_path = staticmethod(PipelineServiceClient.parse_execution_path)
    model_path = staticmethod(PipelineServiceClient.model_path)
    parse_model_path = staticmethod(PipelineServiceClient.parse_model_path)
    network_path = staticmethod(PipelineServiceClient.network_path)
    parse_network_path = staticmethod(PipelineServiceClient.parse_network_path)
    network_attachment_path = staticmethod(
        PipelineServiceClient.network_attachment_path
    )
    parse_network_attachment_path = staticmethod(
        PipelineServiceClient.parse_network_attachment_path
    )
    pipeline_job_path = staticmethod(PipelineServiceClient.pipeline_job_path)
    parse_pipeline_job_path = staticmethod(
        PipelineServiceClient.parse_pipeline_job_path
    )
    training_pipeline_path = staticmethod(PipelineServiceClient.training_pipeline_path)
    parse_training_pipeline_path = staticmethod(
        PipelineServiceClient.parse_training_pipeline_path
    )
    common_billing_account_path = staticmethod(
        PipelineServiceClient.common_billing_account_path
    )
    parse_common_billing_account_path = staticmethod(
        PipelineServiceClient.parse_common_billing_account_path
    )
    common_folder_path = staticmethod(PipelineServiceClient.common_folder_path)
    parse_common_folder_path = staticmethod(
        PipelineServiceClient.parse_common_folder_path
    )
    common_organization_path = staticmethod(
        PipelineServiceClient.common_organization_path
    )
    parse_common_organization_path = staticmethod(
        PipelineServiceClient.parse_common_organization_path
    )
    common_project_path = staticmethod(PipelineServiceClient.common_project_path)
    parse_common_project_path = staticmethod(
        PipelineServiceClient.parse_common_project_path
    )
    common_location_path = staticmethod(PipelineServiceClient.common_location_path)
    parse_common_location_path = staticmethod(
        PipelineServiceClient.parse_common_location_path
    )

    @classmethod
    def from_service_account_info(cls, info: dict, *args, **kwargs):
        """Creates an instance of this client using the provided credentials
            info.

        Args:
            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:
            PipelineServiceAsyncClient: The constructed client.
        """
        return PipelineServiceClient.from_service_account_info.__func__(PipelineServiceAsyncClient, info, *args, **kwargs)  # type: ignore

    @classmethod
    def from_service_account_file(cls, filename: str, *args, **kwargs):
        """Creates an instance of this client using the provided credentials
            file.

        Args:
            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:
            PipelineServiceAsyncClient: The constructed client.
        """
        return PipelineServiceClient.from_service_account_file.__func__(PipelineServiceAsyncClient, filename, *args, **kwargs)  # type: ignore

    from_service_account_json = from_service_account_file

    @classmethod
    def get_mtls_endpoint_and_cert_source(
        cls, client_options: Optional[ClientOptions] = None
    ):
        """Return the API endpoint and client cert source for mutual TLS.

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

        The API endpoint is determined in the following order:
        (1) if `client_options.api_endpoint` if provided, use the provided one.
        (2) if `GOOGLE_API_USE_CLIENT_CERTIFICATE` environment variable is "always", use the
        default mTLS endpoint; if the environment 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.

        Args:
            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:
            Tuple[str, Callable[[], Tuple[bytes, bytes]]]: returns the API endpoint and the
                client cert source to use.

        Raises:
            google.auth.exceptions.MutualTLSChannelError: If any errors happen.
        """
        return PipelineServiceClient.get_mtls_endpoint_and_cert_source(client_options)  # type: ignore

    @property
    def transport(self) -> PipelineServiceTransport:
        """Returns the transport used by the client instance.

        Returns:
            PipelineServiceTransport: The transport used by the client instance.
        """
        return self._client.transport

    @property
    def api_endpoint(self):
        """Return the API endpoint used by the client instance.

        Returns:
            str: The API endpoint used by the client instance.
        """
        return self._client._api_endpoint

    @property
    def universe_domain(self) -> str:
        """Return the universe domain used by the client instance.

        Returns:
            str: The universe domain used
                by the client instance.
        """
        return self._client._universe_domain

    get_transport_class = PipelineServiceClient.get_transport_class

    def __init__(
        self,
        *,
        credentials: Optional[ga_credentials.Credentials] = None,
        transport: Optional[
            Union[
                str, PipelineServiceTransport, Callable[..., PipelineServiceTransport]
            ]
        ] = "grpc_asyncio",
        client_options: Optional[ClientOptions] = None,
        client_info: gapic_v1.client_info.ClientInfo = DEFAULT_CLIENT_INFO,
    ) -> None:
        """Instantiates the pipeline service async client.

        Args:
            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 to use.
                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 ``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.
        """
        self._client = PipelineServiceClient(
            credentials=credentials,
            transport=transport,
            client_options=client_options,
            client_info=client_info,
        )

        if CLIENT_LOGGING_SUPPORTED and _LOGGER.isEnabledFor(
            std_logging.DEBUG
        ):  # pragma: NO COVER
            _LOGGER.debug(
                "Created client `google.cloud.aiplatform_v1beta1.PipelineServiceAsyncClient`.",
                extra=(
                    {
                        "serviceName": "google.cloud.aiplatform.v1beta1.PipelineService",
                        "universeDomain": getattr(
                            self._client._transport._credentials, "universe_domain", ""
                        ),
                        "credentialsType": f"{type(self._client._transport._credentials).__module__}.{type(self._client._transport._credentials).__qualname__}",
                        "credentialsInfo": getattr(
                            self.transport._credentials, "get_cred_info", lambda: None
                        )(),
                    }
                    if hasattr(self._client._transport, "_credentials")
                    else {
                        "serviceName": "google.cloud.aiplatform.v1beta1.PipelineService",
                        "credentialsType": None,
                    }
                ),
            )

    async def create_training_pipeline(
        self,
        request: Optional[
            Union[pipeline_service.CreateTrainingPipelineRequest, dict]
        ] = None,
        *,
        parent: Optional[str] = None,
        training_pipeline: Optional[gca_training_pipeline.TrainingPipeline] = None,
        retry: OptionalRetry = gapic_v1.method.DEFAULT,
        timeout: Union[float, object] = gapic_v1.method.DEFAULT,
        metadata: Sequence[Tuple[str, Union[str, bytes]]] = (),
    ) -> gca_training_pipeline.TrainingPipeline:
        r"""Creates a TrainingPipeline. A created
        TrainingPipeline right away will be attempted to be run.

        .. code-block:: python

            # 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_v1beta1

            async def sample_create_training_pipeline():
                # Create a client
                client = aiplatform_v1beta1.PipelineServiceAsyncClient()

                # Initialize request argument(s)
                training_pipeline = aiplatform_v1beta1.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_v1beta1.CreateTrainingPipelineRequest(
                    parent="parent_value",
                    training_pipeline=training_pipeline,
                )

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

                # Handle the response
                print(response)

        Args:
            request (Optional[Union[google.cloud.aiplatform_v1beta1.types.CreateTrainingPipelineRequest, dict]]):
                The request object. Request message for
                [PipelineService.CreateTrainingPipeline][google.cloud.aiplatform.v1beta1.PipelineService.CreateTrainingPipeline].
            parent (:class:`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 (:class:`google.cloud.aiplatform_v1beta1.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, Union[str, bytes]]]): Key/value pairs which should be
                sent along with the request as metadata. Normally, each value must be of type `str`,
                but for metadata keys ending with the suffix `-bin`, the corresponding values must
                be of type `bytes`.

        Returns:
            google.cloud.aiplatform_v1beta1.types.TrainingPipeline:
                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.v1beta1.ModelService.UploadModel]
                   the Model to Vertex AI, and evaluate the Model.

        """
        # 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.
        flattened_params = [parent, training_pipeline]
        has_flattened_params = (
            len([param for param in flattened_params if param is not None]) > 0
        )
        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."
            )

        # - Use the request object if provided (there's no risk of modifying the input as
        #   there are no flattened fields), or create one.
        if not isinstance(request, pipeline_service.CreateTrainingPipelineRequest):
            request = pipeline_service.CreateTrainingPipelineRequest(request)

        # If we have keyword arguments corresponding to fields on the
        # request, apply these.
        if parent is not None:
            request.parent = parent
        if training_pipeline is not None:
            request.training_pipeline = training_pipeline

        # Wrap the RPC method; this adds retry and timeout information,
        # and friendly error handling.
        rpc = self._client._transport._wrapped_methods[
            self._client._transport.create_training_pipeline
        ]

        # 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),)),
        )

        # Validate the universe domain.
        self._client._validate_universe_domain()

        # Send the request.
        response = await rpc(
            request,
            retry=retry,
            timeout=timeout,
            metadata=metadata,
        )

        # Done; return the response.
        return response

    async def get_training_pipeline(
        self,
        request: Optional[
            Union[pipeline_service.GetTrainingPipelineRequest, dict]
        ] = None,
        *,
        name: Optional[str] = None,
        retry: OptionalRetry = gapic_v1.method.DEFAULT,
        timeout: Union[float, object] = gapic_v1.method.DEFAULT,
        metadata: Sequence[Tuple[str, Union[str, bytes]]] = (),
    ) -> training_pipeline.TrainingPipeline:
        r"""Gets a TrainingPipeline.

        .. code-block:: python

            # 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_v1beta1

            async def sample_get_training_pipeline():
                # Create a client
                client = aiplatform_v1beta1.PipelineServiceAsyncClient()

                # Initialize request argument(s)
                request = aiplatform_v1beta1.GetTrainingPipelineRequest(
                    name="name_value",
                )

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

                # Handle the response
                print(response)

        Args:
            request (Optional[Union[google.cloud.aiplatform_v1beta1.types.GetTrainingPipelineRequest, dict]]):
                The request object. Request message for
                [PipelineService.GetTrainingPipeline][google.cloud.aiplatform.v1beta1.PipelineService.GetTrainingPipeline].
            name (:class:`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, Union[str, bytes]]]): Key/value pairs which should be
                sent along with the request as metadata. Normally, each value must be of type `str`,
                but for metadata keys ending with the suffix `-bin`, the corresponding values must
                be of type `bytes`.

        Returns:
            google.cloud.aiplatform_v1beta1.types.TrainingPipeline:
                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.v1beta1.ModelService.UploadModel]
                   the Model to Vertex AI, and evaluate the Model.

        """
        # 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.
        flattened_params = [name]
        has_flattened_params = (
            len([param for param in flattened_params if param is not None]) > 0
        )
        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."
            )

        # - Use the request object if provided (there's no risk of modifying the input as
        #   there are no flattened fields), or create one.
        if not isinstance(request, pipeline_service.GetTrainingPipelineRequest):
            request = pipeline_service.GetTrainingPipelineRequest(request)

        # If we have keyword arguments corresponding to fields on the
        # request, apply these.
        if name is not None:
            request.name = name

        # Wrap the RPC method; this adds retry and timeout information,
        # and friendly error handling.
        rpc = self._client._transport._wrapped_methods[
            self._client._transport.get_training_pipeline
        ]

        # Certain fields should be provided within the metadata header;
        # add these here.
        metadata = tuple(metadata) + (
            gapic_v1.routing_header.to_grpc_metadata((("name", request.name),)),
        )

        # Validate the universe domain.
        self._client._validate_universe_domain()

        # Send the request.
        response = await rpc(
            request,
            retry=retry,
            timeout=timeout,
            metadata=metadata,
        )

        # Done; return the response.
        return response

    async def list_training_pipelines(
        self,
        request: Optional[
            Union[pipeline_service.ListTrainingPipelinesRequest, dict]
        ] = None,
        *,
        parent: Optional[str] = None,
        retry: OptionalRetry = gapic_v1.method.DEFAULT,
        timeout: Union[float, object] = gapic_v1.method.DEFAULT,
        metadata: Sequence[Tuple[str, Union[str, bytes]]] = (),
    ) -> pagers.ListTrainingPipelinesAsyncPager:
        r"""Lists TrainingPipelines in a Location.

        .. code-block:: python

            # 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_v1beta1

            async def sample_list_training_pipelines():
                # Create a client
                client = aiplatform_v1beta1.PipelineServiceAsyncClient()

                # Initialize request argument(s)
                request = aiplatform_v1beta1.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)

        Args:
            request (Optional[Union[google.cloud.aiplatform_v1beta1.types.ListTrainingPipelinesRequest, dict]]):
                The request object. Request message for
                [PipelineService.ListTrainingPipelines][google.cloud.aiplatform.v1beta1.PipelineService.ListTrainingPipelines].
            parent (:class:`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, Union[str, bytes]]]): Key/value pairs which should be
                sent along with the request as metadata. Normally, each value must be of type `str`,
                but for metadata keys ending with the suffix `-bin`, the corresponding values must
                be of type `bytes`.

        Returns:
            google.cloud.aiplatform_v1beta1.services.pipeline_service.pagers.ListTrainingPipelinesAsyncPager:
                Response message for
                   [PipelineService.ListTrainingPipelines][google.cloud.aiplatform.v1beta1.PipelineService.ListTrainingPipelines]

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

        """
        # 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.
        flattened_params = [parent]
        has_flattened_params = (
            len([param for param in flattened_params if param is not None]) > 0
        )
        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."
            )

        # - Use the request object if provided (there's no risk of modifying the input as
        #   there are no flattened fields), or create one.
        if not isinstance(request, pipeline_service.ListTrainingPipelinesRequest):
            request = pipeline_service.ListTrainingPipelinesRequest(request)

        # If we have keyword arguments corresponding to fields on the
        # request, apply these.
        if parent is not None:
            request.parent = parent

        # Wrap the RPC method; this adds retry and timeout information,
        # and friendly error handling.
        rpc = self._client._transport._wrapped_methods[
            self._client._transport.list_training_pipelines
        ]

        # 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),)),
        )

        # Validate the universe domain.
        self._client._validate_universe_domain()

        # Send the request.
        response = await rpc(
            request,
            retry=retry,
            timeout=timeout,
            metadata=metadata,
        )

        # This method is paged; wrap the response in a pager, which provides
        # an `__aiter__` convenience method.
        response = pagers.ListTrainingPipelinesAsyncPager(
            method=rpc,
            request=request,
            response=response,
            retry=retry,
            timeout=timeout,
            metadata=metadata,
        )

        # Done; return the response.
        return response

    async def delete_training_pipeline(
        self,
        request: Optional[
            Union[pipeline_service.DeleteTrainingPipelineRequest, dict]
        ] = None,
        *,
        name: Optional[str] = None,
        retry: OptionalRetry = gapic_v1.method.DEFAULT,
        timeout: Union[float, object] = gapic_v1.method.DEFAULT,
        metadata: Sequence[Tuple[str, Union[str, bytes]]] = (),
    ) -> operation_async.AsyncOperation:
        r"""Deletes a TrainingPipeline.

        .. code-block:: python

            # 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_v1beta1

            async def sample_delete_training_pipeline():
                # Create a client
                client = aiplatform_v1beta1.PipelineServiceAsyncClient()

                # Initialize request argument(s)
                request = aiplatform_v1beta1.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)

        Args:
            request (Optional[Union[google.cloud.aiplatform_v1beta1.types.DeleteTrainingPipelineRequest, dict]]):
                The request object. Request message for
                [PipelineService.DeleteTrainingPipeline][google.cloud.aiplatform.v1beta1.PipelineService.DeleteTrainingPipeline].
            name (:class:`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, Union[str, bytes]]]): Key/value pairs which should be
                sent along with the request as metadata. Normally, each value must be of type `str`,
                but for metadata keys ending with the suffix `-bin`, the corresponding values must
                be of type `bytes`.

        Returns:
            google.api_core.operation_async.AsyncOperation:
                An object representing a long-running operation.

                The result type for the operation will be :class:`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);

                      }

        """
        # 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.
        flattened_params = [name]
        has_flattened_params = (
            len([param for param in flattened_params if param is not None]) > 0
        )
        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."
            )

        # - Use the request object if provided (there's no risk of modifying the input as
        #   there are no flattened fields), or create one.
        if not isinstance(request, pipeline_service.DeleteTrainingPipelineRequest):
            request = pipeline_service.DeleteTrainingPipelineRequest(request)

        # If we have keyword arguments corresponding to fields on the
        # request, apply these.
        if name is not None:
            request.name = name

        # Wrap the RPC method; this adds retry and timeout information,
        # and friendly error handling.
        rpc = self._client._transport._wrapped_methods[
            self._client._transport.delete_training_pipeline
        ]

        # Certain fields should be provided within the metadata header;
        # add these here.
        metadata = tuple(metadata) + (
            gapic_v1.routing_header.to_grpc_metadata((("name", request.name),)),
        )

        # Validate the universe domain.
        self._client._validate_universe_domain()

        # 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,
            empty_pb2.Empty,
            metadata_type=gca_operation.DeleteOperationMetadata,
        )

        # Done; return the response.
        return response

    async def cancel_training_pipeline(
        self,
        request: Optional[
            Union[pipeline_service.CancelTrainingPipelineRequest, dict]
        ] = None,
        *,
        name: Optional[str] = None,
        retry: OptionalRetry = gapic_v1.method.DEFAULT,
        timeout: Union[float, object] = gapic_v1.method.DEFAULT,
        metadata: Sequence[Tuple[str, Union[str, bytes]]] = (),
    ) -> None:
        r"""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.v1beta1.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.v1beta1.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.v1beta1.TrainingPipeline.state]
        is set to ``CANCELLED``.

        .. code-block:: python

            # 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_v1beta1

            async def sample_cancel_training_pipeline():
                # Create a client
                client = aiplatform_v1beta1.PipelineServiceAsyncClient()

                # Initialize request argument(s)
                request = aiplatform_v1beta1.CancelTrainingPipelineRequest(
                    name="name_value",
                )

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

        Args:
            request (Optional[Union[google.cloud.aiplatform_v1beta1.types.CancelTrainingPipelineRequest, dict]]):
                The request object. Request message for
                [PipelineService.CancelTrainingPipeline][google.cloud.aiplatform.v1beta1.PipelineService.CancelTrainingPipeline].
            name (:class:`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, Union[str, bytes]]]): Key/value pairs which should be
                sent along with the request as metadata. Normally, each value must be of type `str`,
                but for metadata keys ending with the suffix `-bin`, the corresponding values must
                be of type `bytes`.
        """
        # 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.
        flattened_params = [name]
        has_flattened_params = (
            len([param for param in flattened_params if param is not None]) > 0
        )
        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."
            )

        # - Use the request object if provided (there's no risk of modifying the input as
        #   there are no flattened fields), or create one.
        if not isinstance(request, pipeline_service.CancelTrainingPipelineRequest):
            request = pipeline_service.CancelTrainingPipelineRequest(request)

        # If we have keyword arguments corresponding to fields on the
        # request, apply these.
        if name is not None:
            request.name = name

        # Wrap the RPC method; this adds retry and timeout information,
        # and friendly error handling.
        rpc = self._client._transport._wrapped_methods[
            self._client._transport.cancel_training_pipeline
        ]

        # Certain fields should be provided within the metadata header;
        # add these here.
        metadata = tuple(metadata) + (
            gapic_v1.routing_header.to_grpc_metadata((("name", request.name),)),
        )

        # Validate the universe domain.
        self._client._validate_universe_domain()

        # Send the request.
        await rpc(
            request,
            retry=retry,
            timeout=timeout,
            metadata=metadata,
        )

    async def create_pipeline_job(
        self,
        request: Optional[
            Union[pipeline_service.CreatePipelineJobRequest, dict]
        ] = None,
        *,
        parent: Optional[str] = None,
        pipeline_job: Optional[gca_pipeline_job.PipelineJob] = None,
        pipeline_job_id: Optional[str] = None,
        retry: OptionalRetry = gapic_v1.method.DEFAULT,
        timeout: Union[float, object] = gapic_v1.method.DEFAULT,
        metadata: Sequence[Tuple[str, Union[str, bytes]]] = (),
    ) -> gca_pipeline_job.PipelineJob:
        r"""Creates a PipelineJob. A PipelineJob will run
        immediately when created.

        .. code-block:: python

            # 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_v1beta1

            async def sample_create_pipeline_job():
                # Create a client
                client = aiplatform_v1beta1.PipelineServiceAsyncClient()

                # Initialize request argument(s)
                request = aiplatform_v1beta1.CreatePipelineJobRequest(
                    parent="parent_value",
                )

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

                # Handle the response
                print(response)

        Args:
            request (Optional[Union[google.cloud.aiplatform_v1beta1.types.CreatePipelineJobRequest, dict]]):
                The request object. Request message for
                [PipelineService.CreatePipelineJob][google.cloud.aiplatform.v1beta1.PipelineService.CreatePipelineJob].
            parent (:class:`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 (:class:`google.cloud.aiplatform_v1beta1.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 (:class:`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, Union[str, bytes]]]): Key/value pairs which should be
                sent along with the request as metadata. Normally, each value must be of type `str`,
                but for metadata keys ending with the suffix `-bin`, the corresponding values must
                be of type `bytes`.

        Returns:
            google.cloud.aiplatform_v1beta1.types.PipelineJob:
                An instance of a machine learning
                PipelineJob.

        """
        # 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.
        flattened_params = [parent, pipeline_job, pipeline_job_id]
        has_flattened_params = (
            len([param for param in flattened_params if param is not None]) > 0
        )
        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."
            )

        # - Use the request object if provided (there's no risk of modifying the input as
        #   there are no flattened fields), or create one.
        if not isinstance(request, pipeline_service.CreatePipelineJobRequest):
            request = pipeline_service.CreatePipelineJobRequest(request)

        # If we have keyword arguments corresponding to fields on the
        # request, apply these.
        if parent is not None:
            request.parent = parent
        if pipeline_job is not None:
            request.pipeline_job = pipeline_job
        if pipeline_job_id is not None:
            request.pipeline_job_id = pipeline_job_id

        # Wrap the RPC method; this adds retry and timeout information,
        # and friendly error handling.
        rpc = self._client._transport._wrapped_methods[
            self._client._transport.create_pipeline_job
        ]

        # 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),)),
        )

        # Validate the universe domain.
        self._client._validate_universe_domain()

        # Send the request.
        response = await rpc(
            request,
            retry=retry,
            timeout=timeout,
            metadata=metadata,
        )

        # Done; return the response.
        return response

    async def get_pipeline_job(
        self,
        request: Optional[Union[pipeline_service.GetPipelineJobRequest, dict]] = None,
        *,
        name: Optional[str] = None,
        retry: OptionalRetry = gapic_v1.method.DEFAULT,
        timeout: Union[float, object] = gapic_v1.method.DEFAULT,
        metadata: Sequence[Tuple[str, Union[str, bytes]]] = (),
    ) -> pipeline_job.PipelineJob:
        r"""Gets a PipelineJob.

        .. code-block:: python

            # 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_v1beta1

            async def sample_get_pipeline_job():
                # Create a client
                client = aiplatform_v1beta1.PipelineServiceAsyncClient()

                # Initialize request argument(s)
                request = aiplatform_v1beta1.GetPipelineJobRequest(
                    name="name_value",
                )

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

                # Handle the response
                print(response)

        Args:
            request (Optional[Union[google.cloud.aiplatform_v1beta1.types.GetPipelineJobRequest, dict]]):
                The request object. Request message for
                [PipelineService.GetPipelineJob][google.cloud.aiplatform.v1beta1.PipelineService.GetPipelineJob].
            name (:class:`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, Union[str, bytes]]]): Key/value pairs which should be
                sent along with the request as metadata. Normally, each value must be of type `str`,
                but for metadata keys ending with the suffix `-bin`, the corresponding values must
                be of type `bytes`.

        Returns:
            google.cloud.aiplatform_v1beta1.types.PipelineJob:
                An instance of a machine learning
                PipelineJob.

        """
        # 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.
        flattened_params = [name]
        has_flattened_params = (
            len([param for param in flattened_params if param is not None]) > 0
        )
        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."
            )

        # - Use the request object if provided (there's no risk of modifying the input as
        #   there are no flattened fields), or create one.
        if not isinstance(request, pipeline_service.GetPipelineJobRequest):
            request = pipeline_service.GetPipelineJobRequest(request)

        # If we have keyword arguments corresponding to fields on the
        # request, apply these.
        if name is not None:
            request.name = name

        # Wrap the RPC method; this adds retry and timeout information,
        # and friendly error handling.
        rpc = self._client._transport._wrapped_methods[
            self._client._transport.get_pipeline_job
        ]

        # Certain fields should be provided within the metadata header;
        # add these here.
        metadata = tuple(metadata) + (
            gapic_v1.routing_header.to_grpc_metadata((("name", request.name),)),
        )

        # Validate the universe domain.
        self._client._validate_universe_domain()

        # Send the request.
        response = await rpc(
            request,
            retry=retry,
            timeout=timeout,
            metadata=metadata,
        )

        # Done; return the response.
        return response

    async def list_pipeline_jobs(
        self,
        request: Optional[Union[pipeline_service.ListPipelineJobsRequest, dict]] = None,
        *,
        parent: Optional[str] = None,
        retry: OptionalRetry = gapic_v1.method.DEFAULT,
        timeout: Union[float, object] = gapic_v1.method.DEFAULT,
        metadata: Sequence[Tuple[str, Union[str, bytes]]] = (),
    ) -> pagers.ListPipelineJobsAsyncPager:
        r"""Lists PipelineJobs in a Location.

        .. code-block:: python

            # 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_v1beta1

            async def sample_list_pipeline_jobs():
                # Create a client
                client = aiplatform_v1beta1.PipelineServiceAsyncClient()

                # Initialize request argument(s)
                request = aiplatform_v1beta1.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)

        Args:
            request (Optional[Union[google.cloud.aiplatform_v1beta1.types.ListPipelineJobsRequest, dict]]):
                The request object. Request message for
                [PipelineService.ListPipelineJobs][google.cloud.aiplatform.v1beta1.PipelineService.ListPipelineJobs].
            parent (:class:`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, Union[str, bytes]]]): Key/value pairs which should be
                sent along with the request as metadata. Normally, each value must be of type `str`,
                but for metadata keys ending with the suffix `-bin`, the corresponding values must
                be of type `bytes`.

        Returns:
            google.cloud.aiplatform_v1beta1.services.pipeline_service.pagers.ListPipelineJobsAsyncPager:
                Response message for
                   [PipelineService.ListPipelineJobs][google.cloud.aiplatform.v1beta1.PipelineService.ListPipelineJobs]

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

        """
        # 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.
        flattened_params = [parent]
        has_flattened_params = (
            len([param for param in flattened_params if param is not None]) > 0
        )
        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."
            )

        # - Use the request object if provided (there's no risk of modifying the input as
        #   there are no flattened fields), or create one.
        if not isinstance(request, pipeline_service.ListPipelineJobsRequest):
            request = pipeline_service.ListPipelineJobsRequest(request)

        # If we have keyword arguments corresponding to fields on the
        # request, apply these.
        if parent is not None:
            request.parent = parent

        # Wrap the RPC method; this adds retry and timeout information,
        # and friendly error handling.
        rpc = self._client._transport._wrapped_methods[
            self._client._transport.list_pipeline_jobs
        ]

        # 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),)),
        )

        # Validate the universe domain.
        self._client._validate_universe_domain()

        # Send the request.
        response = await rpc(
            request,
            retry=retry,
            timeout=timeout,
            metadata=metadata,
        )

        # This method is paged; wrap the response in a pager, which provides
        # an `__aiter__` convenience method.
        response = pagers.ListPipelineJobsAsyncPager(
            method=rpc,
            request=request,
            response=response,
            retry=retry,
            timeout=timeout,
            metadata=metadata,
        )

        # Done; return the response.
        return response

    async def delete_pipeline_job(
        self,
        request: Optional[
            Union[pipeline_service.DeletePipelineJobRequest, dict]
        ] = None,
        *,
        name: Optional[str] = None,
        retry: OptionalRetry = gapic_v1.method.DEFAULT,
        timeout: Union[float, object] = gapic_v1.method.DEFAULT,
        metadata: Sequence[Tuple[str, Union[str, bytes]]] = (),
    ) -> operation_async.AsyncOperation:
        r"""Deletes a PipelineJob.

        .. code-block:: python

            # 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_v1beta1

            async def sample_delete_pipeline_job():
                # Create a client
                client = aiplatform_v1beta1.PipelineServiceAsyncClient()

                # Initialize request argument(s)
                request = aiplatform_v1beta1.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)

        Args:
            request (Optional[Union[google.cloud.aiplatform_v1beta1.types.DeletePipelineJobRequest, dict]]):
                The request object. Request message for
                [PipelineService.DeletePipelineJob][google.cloud.aiplatform.v1beta1.PipelineService.DeletePipelineJob].
            name (:class:`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, Union[str, bytes]]]): Key/value pairs which should be
                sent along with the request as metadata. Normally, each value must be of type `str`,
                but for metadata keys ending with the suffix `-bin`, the corresponding values must
                be of type `bytes`.

        Returns:
            google.api_core.operation_async.AsyncOperation:
                An object representing a long-running operation.

                The result type for the operation will be :class:`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);

                      }

        """
        # 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.
        flattened_params = [name]
        has_flattened_params = (
            len([param for param in flattened_params if param is not None]) > 0
        )
        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."
            )

        # - Use the request object if provided (there's no risk of modifying the input as
        #   there are no flattened fields), or create one.
        if not isinstance(request, pipeline_service.DeletePipelineJobRequest):
            request = pipeline_service.DeletePipelineJobRequest(request)

        # If we have keyword arguments corresponding to fields on the
        # request, apply these.
        if name is not None:
            request.name = name

        # Wrap the RPC method; this adds retry and timeout information,
        # and friendly error handling.
        rpc = self._client._transport._wrapped_methods[
            self._client._transport.delete_pipeline_job
        ]

        # Certain fields should be provided within the metadata header;
        # add these here.
        metadata = tuple(metadata) + (
            gapic_v1.routing_header.to_grpc_metadata((("name", request.name),)),
        )

        # Validate the universe domain.
        self._client._validate_universe_domain()

        # 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,
            empty_pb2.Empty,
            metadata_type=gca_operation.DeleteOperationMetadata,
        )

        # Done; return the response.
        return response

    async def batch_delete_pipeline_jobs(
        self,
        request: Optional[
            Union[pipeline_service.BatchDeletePipelineJobsRequest, dict]
        ] = None,
        *,
        parent: Optional[str] = None,
        names: Optional[MutableSequence[str]] = None,
        retry: OptionalRetry = gapic_v1.method.DEFAULT,
        timeout: Union[float, object] = gapic_v1.method.DEFAULT,
        metadata: Sequence[Tuple[str, Union[str, bytes]]] = (),
    ) -> operation_async.AsyncOperation:
        r"""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.

        .. code-block:: python

            # 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_v1beta1

            async def sample_batch_delete_pipeline_jobs():
                # Create a client
                client = aiplatform_v1beta1.PipelineServiceAsyncClient()

                # Initialize request argument(s)
                request = aiplatform_v1beta1.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)

        Args:
            request (Optional[Union[google.cloud.aiplatform_v1beta1.types.BatchDeletePipelineJobsRequest, dict]]):
                The request object. Request message for
                [PipelineService.BatchDeletePipelineJobs][google.cloud.aiplatform.v1beta1.PipelineService.BatchDeletePipelineJobs].
            parent (:class:`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 (:class:`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, Union[str, bytes]]]): Key/value pairs which should be
                sent along with the request as metadata. Normally, each value must be of type `str`,
                but for metadata keys ending with the suffix `-bin`, the corresponding values must
                be of type `bytes`.

        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_v1beta1.types.BatchDeletePipelineJobsResponse` Response message for
                   [PipelineService.BatchDeletePipelineJobs][google.cloud.aiplatform.v1beta1.PipelineService.BatchDeletePipelineJobs].

        """
        # 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.
        flattened_params = [parent, names]
        has_flattened_params = (
            len([param for param in flattened_params if param is not None]) > 0
        )
        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."
            )

        # - Use the request object if provided (there's no risk of modifying the input as
        #   there are no flattened fields), or create one.
        if not isinstance(request, pipeline_service.BatchDeletePipelineJobsRequest):
            request = pipeline_service.BatchDeletePipelineJobsRequest(request)

        # If we have keyword arguments corresponding to fields on the
        # request, apply these.
        if parent is not None:
            request.parent = parent
        if names:
            request.names.extend(names)

        # Wrap the RPC method; this adds retry and timeout information,
        # and friendly error handling.
        rpc = self._client._transport._wrapped_methods[
            self._client._transport.batch_delete_pipeline_jobs
        ]

        # 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),)),
        )

        # Validate the universe domain.
        self._client._validate_universe_domain()

        # 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,
            pipeline_service.BatchDeletePipelineJobsResponse,
            metadata_type=gca_operation.DeleteOperationMetadata,
        )

        # Done; return the response.
        return response

    async def cancel_pipeline_job(
        self,
        request: Optional[
            Union[pipeline_service.CancelPipelineJobRequest, dict]
        ] = None,
        *,
        name: Optional[str] = None,
        retry: OptionalRetry = gapic_v1.method.DEFAULT,
        timeout: Union[float, object] = gapic_v1.method.DEFAULT,
        metadata: Sequence[Tuple[str, Union[str, bytes]]] = (),
    ) -> None:
        r"""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.v1beta1.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.v1beta1.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.v1beta1.PipelineJob.state]
        is set to ``CANCELLED``.

        .. code-block:: python

            # 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_v1beta1

            async def sample_cancel_pipeline_job():
                # Create a client
                client = aiplatform_v1beta1.PipelineServiceAsyncClient()

                # Initialize request argument(s)
                request = aiplatform_v1beta1.CancelPipelineJobRequest(
                    name="name_value",
                )

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

        Args:
            request (Optional[Union[google.cloud.aiplatform_v1beta1.types.CancelPipelineJobRequest, dict]]):
                The request object. Request message for
                [PipelineService.CancelPipelineJob][google.cloud.aiplatform.v1beta1.PipelineService.CancelPipelineJob].
            name (:class:`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, Union[str, bytes]]]): Key/value pairs which should be
                sent along with the request as metadata. Normally, each value must be of type `str`,
                but for metadata keys ending with the suffix `-bin`, the corresponding values must
                be of type `bytes`.
        """
        # 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.
        flattened_params = [name]
        has_flattened_params = (
            len([param for param in flattened_params if param is not None]) > 0
        )
        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."
            )

        # - Use the request object if provided (there's no risk of modifying the input as
        #   there are no flattened fields), or create one.
        if not isinstance(request, pipeline_service.CancelPipelineJobRequest):
            request = pipeline_service.CancelPipelineJobRequest(request)

        # If we have keyword arguments corresponding to fields on the
        # request, apply these.
        if name is not None:
            request.name = name

        # Wrap the RPC method; this adds retry and timeout information,
        # and friendly error handling.
        rpc = self._client._transport._wrapped_methods[
            self._client._transport.cancel_pipeline_job
        ]

        # Certain fields should be provided within the metadata header;
        # add these here.
        metadata = tuple(metadata) + (
            gapic_v1.routing_header.to_grpc_metadata((("name", request.name),)),
        )

        # Validate the universe domain.
        self._client._validate_universe_domain()

        # Send the request.
        await rpc(
            request,
            retry=retry,
            timeout=timeout,
            metadata=metadata,
        )

    async def batch_cancel_pipeline_jobs(
        self,
        request: Optional[
            Union[pipeline_service.BatchCancelPipelineJobsRequest, dict]
        ] = None,
        *,
        parent: Optional[str] = None,
        names: Optional[MutableSequence[str]] = None,
        retry: OptionalRetry = gapic_v1.method.DEFAULT,
        timeout: Union[float, object] = gapic_v1.method.DEFAULT,
        metadata: Sequence[Tuple[str, Union[str, bytes]]] = (),
    ) -> operation_async.AsyncOperation:
        r"""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.

        .. code-block:: python

            # 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_v1beta1

            async def sample_batch_cancel_pipeline_jobs():
                # Create a client
                client = aiplatform_v1beta1.PipelineServiceAsyncClient()

                # Initialize request argument(s)
                request = aiplatform_v1beta1.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 = (await operation).result()

                # Handle the response
                print(response)

        Args:
            request (Optional[Union[google.cloud.aiplatform_v1beta1.types.BatchCancelPipelineJobsRequest, dict]]):
                The request object. Request message for
                [PipelineService.BatchCancelPipelineJobs][google.cloud.aiplatform.v1beta1.PipelineService.BatchCancelPipelineJobs].
            parent (:class:`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 (:class:`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_async.AsyncRetry): Designation of what errors, if any,
                should be retried.
            timeout (float): The timeout for this request.
            metadata (Sequence[Tuple[str, Union[str, bytes]]]): Key/value pairs which should be
                sent along with the request as metadata. Normally, each value must be of type `str`,
                but for metadata keys ending with the suffix `-bin`, the corresponding values must
                be of type `bytes`.

        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_v1beta1.types.BatchCancelPipelineJobsResponse` Response message for
                   [PipelineService.BatchCancelPipelineJobs][google.cloud.aiplatform.v1beta1.PipelineService.BatchCancelPipelineJobs].

        """
        # 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.
        flattened_params = [parent, names]
        has_flattened_params = (
            len([param for param in flattened_params if param is not None]) > 0
        )
        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."
            )

        # - Use the request object if provided (there's no risk of modifying the input as
        #   there are no flattened fields), or create one.
        if not isinstance(request, pipeline_service.BatchCancelPipelineJobsRequest):
            request = pipeline_service.BatchCancelPipelineJobsRequest(request)

        # If we have keyword arguments corresponding to fields on the
        # request, apply these.
        if parent is not None:
            request.parent = parent
        if names:
            request.names.extend(names)

        # Wrap the RPC method; this adds retry and timeout information,
        # and friendly error handling.
        rpc = self._client._transport._wrapped_methods[
            self._client._transport.batch_cancel_pipeline_jobs
        ]

        # 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),)),
        )

        # Validate the universe domain.
        self._client._validate_universe_domain()

        # 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,
            pipeline_service.BatchCancelPipelineJobsResponse,
            metadata_type=pipeline_service.BatchCancelPipelineJobsOperationMetadata,
        )

        # Done; return the response.
        return response

    async def list_operations(
        self,
        request: Optional[operations_pb2.ListOperationsRequest] = None,
        *,
        retry: OptionalRetry = gapic_v1.method.DEFAULT,
        timeout: Union[float, object] = gapic_v1.method.DEFAULT,
        metadata: Sequence[Tuple[str, Union[str, bytes]]] = (),
    ) -> operations_pb2.ListOperationsResponse:
        r"""Lists operations that match the specified filter in the request.

        Args:
            request (:class:`~.operations_pb2.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, Union[str, bytes]]]): Key/value pairs which should be
                sent along with the request as metadata. Normally, each value must be of type `str`,
                but for metadata keys ending with the suffix `-bin`, the corresponding values must
                be of type `bytes`.
        Returns:
            ~.operations_pb2.ListOperationsResponse:
                Response message for ``ListOperations`` method.
        """
        # Create or coerce a protobuf request object.
        # The request isn't a proto-plus wrapped type,
        # so it must be constructed via keyword expansion.
        if isinstance(request, dict):
            request = operations_pb2.ListOperationsRequest(**request)

        # Wrap the RPC method; this adds retry and timeout information,
        # and friendly error handling.
        rpc = self.transport._wrapped_methods[self._client._transport.list_operations]

        # Certain fields should be provided within the metadata header;
        # add these here.
        metadata = tuple(metadata) + (
            gapic_v1.routing_header.to_grpc_metadata((("name", request.name),)),
        )

        # Validate the universe domain.
        self._client._validate_universe_domain()

        # Send the request.
        response = await rpc(
            request,
            retry=retry,
            timeout=timeout,
            metadata=metadata,
        )

        # Done; return the response.
        return response

    async def get_operation(
        self,
        request: Optional[operations_pb2.GetOperationRequest] = None,
        *,
        retry: OptionalRetry = gapic_v1.method.DEFAULT,
        timeout: Union[float, object] = gapic_v1.method.DEFAULT,
        metadata: Sequence[Tuple[str, Union[str, bytes]]] = (),
    ) -> operations_pb2.Operation:
        r"""Gets the latest state of a long-running operation.

        Args:
            request (:class:`~.operations_pb2.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, Union[str, bytes]]]): Key/value pairs which should be
                sent along with the request as metadata. Normally, each value must be of type `str`,
                but for metadata keys ending with the suffix `-bin`, the corresponding values must
                be of type `bytes`.
        Returns:
            ~.operations_pb2.Operation:
                An ``Operation`` object.
        """
        # Create or coerce a protobuf request object.
        # The request isn't a proto-plus wrapped type,
        # so it must be constructed via keyword expansion.
        if isinstance(request, dict):
            request = operations_pb2.GetOperationRequest(**request)

        # Wrap the RPC method; this adds retry and timeout information,
        # and friendly error handling.
        rpc = self.transport._wrapped_methods[self._client._transport.get_operation]

        # Certain fields should be provided within the metadata header;
        # add these here.
        metadata = tuple(metadata) + (
            gapic_v1.routing_header.to_grpc_metadata((("name", request.name),)),
        )

        # Validate the universe domain.
        self._client._validate_universe_domain()

        # Send the request.
        response = await rpc(
            request,
            retry=retry,
            timeout=timeout,
            metadata=metadata,
        )

        # Done; return the response.
        return response

    async def delete_operation(
        self,
        request: Optional[operations_pb2.DeleteOperationRequest] = None,
        *,
        retry: OptionalRetry = gapic_v1.method.DEFAULT,
        timeout: Union[float, object] = gapic_v1.method.DEFAULT,
        metadata: Sequence[Tuple[str, Union[str, bytes]]] = (),
    ) -> None:
        r"""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`.

        Args:
            request (:class:`~.operations_pb2.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, Union[str, bytes]]]): Key/value pairs which should be
                sent along with the request as metadata. Normally, each value must be of type `str`,
                but for metadata keys ending with the suffix `-bin`, the corresponding values must
                be of type `bytes`.
        Returns:
            None
        """
        # Create or coerce a protobuf request object.
        # The request isn't a proto-plus wrapped type,
        # so it must be constructed via keyword expansion.
        if isinstance(request, dict):
            request = operations_pb2.DeleteOperationRequest(**request)

        # Wrap the RPC method; this adds retry and timeout information,
        # and friendly error handling.
        rpc = self.transport._wrapped_methods[self._client._transport.delete_operation]

        # Certain fields should be provided within the metadata header;
        # add these here.
        metadata = tuple(metadata) + (
            gapic_v1.routing_header.to_grpc_metadata((("name", request.name),)),
        )

        # Validate the universe domain.
        self._client._validate_universe_domain()

        # Send the request.
        await rpc(
            request,
            retry=retry,
            timeout=timeout,
            metadata=metadata,
        )

    async def cancel_operation(
        self,
        request: Optional[operations_pb2.CancelOperationRequest] = None,
        *,
        retry: OptionalRetry = gapic_v1.method.DEFAULT,
        timeout: Union[float, object] = gapic_v1.method.DEFAULT,
        metadata: Sequence[Tuple[str, Union[str, bytes]]] = (),
    ) -> None:
        r"""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`.

        Args:
            request (:class:`~.operations_pb2.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, Union[str, bytes]]]): Key/value pairs which should be
                sent along with the request as metadata. Normally, each value must be of type `str`,
                but for metadata keys ending with the suffix `-bin`, the corresponding values must
                be of type `bytes`.
        Returns:
            None
        """
        # Create or coerce a protobuf request object.
        # The request isn't a proto-plus wrapped type,
        # so it must be constructed via keyword expansion.
        if isinstance(request, dict):
            request = operations_pb2.CancelOperationRequest(**request)

        # Wrap the RPC method; this adds retry and timeout information,
        # and friendly error handling.
        rpc = self.transport._wrapped_methods[self._client._transport.cancel_operation]

        # Certain fields should be provided within the metadata header;
        # add these here.
        metadata = tuple(metadata) + (
            gapic_v1.routing_header.to_grpc_metadata((("name", request.name),)),
        )

        # Validate the universe domain.
        self._client._validate_universe_domain()

        # Send the request.
        await rpc(
            request,
            retry=retry,
            timeout=timeout,
            metadata=metadata,
        )

    async def wait_operation(
        self,
        request: Optional[operations_pb2.WaitOperationRequest] = None,
        *,
        retry: OptionalRetry = gapic_v1.method.DEFAULT,
        timeout: Union[float, object] = gapic_v1.method.DEFAULT,
        metadata: Sequence[Tuple[str, Union[str, bytes]]] = (),
    ) -> operations_pb2.Operation:
        r"""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`.

        Args:
            request (:class:`~.operations_pb2.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, Union[str, bytes]]]): Key/value pairs which should be
                sent along with the request as metadata. Normally, each value must be of type `str`,
                but for metadata keys ending with the suffix `-bin`, the corresponding values must
                be of type `bytes`.
        Returns:
            ~.operations_pb2.Operation:
                An ``Operation`` object.
        """
        # Create or coerce a protobuf request object.
        # The request isn't a proto-plus wrapped type,
        # so it must be constructed via keyword expansion.
        if isinstance(request, dict):
            request = operations_pb2.WaitOperationRequest(**request)

        # Wrap the RPC method; this adds retry and timeout information,
        # and friendly error handling.
        rpc = self.transport._wrapped_methods[self._client._transport.wait_operation]

        # Certain fields should be provided within the metadata header;
        # add these here.
        metadata = tuple(metadata) + (
            gapic_v1.routing_header.to_grpc_metadata((("name", request.name),)),
        )

        # Validate the universe domain.
        self._client._validate_universe_domain()

        # Send the request.
        response = await rpc(
            request,
            retry=retry,
            timeout=timeout,
            metadata=metadata,
        )

        # Done; return the response.
        return response

    async def set_iam_policy(
        self,
        request: Optional[iam_policy_pb2.SetIamPolicyRequest] = None,
        *,
        retry: OptionalRetry = gapic_v1.method.DEFAULT,
        timeout: Union[float, object] = gapic_v1.method.DEFAULT,
        metadata: Sequence[Tuple[str, Union[str, bytes]]] = (),
    ) -> policy_pb2.Policy:
        r"""Sets the IAM access control policy on the specified function.

        Replaces any existing policy.

        Args:
            request (:class:`~.iam_policy_pb2.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, Union[str, bytes]]]): Key/value pairs which should be
                sent along with the request as metadata. Normally, each value must be of type `str`,
                but for metadata keys ending with the suffix `-bin`, the corresponding values must
                be of type `bytes`.
        Returns:
            ~.policy_pb2.Policy:
                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 <https://cloud.google.com/iam/docs>`__.
        """
        # Create or coerce a protobuf request object.

        # The request isn't a proto-plus wrapped type,
        # so it must be constructed via keyword expansion.
        if isinstance(request, dict):
            request = iam_policy_pb2.SetIamPolicyRequest(**request)

        # Wrap the RPC method; this adds retry and timeout information,
        # and friendly error handling.
        rpc = self.transport._wrapped_methods[self._client._transport.set_iam_policy]

        # Certain fields should be provided within the metadata header;
        # add these here.
        metadata = tuple(metadata) + (
            gapic_v1.routing_header.to_grpc_metadata((("resource", request.resource),)),
        )

        # Validate the universe domain.
        self._client._validate_universe_domain()

        # Send the request.
        response = await rpc(
            request,
            retry=retry,
            timeout=timeout,
            metadata=metadata,
        )

        # Done; return the response.
        return response

    async def get_iam_policy(
        self,
        request: Optional[iam_policy_pb2.GetIamPolicyRequest] = None,
        *,
        retry: OptionalRetry = gapic_v1.method.DEFAULT,
        timeout: Union[float, object] = gapic_v1.method.DEFAULT,
        metadata: Sequence[Tuple[str, Union[str, bytes]]] = (),
    ) -> policy_pb2.Policy:
        r"""Gets the IAM access control policy for a function.

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

        Args:
            request (:class:`~.iam_policy_pb2.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, Union[str, bytes]]]): Key/value pairs which should be
                sent along with the request as metadata. Normally, each value must be of type `str`,
                but for metadata keys ending with the suffix `-bin`, the corresponding values must
                be of type `bytes`.
        Returns:
            ~.policy_pb2.Policy:
                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 <https://cloud.google.com/iam/docs>`__.
        """
        # Create or coerce a protobuf request object.

        # The request isn't a proto-plus wrapped type,
        # so it must be constructed via keyword expansion.
        if isinstance(request, dict):
            request = iam_policy_pb2.GetIamPolicyRequest(**request)

        # Wrap the RPC method; this adds retry and timeout information,
        # and friendly error handling.
        rpc = self.transport._wrapped_methods[self._client._transport.get_iam_policy]

        # Certain fields should be provided within the metadata header;
        # add these here.
        metadata = tuple(metadata) + (
            gapic_v1.routing_header.to_grpc_metadata((("resource", request.resource),)),
        )

        # Validate the universe domain.
        self._client._validate_universe_domain()

        # Send the request.
        response = await rpc(
            request,
            retry=retry,
            timeout=timeout,
            metadata=metadata,
        )

        # Done; return the response.
        return response

    async def test_iam_permissions(
        self,
        request: Optional[iam_policy_pb2.TestIamPermissionsRequest] = None,
        *,
        retry: OptionalRetry = gapic_v1.method.DEFAULT,
        timeout: Union[float, object] = gapic_v1.method.DEFAULT,
        metadata: Sequence[Tuple[str, Union[str, bytes]]] = (),
    ) -> iam_policy_pb2.TestIamPermissionsResponse:
        r"""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.

        Args:
            request (:class:`~.iam_policy_pb2.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, Union[str, bytes]]]): Key/value pairs which should be
                sent along with the request as metadata. Normally, each value must be of type `str`,
                but for metadata keys ending with the suffix `-bin`, the corresponding values must
                be of type `bytes`.
        Returns:
            ~.iam_policy_pb2.TestIamPermissionsResponse:
                Response message for ``TestIamPermissions`` method.
        """
        # Create or coerce a protobuf request object.

        # The request isn't a proto-plus wrapped type,
        # so it must be constructed via keyword expansion.
        if isinstance(request, dict):
            request = iam_policy_pb2.TestIamPermissionsRequest(**request)

        # Wrap the RPC method; this adds retry and timeout information,
        # and friendly error handling.
        rpc = self.transport._wrapped_methods[
            self._client._transport.test_iam_permissions
        ]

        # Certain fields should be provided within the metadata header;
        # add these here.
        metadata = tuple(metadata) + (
            gapic_v1.routing_header.to_grpc_metadata((("resource", request.resource),)),
        )

        # Validate the universe domain.
        self._client._validate_universe_domain()

        # Send the request.
        response = await rpc(
            request,
            retry=retry,
            timeout=timeout,
            metadata=metadata,
        )

        # Done; return the response.
        return response

    async def get_location(
        self,
        request: Optional[locations_pb2.GetLocationRequest] = None,
        *,
        retry: OptionalRetry = gapic_v1.method.DEFAULT,
        timeout: Union[float, object] = gapic_v1.method.DEFAULT,
        metadata: Sequence[Tuple[str, Union[str, bytes]]] = (),
    ) -> locations_pb2.Location:
        r"""Gets information about a location.

        Args:
            request (:class:`~.location_pb2.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, Union[str, bytes]]]): Key/value pairs which should be
                sent along with the request as metadata. Normally, each value must be of type `str`,
                but for metadata keys ending with the suffix `-bin`, the corresponding values must
                be of type `bytes`.
        Returns:
            ~.location_pb2.Location:
                Location object.
        """
        # Create or coerce a protobuf request object.
        # The request isn't a proto-plus wrapped type,
        # so it must be constructed via keyword expansion.
        if isinstance(request, dict):
            request = locations_pb2.GetLocationRequest(**request)

        # Wrap the RPC method; this adds retry and timeout information,
        # and friendly error handling.
        rpc = self.transport._wrapped_methods[self._client._transport.get_location]

        # Certain fields should be provided within the metadata header;
        # add these here.
        metadata = tuple(metadata) + (
            gapic_v1.routing_header.to_grpc_metadata((("name", request.name),)),
        )

        # Validate the universe domain.
        self._client._validate_universe_domain()

        # Send the request.
        response = await rpc(
            request,
            retry=retry,
            timeout=timeout,
            metadata=metadata,
        )

        # Done; return the response.
        return response

    async def list_locations(
        self,
        request: Optional[locations_pb2.ListLocationsRequest] = None,
        *,
        retry: OptionalRetry = gapic_v1.method.DEFAULT,
        timeout: Union[float, object] = gapic_v1.method.DEFAULT,
        metadata: Sequence[Tuple[str, Union[str, bytes]]] = (),
    ) -> locations_pb2.ListLocationsResponse:
        r"""Lists information about the supported locations for this service.

        Args:
            request (:class:`~.location_pb2.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, Union[str, bytes]]]): Key/value pairs which should be
                sent along with the request as metadata. Normally, each value must be of type `str`,
                but for metadata keys ending with the suffix `-bin`, the corresponding values must
                be of type `bytes`.
        Returns:
            ~.location_pb2.ListLocationsResponse:
                Response message for ``ListLocations`` method.
        """
        # Create or coerce a protobuf request object.
        # The request isn't a proto-plus wrapped type,
        # so it must be constructed via keyword expansion.
        if isinstance(request, dict):
            request = locations_pb2.ListLocationsRequest(**request)

        # Wrap the RPC method; this adds retry and timeout information,
        # and friendly error handling.
        rpc = self.transport._wrapped_methods[self._client._transport.list_locations]

        # Certain fields should be provided within the metadata header;
        # add these here.
        metadata = tuple(metadata) + (
            gapic_v1.routing_header.to_grpc_metadata((("name", request.name),)),
        )

        # Validate the universe domain.
        self._client._validate_universe_domain()

        # Send the request.
        response = await rpc(
            request,
            retry=retry,
            timeout=timeout,
            metadata=metadata,
        )

        # Done; return the response.
        return response

    async def __aenter__(self) -> "PipelineServiceAsyncClient":
        return self

    async def __aexit__(self, exc_type, exc, tb):
        await self.transport.close()


DEFAULT_CLIENT_INFO = gapic_v1.client_info.ClientInfo(
    gapic_version=package_version.__version__
)

if hasattr(DEFAULT_CLIENT_INFO, "protobuf_runtime_version"):  # pragma: NO COVER
    DEFAULT_CLIENT_INFO.protobuf_runtime_version = google.protobuf.__version__


__all__ = ("PipelineServiceAsyncClient",)
