# -*- 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
import json  # type: ignore

from google.auth.transport.requests import AuthorizedSession  # type: ignore
from google.auth import credentials as ga_credentials  # type: ignore
from google.api_core import exceptions as core_exceptions
from google.api_core import retry as retries
from google.api_core import rest_helpers
from google.api_core import rest_streaming
from google.api_core import gapic_v1
import google.protobuf

from google.protobuf import json_format
from google.api_core import operations_v1
from google.iam.v1 import iam_policy_pb2  # type: ignore
from google.iam.v1 import policy_pb2  # type: ignore
from google.cloud.location import locations_pb2  # type: ignore

from requests import __version__ as requests_version
import dataclasses
from typing import Any, Callable, Dict, List, Optional, Sequence, Tuple, Union
import warnings


from google.cloud.aiplatform_v1.types import pipeline_job
from google.cloud.aiplatform_v1.types import pipeline_job as gca_pipeline_job
from google.cloud.aiplatform_v1.types import pipeline_service
from google.cloud.aiplatform_v1.types import training_pipeline
from google.cloud.aiplatform_v1.types import training_pipeline as gca_training_pipeline
from google.protobuf import empty_pb2  # type: ignore
from google.longrunning import operations_pb2  # type: ignore


from .rest_base import _BasePipelineServiceRestTransport
from .base import DEFAULT_CLIENT_INFO as BASE_DEFAULT_CLIENT_INFO

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

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 = logging.getLogger(__name__)

DEFAULT_CLIENT_INFO = gapic_v1.client_info.ClientInfo(
    gapic_version=BASE_DEFAULT_CLIENT_INFO.gapic_version,
    grpc_version=None,
    rest_version=f"requests@{requests_version}",
)

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


class PipelineServiceRestInterceptor:
    """Interceptor for PipelineService.

    Interceptors are used to manipulate requests, request metadata, and responses
    in arbitrary ways.
    Example use cases include:
    * Logging
    * Verifying requests according to service or custom semantics
    * Stripping extraneous information from responses

    These use cases and more can be enabled by injecting an
    instance of a custom subclass when constructing the PipelineServiceRestTransport.

    .. code-block:: python
        class MyCustomPipelineServiceInterceptor(PipelineServiceRestInterceptor):
            def pre_batch_cancel_pipeline_jobs(self, request, metadata):
                logging.log(f"Received request: {request}")
                return request, metadata

            def post_batch_cancel_pipeline_jobs(self, response):
                logging.log(f"Received response: {response}")
                return response

            def pre_batch_delete_pipeline_jobs(self, request, metadata):
                logging.log(f"Received request: {request}")
                return request, metadata

            def post_batch_delete_pipeline_jobs(self, response):
                logging.log(f"Received response: {response}")
                return response

            def pre_cancel_pipeline_job(self, request, metadata):
                logging.log(f"Received request: {request}")
                return request, metadata

            def pre_cancel_training_pipeline(self, request, metadata):
                logging.log(f"Received request: {request}")
                return request, metadata

            def pre_create_pipeline_job(self, request, metadata):
                logging.log(f"Received request: {request}")
                return request, metadata

            def post_create_pipeline_job(self, response):
                logging.log(f"Received response: {response}")
                return response

            def pre_create_training_pipeline(self, request, metadata):
                logging.log(f"Received request: {request}")
                return request, metadata

            def post_create_training_pipeline(self, response):
                logging.log(f"Received response: {response}")
                return response

            def pre_delete_pipeline_job(self, request, metadata):
                logging.log(f"Received request: {request}")
                return request, metadata

            def post_delete_pipeline_job(self, response):
                logging.log(f"Received response: {response}")
                return response

            def pre_delete_training_pipeline(self, request, metadata):
                logging.log(f"Received request: {request}")
                return request, metadata

            def post_delete_training_pipeline(self, response):
                logging.log(f"Received response: {response}")
                return response

            def pre_get_pipeline_job(self, request, metadata):
                logging.log(f"Received request: {request}")
                return request, metadata

            def post_get_pipeline_job(self, response):
                logging.log(f"Received response: {response}")
                return response

            def pre_get_training_pipeline(self, request, metadata):
                logging.log(f"Received request: {request}")
                return request, metadata

            def post_get_training_pipeline(self, response):
                logging.log(f"Received response: {response}")
                return response

            def pre_list_pipeline_jobs(self, request, metadata):
                logging.log(f"Received request: {request}")
                return request, metadata

            def post_list_pipeline_jobs(self, response):
                logging.log(f"Received response: {response}")
                return response

            def pre_list_training_pipelines(self, request, metadata):
                logging.log(f"Received request: {request}")
                return request, metadata

            def post_list_training_pipelines(self, response):
                logging.log(f"Received response: {response}")
                return response

        transport = PipelineServiceRestTransport(interceptor=MyCustomPipelineServiceInterceptor())
        client = PipelineServiceClient(transport=transport)


    """

    def pre_batch_cancel_pipeline_jobs(
        self,
        request: pipeline_service.BatchCancelPipelineJobsRequest,
        metadata: Sequence[Tuple[str, Union[str, bytes]]],
    ) -> Tuple[
        pipeline_service.BatchCancelPipelineJobsRequest,
        Sequence[Tuple[str, Union[str, bytes]]],
    ]:
        """Pre-rpc interceptor for batch_cancel_pipeline_jobs

        Override in a subclass to manipulate the request or metadata
        before they are sent to the PipelineService server.
        """
        return request, metadata

    def post_batch_cancel_pipeline_jobs(
        self, response: operations_pb2.Operation
    ) -> operations_pb2.Operation:
        """Post-rpc interceptor for batch_cancel_pipeline_jobs

        DEPRECATED. Please use the `post_batch_cancel_pipeline_jobs_with_metadata`
        interceptor instead.

        Override in a subclass to read or manipulate the response
        after it is returned by the PipelineService server but before
        it is returned to user code. This `post_batch_cancel_pipeline_jobs` interceptor runs
        before the `post_batch_cancel_pipeline_jobs_with_metadata` interceptor.
        """
        return response

    def post_batch_cancel_pipeline_jobs_with_metadata(
        self,
        response: operations_pb2.Operation,
        metadata: Sequence[Tuple[str, Union[str, bytes]]],
    ) -> Tuple[operations_pb2.Operation, Sequence[Tuple[str, Union[str, bytes]]]]:
        """Post-rpc interceptor for batch_cancel_pipeline_jobs

        Override in a subclass to read or manipulate the response or metadata after it
        is returned by the PipelineService server but before it is returned to user code.

        We recommend only using this `post_batch_cancel_pipeline_jobs_with_metadata`
        interceptor in new development instead of the `post_batch_cancel_pipeline_jobs` interceptor.
        When both interceptors are used, this `post_batch_cancel_pipeline_jobs_with_metadata` interceptor runs after the
        `post_batch_cancel_pipeline_jobs` interceptor. The (possibly modified) response returned by
        `post_batch_cancel_pipeline_jobs` will be passed to
        `post_batch_cancel_pipeline_jobs_with_metadata`.
        """
        return response, metadata

    def pre_batch_delete_pipeline_jobs(
        self,
        request: pipeline_service.BatchDeletePipelineJobsRequest,
        metadata: Sequence[Tuple[str, Union[str, bytes]]],
    ) -> Tuple[
        pipeline_service.BatchDeletePipelineJobsRequest,
        Sequence[Tuple[str, Union[str, bytes]]],
    ]:
        """Pre-rpc interceptor for batch_delete_pipeline_jobs

        Override in a subclass to manipulate the request or metadata
        before they are sent to the PipelineService server.
        """
        return request, metadata

    def post_batch_delete_pipeline_jobs(
        self, response: operations_pb2.Operation
    ) -> operations_pb2.Operation:
        """Post-rpc interceptor for batch_delete_pipeline_jobs

        DEPRECATED. Please use the `post_batch_delete_pipeline_jobs_with_metadata`
        interceptor instead.

        Override in a subclass to read or manipulate the response
        after it is returned by the PipelineService server but before
        it is returned to user code. This `post_batch_delete_pipeline_jobs` interceptor runs
        before the `post_batch_delete_pipeline_jobs_with_metadata` interceptor.
        """
        return response

    def post_batch_delete_pipeline_jobs_with_metadata(
        self,
        response: operations_pb2.Operation,
        metadata: Sequence[Tuple[str, Union[str, bytes]]],
    ) -> Tuple[operations_pb2.Operation, Sequence[Tuple[str, Union[str, bytes]]]]:
        """Post-rpc interceptor for batch_delete_pipeline_jobs

        Override in a subclass to read or manipulate the response or metadata after it
        is returned by the PipelineService server but before it is returned to user code.

        We recommend only using this `post_batch_delete_pipeline_jobs_with_metadata`
        interceptor in new development instead of the `post_batch_delete_pipeline_jobs` interceptor.
        When both interceptors are used, this `post_batch_delete_pipeline_jobs_with_metadata` interceptor runs after the
        `post_batch_delete_pipeline_jobs` interceptor. The (possibly modified) response returned by
        `post_batch_delete_pipeline_jobs` will be passed to
        `post_batch_delete_pipeline_jobs_with_metadata`.
        """
        return response, metadata

    def pre_cancel_pipeline_job(
        self,
        request: pipeline_service.CancelPipelineJobRequest,
        metadata: Sequence[Tuple[str, Union[str, bytes]]],
    ) -> Tuple[
        pipeline_service.CancelPipelineJobRequest,
        Sequence[Tuple[str, Union[str, bytes]]],
    ]:
        """Pre-rpc interceptor for cancel_pipeline_job

        Override in a subclass to manipulate the request or metadata
        before they are sent to the PipelineService server.
        """
        return request, metadata

    def pre_cancel_training_pipeline(
        self,
        request: pipeline_service.CancelTrainingPipelineRequest,
        metadata: Sequence[Tuple[str, Union[str, bytes]]],
    ) -> Tuple[
        pipeline_service.CancelTrainingPipelineRequest,
        Sequence[Tuple[str, Union[str, bytes]]],
    ]:
        """Pre-rpc interceptor for cancel_training_pipeline

        Override in a subclass to manipulate the request or metadata
        before they are sent to the PipelineService server.
        """
        return request, metadata

    def pre_create_pipeline_job(
        self,
        request: pipeline_service.CreatePipelineJobRequest,
        metadata: Sequence[Tuple[str, Union[str, bytes]]],
    ) -> Tuple[
        pipeline_service.CreatePipelineJobRequest,
        Sequence[Tuple[str, Union[str, bytes]]],
    ]:
        """Pre-rpc interceptor for create_pipeline_job

        Override in a subclass to manipulate the request or metadata
        before they are sent to the PipelineService server.
        """
        return request, metadata

    def post_create_pipeline_job(
        self, response: gca_pipeline_job.PipelineJob
    ) -> gca_pipeline_job.PipelineJob:
        """Post-rpc interceptor for create_pipeline_job

        DEPRECATED. Please use the `post_create_pipeline_job_with_metadata`
        interceptor instead.

        Override in a subclass to read or manipulate the response
        after it is returned by the PipelineService server but before
        it is returned to user code. This `post_create_pipeline_job` interceptor runs
        before the `post_create_pipeline_job_with_metadata` interceptor.
        """
        return response

    def post_create_pipeline_job_with_metadata(
        self,
        response: gca_pipeline_job.PipelineJob,
        metadata: Sequence[Tuple[str, Union[str, bytes]]],
    ) -> Tuple[gca_pipeline_job.PipelineJob, Sequence[Tuple[str, Union[str, bytes]]]]:
        """Post-rpc interceptor for create_pipeline_job

        Override in a subclass to read or manipulate the response or metadata after it
        is returned by the PipelineService server but before it is returned to user code.

        We recommend only using this `post_create_pipeline_job_with_metadata`
        interceptor in new development instead of the `post_create_pipeline_job` interceptor.
        When both interceptors are used, this `post_create_pipeline_job_with_metadata` interceptor runs after the
        `post_create_pipeline_job` interceptor. The (possibly modified) response returned by
        `post_create_pipeline_job` will be passed to
        `post_create_pipeline_job_with_metadata`.
        """
        return response, metadata

    def pre_create_training_pipeline(
        self,
        request: pipeline_service.CreateTrainingPipelineRequest,
        metadata: Sequence[Tuple[str, Union[str, bytes]]],
    ) -> Tuple[
        pipeline_service.CreateTrainingPipelineRequest,
        Sequence[Tuple[str, Union[str, bytes]]],
    ]:
        """Pre-rpc interceptor for create_training_pipeline

        Override in a subclass to manipulate the request or metadata
        before they are sent to the PipelineService server.
        """
        return request, metadata

    def post_create_training_pipeline(
        self, response: gca_training_pipeline.TrainingPipeline
    ) -> gca_training_pipeline.TrainingPipeline:
        """Post-rpc interceptor for create_training_pipeline

        DEPRECATED. Please use the `post_create_training_pipeline_with_metadata`
        interceptor instead.

        Override in a subclass to read or manipulate the response
        after it is returned by the PipelineService server but before
        it is returned to user code. This `post_create_training_pipeline` interceptor runs
        before the `post_create_training_pipeline_with_metadata` interceptor.
        """
        return response

    def post_create_training_pipeline_with_metadata(
        self,
        response: gca_training_pipeline.TrainingPipeline,
        metadata: Sequence[Tuple[str, Union[str, bytes]]],
    ) -> Tuple[
        gca_training_pipeline.TrainingPipeline, Sequence[Tuple[str, Union[str, bytes]]]
    ]:
        """Post-rpc interceptor for create_training_pipeline

        Override in a subclass to read or manipulate the response or metadata after it
        is returned by the PipelineService server but before it is returned to user code.

        We recommend only using this `post_create_training_pipeline_with_metadata`
        interceptor in new development instead of the `post_create_training_pipeline` interceptor.
        When both interceptors are used, this `post_create_training_pipeline_with_metadata` interceptor runs after the
        `post_create_training_pipeline` interceptor. The (possibly modified) response returned by
        `post_create_training_pipeline` will be passed to
        `post_create_training_pipeline_with_metadata`.
        """
        return response, metadata

    def pre_delete_pipeline_job(
        self,
        request: pipeline_service.DeletePipelineJobRequest,
        metadata: Sequence[Tuple[str, Union[str, bytes]]],
    ) -> Tuple[
        pipeline_service.DeletePipelineJobRequest,
        Sequence[Tuple[str, Union[str, bytes]]],
    ]:
        """Pre-rpc interceptor for delete_pipeline_job

        Override in a subclass to manipulate the request or metadata
        before they are sent to the PipelineService server.
        """
        return request, metadata

    def post_delete_pipeline_job(
        self, response: operations_pb2.Operation
    ) -> operations_pb2.Operation:
        """Post-rpc interceptor for delete_pipeline_job

        DEPRECATED. Please use the `post_delete_pipeline_job_with_metadata`
        interceptor instead.

        Override in a subclass to read or manipulate the response
        after it is returned by the PipelineService server but before
        it is returned to user code. This `post_delete_pipeline_job` interceptor runs
        before the `post_delete_pipeline_job_with_metadata` interceptor.
        """
        return response

    def post_delete_pipeline_job_with_metadata(
        self,
        response: operations_pb2.Operation,
        metadata: Sequence[Tuple[str, Union[str, bytes]]],
    ) -> Tuple[operations_pb2.Operation, Sequence[Tuple[str, Union[str, bytes]]]]:
        """Post-rpc interceptor for delete_pipeline_job

        Override in a subclass to read or manipulate the response or metadata after it
        is returned by the PipelineService server but before it is returned to user code.

        We recommend only using this `post_delete_pipeline_job_with_metadata`
        interceptor in new development instead of the `post_delete_pipeline_job` interceptor.
        When both interceptors are used, this `post_delete_pipeline_job_with_metadata` interceptor runs after the
        `post_delete_pipeline_job` interceptor. The (possibly modified) response returned by
        `post_delete_pipeline_job` will be passed to
        `post_delete_pipeline_job_with_metadata`.
        """
        return response, metadata

    def pre_delete_training_pipeline(
        self,
        request: pipeline_service.DeleteTrainingPipelineRequest,
        metadata: Sequence[Tuple[str, Union[str, bytes]]],
    ) -> Tuple[
        pipeline_service.DeleteTrainingPipelineRequest,
        Sequence[Tuple[str, Union[str, bytes]]],
    ]:
        """Pre-rpc interceptor for delete_training_pipeline

        Override in a subclass to manipulate the request or metadata
        before they are sent to the PipelineService server.
        """
        return request, metadata

    def post_delete_training_pipeline(
        self, response: operations_pb2.Operation
    ) -> operations_pb2.Operation:
        """Post-rpc interceptor for delete_training_pipeline

        DEPRECATED. Please use the `post_delete_training_pipeline_with_metadata`
        interceptor instead.

        Override in a subclass to read or manipulate the response
        after it is returned by the PipelineService server but before
        it is returned to user code. This `post_delete_training_pipeline` interceptor runs
        before the `post_delete_training_pipeline_with_metadata` interceptor.
        """
        return response

    def post_delete_training_pipeline_with_metadata(
        self,
        response: operations_pb2.Operation,
        metadata: Sequence[Tuple[str, Union[str, bytes]]],
    ) -> Tuple[operations_pb2.Operation, Sequence[Tuple[str, Union[str, bytes]]]]:
        """Post-rpc interceptor for delete_training_pipeline

        Override in a subclass to read or manipulate the response or metadata after it
        is returned by the PipelineService server but before it is returned to user code.

        We recommend only using this `post_delete_training_pipeline_with_metadata`
        interceptor in new development instead of the `post_delete_training_pipeline` interceptor.
        When both interceptors are used, this `post_delete_training_pipeline_with_metadata` interceptor runs after the
        `post_delete_training_pipeline` interceptor. The (possibly modified) response returned by
        `post_delete_training_pipeline` will be passed to
        `post_delete_training_pipeline_with_metadata`.
        """
        return response, metadata

    def pre_get_pipeline_job(
        self,
        request: pipeline_service.GetPipelineJobRequest,
        metadata: Sequence[Tuple[str, Union[str, bytes]]],
    ) -> Tuple[
        pipeline_service.GetPipelineJobRequest, Sequence[Tuple[str, Union[str, bytes]]]
    ]:
        """Pre-rpc interceptor for get_pipeline_job

        Override in a subclass to manipulate the request or metadata
        before they are sent to the PipelineService server.
        """
        return request, metadata

    def post_get_pipeline_job(
        self, response: pipeline_job.PipelineJob
    ) -> pipeline_job.PipelineJob:
        """Post-rpc interceptor for get_pipeline_job

        DEPRECATED. Please use the `post_get_pipeline_job_with_metadata`
        interceptor instead.

        Override in a subclass to read or manipulate the response
        after it is returned by the PipelineService server but before
        it is returned to user code. This `post_get_pipeline_job` interceptor runs
        before the `post_get_pipeline_job_with_metadata` interceptor.
        """
        return response

    def post_get_pipeline_job_with_metadata(
        self,
        response: pipeline_job.PipelineJob,
        metadata: Sequence[Tuple[str, Union[str, bytes]]],
    ) -> Tuple[pipeline_job.PipelineJob, Sequence[Tuple[str, Union[str, bytes]]]]:
        """Post-rpc interceptor for get_pipeline_job

        Override in a subclass to read or manipulate the response or metadata after it
        is returned by the PipelineService server but before it is returned to user code.

        We recommend only using this `post_get_pipeline_job_with_metadata`
        interceptor in new development instead of the `post_get_pipeline_job` interceptor.
        When both interceptors are used, this `post_get_pipeline_job_with_metadata` interceptor runs after the
        `post_get_pipeline_job` interceptor. The (possibly modified) response returned by
        `post_get_pipeline_job` will be passed to
        `post_get_pipeline_job_with_metadata`.
        """
        return response, metadata

    def pre_get_training_pipeline(
        self,
        request: pipeline_service.GetTrainingPipelineRequest,
        metadata: Sequence[Tuple[str, Union[str, bytes]]],
    ) -> Tuple[
        pipeline_service.GetTrainingPipelineRequest,
        Sequence[Tuple[str, Union[str, bytes]]],
    ]:
        """Pre-rpc interceptor for get_training_pipeline

        Override in a subclass to manipulate the request or metadata
        before they are sent to the PipelineService server.
        """
        return request, metadata

    def post_get_training_pipeline(
        self, response: training_pipeline.TrainingPipeline
    ) -> training_pipeline.TrainingPipeline:
        """Post-rpc interceptor for get_training_pipeline

        DEPRECATED. Please use the `post_get_training_pipeline_with_metadata`
        interceptor instead.

        Override in a subclass to read or manipulate the response
        after it is returned by the PipelineService server but before
        it is returned to user code. This `post_get_training_pipeline` interceptor runs
        before the `post_get_training_pipeline_with_metadata` interceptor.
        """
        return response

    def post_get_training_pipeline_with_metadata(
        self,
        response: training_pipeline.TrainingPipeline,
        metadata: Sequence[Tuple[str, Union[str, bytes]]],
    ) -> Tuple[
        training_pipeline.TrainingPipeline, Sequence[Tuple[str, Union[str, bytes]]]
    ]:
        """Post-rpc interceptor for get_training_pipeline

        Override in a subclass to read or manipulate the response or metadata after it
        is returned by the PipelineService server but before it is returned to user code.

        We recommend only using this `post_get_training_pipeline_with_metadata`
        interceptor in new development instead of the `post_get_training_pipeline` interceptor.
        When both interceptors are used, this `post_get_training_pipeline_with_metadata` interceptor runs after the
        `post_get_training_pipeline` interceptor. The (possibly modified) response returned by
        `post_get_training_pipeline` will be passed to
        `post_get_training_pipeline_with_metadata`.
        """
        return response, metadata

    def pre_list_pipeline_jobs(
        self,
        request: pipeline_service.ListPipelineJobsRequest,
        metadata: Sequence[Tuple[str, Union[str, bytes]]],
    ) -> Tuple[
        pipeline_service.ListPipelineJobsRequest,
        Sequence[Tuple[str, Union[str, bytes]]],
    ]:
        """Pre-rpc interceptor for list_pipeline_jobs

        Override in a subclass to manipulate the request or metadata
        before they are sent to the PipelineService server.
        """
        return request, metadata

    def post_list_pipeline_jobs(
        self, response: pipeline_service.ListPipelineJobsResponse
    ) -> pipeline_service.ListPipelineJobsResponse:
        """Post-rpc interceptor for list_pipeline_jobs

        DEPRECATED. Please use the `post_list_pipeline_jobs_with_metadata`
        interceptor instead.

        Override in a subclass to read or manipulate the response
        after it is returned by the PipelineService server but before
        it is returned to user code. This `post_list_pipeline_jobs` interceptor runs
        before the `post_list_pipeline_jobs_with_metadata` interceptor.
        """
        return response

    def post_list_pipeline_jobs_with_metadata(
        self,
        response: pipeline_service.ListPipelineJobsResponse,
        metadata: Sequence[Tuple[str, Union[str, bytes]]],
    ) -> Tuple[
        pipeline_service.ListPipelineJobsResponse,
        Sequence[Tuple[str, Union[str, bytes]]],
    ]:
        """Post-rpc interceptor for list_pipeline_jobs

        Override in a subclass to read or manipulate the response or metadata after it
        is returned by the PipelineService server but before it is returned to user code.

        We recommend only using this `post_list_pipeline_jobs_with_metadata`
        interceptor in new development instead of the `post_list_pipeline_jobs` interceptor.
        When both interceptors are used, this `post_list_pipeline_jobs_with_metadata` interceptor runs after the
        `post_list_pipeline_jobs` interceptor. The (possibly modified) response returned by
        `post_list_pipeline_jobs` will be passed to
        `post_list_pipeline_jobs_with_metadata`.
        """
        return response, metadata

    def pre_list_training_pipelines(
        self,
        request: pipeline_service.ListTrainingPipelinesRequest,
        metadata: Sequence[Tuple[str, Union[str, bytes]]],
    ) -> Tuple[
        pipeline_service.ListTrainingPipelinesRequest,
        Sequence[Tuple[str, Union[str, bytes]]],
    ]:
        """Pre-rpc interceptor for list_training_pipelines

        Override in a subclass to manipulate the request or metadata
        before they are sent to the PipelineService server.
        """
        return request, metadata

    def post_list_training_pipelines(
        self, response: pipeline_service.ListTrainingPipelinesResponse
    ) -> pipeline_service.ListTrainingPipelinesResponse:
        """Post-rpc interceptor for list_training_pipelines

        DEPRECATED. Please use the `post_list_training_pipelines_with_metadata`
        interceptor instead.

        Override in a subclass to read or manipulate the response
        after it is returned by the PipelineService server but before
        it is returned to user code. This `post_list_training_pipelines` interceptor runs
        before the `post_list_training_pipelines_with_metadata` interceptor.
        """
        return response

    def post_list_training_pipelines_with_metadata(
        self,
        response: pipeline_service.ListTrainingPipelinesResponse,
        metadata: Sequence[Tuple[str, Union[str, bytes]]],
    ) -> Tuple[
        pipeline_service.ListTrainingPipelinesResponse,
        Sequence[Tuple[str, Union[str, bytes]]],
    ]:
        """Post-rpc interceptor for list_training_pipelines

        Override in a subclass to read or manipulate the response or metadata after it
        is returned by the PipelineService server but before it is returned to user code.

        We recommend only using this `post_list_training_pipelines_with_metadata`
        interceptor in new development instead of the `post_list_training_pipelines` interceptor.
        When both interceptors are used, this `post_list_training_pipelines_with_metadata` interceptor runs after the
        `post_list_training_pipelines` interceptor. The (possibly modified) response returned by
        `post_list_training_pipelines` will be passed to
        `post_list_training_pipelines_with_metadata`.
        """
        return response, metadata

    def pre_get_location(
        self,
        request: locations_pb2.GetLocationRequest,
        metadata: Sequence[Tuple[str, Union[str, bytes]]],
    ) -> Tuple[
        locations_pb2.GetLocationRequest, Sequence[Tuple[str, Union[str, bytes]]]
    ]:
        """Pre-rpc interceptor for get_location

        Override in a subclass to manipulate the request or metadata
        before they are sent to the PipelineService server.
        """
        return request, metadata

    def post_get_location(
        self, response: locations_pb2.Location
    ) -> locations_pb2.Location:
        """Post-rpc interceptor for get_location

        Override in a subclass to manipulate the response
        after it is returned by the PipelineService server but before
        it is returned to user code.
        """
        return response

    def pre_list_locations(
        self,
        request: locations_pb2.ListLocationsRequest,
        metadata: Sequence[Tuple[str, Union[str, bytes]]],
    ) -> Tuple[
        locations_pb2.ListLocationsRequest, Sequence[Tuple[str, Union[str, bytes]]]
    ]:
        """Pre-rpc interceptor for list_locations

        Override in a subclass to manipulate the request or metadata
        before they are sent to the PipelineService server.
        """
        return request, metadata

    def post_list_locations(
        self, response: locations_pb2.ListLocationsResponse
    ) -> locations_pb2.ListLocationsResponse:
        """Post-rpc interceptor for list_locations

        Override in a subclass to manipulate the response
        after it is returned by the PipelineService server but before
        it is returned to user code.
        """
        return response

    def pre_get_iam_policy(
        self,
        request: iam_policy_pb2.GetIamPolicyRequest,
        metadata: Sequence[Tuple[str, Union[str, bytes]]],
    ) -> Tuple[
        iam_policy_pb2.GetIamPolicyRequest, Sequence[Tuple[str, Union[str, bytes]]]
    ]:
        """Pre-rpc interceptor for get_iam_policy

        Override in a subclass to manipulate the request or metadata
        before they are sent to the PipelineService server.
        """
        return request, metadata

    def post_get_iam_policy(self, response: policy_pb2.Policy) -> policy_pb2.Policy:
        """Post-rpc interceptor for get_iam_policy

        Override in a subclass to manipulate the response
        after it is returned by the PipelineService server but before
        it is returned to user code.
        """
        return response

    def pre_set_iam_policy(
        self,
        request: iam_policy_pb2.SetIamPolicyRequest,
        metadata: Sequence[Tuple[str, Union[str, bytes]]],
    ) -> Tuple[
        iam_policy_pb2.SetIamPolicyRequest, Sequence[Tuple[str, Union[str, bytes]]]
    ]:
        """Pre-rpc interceptor for set_iam_policy

        Override in a subclass to manipulate the request or metadata
        before they are sent to the PipelineService server.
        """
        return request, metadata

    def post_set_iam_policy(self, response: policy_pb2.Policy) -> policy_pb2.Policy:
        """Post-rpc interceptor for set_iam_policy

        Override in a subclass to manipulate the response
        after it is returned by the PipelineService server but before
        it is returned to user code.
        """
        return response

    def pre_test_iam_permissions(
        self,
        request: iam_policy_pb2.TestIamPermissionsRequest,
        metadata: Sequence[Tuple[str, Union[str, bytes]]],
    ) -> Tuple[
        iam_policy_pb2.TestIamPermissionsRequest,
        Sequence[Tuple[str, Union[str, bytes]]],
    ]:
        """Pre-rpc interceptor for test_iam_permissions

        Override in a subclass to manipulate the request or metadata
        before they are sent to the PipelineService server.
        """
        return request, metadata

    def post_test_iam_permissions(
        self, response: iam_policy_pb2.TestIamPermissionsResponse
    ) -> iam_policy_pb2.TestIamPermissionsResponse:
        """Post-rpc interceptor for test_iam_permissions

        Override in a subclass to manipulate the response
        after it is returned by the PipelineService server but before
        it is returned to user code.
        """
        return response

    def pre_cancel_operation(
        self,
        request: operations_pb2.CancelOperationRequest,
        metadata: Sequence[Tuple[str, Union[str, bytes]]],
    ) -> Tuple[
        operations_pb2.CancelOperationRequest, Sequence[Tuple[str, Union[str, bytes]]]
    ]:
        """Pre-rpc interceptor for cancel_operation

        Override in a subclass to manipulate the request or metadata
        before they are sent to the PipelineService server.
        """
        return request, metadata

    def post_cancel_operation(self, response: None) -> None:
        """Post-rpc interceptor for cancel_operation

        Override in a subclass to manipulate the response
        after it is returned by the PipelineService server but before
        it is returned to user code.
        """
        return response

    def pre_delete_operation(
        self,
        request: operations_pb2.DeleteOperationRequest,
        metadata: Sequence[Tuple[str, Union[str, bytes]]],
    ) -> Tuple[
        operations_pb2.DeleteOperationRequest, Sequence[Tuple[str, Union[str, bytes]]]
    ]:
        """Pre-rpc interceptor for delete_operation

        Override in a subclass to manipulate the request or metadata
        before they are sent to the PipelineService server.
        """
        return request, metadata

    def post_delete_operation(self, response: None) -> None:
        """Post-rpc interceptor for delete_operation

        Override in a subclass to manipulate the response
        after it is returned by the PipelineService server but before
        it is returned to user code.
        """
        return response

    def pre_get_operation(
        self,
        request: operations_pb2.GetOperationRequest,
        metadata: Sequence[Tuple[str, Union[str, bytes]]],
    ) -> Tuple[
        operations_pb2.GetOperationRequest, Sequence[Tuple[str, Union[str, bytes]]]
    ]:
        """Pre-rpc interceptor for get_operation

        Override in a subclass to manipulate the request or metadata
        before they are sent to the PipelineService server.
        """
        return request, metadata

    def post_get_operation(
        self, response: operations_pb2.Operation
    ) -> operations_pb2.Operation:
        """Post-rpc interceptor for get_operation

        Override in a subclass to manipulate the response
        after it is returned by the PipelineService server but before
        it is returned to user code.
        """
        return response

    def pre_list_operations(
        self,
        request: operations_pb2.ListOperationsRequest,
        metadata: Sequence[Tuple[str, Union[str, bytes]]],
    ) -> Tuple[
        operations_pb2.ListOperationsRequest, Sequence[Tuple[str, Union[str, bytes]]]
    ]:
        """Pre-rpc interceptor for list_operations

        Override in a subclass to manipulate the request or metadata
        before they are sent to the PipelineService server.
        """
        return request, metadata

    def post_list_operations(
        self, response: operations_pb2.ListOperationsResponse
    ) -> operations_pb2.ListOperationsResponse:
        """Post-rpc interceptor for list_operations

        Override in a subclass to manipulate the response
        after it is returned by the PipelineService server but before
        it is returned to user code.
        """
        return response

    def pre_wait_operation(
        self,
        request: operations_pb2.WaitOperationRequest,
        metadata: Sequence[Tuple[str, Union[str, bytes]]],
    ) -> Tuple[
        operations_pb2.WaitOperationRequest, Sequence[Tuple[str, Union[str, bytes]]]
    ]:
        """Pre-rpc interceptor for wait_operation

        Override in a subclass to manipulate the request or metadata
        before they are sent to the PipelineService server.
        """
        return request, metadata

    def post_wait_operation(
        self, response: operations_pb2.Operation
    ) -> operations_pb2.Operation:
        """Post-rpc interceptor for wait_operation

        Override in a subclass to manipulate the response
        after it is returned by the PipelineService server but before
        it is returned to user code.
        """
        return response


@dataclasses.dataclass
class PipelineServiceRestStub:
    _session: AuthorizedSession
    _host: str
    _interceptor: PipelineServiceRestInterceptor


class PipelineServiceRestTransport(_BasePipelineServiceRestTransport):
    """REST backend synchronous transport for PipelineService.

    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).

    This class defines the same methods as the primary client, so the
    primary client can load the underlying transport implementation
    and call it.

    It sends JSON representations of protocol buffers over HTTP/1.1
    """

    def __init__(
        self,
        *,
        host: str = "aiplatform.googleapis.com",
        credentials: Optional[ga_credentials.Credentials] = None,
        credentials_file: Optional[str] = None,
        scopes: Optional[Sequence[str]] = None,
        client_cert_source_for_mtls: Optional[Callable[[], Tuple[bytes, bytes]]] = None,
        quota_project_id: Optional[str] = None,
        client_info: gapic_v1.client_info.ClientInfo = DEFAULT_CLIENT_INFO,
        always_use_jwt_access: Optional[bool] = False,
        url_scheme: str = "https",
        interceptor: Optional[PipelineServiceRestInterceptor] = None,
        api_audience: Optional[str] = None,
    ) -> None:
        """Instantiate the transport.

        Args:
            host (Optional[str]):
                 The hostname to connect to (default: 'aiplatform.googleapis.com').
            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.

            credentials_file (Optional[str]): Deprecated. A file with credentials that can
                be loaded with :func:`google.auth.load_credentials_from_file`.
                This argument is ignored if ``channel`` is provided. This argument will be
                removed in the next major version of this library.
            scopes (Optional(Sequence[str])): A list of scopes. This argument is
                ignored if ``channel`` is provided.
            client_cert_source_for_mtls (Callable[[], Tuple[bytes, bytes]]): Client
                certificate to configure mutual TLS HTTP channel. It is ignored
                if ``channel`` is provided.
            quota_project_id (Optional[str]): An optional project to use for billing
                and quota.
            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 are developing
                your own client library.
            always_use_jwt_access (Optional[bool]): Whether self signed JWT should
                be used for service account credentials.
            url_scheme: the protocol scheme for the API endpoint.  Normally
                "https", but for testing or local servers,
                "http" can be specified.
        """
        # Run the base constructor
        # TODO(yon-mg): resolve other ctor params i.e. scopes, quota, etc.
        # TODO: When custom host (api_endpoint) is set, `scopes` must *also* be set on the
        # credentials object
        super().__init__(
            host=host,
            credentials=credentials,
            client_info=client_info,
            always_use_jwt_access=always_use_jwt_access,
            url_scheme=url_scheme,
            api_audience=api_audience,
        )
        self._session = AuthorizedSession(
            self._credentials, default_host=self.DEFAULT_HOST
        )
        self._operations_client: Optional[operations_v1.AbstractOperationsClient] = None
        if client_cert_source_for_mtls:
            self._session.configure_mtls_channel(client_cert_source_for_mtls)
        self._interceptor = interceptor or PipelineServiceRestInterceptor()
        self._prep_wrapped_messages(client_info)

    @property
    def operations_client(self) -> operations_v1.AbstractOperationsClient:
        """Create the client designed to process long-running operations.

        This property caches on the instance; repeated calls return the same
        client.
        """
        # Only create a new client if we do not already have one.
        if self._operations_client is None:
            http_options: Dict[str, List[Dict[str, str]]] = {
                "google.longrunning.Operations.CancelOperation": [
                    {
                        "method": "post",
                        "uri": "/ui/{name=projects/*/locations/*/operations/*}:cancel",
                    },
                    {
                        "method": "post",
                        "uri": "/ui/{name=projects/*/locations/*/agents/*/operations/*}:cancel",
                    },
                    {
                        "method": "post",
                        "uri": "/ui/{name=projects/*/locations/*/apps/*/operations/*}:cancel",
                    },
                    {
                        "method": "post",
                        "uri": "/ui/{name=projects/*/locations/*/datasets/*/operations/*}:cancel",
                    },
                    {
                        "method": "post",
                        "uri": "/ui/{name=projects/*/locations/*/datasets/*/dataItems/*/operations/*}:cancel",
                    },
                    {
                        "method": "post",
                        "uri": "/ui/{name=projects/*/locations/*/datasets/*/savedQueries/*/operations/*}:cancel",
                    },
                    {
                        "method": "post",
                        "uri": "/ui/{name=projects/*/locations/*/datasets/*/annotationSpecs/*/operations/*}:cancel",
                    },
                    {
                        "method": "post",
                        "uri": "/ui/{name=projects/*/locations/*/datasets/*/dataItems/*/annotations/*/operations/*}:cancel",
                    },
                    {
                        "method": "post",
                        "uri": "/ui/{name=projects/*/locations/*/deploymentResourcePools/*/operations/*}:cancel",
                    },
                    {
                        "method": "post",
                        "uri": "/ui/{name=projects/*/locations/*/edgeDevices/*/operations/*}:cancel",
                    },
                    {
                        "method": "post",
                        "uri": "/ui/{name=projects/*/locations/*/endpoints/*/operations/*}:cancel",
                    },
                    {
                        "method": "post",
                        "uri": "/ui/{name=projects/*/locations/*/extensionControllers/*/operations/*}:cancel",
                    },
                    {
                        "method": "post",
                        "uri": "/ui/{name=projects/*/locations/*/extensions/*/operations/*}:cancel",
                    },
                    {
                        "method": "post",
                        "uri": "/ui/{name=projects/*/locations/*/featurestores/*/operations/*}:cancel",
                    },
                    {
                        "method": "post",
                        "uri": "/ui/{name=projects/*/locations/*/featurestores/*/entityTypes/*/operations/*}:cancel",
                    },
                    {
                        "method": "post",
                        "uri": "/ui/{name=projects/*/locations/*/featurestores/*/entityTypes/*/features/*/operations/*}:cancel",
                    },
                    {
                        "method": "post",
                        "uri": "/ui/{name=projects/*/locations/*/customJobs/*/operations/*}:cancel",
                    },
                    {
                        "method": "post",
                        "uri": "/ui/{name=projects/*/locations/*/dataLabelingJobs/*/operations/*}:cancel",
                    },
                    {
                        "method": "post",
                        "uri": "/ui/{name=projects/*/locations/*/hyperparameterTuningJobs/*/operations/*}:cancel",
                    },
                    {
                        "method": "post",
                        "uri": "/ui/{name=projects/*/locations/*/tuningJobs/*/operations/*}:cancel",
                    },
                    {
                        "method": "post",
                        "uri": "/ui/{name=projects/*/locations/*/indexes/*/operations/*}:cancel",
                    },
                    {
                        "method": "post",
                        "uri": "/ui/{name=projects/*/locations/*/indexEndpoints/*/operations/*}:cancel",
                    },
                    {
                        "method": "post",
                        "uri": "/ui/{name=projects/*/locations/*/metadataStores/*/operations/*}:cancel",
                    },
                    {
                        "method": "post",
                        "uri": "/ui/{name=projects/*/locations/*/metadataStores/*/artifacts/*/operations/*}:cancel",
                    },
                    {
                        "method": "post",
                        "uri": "/ui/{name=projects/*/locations/*/metadataStores/*/contexts/*/operations/*}:cancel",
                    },
                    {
                        "method": "post",
                        "uri": "/ui/{name=projects/*/locations/*/metadataStores/*/executions/*/operations/*}:cancel",
                    },
                    {
                        "method": "post",
                        "uri": "/ui/{name=projects/*/locations/*/modelDeploymentMonitoringJobs/*/operations/*}:cancel",
                    },
                    {
                        "method": "post",
                        "uri": "/ui/{name=projects/*/locations/*/modelMonitors/*/operations/*}:cancel",
                    },
                    {
                        "method": "post",
                        "uri": "/ui/{name=projects/*/locations/*/migratableResources/*/operations/*}:cancel",
                    },
                    {
                        "method": "post",
                        "uri": "/ui/{name=projects/*/locations/*/models/*/operations/*}:cancel",
                    },
                    {
                        "method": "post",
                        "uri": "/ui/{name=projects/*/locations/*/models/*/evaluations/*/operations/*}:cancel",
                    },
                    {
                        "method": "post",
                        "uri": "/ui/{name=projects/*/locations/*/notebookExecutionJobs/*/operations/*}:cancel",
                    },
                    {
                        "method": "post",
                        "uri": "/ui/{name=projects/*/locations/*/notebookRuntimes/*/operations/*}:cancel",
                    },
                    {
                        "method": "post",
                        "uri": "/ui/{name=projects/*/locations/*/notebookRuntimeTemplates/*/operations/*}:cancel",
                    },
                    {
                        "method": "post",
                        "uri": "/ui/{name=projects/*/locations/*/persistentResources/*/operations/*}:cancel",
                    },
                    {
                        "method": "post",
                        "uri": "/ui/{name=projects/*/locations/*/studies/*/operations/*}:cancel",
                    },
                    {
                        "method": "post",
                        "uri": "/ui/{name=projects/*/locations/*/studies/*/trials/*/operations/*}:cancel",
                    },
                    {
                        "method": "post",
                        "uri": "/ui/{name=projects/*/locations/*/trainingPipelines/*/operations/*}:cancel",
                    },
                    {
                        "method": "post",
                        "uri": "/ui/{name=projects/*/locations/*/pipelineJobs/*/operations/*}:cancel",
                    },
                    {
                        "method": "post",
                        "uri": "/ui/{name=projects/*/locations/*/schedules/*/operations/*}:cancel",
                    },
                    {
                        "method": "post",
                        "uri": "/ui/{name=projects/*/locations/*/ragEngineConfig/operations/*}:cancel",
                    },
                    {
                        "method": "post",
                        "uri": "/ui/{name=projects/*/locations/*/specialistPools/*/operations/*}:cancel",
                    },
                    {
                        "method": "post",
                        "uri": "/ui/{name=projects/*/locations/*/tensorboards/*/operations/*}:cancel",
                    },
                    {
                        "method": "post",
                        "uri": "/ui/{name=projects/*/locations/*/tensorboards/*/experiments/*/operations/*}:cancel",
                    },
                    {
                        "method": "post",
                        "uri": "/ui/{name=projects/*/locations/*/tensorboards/*/experiments/*/runs/*/operations/*}:cancel",
                    },
                    {
                        "method": "post",
                        "uri": "/ui/{name=projects/*/locations/*/tensorboards/*/experiments/*/runs/*/timeSeries/*/operations/*}:cancel",
                    },
                    {
                        "method": "post",
                        "uri": "/v1/{name=projects/*/locations/*/operations/*}:cancel",
                    },
                    {
                        "method": "post",
                        "uri": "/v1/{name=projects/*/locations/*/datasets/*/operations/*}:cancel",
                    },
                    {
                        "method": "post",
                        "uri": "/v1/{name=projects/*/locations/*/datasets/*/dataItems/*/operations/*}:cancel",
                    },
                    {
                        "method": "post",
                        "uri": "/v1/{name=projects/*/locations/*/datasets/*/savedQueries/*/operations/*}:cancel",
                    },
                    {
                        "method": "post",
                        "uri": "/v1/{name=projects/*/locations/*/datasets/*/annotationSpecs/*/operations/*}:cancel",
                    },
                    {
                        "method": "post",
                        "uri": "/v1/{name=projects/*/locations/*/datasets/*/dataItems/*/annotations/*/operations/*}:cancel",
                    },
                    {
                        "method": "post",
                        "uri": "/v1/{name=projects/*/locations/*/deploymentResourcePools/*/operations/*}:cancel",
                    },
                    {
                        "method": "post",
                        "uri": "/v1/{name=projects/*/locations/*/endpoints/*/operations/*}:cancel",
                    },
                    {
                        "method": "post",
                        "uri": "/v1/{name=projects/*/locations/*/featurestores/*/operations/*}:cancel",
                    },
                    {
                        "method": "post",
                        "uri": "/v1/{name=projects/*/locations/*/featurestores/*/entityTypes/*/operations/*}:cancel",
                    },
                    {
                        "method": "post",
                        "uri": "/v1/{name=projects/*/locations/*/featurestores/*/entityTypes/*/features/*/operations/*}:cancel",
                    },
                    {
                        "method": "post",
                        "uri": "/v1/{name=projects/*/locations/*/customJobs/*/operations/*}:cancel",
                    },
                    {
                        "method": "post",
                        "uri": "/v1/{name=projects/*/locations/*/dataLabelingJobs/*/operations/*}:cancel",
                    },
                    {
                        "method": "post",
                        "uri": "/v1/{name=projects/*/locations/*/hyperparameterTuningJobs/*/operations/*}:cancel",
                    },
                    {
                        "method": "post",
                        "uri": "/v1/{name=projects/*/locations/*/tuningJobs/*/operations/*}:cancel",
                    },
                    {
                        "method": "post",
                        "uri": "/v1/{name=projects/*/locations/*/indexes/*/operations/*}:cancel",
                    },
                    {
                        "method": "post",
                        "uri": "/v1/{name=projects/*/locations/*/indexEndpoints/*/operations/*}:cancel",
                    },
                    {
                        "method": "post",
                        "uri": "/v1/{name=projects/*/locations/*/metadataStores/*/operations/*}:cancel",
                    },
                    {
                        "method": "post",
                        "uri": "/v1/{name=projects/*/locations/*/metadataStores/*/artifacts/*/operations/*}:cancel",
                    },
                    {
                        "method": "post",
                        "uri": "/v1/{name=projects/*/locations/*/metadataStores/*/contexts/*/operations/*}:cancel",
                    },
                    {
                        "method": "post",
                        "uri": "/v1/{name=projects/*/locations/*/metadataStores/*/executions/*/operations/*}:cancel",
                    },
                    {
                        "method": "post",
                        "uri": "/v1/{name=projects/*/locations/*/modelDeploymentMonitoringJobs/*/operations/*}:cancel",
                    },
                    {
                        "method": "post",
                        "uri": "/v1/{name=projects/*/locations/*/migratableResources/*/operations/*}:cancel",
                    },
                    {
                        "method": "post",
                        "uri": "/v1/{name=projects/*/locations/*/models/*/operations/*}:cancel",
                    },
                    {
                        "method": "post",
                        "uri": "/v1/{name=projects/*/locations/*/models/*/evaluations/*/operations/*}:cancel",
                    },
                    {
                        "method": "post",
                        "uri": "/v1/{name=projects/*/locations/*/notebookExecutionJobs/*/operations/*}:cancel",
                    },
                    {
                        "method": "post",
                        "uri": "/v1/{name=projects/*/locations/*/notebookRuntimes/*/operations/*}:cancel",
                    },
                    {
                        "method": "post",
                        "uri": "/v1/{name=projects/*/locations/*/notebookRuntimeTemplates/*/operations/*}:cancel",
                    },
                    {
                        "method": "post",
                        "uri": "/v1/{name=projects/*/locations/*/persistentResources/*/operations/*}:cancel",
                    },
                    {
                        "method": "post",
                        "uri": "/v1/{name=projects/*/locations/*/ragEngineConfig/operations/*}:cancel",
                    },
                    {
                        "method": "post",
                        "uri": "/v1/{name=projects/*/locations/*/ragCorpora/*/operations/*}:cancel",
                    },
                    {
                        "method": "post",
                        "uri": "/v1/{name=projects/*/locations/*/ragCorpora/*/ragFiles/*/operations/*}:cancel",
                    },
                    {
                        "method": "post",
                        "uri": "/v1/{name=projects/*/locations/*/reasoningEngines/*/operations/*}:cancel",
                    },
                    {
                        "method": "post",
                        "uri": "/v1/{name=projects/*/locations/*/studies/*/operations/*}:cancel",
                    },
                    {
                        "method": "post",
                        "uri": "/v1/{name=projects/*/locations/*/studies/*/trials/*/operations/*}:cancel",
                    },
                    {
                        "method": "post",
                        "uri": "/v1/{name=projects/*/locations/*/trainingPipelines/*/operations/*}:cancel",
                    },
                    {
                        "method": "post",
                        "uri": "/v1/{name=projects/*/locations/*/pipelineJobs/*/operations/*}:cancel",
                    },
                    {
                        "method": "post",
                        "uri": "/v1/{name=projects/*/locations/*/schedules/*/operations/*}:cancel",
                    },
                    {
                        "method": "post",
                        "uri": "/v1/{name=projects/*/locations/*/specialistPools/*/operations/*}:cancel",
                    },
                    {
                        "method": "post",
                        "uri": "/v1/{name=projects/*/locations/*/tensorboards/*/operations/*}:cancel",
                    },
                    {
                        "method": "post",
                        "uri": "/v1/{name=projects/*/locations/*/tensorboards/*/experiments/*/operations/*}:cancel",
                    },
                    {
                        "method": "post",
                        "uri": "/v1/{name=projects/*/locations/*/tensorboards/*/experiments/*/runs/*/operations/*}:cancel",
                    },
                    {
                        "method": "post",
                        "uri": "/v1/{name=projects/*/locations/*/tensorboards/*/experiments/*/runs/*/timeSeries/*/operations/*}:cancel",
                    },
                ],
                "google.longrunning.Operations.DeleteOperation": [
                    {
                        "method": "delete",
                        "uri": "/ui/{name=projects/*/locations/*/operations/*}",
                    },
                    {
                        "method": "delete",
                        "uri": "/ui/{name=projects/*/locations/*/agents/*/operations/*}",
                    },
                    {
                        "method": "delete",
                        "uri": "/ui/{name=projects/*/locations/*/apps/*/operations/*}",
                    },
                    {
                        "method": "delete",
                        "uri": "/ui/{name=projects/*/locations/*/datasets/*/operations/*}",
                    },
                    {
                        "method": "delete",
                        "uri": "/ui/{name=projects/*/locations/*/datasets/*/dataItems/*/operations/*}",
                    },
                    {
                        "method": "delete",
                        "uri": "/ui/{name=projects/*/locations/*/datasets/*/savedQueries/*/operations/*}",
                    },
                    {
                        "method": "delete",
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                    {
                        "method": "post",
                        "uri": "/v1/{name=projects/*/locations/*/ragCorpora/*/operations/*}:wait",
                    },
                    {
                        "method": "post",
                        "uri": "/v1/{name=projects/*/locations/*/ragCorpora/*/ragFiles/*/operations/*}:wait",
                    },
                    {
                        "method": "post",
                        "uri": "/v1/{name=projects/*/locations/*/reasoningEngines/*/operations/*}:wait",
                    },
                    {
                        "method": "post",
                        "uri": "/v1/{name=projects/*/locations/*/studies/*/operations/*}:wait",
                    },
                    {
                        "method": "post",
                        "uri": "/v1/{name=projects/*/locations/*/studies/*/trials/*/operations/*}:wait",
                    },
                    {
                        "method": "post",
                        "uri": "/v1/{name=projects/*/locations/*/trainingPipelines/*/operations/*}:wait",
                    },
                    {
                        "method": "post",
                        "uri": "/v1/{name=projects/*/locations/*/persistentResources/*/operations/*}:wait",
                    },
                    {
                        "method": "post",
                        "uri": "/v1/{name=projects/*/locations/*/pipelineJobs/*/operations/*}:wait",
                    },
                    {
                        "method": "post",
                        "uri": "/v1/{name=projects/*/locations/*/schedules/*/operations/*}:wait",
                    },
                    {
                        "method": "post",
                        "uri": "/v1/{name=projects/*/locations/*/specialistPools/*/operations/*}:wait",
                    },
                    {
                        "method": "post",
                        "uri": "/v1/{name=projects/*/locations/*/tensorboards/*/operations/*}:wait",
                    },
                    {
                        "method": "post",
                        "uri": "/v1/{name=projects/*/locations/*/tensorboards/*/experiments/*/operations/*}:wait",
                    },
                    {
                        "method": "post",
                        "uri": "/v1/{name=projects/*/locations/*/tensorboards/*/experiments/*/runs/*/operations/*}:wait",
                    },
                    {
                        "method": "post",
                        "uri": "/v1/{name=projects/*/locations/*/tensorboards/*/experiments/*/runs/*/timeSeries/*/operations/*}:wait",
                    },
                    {
                        "method": "post",
                        "uri": "/v1/{name=projects/*/locations/*/featureOnlineStores/*/operations/*}:wait",
                    },
                    {
                        "method": "post",
                        "uri": "/v1/{name=projects/*/locations/*/featureOnlineStores/*/featureViews/*/operations/*}:wait",
                    },
                    {
                        "method": "post",
                        "uri": "/v1/{name=projects/*/locations/*/featureGroups/*/operations/*}:wait",
                    },
                    {
                        "method": "post",
                        "uri": "/v1/{name=projects/*/locations/*/featureGroups/*/features/*/operations/*}:wait",
                    },
                ],
            }

            rest_transport = operations_v1.OperationsRestTransport(
                host=self._host,
                # use the credentials which are saved
                credentials=self._credentials,
                scopes=self._scopes,
                http_options=http_options,
                path_prefix="v1",
            )

            self._operations_client = operations_v1.AbstractOperationsClient(
                transport=rest_transport
            )

        # Return the client from cache.
        return self._operations_client

    class _BatchCancelPipelineJobs(
        _BasePipelineServiceRestTransport._BaseBatchCancelPipelineJobs,
        PipelineServiceRestStub,
    ):
        def __hash__(self):
            return hash("PipelineServiceRestTransport.BatchCancelPipelineJobs")

        @staticmethod
        def _get_response(
            host,
            metadata,
            query_params,
            session,
            timeout,
            transcoded_request,
            body=None,
        ):

            uri = transcoded_request["uri"]
            method = transcoded_request["method"]
            headers = dict(metadata)
            headers["Content-Type"] = "application/json"
            response = getattr(session, method)(
                "{host}{uri}".format(host=host, uri=uri),
                timeout=timeout,
                headers=headers,
                params=rest_helpers.flatten_query_params(query_params, strict=True),
                data=body,
            )
            return response

        def __call__(
            self,
            request: pipeline_service.BatchCancelPipelineJobsRequest,
            *,
            retry: OptionalRetry = gapic_v1.method.DEFAULT,
            timeout: Optional[float] = None,
            metadata: Sequence[Tuple[str, Union[str, bytes]]] = (),
        ) -> operations_pb2.Operation:
            r"""Call the batch cancel pipeline
            jobs method over HTTP.

                Args:
                    request (~.pipeline_service.BatchCancelPipelineJobsRequest):
                        The request object. Request message for
                    [PipelineService.BatchCancelPipelineJobs][google.cloud.aiplatform.v1.PipelineService.BatchCancelPipelineJobs].
                    retry (google.api_core.retry.Retry): Designation of what errors, if any,
                        should be retried.
                    timeout (float): The timeout for this request.
                    metadata (Sequence[Tuple[str, 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:
                        This resource represents a
                    long-running operation that is the
                    result of a network API call.

            """

            http_options = (
                _BasePipelineServiceRestTransport._BaseBatchCancelPipelineJobs._get_http_options()
            )

            request, metadata = self._interceptor.pre_batch_cancel_pipeline_jobs(
                request, metadata
            )
            transcoded_request = _BasePipelineServiceRestTransport._BaseBatchCancelPipelineJobs._get_transcoded_request(
                http_options, request
            )

            body = _BasePipelineServiceRestTransport._BaseBatchCancelPipelineJobs._get_request_body_json(
                transcoded_request
            )

            # Jsonify the query params
            query_params = _BasePipelineServiceRestTransport._BaseBatchCancelPipelineJobs._get_query_params_json(
                transcoded_request
            )

            if CLIENT_LOGGING_SUPPORTED and _LOGGER.isEnabledFor(
                logging.DEBUG
            ):  # pragma: NO COVER
                request_url = "{host}{uri}".format(
                    host=self._host, uri=transcoded_request["uri"]
                )
                method = transcoded_request["method"]
                try:
                    request_payload = json_format.MessageToJson(request)
                except:
                    request_payload = None
                http_request = {
                    "payload": request_payload,
                    "requestMethod": method,
                    "requestUrl": request_url,
                    "headers": dict(metadata),
                }
                _LOGGER.debug(
                    f"Sending request for google.cloud.aiplatform_v1.PipelineServiceClient.BatchCancelPipelineJobs",
                    extra={
                        "serviceName": "google.cloud.aiplatform.v1.PipelineService",
                        "rpcName": "BatchCancelPipelineJobs",
                        "httpRequest": http_request,
                        "metadata": http_request["headers"],
                    },
                )

            # Send the request
            response = (
                PipelineServiceRestTransport._BatchCancelPipelineJobs._get_response(
                    self._host,
                    metadata,
                    query_params,
                    self._session,
                    timeout,
                    transcoded_request,
                    body,
                )
            )

            # In case of error, raise the appropriate core_exceptions.GoogleAPICallError exception
            # subclass.
            if response.status_code >= 400:
                raise core_exceptions.from_http_response(response)

            # Return the response
            resp = operations_pb2.Operation()
            json_format.Parse(response.content, resp, ignore_unknown_fields=True)

            resp = self._interceptor.post_batch_cancel_pipeline_jobs(resp)
            response_metadata = [(k, str(v)) for k, v in response.headers.items()]
            resp, _ = self._interceptor.post_batch_cancel_pipeline_jobs_with_metadata(
                resp, response_metadata
            )
            if CLIENT_LOGGING_SUPPORTED and _LOGGER.isEnabledFor(
                logging.DEBUG
            ):  # pragma: NO COVER
                try:
                    response_payload = json_format.MessageToJson(resp)
                except:
                    response_payload = None
                http_response = {
                    "payload": response_payload,
                    "headers": dict(response.headers),
                    "status": response.status_code,
                }
                _LOGGER.debug(
                    "Received response for google.cloud.aiplatform_v1.PipelineServiceClient.batch_cancel_pipeline_jobs",
                    extra={
                        "serviceName": "google.cloud.aiplatform.v1.PipelineService",
                        "rpcName": "BatchCancelPipelineJobs",
                        "metadata": http_response["headers"],
                        "httpResponse": http_response,
                    },
                )
            return resp

    class _BatchDeletePipelineJobs(
        _BasePipelineServiceRestTransport._BaseBatchDeletePipelineJobs,
        PipelineServiceRestStub,
    ):
        def __hash__(self):
            return hash("PipelineServiceRestTransport.BatchDeletePipelineJobs")

        @staticmethod
        def _get_response(
            host,
            metadata,
            query_params,
            session,
            timeout,
            transcoded_request,
            body=None,
        ):

            uri = transcoded_request["uri"]
            method = transcoded_request["method"]
            headers = dict(metadata)
            headers["Content-Type"] = "application/json"
            response = getattr(session, method)(
                "{host}{uri}".format(host=host, uri=uri),
                timeout=timeout,
                headers=headers,
                params=rest_helpers.flatten_query_params(query_params, strict=True),
                data=body,
            )
            return response

        def __call__(
            self,
            request: pipeline_service.BatchDeletePipelineJobsRequest,
            *,
            retry: OptionalRetry = gapic_v1.method.DEFAULT,
            timeout: Optional[float] = None,
            metadata: Sequence[Tuple[str, Union[str, bytes]]] = (),
        ) -> operations_pb2.Operation:
            r"""Call the batch delete pipeline
            jobs method over HTTP.

                Args:
                    request (~.pipeline_service.BatchDeletePipelineJobsRequest):
                        The request object. Request message for
                    [PipelineService.BatchDeletePipelineJobs][google.cloud.aiplatform.v1.PipelineService.BatchDeletePipelineJobs].
                    retry (google.api_core.retry.Retry): Designation of what errors, if any,
                        should be retried.
                    timeout (float): The timeout for this request.
                    metadata (Sequence[Tuple[str, 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:
                        This resource represents a
                    long-running operation that is the
                    result of a network API call.

            """

            http_options = (
                _BasePipelineServiceRestTransport._BaseBatchDeletePipelineJobs._get_http_options()
            )

            request, metadata = self._interceptor.pre_batch_delete_pipeline_jobs(
                request, metadata
            )
            transcoded_request = _BasePipelineServiceRestTransport._BaseBatchDeletePipelineJobs._get_transcoded_request(
                http_options, request
            )

            body = _BasePipelineServiceRestTransport._BaseBatchDeletePipelineJobs._get_request_body_json(
                transcoded_request
            )

            # Jsonify the query params
            query_params = _BasePipelineServiceRestTransport._BaseBatchDeletePipelineJobs._get_query_params_json(
                transcoded_request
            )

            if CLIENT_LOGGING_SUPPORTED and _LOGGER.isEnabledFor(
                logging.DEBUG
            ):  # pragma: NO COVER
                request_url = "{host}{uri}".format(
                    host=self._host, uri=transcoded_request["uri"]
                )
                method = transcoded_request["method"]
                try:
                    request_payload = json_format.MessageToJson(request)
                except:
                    request_payload = None
                http_request = {
                    "payload": request_payload,
                    "requestMethod": method,
                    "requestUrl": request_url,
                    "headers": dict(metadata),
                }
                _LOGGER.debug(
                    f"Sending request for google.cloud.aiplatform_v1.PipelineServiceClient.BatchDeletePipelineJobs",
                    extra={
                        "serviceName": "google.cloud.aiplatform.v1.PipelineService",
                        "rpcName": "BatchDeletePipelineJobs",
                        "httpRequest": http_request,
                        "metadata": http_request["headers"],
                    },
                )

            # Send the request
            response = (
                PipelineServiceRestTransport._BatchDeletePipelineJobs._get_response(
                    self._host,
                    metadata,
                    query_params,
                    self._session,
                    timeout,
                    transcoded_request,
                    body,
                )
            )

            # In case of error, raise the appropriate core_exceptions.GoogleAPICallError exception
            # subclass.
            if response.status_code >= 400:
                raise core_exceptions.from_http_response(response)

            # Return the response
            resp = operations_pb2.Operation()
            json_format.Parse(response.content, resp, ignore_unknown_fields=True)

            resp = self._interceptor.post_batch_delete_pipeline_jobs(resp)
            response_metadata = [(k, str(v)) for k, v in response.headers.items()]
            resp, _ = self._interceptor.post_batch_delete_pipeline_jobs_with_metadata(
                resp, response_metadata
            )
            if CLIENT_LOGGING_SUPPORTED and _LOGGER.isEnabledFor(
                logging.DEBUG
            ):  # pragma: NO COVER
                try:
                    response_payload = json_format.MessageToJson(resp)
                except:
                    response_payload = None
                http_response = {
                    "payload": response_payload,
                    "headers": dict(response.headers),
                    "status": response.status_code,
                }
                _LOGGER.debug(
                    "Received response for google.cloud.aiplatform_v1.PipelineServiceClient.batch_delete_pipeline_jobs",
                    extra={
                        "serviceName": "google.cloud.aiplatform.v1.PipelineService",
                        "rpcName": "BatchDeletePipelineJobs",
                        "metadata": http_response["headers"],
                        "httpResponse": http_response,
                    },
                )
            return resp

    class _CancelPipelineJob(
        _BasePipelineServiceRestTransport._BaseCancelPipelineJob,
        PipelineServiceRestStub,
    ):
        def __hash__(self):
            return hash("PipelineServiceRestTransport.CancelPipelineJob")

        @staticmethod
        def _get_response(
            host,
            metadata,
            query_params,
            session,
            timeout,
            transcoded_request,
            body=None,
        ):

            uri = transcoded_request["uri"]
            method = transcoded_request["method"]
            headers = dict(metadata)
            headers["Content-Type"] = "application/json"
            response = getattr(session, method)(
                "{host}{uri}".format(host=host, uri=uri),
                timeout=timeout,
                headers=headers,
                params=rest_helpers.flatten_query_params(query_params, strict=True),
                data=body,
            )
            return response

        def __call__(
            self,
            request: pipeline_service.CancelPipelineJobRequest,
            *,
            retry: OptionalRetry = gapic_v1.method.DEFAULT,
            timeout: Optional[float] = None,
            metadata: Sequence[Tuple[str, Union[str, bytes]]] = (),
        ):
            r"""Call the cancel pipeline job method over HTTP.

            Args:
                request (~.pipeline_service.CancelPipelineJobRequest):
                    The request object. Request message for
                [PipelineService.CancelPipelineJob][google.cloud.aiplatform.v1.PipelineService.CancelPipelineJob].
                retry (google.api_core.retry.Retry): Designation of what errors, if any,
                    should be retried.
                timeout (float): The timeout for this request.
                metadata (Sequence[Tuple[str, 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`.
            """

            http_options = (
                _BasePipelineServiceRestTransport._BaseCancelPipelineJob._get_http_options()
            )

            request, metadata = self._interceptor.pre_cancel_pipeline_job(
                request, metadata
            )
            transcoded_request = _BasePipelineServiceRestTransport._BaseCancelPipelineJob._get_transcoded_request(
                http_options, request
            )

            body = _BasePipelineServiceRestTransport._BaseCancelPipelineJob._get_request_body_json(
                transcoded_request
            )

            # Jsonify the query params
            query_params = _BasePipelineServiceRestTransport._BaseCancelPipelineJob._get_query_params_json(
                transcoded_request
            )

            if CLIENT_LOGGING_SUPPORTED and _LOGGER.isEnabledFor(
                logging.DEBUG
            ):  # pragma: NO COVER
                request_url = "{host}{uri}".format(
                    host=self._host, uri=transcoded_request["uri"]
                )
                method = transcoded_request["method"]
                try:
                    request_payload = json_format.MessageToJson(request)
                except:
                    request_payload = None
                http_request = {
                    "payload": request_payload,
                    "requestMethod": method,
                    "requestUrl": request_url,
                    "headers": dict(metadata),
                }
                _LOGGER.debug(
                    f"Sending request for google.cloud.aiplatform_v1.PipelineServiceClient.CancelPipelineJob",
                    extra={
                        "serviceName": "google.cloud.aiplatform.v1.PipelineService",
                        "rpcName": "CancelPipelineJob",
                        "httpRequest": http_request,
                        "metadata": http_request["headers"],
                    },
                )

            # Send the request
            response = PipelineServiceRestTransport._CancelPipelineJob._get_response(
                self._host,
                metadata,
                query_params,
                self._session,
                timeout,
                transcoded_request,
                body,
            )

            # In case of error, raise the appropriate core_exceptions.GoogleAPICallError exception
            # subclass.
            if response.status_code >= 400:
                raise core_exceptions.from_http_response(response)

    class _CancelTrainingPipeline(
        _BasePipelineServiceRestTransport._BaseCancelTrainingPipeline,
        PipelineServiceRestStub,
    ):
        def __hash__(self):
            return hash("PipelineServiceRestTransport.CancelTrainingPipeline")

        @staticmethod
        def _get_response(
            host,
            metadata,
            query_params,
            session,
            timeout,
            transcoded_request,
            body=None,
        ):

            uri = transcoded_request["uri"]
            method = transcoded_request["method"]
            headers = dict(metadata)
            headers["Content-Type"] = "application/json"
            response = getattr(session, method)(
                "{host}{uri}".format(host=host, uri=uri),
                timeout=timeout,
                headers=headers,
                params=rest_helpers.flatten_query_params(query_params, strict=True),
                data=body,
            )
            return response

        def __call__(
            self,
            request: pipeline_service.CancelTrainingPipelineRequest,
            *,
            retry: OptionalRetry = gapic_v1.method.DEFAULT,
            timeout: Optional[float] = None,
            metadata: Sequence[Tuple[str, Union[str, bytes]]] = (),
        ):
            r"""Call the cancel training pipeline method over HTTP.

            Args:
                request (~.pipeline_service.CancelTrainingPipelineRequest):
                    The request object. Request message for
                [PipelineService.CancelTrainingPipeline][google.cloud.aiplatform.v1.PipelineService.CancelTrainingPipeline].
                retry (google.api_core.retry.Retry): Designation of what errors, if any,
                    should be retried.
                timeout (float): The timeout for this request.
                metadata (Sequence[Tuple[str, 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`.
            """

            http_options = (
                _BasePipelineServiceRestTransport._BaseCancelTrainingPipeline._get_http_options()
            )

            request, metadata = self._interceptor.pre_cancel_training_pipeline(
                request, metadata
            )
            transcoded_request = _BasePipelineServiceRestTransport._BaseCancelTrainingPipeline._get_transcoded_request(
                http_options, request
            )

            body = _BasePipelineServiceRestTransport._BaseCancelTrainingPipeline._get_request_body_json(
                transcoded_request
            )

            # Jsonify the query params
            query_params = _BasePipelineServiceRestTransport._BaseCancelTrainingPipeline._get_query_params_json(
                transcoded_request
            )

            if CLIENT_LOGGING_SUPPORTED and _LOGGER.isEnabledFor(
                logging.DEBUG
            ):  # pragma: NO COVER
                request_url = "{host}{uri}".format(
                    host=self._host, uri=transcoded_request["uri"]
                )
                method = transcoded_request["method"]
                try:
                    request_payload = json_format.MessageToJson(request)
                except:
                    request_payload = None
                http_request = {
                    "payload": request_payload,
                    "requestMethod": method,
                    "requestUrl": request_url,
                    "headers": dict(metadata),
                }
                _LOGGER.debug(
                    f"Sending request for google.cloud.aiplatform_v1.PipelineServiceClient.CancelTrainingPipeline",
                    extra={
                        "serviceName": "google.cloud.aiplatform.v1.PipelineService",
                        "rpcName": "CancelTrainingPipeline",
                        "httpRequest": http_request,
                        "metadata": http_request["headers"],
                    },
                )

            # Send the request
            response = (
                PipelineServiceRestTransport._CancelTrainingPipeline._get_response(
                    self._host,
                    metadata,
                    query_params,
                    self._session,
                    timeout,
                    transcoded_request,
                    body,
                )
            )

            # In case of error, raise the appropriate core_exceptions.GoogleAPICallError exception
            # subclass.
            if response.status_code >= 400:
                raise core_exceptions.from_http_response(response)

    class _CreatePipelineJob(
        _BasePipelineServiceRestTransport._BaseCreatePipelineJob,
        PipelineServiceRestStub,
    ):
        def __hash__(self):
            return hash("PipelineServiceRestTransport.CreatePipelineJob")

        @staticmethod
        def _get_response(
            host,
            metadata,
            query_params,
            session,
            timeout,
            transcoded_request,
            body=None,
        ):

            uri = transcoded_request["uri"]
            method = transcoded_request["method"]
            headers = dict(metadata)
            headers["Content-Type"] = "application/json"
            response = getattr(session, method)(
                "{host}{uri}".format(host=host, uri=uri),
                timeout=timeout,
                headers=headers,
                params=rest_helpers.flatten_query_params(query_params, strict=True),
                data=body,
            )
            return response

        def __call__(
            self,
            request: pipeline_service.CreatePipelineJobRequest,
            *,
            retry: OptionalRetry = gapic_v1.method.DEFAULT,
            timeout: Optional[float] = None,
            metadata: Sequence[Tuple[str, Union[str, bytes]]] = (),
        ) -> gca_pipeline_job.PipelineJob:
            r"""Call the create pipeline job method over HTTP.

            Args:
                request (~.pipeline_service.CreatePipelineJobRequest):
                    The request object. Request message for
                [PipelineService.CreatePipelineJob][google.cloud.aiplatform.v1.PipelineService.CreatePipelineJob].
                retry (google.api_core.retry.Retry): Designation of what errors, if any,
                    should be retried.
                timeout (float): The timeout for this request.
                metadata (Sequence[Tuple[str, 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:
                ~.gca_pipeline_job.PipelineJob:
                    An instance of a machine learning
                PipelineJob.

            """

            http_options = (
                _BasePipelineServiceRestTransport._BaseCreatePipelineJob._get_http_options()
            )

            request, metadata = self._interceptor.pre_create_pipeline_job(
                request, metadata
            )
            transcoded_request = _BasePipelineServiceRestTransport._BaseCreatePipelineJob._get_transcoded_request(
                http_options, request
            )

            body = _BasePipelineServiceRestTransport._BaseCreatePipelineJob._get_request_body_json(
                transcoded_request
            )

            # Jsonify the query params
            query_params = _BasePipelineServiceRestTransport._BaseCreatePipelineJob._get_query_params_json(
                transcoded_request
            )

            if CLIENT_LOGGING_SUPPORTED and _LOGGER.isEnabledFor(
                logging.DEBUG
            ):  # pragma: NO COVER
                request_url = "{host}{uri}".format(
                    host=self._host, uri=transcoded_request["uri"]
                )
                method = transcoded_request["method"]
                try:
                    request_payload = type(request).to_json(request)
                except:
                    request_payload = None
                http_request = {
                    "payload": request_payload,
                    "requestMethod": method,
                    "requestUrl": request_url,
                    "headers": dict(metadata),
                }
                _LOGGER.debug(
                    f"Sending request for google.cloud.aiplatform_v1.PipelineServiceClient.CreatePipelineJob",
                    extra={
                        "serviceName": "google.cloud.aiplatform.v1.PipelineService",
                        "rpcName": "CreatePipelineJob",
                        "httpRequest": http_request,
                        "metadata": http_request["headers"],
                    },
                )

            # Send the request
            response = PipelineServiceRestTransport._CreatePipelineJob._get_response(
                self._host,
                metadata,
                query_params,
                self._session,
                timeout,
                transcoded_request,
                body,
            )

            # In case of error, raise the appropriate core_exceptions.GoogleAPICallError exception
            # subclass.
            if response.status_code >= 400:
                raise core_exceptions.from_http_response(response)

            # Return the response
            resp = gca_pipeline_job.PipelineJob()
            pb_resp = gca_pipeline_job.PipelineJob.pb(resp)

            json_format.Parse(response.content, pb_resp, ignore_unknown_fields=True)

            resp = self._interceptor.post_create_pipeline_job(resp)
            response_metadata = [(k, str(v)) for k, v in response.headers.items()]
            resp, _ = self._interceptor.post_create_pipeline_job_with_metadata(
                resp, response_metadata
            )
            if CLIENT_LOGGING_SUPPORTED and _LOGGER.isEnabledFor(
                logging.DEBUG
            ):  # pragma: NO COVER
                try:
                    response_payload = gca_pipeline_job.PipelineJob.to_json(response)
                except:
                    response_payload = None
                http_response = {
                    "payload": response_payload,
                    "headers": dict(response.headers),
                    "status": response.status_code,
                }
                _LOGGER.debug(
                    "Received response for google.cloud.aiplatform_v1.PipelineServiceClient.create_pipeline_job",
                    extra={
                        "serviceName": "google.cloud.aiplatform.v1.PipelineService",
                        "rpcName": "CreatePipelineJob",
                        "metadata": http_response["headers"],
                        "httpResponse": http_response,
                    },
                )
            return resp

    class _CreateTrainingPipeline(
        _BasePipelineServiceRestTransport._BaseCreateTrainingPipeline,
        PipelineServiceRestStub,
    ):
        def __hash__(self):
            return hash("PipelineServiceRestTransport.CreateTrainingPipeline")

        @staticmethod
        def _get_response(
            host,
            metadata,
            query_params,
            session,
            timeout,
            transcoded_request,
            body=None,
        ):

            uri = transcoded_request["uri"]
            method = transcoded_request["method"]
            headers = dict(metadata)
            headers["Content-Type"] = "application/json"
            response = getattr(session, method)(
                "{host}{uri}".format(host=host, uri=uri),
                timeout=timeout,
                headers=headers,
                params=rest_helpers.flatten_query_params(query_params, strict=True),
                data=body,
            )
            return response

        def __call__(
            self,
            request: pipeline_service.CreateTrainingPipelineRequest,
            *,
            retry: OptionalRetry = gapic_v1.method.DEFAULT,
            timeout: Optional[float] = None,
            metadata: Sequence[Tuple[str, Union[str, bytes]]] = (),
        ) -> gca_training_pipeline.TrainingPipeline:
            r"""Call the create training pipeline method over HTTP.

            Args:
                request (~.pipeline_service.CreateTrainingPipelineRequest):
                    The request object. Request message for
                [PipelineService.CreateTrainingPipeline][google.cloud.aiplatform.v1.PipelineService.CreateTrainingPipeline].
                retry (google.api_core.retry.Retry): Designation of what errors, if any,
                    should be retried.
                timeout (float): The timeout for this request.
                metadata (Sequence[Tuple[str, 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:
                ~.gca_training_pipeline.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.v1.ModelService.UploadModel]
                the Model to Vertex AI, and evaluate the Model.

            """

            http_options = (
                _BasePipelineServiceRestTransport._BaseCreateTrainingPipeline._get_http_options()
            )

            request, metadata = self._interceptor.pre_create_training_pipeline(
                request, metadata
            )
            transcoded_request = _BasePipelineServiceRestTransport._BaseCreateTrainingPipeline._get_transcoded_request(
                http_options, request
            )

            body = _BasePipelineServiceRestTransport._BaseCreateTrainingPipeline._get_request_body_json(
                transcoded_request
            )

            # Jsonify the query params
            query_params = _BasePipelineServiceRestTransport._BaseCreateTrainingPipeline._get_query_params_json(
                transcoded_request
            )

            if CLIENT_LOGGING_SUPPORTED and _LOGGER.isEnabledFor(
                logging.DEBUG
            ):  # pragma: NO COVER
                request_url = "{host}{uri}".format(
                    host=self._host, uri=transcoded_request["uri"]
                )
                method = transcoded_request["method"]
                try:
                    request_payload = type(request).to_json(request)
                except:
                    request_payload = None
                http_request = {
                    "payload": request_payload,
                    "requestMethod": method,
                    "requestUrl": request_url,
                    "headers": dict(metadata),
                }
                _LOGGER.debug(
                    f"Sending request for google.cloud.aiplatform_v1.PipelineServiceClient.CreateTrainingPipeline",
                    extra={
                        "serviceName": "google.cloud.aiplatform.v1.PipelineService",
                        "rpcName": "CreateTrainingPipeline",
                        "httpRequest": http_request,
                        "metadata": http_request["headers"],
                    },
                )

            # Send the request
            response = (
                PipelineServiceRestTransport._CreateTrainingPipeline._get_response(
                    self._host,
                    metadata,
                    query_params,
                    self._session,
                    timeout,
                    transcoded_request,
                    body,
                )
            )

            # In case of error, raise the appropriate core_exceptions.GoogleAPICallError exception
            # subclass.
            if response.status_code >= 400:
                raise core_exceptions.from_http_response(response)

            # Return the response
            resp = gca_training_pipeline.TrainingPipeline()
            pb_resp = gca_training_pipeline.TrainingPipeline.pb(resp)

            json_format.Parse(response.content, pb_resp, ignore_unknown_fields=True)

            resp = self._interceptor.post_create_training_pipeline(resp)
            response_metadata = [(k, str(v)) for k, v in response.headers.items()]
            resp, _ = self._interceptor.post_create_training_pipeline_with_metadata(
                resp, response_metadata
            )
            if CLIENT_LOGGING_SUPPORTED and _LOGGER.isEnabledFor(
                logging.DEBUG
            ):  # pragma: NO COVER
                try:
                    response_payload = gca_training_pipeline.TrainingPipeline.to_json(
                        response
                    )
                except:
                    response_payload = None
                http_response = {
                    "payload": response_payload,
                    "headers": dict(response.headers),
                    "status": response.status_code,
                }
                _LOGGER.debug(
                    "Received response for google.cloud.aiplatform_v1.PipelineServiceClient.create_training_pipeline",
                    extra={
                        "serviceName": "google.cloud.aiplatform.v1.PipelineService",
                        "rpcName": "CreateTrainingPipeline",
                        "metadata": http_response["headers"],
                        "httpResponse": http_response,
                    },
                )
            return resp

    class _DeletePipelineJob(
        _BasePipelineServiceRestTransport._BaseDeletePipelineJob,
        PipelineServiceRestStub,
    ):
        def __hash__(self):
            return hash("PipelineServiceRestTransport.DeletePipelineJob")

        @staticmethod
        def _get_response(
            host,
            metadata,
            query_params,
            session,
            timeout,
            transcoded_request,
            body=None,
        ):

            uri = transcoded_request["uri"]
            method = transcoded_request["method"]
            headers = dict(metadata)
            headers["Content-Type"] = "application/json"
            response = getattr(session, method)(
                "{host}{uri}".format(host=host, uri=uri),
                timeout=timeout,
                headers=headers,
                params=rest_helpers.flatten_query_params(query_params, strict=True),
            )
            return response

        def __call__(
            self,
            request: pipeline_service.DeletePipelineJobRequest,
            *,
            retry: OptionalRetry = gapic_v1.method.DEFAULT,
            timeout: Optional[float] = None,
            metadata: Sequence[Tuple[str, Union[str, bytes]]] = (),
        ) -> operations_pb2.Operation:
            r"""Call the delete pipeline job method over HTTP.

            Args:
                request (~.pipeline_service.DeletePipelineJobRequest):
                    The request object. Request message for
                [PipelineService.DeletePipelineJob][google.cloud.aiplatform.v1.PipelineService.DeletePipelineJob].
                retry (google.api_core.retry.Retry): Designation of what errors, if any,
                    should be retried.
                timeout (float): The timeout for this request.
                metadata (Sequence[Tuple[str, 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:
                    This resource represents a
                long-running operation that is the
                result of a network API call.

            """

            http_options = (
                _BasePipelineServiceRestTransport._BaseDeletePipelineJob._get_http_options()
            )

            request, metadata = self._interceptor.pre_delete_pipeline_job(
                request, metadata
            )
            transcoded_request = _BasePipelineServiceRestTransport._BaseDeletePipelineJob._get_transcoded_request(
                http_options, request
            )

            # Jsonify the query params
            query_params = _BasePipelineServiceRestTransport._BaseDeletePipelineJob._get_query_params_json(
                transcoded_request
            )

            if CLIENT_LOGGING_SUPPORTED and _LOGGER.isEnabledFor(
                logging.DEBUG
            ):  # pragma: NO COVER
                request_url = "{host}{uri}".format(
                    host=self._host, uri=transcoded_request["uri"]
                )
                method = transcoded_request["method"]
                try:
                    request_payload = json_format.MessageToJson(request)
                except:
                    request_payload = None
                http_request = {
                    "payload": request_payload,
                    "requestMethod": method,
                    "requestUrl": request_url,
                    "headers": dict(metadata),
                }
                _LOGGER.debug(
                    f"Sending request for google.cloud.aiplatform_v1.PipelineServiceClient.DeletePipelineJob",
                    extra={
                        "serviceName": "google.cloud.aiplatform.v1.PipelineService",
                        "rpcName": "DeletePipelineJob",
                        "httpRequest": http_request,
                        "metadata": http_request["headers"],
                    },
                )

            # Send the request
            response = PipelineServiceRestTransport._DeletePipelineJob._get_response(
                self._host,
                metadata,
                query_params,
                self._session,
                timeout,
                transcoded_request,
            )

            # In case of error, raise the appropriate core_exceptions.GoogleAPICallError exception
            # subclass.
            if response.status_code >= 400:
                raise core_exceptions.from_http_response(response)

            # Return the response
            resp = operations_pb2.Operation()
            json_format.Parse(response.content, resp, ignore_unknown_fields=True)

            resp = self._interceptor.post_delete_pipeline_job(resp)
            response_metadata = [(k, str(v)) for k, v in response.headers.items()]
            resp, _ = self._interceptor.post_delete_pipeline_job_with_metadata(
                resp, response_metadata
            )
            if CLIENT_LOGGING_SUPPORTED and _LOGGER.isEnabledFor(
                logging.DEBUG
            ):  # pragma: NO COVER
                try:
                    response_payload = json_format.MessageToJson(resp)
                except:
                    response_payload = None
                http_response = {
                    "payload": response_payload,
                    "headers": dict(response.headers),
                    "status": response.status_code,
                }
                _LOGGER.debug(
                    "Received response for google.cloud.aiplatform_v1.PipelineServiceClient.delete_pipeline_job",
                    extra={
                        "serviceName": "google.cloud.aiplatform.v1.PipelineService",
                        "rpcName": "DeletePipelineJob",
                        "metadata": http_response["headers"],
                        "httpResponse": http_response,
                    },
                )
            return resp

    class _DeleteTrainingPipeline(
        _BasePipelineServiceRestTransport._BaseDeleteTrainingPipeline,
        PipelineServiceRestStub,
    ):
        def __hash__(self):
            return hash("PipelineServiceRestTransport.DeleteTrainingPipeline")

        @staticmethod
        def _get_response(
            host,
            metadata,
            query_params,
            session,
            timeout,
            transcoded_request,
            body=None,
        ):

            uri = transcoded_request["uri"]
            method = transcoded_request["method"]
            headers = dict(metadata)
            headers["Content-Type"] = "application/json"
            response = getattr(session, method)(
                "{host}{uri}".format(host=host, uri=uri),
                timeout=timeout,
                headers=headers,
                params=rest_helpers.flatten_query_params(query_params, strict=True),
            )
            return response

        def __call__(
            self,
            request: pipeline_service.DeleteTrainingPipelineRequest,
            *,
            retry: OptionalRetry = gapic_v1.method.DEFAULT,
            timeout: Optional[float] = None,
            metadata: Sequence[Tuple[str, Union[str, bytes]]] = (),
        ) -> operations_pb2.Operation:
            r"""Call the delete training pipeline method over HTTP.

            Args:
                request (~.pipeline_service.DeleteTrainingPipelineRequest):
                    The request object. Request message for
                [PipelineService.DeleteTrainingPipeline][google.cloud.aiplatform.v1.PipelineService.DeleteTrainingPipeline].
                retry (google.api_core.retry.Retry): Designation of what errors, if any,
                    should be retried.
                timeout (float): The timeout for this request.
                metadata (Sequence[Tuple[str, 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:
                    This resource represents a
                long-running operation that is the
                result of a network API call.

            """

            http_options = (
                _BasePipelineServiceRestTransport._BaseDeleteTrainingPipeline._get_http_options()
            )

            request, metadata = self._interceptor.pre_delete_training_pipeline(
                request, metadata
            )
            transcoded_request = _BasePipelineServiceRestTransport._BaseDeleteTrainingPipeline._get_transcoded_request(
                http_options, request
            )

            # Jsonify the query params
            query_params = _BasePipelineServiceRestTransport._BaseDeleteTrainingPipeline._get_query_params_json(
                transcoded_request
            )

            if CLIENT_LOGGING_SUPPORTED and _LOGGER.isEnabledFor(
                logging.DEBUG
            ):  # pragma: NO COVER
                request_url = "{host}{uri}".format(
                    host=self._host, uri=transcoded_request["uri"]
                )
                method = transcoded_request["method"]
                try:
                    request_payload = json_format.MessageToJson(request)
                except:
                    request_payload = None
                http_request = {
                    "payload": request_payload,
                    "requestMethod": method,
                    "requestUrl": request_url,
                    "headers": dict(metadata),
                }
                _LOGGER.debug(
                    f"Sending request for google.cloud.aiplatform_v1.PipelineServiceClient.DeleteTrainingPipeline",
                    extra={
                        "serviceName": "google.cloud.aiplatform.v1.PipelineService",
                        "rpcName": "DeleteTrainingPipeline",
                        "httpRequest": http_request,
                        "metadata": http_request["headers"],
                    },
                )

            # Send the request
            response = (
                PipelineServiceRestTransport._DeleteTrainingPipeline._get_response(
                    self._host,
                    metadata,
                    query_params,
                    self._session,
                    timeout,
                    transcoded_request,
                )
            )

            # In case of error, raise the appropriate core_exceptions.GoogleAPICallError exception
            # subclass.
            if response.status_code >= 400:
                raise core_exceptions.from_http_response(response)

            # Return the response
            resp = operations_pb2.Operation()
            json_format.Parse(response.content, resp, ignore_unknown_fields=True)

            resp = self._interceptor.post_delete_training_pipeline(resp)
            response_metadata = [(k, str(v)) for k, v in response.headers.items()]
            resp, _ = self._interceptor.post_delete_training_pipeline_with_metadata(
                resp, response_metadata
            )
            if CLIENT_LOGGING_SUPPORTED and _LOGGER.isEnabledFor(
                logging.DEBUG
            ):  # pragma: NO COVER
                try:
                    response_payload = json_format.MessageToJson(resp)
                except:
                    response_payload = None
                http_response = {
                    "payload": response_payload,
                    "headers": dict(response.headers),
                    "status": response.status_code,
                }
                _LOGGER.debug(
                    "Received response for google.cloud.aiplatform_v1.PipelineServiceClient.delete_training_pipeline",
                    extra={
                        "serviceName": "google.cloud.aiplatform.v1.PipelineService",
                        "rpcName": "DeleteTrainingPipeline",
                        "metadata": http_response["headers"],
                        "httpResponse": http_response,
                    },
                )
            return resp

    class _GetPipelineJob(
        _BasePipelineServiceRestTransport._BaseGetPipelineJob, PipelineServiceRestStub
    ):
        def __hash__(self):
            return hash("PipelineServiceRestTransport.GetPipelineJob")

        @staticmethod
        def _get_response(
            host,
            metadata,
            query_params,
            session,
            timeout,
            transcoded_request,
            body=None,
        ):

            uri = transcoded_request["uri"]
            method = transcoded_request["method"]
            headers = dict(metadata)
            headers["Content-Type"] = "application/json"
            response = getattr(session, method)(
                "{host}{uri}".format(host=host, uri=uri),
                timeout=timeout,
                headers=headers,
                params=rest_helpers.flatten_query_params(query_params, strict=True),
            )
            return response

        def __call__(
            self,
            request: pipeline_service.GetPipelineJobRequest,
            *,
            retry: OptionalRetry = gapic_v1.method.DEFAULT,
            timeout: Optional[float] = None,
            metadata: Sequence[Tuple[str, Union[str, bytes]]] = (),
        ) -> pipeline_job.PipelineJob:
            r"""Call the get pipeline job method over HTTP.

            Args:
                request (~.pipeline_service.GetPipelineJobRequest):
                    The request object. Request message for
                [PipelineService.GetPipelineJob][google.cloud.aiplatform.v1.PipelineService.GetPipelineJob].
                retry (google.api_core.retry.Retry): Designation of what errors, if any,
                    should be retried.
                timeout (float): The timeout for this request.
                metadata (Sequence[Tuple[str, 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:
                ~.pipeline_job.PipelineJob:
                    An instance of a machine learning
                PipelineJob.

            """

            http_options = (
                _BasePipelineServiceRestTransport._BaseGetPipelineJob._get_http_options()
            )

            request, metadata = self._interceptor.pre_get_pipeline_job(
                request, metadata
            )
            transcoded_request = _BasePipelineServiceRestTransport._BaseGetPipelineJob._get_transcoded_request(
                http_options, request
            )

            # Jsonify the query params
            query_params = _BasePipelineServiceRestTransport._BaseGetPipelineJob._get_query_params_json(
                transcoded_request
            )

            if CLIENT_LOGGING_SUPPORTED and _LOGGER.isEnabledFor(
                logging.DEBUG
            ):  # pragma: NO COVER
                request_url = "{host}{uri}".format(
                    host=self._host, uri=transcoded_request["uri"]
                )
                method = transcoded_request["method"]
                try:
                    request_payload = type(request).to_json(request)
                except:
                    request_payload = None
                http_request = {
                    "payload": request_payload,
                    "requestMethod": method,
                    "requestUrl": request_url,
                    "headers": dict(metadata),
                }
                _LOGGER.debug(
                    f"Sending request for google.cloud.aiplatform_v1.PipelineServiceClient.GetPipelineJob",
                    extra={
                        "serviceName": "google.cloud.aiplatform.v1.PipelineService",
                        "rpcName": "GetPipelineJob",
                        "httpRequest": http_request,
                        "metadata": http_request["headers"],
                    },
                )

            # Send the request
            response = PipelineServiceRestTransport._GetPipelineJob._get_response(
                self._host,
                metadata,
                query_params,
                self._session,
                timeout,
                transcoded_request,
            )

            # In case of error, raise the appropriate core_exceptions.GoogleAPICallError exception
            # subclass.
            if response.status_code >= 400:
                raise core_exceptions.from_http_response(response)

            # Return the response
            resp = pipeline_job.PipelineJob()
            pb_resp = pipeline_job.PipelineJob.pb(resp)

            json_format.Parse(response.content, pb_resp, ignore_unknown_fields=True)

            resp = self._interceptor.post_get_pipeline_job(resp)
            response_metadata = [(k, str(v)) for k, v in response.headers.items()]
            resp, _ = self._interceptor.post_get_pipeline_job_with_metadata(
                resp, response_metadata
            )
            if CLIENT_LOGGING_SUPPORTED and _LOGGER.isEnabledFor(
                logging.DEBUG
            ):  # pragma: NO COVER
                try:
                    response_payload = pipeline_job.PipelineJob.to_json(response)
                except:
                    response_payload = None
                http_response = {
                    "payload": response_payload,
                    "headers": dict(response.headers),
                    "status": response.status_code,
                }
                _LOGGER.debug(
                    "Received response for google.cloud.aiplatform_v1.PipelineServiceClient.get_pipeline_job",
                    extra={
                        "serviceName": "google.cloud.aiplatform.v1.PipelineService",
                        "rpcName": "GetPipelineJob",
                        "metadata": http_response["headers"],
                        "httpResponse": http_response,
                    },
                )
            return resp

    class _GetTrainingPipeline(
        _BasePipelineServiceRestTransport._BaseGetTrainingPipeline,
        PipelineServiceRestStub,
    ):
        def __hash__(self):
            return hash("PipelineServiceRestTransport.GetTrainingPipeline")

        @staticmethod
        def _get_response(
            host,
            metadata,
            query_params,
            session,
            timeout,
            transcoded_request,
            body=None,
        ):

            uri = transcoded_request["uri"]
            method = transcoded_request["method"]
            headers = dict(metadata)
            headers["Content-Type"] = "application/json"
            response = getattr(session, method)(
                "{host}{uri}".format(host=host, uri=uri),
                timeout=timeout,
                headers=headers,
                params=rest_helpers.flatten_query_params(query_params, strict=True),
            )
            return response

        def __call__(
            self,
            request: pipeline_service.GetTrainingPipelineRequest,
            *,
            retry: OptionalRetry = gapic_v1.method.DEFAULT,
            timeout: Optional[float] = None,
            metadata: Sequence[Tuple[str, Union[str, bytes]]] = (),
        ) -> training_pipeline.TrainingPipeline:
            r"""Call the get training pipeline method over HTTP.

            Args:
                request (~.pipeline_service.GetTrainingPipelineRequest):
                    The request object. Request message for
                [PipelineService.GetTrainingPipeline][google.cloud.aiplatform.v1.PipelineService.GetTrainingPipeline].
                retry (google.api_core.retry.Retry): Designation of what errors, if any,
                    should be retried.
                timeout (float): The timeout for this request.
                metadata (Sequence[Tuple[str, 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:
                ~.training_pipeline.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.v1.ModelService.UploadModel]
                the Model to Vertex AI, and evaluate the Model.

            """

            http_options = (
                _BasePipelineServiceRestTransport._BaseGetTrainingPipeline._get_http_options()
            )

            request, metadata = self._interceptor.pre_get_training_pipeline(
                request, metadata
            )
            transcoded_request = _BasePipelineServiceRestTransport._BaseGetTrainingPipeline._get_transcoded_request(
                http_options, request
            )

            # Jsonify the query params
            query_params = _BasePipelineServiceRestTransport._BaseGetTrainingPipeline._get_query_params_json(
                transcoded_request
            )

            if CLIENT_LOGGING_SUPPORTED and _LOGGER.isEnabledFor(
                logging.DEBUG
            ):  # pragma: NO COVER
                request_url = "{host}{uri}".format(
                    host=self._host, uri=transcoded_request["uri"]
                )
                method = transcoded_request["method"]
                try:
                    request_payload = type(request).to_json(request)
                except:
                    request_payload = None
                http_request = {
                    "payload": request_payload,
                    "requestMethod": method,
                    "requestUrl": request_url,
                    "headers": dict(metadata),
                }
                _LOGGER.debug(
                    f"Sending request for google.cloud.aiplatform_v1.PipelineServiceClient.GetTrainingPipeline",
                    extra={
                        "serviceName": "google.cloud.aiplatform.v1.PipelineService",
                        "rpcName": "GetTrainingPipeline",
                        "httpRequest": http_request,
                        "metadata": http_request["headers"],
                    },
                )

            # Send the request
            response = PipelineServiceRestTransport._GetTrainingPipeline._get_response(
                self._host,
                metadata,
                query_params,
                self._session,
                timeout,
                transcoded_request,
            )

            # In case of error, raise the appropriate core_exceptions.GoogleAPICallError exception
            # subclass.
            if response.status_code >= 400:
                raise core_exceptions.from_http_response(response)

            # Return the response
            resp = training_pipeline.TrainingPipeline()
            pb_resp = training_pipeline.TrainingPipeline.pb(resp)

            json_format.Parse(response.content, pb_resp, ignore_unknown_fields=True)

            resp = self._interceptor.post_get_training_pipeline(resp)
            response_metadata = [(k, str(v)) for k, v in response.headers.items()]
            resp, _ = self._interceptor.post_get_training_pipeline_with_metadata(
                resp, response_metadata
            )
            if CLIENT_LOGGING_SUPPORTED and _LOGGER.isEnabledFor(
                logging.DEBUG
            ):  # pragma: NO COVER
                try:
                    response_payload = training_pipeline.TrainingPipeline.to_json(
                        response
                    )
                except:
                    response_payload = None
                http_response = {
                    "payload": response_payload,
                    "headers": dict(response.headers),
                    "status": response.status_code,
                }
                _LOGGER.debug(
                    "Received response for google.cloud.aiplatform_v1.PipelineServiceClient.get_training_pipeline",
                    extra={
                        "serviceName": "google.cloud.aiplatform.v1.PipelineService",
                        "rpcName": "GetTrainingPipeline",
                        "metadata": http_response["headers"],
                        "httpResponse": http_response,
                    },
                )
            return resp

    class _ListPipelineJobs(
        _BasePipelineServiceRestTransport._BaseListPipelineJobs, PipelineServiceRestStub
    ):
        def __hash__(self):
            return hash("PipelineServiceRestTransport.ListPipelineJobs")

        @staticmethod
        def _get_response(
            host,
            metadata,
            query_params,
            session,
            timeout,
            transcoded_request,
            body=None,
        ):

            uri = transcoded_request["uri"]
            method = transcoded_request["method"]
            headers = dict(metadata)
            headers["Content-Type"] = "application/json"
            response = getattr(session, method)(
                "{host}{uri}".format(host=host, uri=uri),
                timeout=timeout,
                headers=headers,
                params=rest_helpers.flatten_query_params(query_params, strict=True),
            )
            return response

        def __call__(
            self,
            request: pipeline_service.ListPipelineJobsRequest,
            *,
            retry: OptionalRetry = gapic_v1.method.DEFAULT,
            timeout: Optional[float] = None,
            metadata: Sequence[Tuple[str, Union[str, bytes]]] = (),
        ) -> pipeline_service.ListPipelineJobsResponse:
            r"""Call the list pipeline jobs method over HTTP.

            Args:
                request (~.pipeline_service.ListPipelineJobsRequest):
                    The request object. Request message for
                [PipelineService.ListPipelineJobs][google.cloud.aiplatform.v1.PipelineService.ListPipelineJobs].
                retry (google.api_core.retry.Retry): Designation of what errors, if any,
                    should be retried.
                timeout (float): The timeout for this request.
                metadata (Sequence[Tuple[str, 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:
                ~.pipeline_service.ListPipelineJobsResponse:
                    Response message for
                [PipelineService.ListPipelineJobs][google.cloud.aiplatform.v1.PipelineService.ListPipelineJobs]

            """

            http_options = (
                _BasePipelineServiceRestTransport._BaseListPipelineJobs._get_http_options()
            )

            request, metadata = self._interceptor.pre_list_pipeline_jobs(
                request, metadata
            )
            transcoded_request = _BasePipelineServiceRestTransport._BaseListPipelineJobs._get_transcoded_request(
                http_options, request
            )

            # Jsonify the query params
            query_params = _BasePipelineServiceRestTransport._BaseListPipelineJobs._get_query_params_json(
                transcoded_request
            )

            if CLIENT_LOGGING_SUPPORTED and _LOGGER.isEnabledFor(
                logging.DEBUG
            ):  # pragma: NO COVER
                request_url = "{host}{uri}".format(
                    host=self._host, uri=transcoded_request["uri"]
                )
                method = transcoded_request["method"]
                try:
                    request_payload = type(request).to_json(request)
                except:
                    request_payload = None
                http_request = {
                    "payload": request_payload,
                    "requestMethod": method,
                    "requestUrl": request_url,
                    "headers": dict(metadata),
                }
                _LOGGER.debug(
                    f"Sending request for google.cloud.aiplatform_v1.PipelineServiceClient.ListPipelineJobs",
                    extra={
                        "serviceName": "google.cloud.aiplatform.v1.PipelineService",
                        "rpcName": "ListPipelineJobs",
                        "httpRequest": http_request,
                        "metadata": http_request["headers"],
                    },
                )

            # Send the request
            response = PipelineServiceRestTransport._ListPipelineJobs._get_response(
                self._host,
                metadata,
                query_params,
                self._session,
                timeout,
                transcoded_request,
            )

            # In case of error, raise the appropriate core_exceptions.GoogleAPICallError exception
            # subclass.
            if response.status_code >= 400:
                raise core_exceptions.from_http_response(response)

            # Return the response
            resp = pipeline_service.ListPipelineJobsResponse()
            pb_resp = pipeline_service.ListPipelineJobsResponse.pb(resp)

            json_format.Parse(response.content, pb_resp, ignore_unknown_fields=True)

            resp = self._interceptor.post_list_pipeline_jobs(resp)
            response_metadata = [(k, str(v)) for k, v in response.headers.items()]
            resp, _ = self._interceptor.post_list_pipeline_jobs_with_metadata(
                resp, response_metadata
            )
            if CLIENT_LOGGING_SUPPORTED and _LOGGER.isEnabledFor(
                logging.DEBUG
            ):  # pragma: NO COVER
                try:
                    response_payload = (
                        pipeline_service.ListPipelineJobsResponse.to_json(response)
                    )
                except:
                    response_payload = None
                http_response = {
                    "payload": response_payload,
                    "headers": dict(response.headers),
                    "status": response.status_code,
                }
                _LOGGER.debug(
                    "Received response for google.cloud.aiplatform_v1.PipelineServiceClient.list_pipeline_jobs",
                    extra={
                        "serviceName": "google.cloud.aiplatform.v1.PipelineService",
                        "rpcName": "ListPipelineJobs",
                        "metadata": http_response["headers"],
                        "httpResponse": http_response,
                    },
                )
            return resp

    class _ListTrainingPipelines(
        _BasePipelineServiceRestTransport._BaseListTrainingPipelines,
        PipelineServiceRestStub,
    ):
        def __hash__(self):
            return hash("PipelineServiceRestTransport.ListTrainingPipelines")

        @staticmethod
        def _get_response(
            host,
            metadata,
            query_params,
            session,
            timeout,
            transcoded_request,
            body=None,
        ):

            uri = transcoded_request["uri"]
            method = transcoded_request["method"]
            headers = dict(metadata)
            headers["Content-Type"] = "application/json"
            response = getattr(session, method)(
                "{host}{uri}".format(host=host, uri=uri),
                timeout=timeout,
                headers=headers,
                params=rest_helpers.flatten_query_params(query_params, strict=True),
            )
            return response

        def __call__(
            self,
            request: pipeline_service.ListTrainingPipelinesRequest,
            *,
            retry: OptionalRetry = gapic_v1.method.DEFAULT,
            timeout: Optional[float] = None,
            metadata: Sequence[Tuple[str, Union[str, bytes]]] = (),
        ) -> pipeline_service.ListTrainingPipelinesResponse:
            r"""Call the list training pipelines method over HTTP.

            Args:
                request (~.pipeline_service.ListTrainingPipelinesRequest):
                    The request object. Request message for
                [PipelineService.ListTrainingPipelines][google.cloud.aiplatform.v1.PipelineService.ListTrainingPipelines].
                retry (google.api_core.retry.Retry): Designation of what errors, if any,
                    should be retried.
                timeout (float): The timeout for this request.
                metadata (Sequence[Tuple[str, 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:
                ~.pipeline_service.ListTrainingPipelinesResponse:
                    Response message for
                [PipelineService.ListTrainingPipelines][google.cloud.aiplatform.v1.PipelineService.ListTrainingPipelines]

            """

            http_options = (
                _BasePipelineServiceRestTransport._BaseListTrainingPipelines._get_http_options()
            )

            request, metadata = self._interceptor.pre_list_training_pipelines(
                request, metadata
            )
            transcoded_request = _BasePipelineServiceRestTransport._BaseListTrainingPipelines._get_transcoded_request(
                http_options, request
            )

            # Jsonify the query params
            query_params = _BasePipelineServiceRestTransport._BaseListTrainingPipelines._get_query_params_json(
                transcoded_request
            )

            if CLIENT_LOGGING_SUPPORTED and _LOGGER.isEnabledFor(
                logging.DEBUG
            ):  # pragma: NO COVER
                request_url = "{host}{uri}".format(
                    host=self._host, uri=transcoded_request["uri"]
                )
                method = transcoded_request["method"]
                try:
                    request_payload = type(request).to_json(request)
                except:
                    request_payload = None
                http_request = {
                    "payload": request_payload,
                    "requestMethod": method,
                    "requestUrl": request_url,
                    "headers": dict(metadata),
                }
                _LOGGER.debug(
                    f"Sending request for google.cloud.aiplatform_v1.PipelineServiceClient.ListTrainingPipelines",
                    extra={
                        "serviceName": "google.cloud.aiplatform.v1.PipelineService",
                        "rpcName": "ListTrainingPipelines",
                        "httpRequest": http_request,
                        "metadata": http_request["headers"],
                    },
                )

            # Send the request
            response = (
                PipelineServiceRestTransport._ListTrainingPipelines._get_response(
                    self._host,
                    metadata,
                    query_params,
                    self._session,
                    timeout,
                    transcoded_request,
                )
            )

            # In case of error, raise the appropriate core_exceptions.GoogleAPICallError exception
            # subclass.
            if response.status_code >= 400:
                raise core_exceptions.from_http_response(response)

            # Return the response
            resp = pipeline_service.ListTrainingPipelinesResponse()
            pb_resp = pipeline_service.ListTrainingPipelinesResponse.pb(resp)

            json_format.Parse(response.content, pb_resp, ignore_unknown_fields=True)

            resp = self._interceptor.post_list_training_pipelines(resp)
            response_metadata = [(k, str(v)) for k, v in response.headers.items()]
            resp, _ = self._interceptor.post_list_training_pipelines_with_metadata(
                resp, response_metadata
            )
            if CLIENT_LOGGING_SUPPORTED and _LOGGER.isEnabledFor(
                logging.DEBUG
            ):  # pragma: NO COVER
                try:
                    response_payload = (
                        pipeline_service.ListTrainingPipelinesResponse.to_json(response)
                    )
                except:
                    response_payload = None
                http_response = {
                    "payload": response_payload,
                    "headers": dict(response.headers),
                    "status": response.status_code,
                }
                _LOGGER.debug(
                    "Received response for google.cloud.aiplatform_v1.PipelineServiceClient.list_training_pipelines",
                    extra={
                        "serviceName": "google.cloud.aiplatform.v1.PipelineService",
                        "rpcName": "ListTrainingPipelines",
                        "metadata": http_response["headers"],
                        "httpResponse": http_response,
                    },
                )
            return resp

    @property
    def batch_cancel_pipeline_jobs(
        self,
    ) -> Callable[
        [pipeline_service.BatchCancelPipelineJobsRequest], operations_pb2.Operation
    ]:
        # The return type is fine, but mypy isn't sophisticated enough to determine what's going on here.
        # In C++ this would require a dynamic_cast
        return self._BatchCancelPipelineJobs(self._session, self._host, self._interceptor)  # type: ignore

    @property
    def batch_delete_pipeline_jobs(
        self,
    ) -> Callable[
        [pipeline_service.BatchDeletePipelineJobsRequest], operations_pb2.Operation
    ]:
        # The return type is fine, but mypy isn't sophisticated enough to determine what's going on here.
        # In C++ this would require a dynamic_cast
        return self._BatchDeletePipelineJobs(self._session, self._host, self._interceptor)  # type: ignore

    @property
    def cancel_pipeline_job(
        self,
    ) -> Callable[[pipeline_service.CancelPipelineJobRequest], empty_pb2.Empty]:
        # The return type is fine, but mypy isn't sophisticated enough to determine what's going on here.
        # In C++ this would require a dynamic_cast
        return self._CancelPipelineJob(self._session, self._host, self._interceptor)  # type: ignore

    @property
    def cancel_training_pipeline(
        self,
    ) -> Callable[[pipeline_service.CancelTrainingPipelineRequest], empty_pb2.Empty]:
        # The return type is fine, but mypy isn't sophisticated enough to determine what's going on here.
        # In C++ this would require a dynamic_cast
        return self._CancelTrainingPipeline(self._session, self._host, self._interceptor)  # type: ignore

    @property
    def create_pipeline_job(
        self,
    ) -> Callable[
        [pipeline_service.CreatePipelineJobRequest], gca_pipeline_job.PipelineJob
    ]:
        # The return type is fine, but mypy isn't sophisticated enough to determine what's going on here.
        # In C++ this would require a dynamic_cast
        return self._CreatePipelineJob(self._session, self._host, self._interceptor)  # type: ignore

    @property
    def create_training_pipeline(
        self,
    ) -> Callable[
        [pipeline_service.CreateTrainingPipelineRequest],
        gca_training_pipeline.TrainingPipeline,
    ]:
        # The return type is fine, but mypy isn't sophisticated enough to determine what's going on here.
        # In C++ this would require a dynamic_cast
        return self._CreateTrainingPipeline(self._session, self._host, self._interceptor)  # type: ignore

    @property
    def delete_pipeline_job(
        self,
    ) -> Callable[
        [pipeline_service.DeletePipelineJobRequest], operations_pb2.Operation
    ]:
        # The return type is fine, but mypy isn't sophisticated enough to determine what's going on here.
        # In C++ this would require a dynamic_cast
        return self._DeletePipelineJob(self._session, self._host, self._interceptor)  # type: ignore

    @property
    def delete_training_pipeline(
        self,
    ) -> Callable[
        [pipeline_service.DeleteTrainingPipelineRequest], operations_pb2.Operation
    ]:
        # The return type is fine, but mypy isn't sophisticated enough to determine what's going on here.
        # In C++ this would require a dynamic_cast
        return self._DeleteTrainingPipeline(self._session, self._host, self._interceptor)  # type: ignore

    @property
    def get_pipeline_job(
        self,
    ) -> Callable[[pipeline_service.GetPipelineJobRequest], pipeline_job.PipelineJob]:
        # The return type is fine, but mypy isn't sophisticated enough to determine what's going on here.
        # In C++ this would require a dynamic_cast
        return self._GetPipelineJob(self._session, self._host, self._interceptor)  # type: ignore

    @property
    def get_training_pipeline(
        self,
    ) -> Callable[
        [pipeline_service.GetTrainingPipelineRequest],
        training_pipeline.TrainingPipeline,
    ]:
        # The return type is fine, but mypy isn't sophisticated enough to determine what's going on here.
        # In C++ this would require a dynamic_cast
        return self._GetTrainingPipeline(self._session, self._host, self._interceptor)  # type: ignore

    @property
    def list_pipeline_jobs(
        self,
    ) -> Callable[
        [pipeline_service.ListPipelineJobsRequest],
        pipeline_service.ListPipelineJobsResponse,
    ]:
        # The return type is fine, but mypy isn't sophisticated enough to determine what's going on here.
        # In C++ this would require a dynamic_cast
        return self._ListPipelineJobs(self._session, self._host, self._interceptor)  # type: ignore

    @property
    def list_training_pipelines(
        self,
    ) -> Callable[
        [pipeline_service.ListTrainingPipelinesRequest],
        pipeline_service.ListTrainingPipelinesResponse,
    ]:
        # The return type is fine, but mypy isn't sophisticated enough to determine what's going on here.
        # In C++ this would require a dynamic_cast
        return self._ListTrainingPipelines(self._session, self._host, self._interceptor)  # type: ignore

    @property
    def get_location(self):
        return self._GetLocation(self._session, self._host, self._interceptor)  # type: ignore

    class _GetLocation(
        _BasePipelineServiceRestTransport._BaseGetLocation, PipelineServiceRestStub
    ):
        def __hash__(self):
            return hash("PipelineServiceRestTransport.GetLocation")

        @staticmethod
        def _get_response(
            host,
            metadata,
            query_params,
            session,
            timeout,
            transcoded_request,
            body=None,
        ):

            uri = transcoded_request["uri"]
            method = transcoded_request["method"]
            headers = dict(metadata)
            headers["Content-Type"] = "application/json"
            response = getattr(session, method)(
                "{host}{uri}".format(host=host, uri=uri),
                timeout=timeout,
                headers=headers,
                params=rest_helpers.flatten_query_params(query_params, strict=True),
            )
            return response

        def __call__(
            self,
            request: locations_pb2.GetLocationRequest,
            *,
            retry: OptionalRetry = gapic_v1.method.DEFAULT,
            timeout: Optional[float] = None,
            metadata: Sequence[Tuple[str, Union[str, bytes]]] = (),
        ) -> locations_pb2.Location:
            r"""Call the get location method over HTTP.

            Args:
                request (locations_pb2.GetLocationRequest):
                    The request object for GetLocation method.
                retry (google.api_core.retry.Retry): Designation of what errors, if any,
                    should be retried.
                timeout (float): The timeout for this request.
                metadata (Sequence[Tuple[str, 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:
                locations_pb2.Location: Response from GetLocation method.
            """

            http_options = (
                _BasePipelineServiceRestTransport._BaseGetLocation._get_http_options()
            )

            request, metadata = self._interceptor.pre_get_location(request, metadata)
            transcoded_request = _BasePipelineServiceRestTransport._BaseGetLocation._get_transcoded_request(
                http_options, request
            )

            # Jsonify the query params
            query_params = _BasePipelineServiceRestTransport._BaseGetLocation._get_query_params_json(
                transcoded_request
            )

            if CLIENT_LOGGING_SUPPORTED and _LOGGER.isEnabledFor(
                logging.DEBUG
            ):  # pragma: NO COVER
                request_url = "{host}{uri}".format(
                    host=self._host, uri=transcoded_request["uri"]
                )
                method = transcoded_request["method"]
                try:
                    request_payload = json_format.MessageToJson(request)
                except:
                    request_payload = None
                http_request = {
                    "payload": request_payload,
                    "requestMethod": method,
                    "requestUrl": request_url,
                    "headers": dict(metadata),
                }
                _LOGGER.debug(
                    f"Sending request for google.cloud.aiplatform_v1.PipelineServiceClient.GetLocation",
                    extra={
                        "serviceName": "google.cloud.aiplatform.v1.PipelineService",
                        "rpcName": "GetLocation",
                        "httpRequest": http_request,
                        "metadata": http_request["headers"],
                    },
                )

            # Send the request
            response = PipelineServiceRestTransport._GetLocation._get_response(
                self._host,
                metadata,
                query_params,
                self._session,
                timeout,
                transcoded_request,
            )

            # In case of error, raise the appropriate core_exceptions.GoogleAPICallError exception
            # subclass.
            if response.status_code >= 400:
                raise core_exceptions.from_http_response(response)

            content = response.content.decode("utf-8")
            resp = locations_pb2.Location()
            resp = json_format.Parse(content, resp)
            resp = self._interceptor.post_get_location(resp)
            if CLIENT_LOGGING_SUPPORTED and _LOGGER.isEnabledFor(
                logging.DEBUG
            ):  # pragma: NO COVER
                try:
                    response_payload = json_format.MessageToJson(resp)
                except:
                    response_payload = None
                http_response = {
                    "payload": response_payload,
                    "headers": dict(response.headers),
                    "status": response.status_code,
                }
                _LOGGER.debug(
                    "Received response for google.cloud.aiplatform_v1.PipelineServiceAsyncClient.GetLocation",
                    extra={
                        "serviceName": "google.cloud.aiplatform.v1.PipelineService",
                        "rpcName": "GetLocation",
                        "httpResponse": http_response,
                        "metadata": http_response["headers"],
                    },
                )
            return resp

    @property
    def list_locations(self):
        return self._ListLocations(self._session, self._host, self._interceptor)  # type: ignore

    class _ListLocations(
        _BasePipelineServiceRestTransport._BaseListLocations, PipelineServiceRestStub
    ):
        def __hash__(self):
            return hash("PipelineServiceRestTransport.ListLocations")

        @staticmethod
        def _get_response(
            host,
            metadata,
            query_params,
            session,
            timeout,
            transcoded_request,
            body=None,
        ):

            uri = transcoded_request["uri"]
            method = transcoded_request["method"]
            headers = dict(metadata)
            headers["Content-Type"] = "application/json"
            response = getattr(session, method)(
                "{host}{uri}".format(host=host, uri=uri),
                timeout=timeout,
                headers=headers,
                params=rest_helpers.flatten_query_params(query_params, strict=True),
            )
            return response

        def __call__(
            self,
            request: locations_pb2.ListLocationsRequest,
            *,
            retry: OptionalRetry = gapic_v1.method.DEFAULT,
            timeout: Optional[float] = None,
            metadata: Sequence[Tuple[str, Union[str, bytes]]] = (),
        ) -> locations_pb2.ListLocationsResponse:
            r"""Call the list locations method over HTTP.

            Args:
                request (locations_pb2.ListLocationsRequest):
                    The request object for ListLocations method.
                retry (google.api_core.retry.Retry): Designation of what errors, if any,
                    should be retried.
                timeout (float): The timeout for this request.
                metadata (Sequence[Tuple[str, 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:
                locations_pb2.ListLocationsResponse: Response from ListLocations method.
            """

            http_options = (
                _BasePipelineServiceRestTransport._BaseListLocations._get_http_options()
            )

            request, metadata = self._interceptor.pre_list_locations(request, metadata)
            transcoded_request = _BasePipelineServiceRestTransport._BaseListLocations._get_transcoded_request(
                http_options, request
            )

            # Jsonify the query params
            query_params = _BasePipelineServiceRestTransport._BaseListLocations._get_query_params_json(
                transcoded_request
            )

            if CLIENT_LOGGING_SUPPORTED and _LOGGER.isEnabledFor(
                logging.DEBUG
            ):  # pragma: NO COVER
                request_url = "{host}{uri}".format(
                    host=self._host, uri=transcoded_request["uri"]
                )
                method = transcoded_request["method"]
                try:
                    request_payload = json_format.MessageToJson(request)
                except:
                    request_payload = None
                http_request = {
                    "payload": request_payload,
                    "requestMethod": method,
                    "requestUrl": request_url,
                    "headers": dict(metadata),
                }
                _LOGGER.debug(
                    f"Sending request for google.cloud.aiplatform_v1.PipelineServiceClient.ListLocations",
                    extra={
                        "serviceName": "google.cloud.aiplatform.v1.PipelineService",
                        "rpcName": "ListLocations",
                        "httpRequest": http_request,
                        "metadata": http_request["headers"],
                    },
                )

            # Send the request
            response = PipelineServiceRestTransport._ListLocations._get_response(
                self._host,
                metadata,
                query_params,
                self._session,
                timeout,
                transcoded_request,
            )

            # In case of error, raise the appropriate core_exceptions.GoogleAPICallError exception
            # subclass.
            if response.status_code >= 400:
                raise core_exceptions.from_http_response(response)

            content = response.content.decode("utf-8")
            resp = locations_pb2.ListLocationsResponse()
            resp = json_format.Parse(content, resp)
            resp = self._interceptor.post_list_locations(resp)
            if CLIENT_LOGGING_SUPPORTED and _LOGGER.isEnabledFor(
                logging.DEBUG
            ):  # pragma: NO COVER
                try:
                    response_payload = json_format.MessageToJson(resp)
                except:
                    response_payload = None
                http_response = {
                    "payload": response_payload,
                    "headers": dict(response.headers),
                    "status": response.status_code,
                }
                _LOGGER.debug(
                    "Received response for google.cloud.aiplatform_v1.PipelineServiceAsyncClient.ListLocations",
                    extra={
                        "serviceName": "google.cloud.aiplatform.v1.PipelineService",
                        "rpcName": "ListLocations",
                        "httpResponse": http_response,
                        "metadata": http_response["headers"],
                    },
                )
            return resp

    @property
    def get_iam_policy(self):
        return self._GetIamPolicy(self._session, self._host, self._interceptor)  # type: ignore

    class _GetIamPolicy(
        _BasePipelineServiceRestTransport._BaseGetIamPolicy, PipelineServiceRestStub
    ):
        def __hash__(self):
            return hash("PipelineServiceRestTransport.GetIamPolicy")

        @staticmethod
        def _get_response(
            host,
            metadata,
            query_params,
            session,
            timeout,
            transcoded_request,
            body=None,
        ):

            uri = transcoded_request["uri"]
            method = transcoded_request["method"]
            headers = dict(metadata)
            headers["Content-Type"] = "application/json"
            response = getattr(session, method)(
                "{host}{uri}".format(host=host, uri=uri),
                timeout=timeout,
                headers=headers,
                params=rest_helpers.flatten_query_params(query_params, strict=True),
            )
            return response

        def __call__(
            self,
            request: iam_policy_pb2.GetIamPolicyRequest,
            *,
            retry: OptionalRetry = gapic_v1.method.DEFAULT,
            timeout: Optional[float] = None,
            metadata: Sequence[Tuple[str, Union[str, bytes]]] = (),
        ) -> policy_pb2.Policy:
            r"""Call the get iam policy method over HTTP.

            Args:
                request (iam_policy_pb2.GetIamPolicyRequest):
                    The request object for GetIamPolicy method.
                retry (google.api_core.retry.Retry): Designation of what errors, if any,
                    should be retried.
                timeout (float): The timeout for this request.
                metadata (Sequence[Tuple[str, 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: Response from GetIamPolicy method.
            """

            http_options = (
                _BasePipelineServiceRestTransport._BaseGetIamPolicy._get_http_options()
            )

            request, metadata = self._interceptor.pre_get_iam_policy(request, metadata)
            transcoded_request = _BasePipelineServiceRestTransport._BaseGetIamPolicy._get_transcoded_request(
                http_options, request
            )

            # Jsonify the query params
            query_params = _BasePipelineServiceRestTransport._BaseGetIamPolicy._get_query_params_json(
                transcoded_request
            )

            if CLIENT_LOGGING_SUPPORTED and _LOGGER.isEnabledFor(
                logging.DEBUG
            ):  # pragma: NO COVER
                request_url = "{host}{uri}".format(
                    host=self._host, uri=transcoded_request["uri"]
                )
                method = transcoded_request["method"]
                try:
                    request_payload = json_format.MessageToJson(request)
                except:
                    request_payload = None
                http_request = {
                    "payload": request_payload,
                    "requestMethod": method,
                    "requestUrl": request_url,
                    "headers": dict(metadata),
                }
                _LOGGER.debug(
                    f"Sending request for google.cloud.aiplatform_v1.PipelineServiceClient.GetIamPolicy",
                    extra={
                        "serviceName": "google.cloud.aiplatform.v1.PipelineService",
                        "rpcName": "GetIamPolicy",
                        "httpRequest": http_request,
                        "metadata": http_request["headers"],
                    },
                )

            # Send the request
            response = PipelineServiceRestTransport._GetIamPolicy._get_response(
                self._host,
                metadata,
                query_params,
                self._session,
                timeout,
                transcoded_request,
            )

            # In case of error, raise the appropriate core_exceptions.GoogleAPICallError exception
            # subclass.
            if response.status_code >= 400:
                raise core_exceptions.from_http_response(response)

            content = response.content.decode("utf-8")
            resp = policy_pb2.Policy()
            resp = json_format.Parse(content, resp)
            resp = self._interceptor.post_get_iam_policy(resp)
            if CLIENT_LOGGING_SUPPORTED and _LOGGER.isEnabledFor(
                logging.DEBUG
            ):  # pragma: NO COVER
                try:
                    response_payload = json_format.MessageToJson(resp)
                except:
                    response_payload = None
                http_response = {
                    "payload": response_payload,
                    "headers": dict(response.headers),
                    "status": response.status_code,
                }
                _LOGGER.debug(
                    "Received response for google.cloud.aiplatform_v1.PipelineServiceAsyncClient.GetIamPolicy",
                    extra={
                        "serviceName": "google.cloud.aiplatform.v1.PipelineService",
                        "rpcName": "GetIamPolicy",
                        "httpResponse": http_response,
                        "metadata": http_response["headers"],
                    },
                )
            return resp

    @property
    def set_iam_policy(self):
        return self._SetIamPolicy(self._session, self._host, self._interceptor)  # type: ignore

    class _SetIamPolicy(
        _BasePipelineServiceRestTransport._BaseSetIamPolicy, PipelineServiceRestStub
    ):
        def __hash__(self):
            return hash("PipelineServiceRestTransport.SetIamPolicy")

        @staticmethod
        def _get_response(
            host,
            metadata,
            query_params,
            session,
            timeout,
            transcoded_request,
            body=None,
        ):

            uri = transcoded_request["uri"]
            method = transcoded_request["method"]
            headers = dict(metadata)
            headers["Content-Type"] = "application/json"
            response = getattr(session, method)(
                "{host}{uri}".format(host=host, uri=uri),
                timeout=timeout,
                headers=headers,
                params=rest_helpers.flatten_query_params(query_params, strict=True),
                data=body,
            )
            return response

        def __call__(
            self,
            request: iam_policy_pb2.SetIamPolicyRequest,
            *,
            retry: OptionalRetry = gapic_v1.method.DEFAULT,
            timeout: Optional[float] = None,
            metadata: Sequence[Tuple[str, Union[str, bytes]]] = (),
        ) -> policy_pb2.Policy:
            r"""Call the set iam policy method over HTTP.

            Args:
                request (iam_policy_pb2.SetIamPolicyRequest):
                    The request object for SetIamPolicy method.
                retry (google.api_core.retry.Retry): Designation of what errors, if any,
                    should be retried.
                timeout (float): The timeout for this request.
                metadata (Sequence[Tuple[str, 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: Response from SetIamPolicy method.
            """

            http_options = (
                _BasePipelineServiceRestTransport._BaseSetIamPolicy._get_http_options()
            )

            request, metadata = self._interceptor.pre_set_iam_policy(request, metadata)
            transcoded_request = _BasePipelineServiceRestTransport._BaseSetIamPolicy._get_transcoded_request(
                http_options, request
            )

            body = _BasePipelineServiceRestTransport._BaseSetIamPolicy._get_request_body_json(
                transcoded_request
            )

            # Jsonify the query params
            query_params = _BasePipelineServiceRestTransport._BaseSetIamPolicy._get_query_params_json(
                transcoded_request
            )

            if CLIENT_LOGGING_SUPPORTED and _LOGGER.isEnabledFor(
                logging.DEBUG
            ):  # pragma: NO COVER
                request_url = "{host}{uri}".format(
                    host=self._host, uri=transcoded_request["uri"]
                )
                method = transcoded_request["method"]
                try:
                    request_payload = json_format.MessageToJson(request)
                except:
                    request_payload = None
                http_request = {
                    "payload": request_payload,
                    "requestMethod": method,
                    "requestUrl": request_url,
                    "headers": dict(metadata),
                }
                _LOGGER.debug(
                    f"Sending request for google.cloud.aiplatform_v1.PipelineServiceClient.SetIamPolicy",
                    extra={
                        "serviceName": "google.cloud.aiplatform.v1.PipelineService",
                        "rpcName": "SetIamPolicy",
                        "httpRequest": http_request,
                        "metadata": http_request["headers"],
                    },
                )

            # Send the request
            response = PipelineServiceRestTransport._SetIamPolicy._get_response(
                self._host,
                metadata,
                query_params,
                self._session,
                timeout,
                transcoded_request,
                body,
            )

            # In case of error, raise the appropriate core_exceptions.GoogleAPICallError exception
            # subclass.
            if response.status_code >= 400:
                raise core_exceptions.from_http_response(response)

            content = response.content.decode("utf-8")
            resp = policy_pb2.Policy()
            resp = json_format.Parse(content, resp)
            resp = self._interceptor.post_set_iam_policy(resp)
            if CLIENT_LOGGING_SUPPORTED and _LOGGER.isEnabledFor(
                logging.DEBUG
            ):  # pragma: NO COVER
                try:
                    response_payload = json_format.MessageToJson(resp)
                except:
                    response_payload = None
                http_response = {
                    "payload": response_payload,
                    "headers": dict(response.headers),
                    "status": response.status_code,
                }
                _LOGGER.debug(
                    "Received response for google.cloud.aiplatform_v1.PipelineServiceAsyncClient.SetIamPolicy",
                    extra={
                        "serviceName": "google.cloud.aiplatform.v1.PipelineService",
                        "rpcName": "SetIamPolicy",
                        "httpResponse": http_response,
                        "metadata": http_response["headers"],
                    },
                )
            return resp

    @property
    def test_iam_permissions(self):
        return self._TestIamPermissions(self._session, self._host, self._interceptor)  # type: ignore

    class _TestIamPermissions(
        _BasePipelineServiceRestTransport._BaseTestIamPermissions,
        PipelineServiceRestStub,
    ):
        def __hash__(self):
            return hash("PipelineServiceRestTransport.TestIamPermissions")

        @staticmethod
        def _get_response(
            host,
            metadata,
            query_params,
            session,
            timeout,
            transcoded_request,
            body=None,
        ):

            uri = transcoded_request["uri"]
            method = transcoded_request["method"]
            headers = dict(metadata)
            headers["Content-Type"] = "application/json"
            response = getattr(session, method)(
                "{host}{uri}".format(host=host, uri=uri),
                timeout=timeout,
                headers=headers,
                params=rest_helpers.flatten_query_params(query_params, strict=True),
            )
            return response

        def __call__(
            self,
            request: iam_policy_pb2.TestIamPermissionsRequest,
            *,
            retry: OptionalRetry = gapic_v1.method.DEFAULT,
            timeout: Optional[float] = None,
            metadata: Sequence[Tuple[str, Union[str, bytes]]] = (),
        ) -> iam_policy_pb2.TestIamPermissionsResponse:
            r"""Call the test iam permissions method over HTTP.

            Args:
                request (iam_policy_pb2.TestIamPermissionsRequest):
                    The request object for TestIamPermissions method.
                retry (google.api_core.retry.Retry): Designation of what errors, if any,
                    should be retried.
                timeout (float): The timeout for this request.
                metadata (Sequence[Tuple[str, 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 from TestIamPermissions method.
            """

            http_options = (
                _BasePipelineServiceRestTransport._BaseTestIamPermissions._get_http_options()
            )

            request, metadata = self._interceptor.pre_test_iam_permissions(
                request, metadata
            )
            transcoded_request = _BasePipelineServiceRestTransport._BaseTestIamPermissions._get_transcoded_request(
                http_options, request
            )

            # Jsonify the query params
            query_params = _BasePipelineServiceRestTransport._BaseTestIamPermissions._get_query_params_json(
                transcoded_request
            )

            if CLIENT_LOGGING_SUPPORTED and _LOGGER.isEnabledFor(
                logging.DEBUG
            ):  # pragma: NO COVER
                request_url = "{host}{uri}".format(
                    host=self._host, uri=transcoded_request["uri"]
                )
                method = transcoded_request["method"]
                try:
                    request_payload = json_format.MessageToJson(request)
                except:
                    request_payload = None
                http_request = {
                    "payload": request_payload,
                    "requestMethod": method,
                    "requestUrl": request_url,
                    "headers": dict(metadata),
                }
                _LOGGER.debug(
                    f"Sending request for google.cloud.aiplatform_v1.PipelineServiceClient.TestIamPermissions",
                    extra={
                        "serviceName": "google.cloud.aiplatform.v1.PipelineService",
                        "rpcName": "TestIamPermissions",
                        "httpRequest": http_request,
                        "metadata": http_request["headers"],
                    },
                )

            # Send the request
            response = PipelineServiceRestTransport._TestIamPermissions._get_response(
                self._host,
                metadata,
                query_params,
                self._session,
                timeout,
                transcoded_request,
            )

            # In case of error, raise the appropriate core_exceptions.GoogleAPICallError exception
            # subclass.
            if response.status_code >= 400:
                raise core_exceptions.from_http_response(response)

            content = response.content.decode("utf-8")
            resp = iam_policy_pb2.TestIamPermissionsResponse()
            resp = json_format.Parse(content, resp)
            resp = self._interceptor.post_test_iam_permissions(resp)
            if CLIENT_LOGGING_SUPPORTED and _LOGGER.isEnabledFor(
                logging.DEBUG
            ):  # pragma: NO COVER
                try:
                    response_payload = json_format.MessageToJson(resp)
                except:
                    response_payload = None
                http_response = {
                    "payload": response_payload,
                    "headers": dict(response.headers),
                    "status": response.status_code,
                }
                _LOGGER.debug(
                    "Received response for google.cloud.aiplatform_v1.PipelineServiceAsyncClient.TestIamPermissions",
                    extra={
                        "serviceName": "google.cloud.aiplatform.v1.PipelineService",
                        "rpcName": "TestIamPermissions",
                        "httpResponse": http_response,
                        "metadata": http_response["headers"],
                    },
                )
            return resp

    @property
    def cancel_operation(self):
        return self._CancelOperation(self._session, self._host, self._interceptor)  # type: ignore

    class _CancelOperation(
        _BasePipelineServiceRestTransport._BaseCancelOperation, PipelineServiceRestStub
    ):
        def __hash__(self):
            return hash("PipelineServiceRestTransport.CancelOperation")

        @staticmethod
        def _get_response(
            host,
            metadata,
            query_params,
            session,
            timeout,
            transcoded_request,
            body=None,
        ):

            uri = transcoded_request["uri"]
            method = transcoded_request["method"]
            headers = dict(metadata)
            headers["Content-Type"] = "application/json"
            response = getattr(session, method)(
                "{host}{uri}".format(host=host, uri=uri),
                timeout=timeout,
                headers=headers,
                params=rest_helpers.flatten_query_params(query_params, strict=True),
            )
            return response

        def __call__(
            self,
            request: operations_pb2.CancelOperationRequest,
            *,
            retry: OptionalRetry = gapic_v1.method.DEFAULT,
            timeout: Optional[float] = None,
            metadata: Sequence[Tuple[str, Union[str, bytes]]] = (),
        ) -> None:
            r"""Call the cancel operation method over HTTP.

            Args:
                request (operations_pb2.CancelOperationRequest):
                    The request object for CancelOperation method.
                retry (google.api_core.retry.Retry): Designation of what errors, if any,
                    should be retried.
                timeout (float): The timeout for this request.
                metadata (Sequence[Tuple[str, 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`.
            """

            http_options = (
                _BasePipelineServiceRestTransport._BaseCancelOperation._get_http_options()
            )

            request, metadata = self._interceptor.pre_cancel_operation(
                request, metadata
            )
            transcoded_request = _BasePipelineServiceRestTransport._BaseCancelOperation._get_transcoded_request(
                http_options, request
            )

            # Jsonify the query params
            query_params = _BasePipelineServiceRestTransport._BaseCancelOperation._get_query_params_json(
                transcoded_request
            )

            if CLIENT_LOGGING_SUPPORTED and _LOGGER.isEnabledFor(
                logging.DEBUG
            ):  # pragma: NO COVER
                request_url = "{host}{uri}".format(
                    host=self._host, uri=transcoded_request["uri"]
                )
                method = transcoded_request["method"]
                try:
                    request_payload = json_format.MessageToJson(request)
                except:
                    request_payload = None
                http_request = {
                    "payload": request_payload,
                    "requestMethod": method,
                    "requestUrl": request_url,
                    "headers": dict(metadata),
                }
                _LOGGER.debug(
                    f"Sending request for google.cloud.aiplatform_v1.PipelineServiceClient.CancelOperation",
                    extra={
                        "serviceName": "google.cloud.aiplatform.v1.PipelineService",
                        "rpcName": "CancelOperation",
                        "httpRequest": http_request,
                        "metadata": http_request["headers"],
                    },
                )

            # Send the request
            response = PipelineServiceRestTransport._CancelOperation._get_response(
                self._host,
                metadata,
                query_params,
                self._session,
                timeout,
                transcoded_request,
            )

            # In case of error, raise the appropriate core_exceptions.GoogleAPICallError exception
            # subclass.
            if response.status_code >= 400:
                raise core_exceptions.from_http_response(response)

            return self._interceptor.post_cancel_operation(None)

    @property
    def delete_operation(self):
        return self._DeleteOperation(self._session, self._host, self._interceptor)  # type: ignore

    class _DeleteOperation(
        _BasePipelineServiceRestTransport._BaseDeleteOperation, PipelineServiceRestStub
    ):
        def __hash__(self):
            return hash("PipelineServiceRestTransport.DeleteOperation")

        @staticmethod
        def _get_response(
            host,
            metadata,
            query_params,
            session,
            timeout,
            transcoded_request,
            body=None,
        ):

            uri = transcoded_request["uri"]
            method = transcoded_request["method"]
            headers = dict(metadata)
            headers["Content-Type"] = "application/json"
            response = getattr(session, method)(
                "{host}{uri}".format(host=host, uri=uri),
                timeout=timeout,
                headers=headers,
                params=rest_helpers.flatten_query_params(query_params, strict=True),
            )
            return response

        def __call__(
            self,
            request: operations_pb2.DeleteOperationRequest,
            *,
            retry: OptionalRetry = gapic_v1.method.DEFAULT,
            timeout: Optional[float] = None,
            metadata: Sequence[Tuple[str, Union[str, bytes]]] = (),
        ) -> None:
            r"""Call the delete operation method over HTTP.

            Args:
                request (operations_pb2.DeleteOperationRequest):
                    The request object for DeleteOperation method.
                retry (google.api_core.retry.Retry): Designation of what errors, if any,
                    should be retried.
                timeout (float): The timeout for this request.
                metadata (Sequence[Tuple[str, 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`.
            """

            http_options = (
                _BasePipelineServiceRestTransport._BaseDeleteOperation._get_http_options()
            )

            request, metadata = self._interceptor.pre_delete_operation(
                request, metadata
            )
            transcoded_request = _BasePipelineServiceRestTransport._BaseDeleteOperation._get_transcoded_request(
                http_options, request
            )

            # Jsonify the query params
            query_params = _BasePipelineServiceRestTransport._BaseDeleteOperation._get_query_params_json(
                transcoded_request
            )

            if CLIENT_LOGGING_SUPPORTED and _LOGGER.isEnabledFor(
                logging.DEBUG
            ):  # pragma: NO COVER
                request_url = "{host}{uri}".format(
                    host=self._host, uri=transcoded_request["uri"]
                )
                method = transcoded_request["method"]
                try:
                    request_payload = json_format.MessageToJson(request)
                except:
                    request_payload = None
                http_request = {
                    "payload": request_payload,
                    "requestMethod": method,
                    "requestUrl": request_url,
                    "headers": dict(metadata),
                }
                _LOGGER.debug(
                    f"Sending request for google.cloud.aiplatform_v1.PipelineServiceClient.DeleteOperation",
                    extra={
                        "serviceName": "google.cloud.aiplatform.v1.PipelineService",
                        "rpcName": "DeleteOperation",
                        "httpRequest": http_request,
                        "metadata": http_request["headers"],
                    },
                )

            # Send the request
            response = PipelineServiceRestTransport._DeleteOperation._get_response(
                self._host,
                metadata,
                query_params,
                self._session,
                timeout,
                transcoded_request,
            )

            # In case of error, raise the appropriate core_exceptions.GoogleAPICallError exception
            # subclass.
            if response.status_code >= 400:
                raise core_exceptions.from_http_response(response)

            return self._interceptor.post_delete_operation(None)

    @property
    def get_operation(self):
        return self._GetOperation(self._session, self._host, self._interceptor)  # type: ignore

    class _GetOperation(
        _BasePipelineServiceRestTransport._BaseGetOperation, PipelineServiceRestStub
    ):
        def __hash__(self):
            return hash("PipelineServiceRestTransport.GetOperation")

        @staticmethod
        def _get_response(
            host,
            metadata,
            query_params,
            session,
            timeout,
            transcoded_request,
            body=None,
        ):

            uri = transcoded_request["uri"]
            method = transcoded_request["method"]
            headers = dict(metadata)
            headers["Content-Type"] = "application/json"
            response = getattr(session, method)(
                "{host}{uri}".format(host=host, uri=uri),
                timeout=timeout,
                headers=headers,
                params=rest_helpers.flatten_query_params(query_params, strict=True),
            )
            return response

        def __call__(
            self,
            request: operations_pb2.GetOperationRequest,
            *,
            retry: OptionalRetry = gapic_v1.method.DEFAULT,
            timeout: Optional[float] = None,
            metadata: Sequence[Tuple[str, Union[str, bytes]]] = (),
        ) -> operations_pb2.Operation:
            r"""Call the get operation method over HTTP.

            Args:
                request (operations_pb2.GetOperationRequest):
                    The request object for GetOperation method.
                retry (google.api_core.retry.Retry): Designation of what errors, if any,
                    should be retried.
                timeout (float): The timeout for this request.
                metadata (Sequence[Tuple[str, 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: Response from GetOperation method.
            """

            http_options = (
                _BasePipelineServiceRestTransport._BaseGetOperation._get_http_options()
            )

            request, metadata = self._interceptor.pre_get_operation(request, metadata)
            transcoded_request = _BasePipelineServiceRestTransport._BaseGetOperation._get_transcoded_request(
                http_options, request
            )

            # Jsonify the query params
            query_params = _BasePipelineServiceRestTransport._BaseGetOperation._get_query_params_json(
                transcoded_request
            )

            if CLIENT_LOGGING_SUPPORTED and _LOGGER.isEnabledFor(
                logging.DEBUG
            ):  # pragma: NO COVER
                request_url = "{host}{uri}".format(
                    host=self._host, uri=transcoded_request["uri"]
                )
                method = transcoded_request["method"]
                try:
                    request_payload = json_format.MessageToJson(request)
                except:
                    request_payload = None
                http_request = {
                    "payload": request_payload,
                    "requestMethod": method,
                    "requestUrl": request_url,
                    "headers": dict(metadata),
                }
                _LOGGER.debug(
                    f"Sending request for google.cloud.aiplatform_v1.PipelineServiceClient.GetOperation",
                    extra={
                        "serviceName": "google.cloud.aiplatform.v1.PipelineService",
                        "rpcName": "GetOperation",
                        "httpRequest": http_request,
                        "metadata": http_request["headers"],
                    },
                )

            # Send the request
            response = PipelineServiceRestTransport._GetOperation._get_response(
                self._host,
                metadata,
                query_params,
                self._session,
                timeout,
                transcoded_request,
            )

            # In case of error, raise the appropriate core_exceptions.GoogleAPICallError exception
            # subclass.
            if response.status_code >= 400:
                raise core_exceptions.from_http_response(response)

            content = response.content.decode("utf-8")
            resp = operations_pb2.Operation()
            resp = json_format.Parse(content, resp)
            resp = self._interceptor.post_get_operation(resp)
            if CLIENT_LOGGING_SUPPORTED and _LOGGER.isEnabledFor(
                logging.DEBUG
            ):  # pragma: NO COVER
                try:
                    response_payload = json_format.MessageToJson(resp)
                except:
                    response_payload = None
                http_response = {
                    "payload": response_payload,
                    "headers": dict(response.headers),
                    "status": response.status_code,
                }
                _LOGGER.debug(
                    "Received response for google.cloud.aiplatform_v1.PipelineServiceAsyncClient.GetOperation",
                    extra={
                        "serviceName": "google.cloud.aiplatform.v1.PipelineService",
                        "rpcName": "GetOperation",
                        "httpResponse": http_response,
                        "metadata": http_response["headers"],
                    },
                )
            return resp

    @property
    def list_operations(self):
        return self._ListOperations(self._session, self._host, self._interceptor)  # type: ignore

    class _ListOperations(
        _BasePipelineServiceRestTransport._BaseListOperations, PipelineServiceRestStub
    ):
        def __hash__(self):
            return hash("PipelineServiceRestTransport.ListOperations")

        @staticmethod
        def _get_response(
            host,
            metadata,
            query_params,
            session,
            timeout,
            transcoded_request,
            body=None,
        ):

            uri = transcoded_request["uri"]
            method = transcoded_request["method"]
            headers = dict(metadata)
            headers["Content-Type"] = "application/json"
            response = getattr(session, method)(
                "{host}{uri}".format(host=host, uri=uri),
                timeout=timeout,
                headers=headers,
                params=rest_helpers.flatten_query_params(query_params, strict=True),
            )
            return response

        def __call__(
            self,
            request: operations_pb2.ListOperationsRequest,
            *,
            retry: OptionalRetry = gapic_v1.method.DEFAULT,
            timeout: Optional[float] = None,
            metadata: Sequence[Tuple[str, Union[str, bytes]]] = (),
        ) -> operations_pb2.ListOperationsResponse:
            r"""Call the list operations method over HTTP.

            Args:
                request (operations_pb2.ListOperationsRequest):
                    The request object for ListOperations method.
                retry (google.api_core.retry.Retry): Designation of what errors, if any,
                    should be retried.
                timeout (float): The timeout for this request.
                metadata (Sequence[Tuple[str, 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 from ListOperations method.
            """

            http_options = (
                _BasePipelineServiceRestTransport._BaseListOperations._get_http_options()
            )

            request, metadata = self._interceptor.pre_list_operations(request, metadata)
            transcoded_request = _BasePipelineServiceRestTransport._BaseListOperations._get_transcoded_request(
                http_options, request
            )

            # Jsonify the query params
            query_params = _BasePipelineServiceRestTransport._BaseListOperations._get_query_params_json(
                transcoded_request
            )

            if CLIENT_LOGGING_SUPPORTED and _LOGGER.isEnabledFor(
                logging.DEBUG
            ):  # pragma: NO COVER
                request_url = "{host}{uri}".format(
                    host=self._host, uri=transcoded_request["uri"]
                )
                method = transcoded_request["method"]
                try:
                    request_payload = json_format.MessageToJson(request)
                except:
                    request_payload = None
                http_request = {
                    "payload": request_payload,
                    "requestMethod": method,
                    "requestUrl": request_url,
                    "headers": dict(metadata),
                }
                _LOGGER.debug(
                    f"Sending request for google.cloud.aiplatform_v1.PipelineServiceClient.ListOperations",
                    extra={
                        "serviceName": "google.cloud.aiplatform.v1.PipelineService",
                        "rpcName": "ListOperations",
                        "httpRequest": http_request,
                        "metadata": http_request["headers"],
                    },
                )

            # Send the request
            response = PipelineServiceRestTransport._ListOperations._get_response(
                self._host,
                metadata,
                query_params,
                self._session,
                timeout,
                transcoded_request,
            )

            # In case of error, raise the appropriate core_exceptions.GoogleAPICallError exception
            # subclass.
            if response.status_code >= 400:
                raise core_exceptions.from_http_response(response)

            content = response.content.decode("utf-8")
            resp = operations_pb2.ListOperationsResponse()
            resp = json_format.Parse(content, resp)
            resp = self._interceptor.post_list_operations(resp)
            if CLIENT_LOGGING_SUPPORTED and _LOGGER.isEnabledFor(
                logging.DEBUG
            ):  # pragma: NO COVER
                try:
                    response_payload = json_format.MessageToJson(resp)
                except:
                    response_payload = None
                http_response = {
                    "payload": response_payload,
                    "headers": dict(response.headers),
                    "status": response.status_code,
                }
                _LOGGER.debug(
                    "Received response for google.cloud.aiplatform_v1.PipelineServiceAsyncClient.ListOperations",
                    extra={
                        "serviceName": "google.cloud.aiplatform.v1.PipelineService",
                        "rpcName": "ListOperations",
                        "httpResponse": http_response,
                        "metadata": http_response["headers"],
                    },
                )
            return resp

    @property
    def wait_operation(self):
        return self._WaitOperation(self._session, self._host, self._interceptor)  # type: ignore

    class _WaitOperation(
        _BasePipelineServiceRestTransport._BaseWaitOperation, PipelineServiceRestStub
    ):
        def __hash__(self):
            return hash("PipelineServiceRestTransport.WaitOperation")

        @staticmethod
        def _get_response(
            host,
            metadata,
            query_params,
            session,
            timeout,
            transcoded_request,
            body=None,
        ):

            uri = transcoded_request["uri"]
            method = transcoded_request["method"]
            headers = dict(metadata)
            headers["Content-Type"] = "application/json"
            response = getattr(session, method)(
                "{host}{uri}".format(host=host, uri=uri),
                timeout=timeout,
                headers=headers,
                params=rest_helpers.flatten_query_params(query_params, strict=True),
            )
            return response

        def __call__(
            self,
            request: operations_pb2.WaitOperationRequest,
            *,
            retry: OptionalRetry = gapic_v1.method.DEFAULT,
            timeout: Optional[float] = None,
            metadata: Sequence[Tuple[str, Union[str, bytes]]] = (),
        ) -> operations_pb2.Operation:
            r"""Call the wait operation method over HTTP.

            Args:
                request (operations_pb2.WaitOperationRequest):
                    The request object for WaitOperation method.
                retry (google.api_core.retry.Retry): Designation of what errors, if any,
                    should be retried.
                timeout (float): The timeout for this request.
                metadata (Sequence[Tuple[str, 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: Response from WaitOperation method.
            """

            http_options = (
                _BasePipelineServiceRestTransport._BaseWaitOperation._get_http_options()
            )

            request, metadata = self._interceptor.pre_wait_operation(request, metadata)
            transcoded_request = _BasePipelineServiceRestTransport._BaseWaitOperation._get_transcoded_request(
                http_options, request
            )

            # Jsonify the query params
            query_params = _BasePipelineServiceRestTransport._BaseWaitOperation._get_query_params_json(
                transcoded_request
            )

            if CLIENT_LOGGING_SUPPORTED and _LOGGER.isEnabledFor(
                logging.DEBUG
            ):  # pragma: NO COVER
                request_url = "{host}{uri}".format(
                    host=self._host, uri=transcoded_request["uri"]
                )
                method = transcoded_request["method"]
                try:
                    request_payload = json_format.MessageToJson(request)
                except:
                    request_payload = None
                http_request = {
                    "payload": request_payload,
                    "requestMethod": method,
                    "requestUrl": request_url,
                    "headers": dict(metadata),
                }
                _LOGGER.debug(
                    f"Sending request for google.cloud.aiplatform_v1.PipelineServiceClient.WaitOperation",
                    extra={
                        "serviceName": "google.cloud.aiplatform.v1.PipelineService",
                        "rpcName": "WaitOperation",
                        "httpRequest": http_request,
                        "metadata": http_request["headers"],
                    },
                )

            # Send the request
            response = PipelineServiceRestTransport._WaitOperation._get_response(
                self._host,
                metadata,
                query_params,
                self._session,
                timeout,
                transcoded_request,
            )

            # In case of error, raise the appropriate core_exceptions.GoogleAPICallError exception
            # subclass.
            if response.status_code >= 400:
                raise core_exceptions.from_http_response(response)

            content = response.content.decode("utf-8")
            resp = operations_pb2.Operation()
            resp = json_format.Parse(content, resp)
            resp = self._interceptor.post_wait_operation(resp)
            if CLIENT_LOGGING_SUPPORTED and _LOGGER.isEnabledFor(
                logging.DEBUG
            ):  # pragma: NO COVER
                try:
                    response_payload = json_format.MessageToJson(resp)
                except:
                    response_payload = None
                http_response = {
                    "payload": response_payload,
                    "headers": dict(response.headers),
                    "status": response.status_code,
                }
                _LOGGER.debug(
                    "Received response for google.cloud.aiplatform_v1.PipelineServiceAsyncClient.WaitOperation",
                    extra={
                        "serviceName": "google.cloud.aiplatform.v1.PipelineService",
                        "rpcName": "WaitOperation",
                        "httpResponse": http_response,
                        "metadata": http_response["headers"],
                    },
                )
            return resp

    @property
    def kind(self) -> str:
        return "rest"

    def close(self):
        self._session.close()


__all__ = ("PipelineServiceRestTransport",)
