# -*- 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 annotation_spec
from google.cloud.aiplatform_v1.types import dataset
from google.cloud.aiplatform_v1.types import dataset as gca_dataset
from google.cloud.aiplatform_v1.types import dataset_service
from google.cloud.aiplatform_v1.types import dataset_version
from google.cloud.aiplatform_v1.types import dataset_version as gca_dataset_version
from google.longrunning import operations_pb2  # type: ignore


from .rest_base import _BaseDatasetServiceRestTransport
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 DatasetServiceRestInterceptor:
    """Interceptor for DatasetService.

    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 DatasetServiceRestTransport.

    .. code-block:: python
        class MyCustomDatasetServiceInterceptor(DatasetServiceRestInterceptor):
            def pre_create_dataset(self, request, metadata):
                logging.log(f"Received request: {request}")
                return request, metadata

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

        transport = DatasetServiceRestTransport(interceptor=MyCustomDatasetServiceInterceptor())
        client = DatasetServiceClient(transport=transport)


    """

    def pre_create_dataset(
        self,
        request: dataset_service.CreateDatasetRequest,
        metadata: Sequence[Tuple[str, Union[str, bytes]]],
    ) -> Tuple[
        dataset_service.CreateDatasetRequest, Sequence[Tuple[str, Union[str, bytes]]]
    ]:
        """Pre-rpc interceptor for create_dataset

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

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

        DEPRECATED. Please use the `post_create_dataset_with_metadata`
        interceptor instead.

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

    def post_create_dataset_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 create_dataset

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

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

    def pre_create_dataset_version(
        self,
        request: dataset_service.CreateDatasetVersionRequest,
        metadata: Sequence[Tuple[str, Union[str, bytes]]],
    ) -> Tuple[
        dataset_service.CreateDatasetVersionRequest,
        Sequence[Tuple[str, Union[str, bytes]]],
    ]:
        """Pre-rpc interceptor for create_dataset_version

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

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

        DEPRECATED. Please use the `post_create_dataset_version_with_metadata`
        interceptor instead.

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

    def post_create_dataset_version_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 create_dataset_version

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

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

    def pre_delete_dataset(
        self,
        request: dataset_service.DeleteDatasetRequest,
        metadata: Sequence[Tuple[str, Union[str, bytes]]],
    ) -> Tuple[
        dataset_service.DeleteDatasetRequest, Sequence[Tuple[str, Union[str, bytes]]]
    ]:
        """Pre-rpc interceptor for delete_dataset

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

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

        DEPRECATED. Please use the `post_delete_dataset_with_metadata`
        interceptor instead.

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

    def post_delete_dataset_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_dataset

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

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

    def pre_delete_dataset_version(
        self,
        request: dataset_service.DeleteDatasetVersionRequest,
        metadata: Sequence[Tuple[str, Union[str, bytes]]],
    ) -> Tuple[
        dataset_service.DeleteDatasetVersionRequest,
        Sequence[Tuple[str, Union[str, bytes]]],
    ]:
        """Pre-rpc interceptor for delete_dataset_version

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

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

        DEPRECATED. Please use the `post_delete_dataset_version_with_metadata`
        interceptor instead.

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

    def post_delete_dataset_version_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_dataset_version

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

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

    def pre_delete_saved_query(
        self,
        request: dataset_service.DeleteSavedQueryRequest,
        metadata: Sequence[Tuple[str, Union[str, bytes]]],
    ) -> Tuple[
        dataset_service.DeleteSavedQueryRequest, Sequence[Tuple[str, Union[str, bytes]]]
    ]:
        """Pre-rpc interceptor for delete_saved_query

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

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

        DEPRECATED. Please use the `post_delete_saved_query_with_metadata`
        interceptor instead.

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

    def post_delete_saved_query_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_saved_query

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

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

    def pre_export_data(
        self,
        request: dataset_service.ExportDataRequest,
        metadata: Sequence[Tuple[str, Union[str, bytes]]],
    ) -> Tuple[
        dataset_service.ExportDataRequest, Sequence[Tuple[str, Union[str, bytes]]]
    ]:
        """Pre-rpc interceptor for export_data

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

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

        DEPRECATED. Please use the `post_export_data_with_metadata`
        interceptor instead.

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

    def post_export_data_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 export_data

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

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

    def pre_get_annotation_spec(
        self,
        request: dataset_service.GetAnnotationSpecRequest,
        metadata: Sequence[Tuple[str, Union[str, bytes]]],
    ) -> Tuple[
        dataset_service.GetAnnotationSpecRequest,
        Sequence[Tuple[str, Union[str, bytes]]],
    ]:
        """Pre-rpc interceptor for get_annotation_spec

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

    def post_get_annotation_spec(
        self, response: annotation_spec.AnnotationSpec
    ) -> annotation_spec.AnnotationSpec:
        """Post-rpc interceptor for get_annotation_spec

        DEPRECATED. Please use the `post_get_annotation_spec_with_metadata`
        interceptor instead.

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

    def post_get_annotation_spec_with_metadata(
        self,
        response: annotation_spec.AnnotationSpec,
        metadata: Sequence[Tuple[str, Union[str, bytes]]],
    ) -> Tuple[annotation_spec.AnnotationSpec, Sequence[Tuple[str, Union[str, bytes]]]]:
        """Post-rpc interceptor for get_annotation_spec

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

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

    def pre_get_dataset(
        self,
        request: dataset_service.GetDatasetRequest,
        metadata: Sequence[Tuple[str, Union[str, bytes]]],
    ) -> Tuple[
        dataset_service.GetDatasetRequest, Sequence[Tuple[str, Union[str, bytes]]]
    ]:
        """Pre-rpc interceptor for get_dataset

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

    def post_get_dataset(self, response: dataset.Dataset) -> dataset.Dataset:
        """Post-rpc interceptor for get_dataset

        DEPRECATED. Please use the `post_get_dataset_with_metadata`
        interceptor instead.

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

    def post_get_dataset_with_metadata(
        self,
        response: dataset.Dataset,
        metadata: Sequence[Tuple[str, Union[str, bytes]]],
    ) -> Tuple[dataset.Dataset, Sequence[Tuple[str, Union[str, bytes]]]]:
        """Post-rpc interceptor for get_dataset

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

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

    def pre_get_dataset_version(
        self,
        request: dataset_service.GetDatasetVersionRequest,
        metadata: Sequence[Tuple[str, Union[str, bytes]]],
    ) -> Tuple[
        dataset_service.GetDatasetVersionRequest,
        Sequence[Tuple[str, Union[str, bytes]]],
    ]:
        """Pre-rpc interceptor for get_dataset_version

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

    def post_get_dataset_version(
        self, response: dataset_version.DatasetVersion
    ) -> dataset_version.DatasetVersion:
        """Post-rpc interceptor for get_dataset_version

        DEPRECATED. Please use the `post_get_dataset_version_with_metadata`
        interceptor instead.

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

    def post_get_dataset_version_with_metadata(
        self,
        response: dataset_version.DatasetVersion,
        metadata: Sequence[Tuple[str, Union[str, bytes]]],
    ) -> Tuple[dataset_version.DatasetVersion, Sequence[Tuple[str, Union[str, bytes]]]]:
        """Post-rpc interceptor for get_dataset_version

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

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

    def pre_import_data(
        self,
        request: dataset_service.ImportDataRequest,
        metadata: Sequence[Tuple[str, Union[str, bytes]]],
    ) -> Tuple[
        dataset_service.ImportDataRequest, Sequence[Tuple[str, Union[str, bytes]]]
    ]:
        """Pre-rpc interceptor for import_data

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

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

        DEPRECATED. Please use the `post_import_data_with_metadata`
        interceptor instead.

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

    def post_import_data_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 import_data

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

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

    def pre_list_annotations(
        self,
        request: dataset_service.ListAnnotationsRequest,
        metadata: Sequence[Tuple[str, Union[str, bytes]]],
    ) -> Tuple[
        dataset_service.ListAnnotationsRequest, Sequence[Tuple[str, Union[str, bytes]]]
    ]:
        """Pre-rpc interceptor for list_annotations

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

    def post_list_annotations(
        self, response: dataset_service.ListAnnotationsResponse
    ) -> dataset_service.ListAnnotationsResponse:
        """Post-rpc interceptor for list_annotations

        DEPRECATED. Please use the `post_list_annotations_with_metadata`
        interceptor instead.

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

    def post_list_annotations_with_metadata(
        self,
        response: dataset_service.ListAnnotationsResponse,
        metadata: Sequence[Tuple[str, Union[str, bytes]]],
    ) -> Tuple[
        dataset_service.ListAnnotationsResponse, Sequence[Tuple[str, Union[str, bytes]]]
    ]:
        """Post-rpc interceptor for list_annotations

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

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

    def pre_list_data_items(
        self,
        request: dataset_service.ListDataItemsRequest,
        metadata: Sequence[Tuple[str, Union[str, bytes]]],
    ) -> Tuple[
        dataset_service.ListDataItemsRequest, Sequence[Tuple[str, Union[str, bytes]]]
    ]:
        """Pre-rpc interceptor for list_data_items

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

    def post_list_data_items(
        self, response: dataset_service.ListDataItemsResponse
    ) -> dataset_service.ListDataItemsResponse:
        """Post-rpc interceptor for list_data_items

        DEPRECATED. Please use the `post_list_data_items_with_metadata`
        interceptor instead.

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

    def post_list_data_items_with_metadata(
        self,
        response: dataset_service.ListDataItemsResponse,
        metadata: Sequence[Tuple[str, Union[str, bytes]]],
    ) -> Tuple[
        dataset_service.ListDataItemsResponse, Sequence[Tuple[str, Union[str, bytes]]]
    ]:
        """Post-rpc interceptor for list_data_items

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

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

    def pre_list_datasets(
        self,
        request: dataset_service.ListDatasetsRequest,
        metadata: Sequence[Tuple[str, Union[str, bytes]]],
    ) -> Tuple[
        dataset_service.ListDatasetsRequest, Sequence[Tuple[str, Union[str, bytes]]]
    ]:
        """Pre-rpc interceptor for list_datasets

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

    def post_list_datasets(
        self, response: dataset_service.ListDatasetsResponse
    ) -> dataset_service.ListDatasetsResponse:
        """Post-rpc interceptor for list_datasets

        DEPRECATED. Please use the `post_list_datasets_with_metadata`
        interceptor instead.

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

    def post_list_datasets_with_metadata(
        self,
        response: dataset_service.ListDatasetsResponse,
        metadata: Sequence[Tuple[str, Union[str, bytes]]],
    ) -> Tuple[
        dataset_service.ListDatasetsResponse, Sequence[Tuple[str, Union[str, bytes]]]
    ]:
        """Post-rpc interceptor for list_datasets

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

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

    def pre_list_dataset_versions(
        self,
        request: dataset_service.ListDatasetVersionsRequest,
        metadata: Sequence[Tuple[str, Union[str, bytes]]],
    ) -> Tuple[
        dataset_service.ListDatasetVersionsRequest,
        Sequence[Tuple[str, Union[str, bytes]]],
    ]:
        """Pre-rpc interceptor for list_dataset_versions

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

    def post_list_dataset_versions(
        self, response: dataset_service.ListDatasetVersionsResponse
    ) -> dataset_service.ListDatasetVersionsResponse:
        """Post-rpc interceptor for list_dataset_versions

        DEPRECATED. Please use the `post_list_dataset_versions_with_metadata`
        interceptor instead.

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

    def post_list_dataset_versions_with_metadata(
        self,
        response: dataset_service.ListDatasetVersionsResponse,
        metadata: Sequence[Tuple[str, Union[str, bytes]]],
    ) -> Tuple[
        dataset_service.ListDatasetVersionsResponse,
        Sequence[Tuple[str, Union[str, bytes]]],
    ]:
        """Post-rpc interceptor for list_dataset_versions

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

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

    def pre_list_saved_queries(
        self,
        request: dataset_service.ListSavedQueriesRequest,
        metadata: Sequence[Tuple[str, Union[str, bytes]]],
    ) -> Tuple[
        dataset_service.ListSavedQueriesRequest, Sequence[Tuple[str, Union[str, bytes]]]
    ]:
        """Pre-rpc interceptor for list_saved_queries

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

    def post_list_saved_queries(
        self, response: dataset_service.ListSavedQueriesResponse
    ) -> dataset_service.ListSavedQueriesResponse:
        """Post-rpc interceptor for list_saved_queries

        DEPRECATED. Please use the `post_list_saved_queries_with_metadata`
        interceptor instead.

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

    def post_list_saved_queries_with_metadata(
        self,
        response: dataset_service.ListSavedQueriesResponse,
        metadata: Sequence[Tuple[str, Union[str, bytes]]],
    ) -> Tuple[
        dataset_service.ListSavedQueriesResponse,
        Sequence[Tuple[str, Union[str, bytes]]],
    ]:
        """Post-rpc interceptor for list_saved_queries

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

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

    def pre_restore_dataset_version(
        self,
        request: dataset_service.RestoreDatasetVersionRequest,
        metadata: Sequence[Tuple[str, Union[str, bytes]]],
    ) -> Tuple[
        dataset_service.RestoreDatasetVersionRequest,
        Sequence[Tuple[str, Union[str, bytes]]],
    ]:
        """Pre-rpc interceptor for restore_dataset_version

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

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

        DEPRECATED. Please use the `post_restore_dataset_version_with_metadata`
        interceptor instead.

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

    def post_restore_dataset_version_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 restore_dataset_version

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

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

    def pre_search_data_items(
        self,
        request: dataset_service.SearchDataItemsRequest,
        metadata: Sequence[Tuple[str, Union[str, bytes]]],
    ) -> Tuple[
        dataset_service.SearchDataItemsRequest, Sequence[Tuple[str, Union[str, bytes]]]
    ]:
        """Pre-rpc interceptor for search_data_items

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

    def post_search_data_items(
        self, response: dataset_service.SearchDataItemsResponse
    ) -> dataset_service.SearchDataItemsResponse:
        """Post-rpc interceptor for search_data_items

        DEPRECATED. Please use the `post_search_data_items_with_metadata`
        interceptor instead.

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

    def post_search_data_items_with_metadata(
        self,
        response: dataset_service.SearchDataItemsResponse,
        metadata: Sequence[Tuple[str, Union[str, bytes]]],
    ) -> Tuple[
        dataset_service.SearchDataItemsResponse, Sequence[Tuple[str, Union[str, bytes]]]
    ]:
        """Post-rpc interceptor for search_data_items

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

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

    def pre_update_dataset(
        self,
        request: dataset_service.UpdateDatasetRequest,
        metadata: Sequence[Tuple[str, Union[str, bytes]]],
    ) -> Tuple[
        dataset_service.UpdateDatasetRequest, Sequence[Tuple[str, Union[str, bytes]]]
    ]:
        """Pre-rpc interceptor for update_dataset

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

    def post_update_dataset(self, response: gca_dataset.Dataset) -> gca_dataset.Dataset:
        """Post-rpc interceptor for update_dataset

        DEPRECATED. Please use the `post_update_dataset_with_metadata`
        interceptor instead.

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

    def post_update_dataset_with_metadata(
        self,
        response: gca_dataset.Dataset,
        metadata: Sequence[Tuple[str, Union[str, bytes]]],
    ) -> Tuple[gca_dataset.Dataset, Sequence[Tuple[str, Union[str, bytes]]]]:
        """Post-rpc interceptor for update_dataset

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

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

    def pre_update_dataset_version(
        self,
        request: dataset_service.UpdateDatasetVersionRequest,
        metadata: Sequence[Tuple[str, Union[str, bytes]]],
    ) -> Tuple[
        dataset_service.UpdateDatasetVersionRequest,
        Sequence[Tuple[str, Union[str, bytes]]],
    ]:
        """Pre-rpc interceptor for update_dataset_version

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

    def post_update_dataset_version(
        self, response: gca_dataset_version.DatasetVersion
    ) -> gca_dataset_version.DatasetVersion:
        """Post-rpc interceptor for update_dataset_version

        DEPRECATED. Please use the `post_update_dataset_version_with_metadata`
        interceptor instead.

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

    def post_update_dataset_version_with_metadata(
        self,
        response: gca_dataset_version.DatasetVersion,
        metadata: Sequence[Tuple[str, Union[str, bytes]]],
    ) -> Tuple[
        gca_dataset_version.DatasetVersion, Sequence[Tuple[str, Union[str, bytes]]]
    ]:
        """Post-rpc interceptor for update_dataset_version

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

        We recommend only using this `post_update_dataset_version_with_metadata`
        interceptor in new development instead of the `post_update_dataset_version` interceptor.
        When both interceptors are used, this `post_update_dataset_version_with_metadata` interceptor runs after the
        `post_update_dataset_version` interceptor. The (possibly modified) response returned by
        `post_update_dataset_version` will be passed to
        `post_update_dataset_version_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 DatasetService 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 DatasetService 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 DatasetService 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 DatasetService 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 DatasetService 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 DatasetService 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 DatasetService 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 DatasetService 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 DatasetService 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 DatasetService 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 DatasetService 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 DatasetService 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 DatasetService 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 DatasetService 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 DatasetService 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 DatasetService 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 DatasetService 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 DatasetService 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 DatasetService 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 DatasetService server but before
        it is returned to user code.
        """
        return response


@dataclasses.dataclass
class DatasetServiceRestStub:
    _session: AuthorizedSession
    _host: str
    _interceptor: DatasetServiceRestInterceptor


class DatasetServiceRestTransport(_BaseDatasetServiceRestTransport):
    """REST backend synchronous transport for DatasetService.

    The service that manages Vertex AI Dataset and its child
    resources.

    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[DatasetServiceRestInterceptor] = 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 DatasetServiceRestInterceptor()
        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/*/reasoningEngines/*/sessions/*/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",
                    },
                    {
                        "method": "post",
                        "uri": "/v1/{name=reasoningEngines/*/sessions/*/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",
                        "uri": "/ui/{name=projects/*/locations/*/datasets/*/annotationSpecs/*/operations/*}",
                    },
                    {
                        "method": "delete",
                        "uri": "/ui/{name=projects/*/locations/*/datasets/*/dataItems/*/annotations/*/operations/*}",
                    },
                    {
                        "method": "delete",
                        "uri": "/ui/{name=projects/*/locations/*/deploymentResourcePools/*/operations/*}",
                    },
                    {
                        "method": "delete",
                        "uri": "/ui/{name=projects/*/locations/*/edgeDevices/*/operations/*}",
                    },
                    {
                        "method": "delete",
                        "uri": "/ui/{name=projects/*/locations/*/endpoints/*/operations/*}",
                    },
                    {
                        "method": "delete",
                        "uri": "/ui/{name=projects/*/locations/*/extensionControllers/*}/operations",
                    },
                    {
                        "method": "delete",
                        "uri": "/ui/{name=projects/*/locations/*/extensions/*}/operations",
                    },
                    {
                        "method": "delete",
                        "uri": "/ui/{name=projects/*/locations/*/featurestores/*/operations/*}",
                    },
                    {
                        "method": "delete",
                        "uri": "/ui/{name=projects/*/locations/*/featurestores/*/entityTypes/*/operations/*}",
                    },
                    {
                        "method": "delete",
                        "uri": "/ui/{name=projects/*/locations/*/featurestores/*/entityTypes/*/features/*/operations/*}",
                    },
                    {
                        "method": "delete",
                        "uri": "/ui/{name=projects/*/locations/*/customJobs/*/operations/*}",
                    },
                    {
                        "method": "delete",
                        "uri": "/ui/{name=projects/*/locations/*/dataLabelingJobs/*/operations/*}",
                    },
                    {
                        "method": "delete",
                        "uri": "/ui/{name=projects/*/locations/*/hyperparameterTuningJobs/*/operations/*}",
                    },
                    {
                        "method": "delete",
                        "uri": "/ui/{name=projects/*/locations/*/indexes/*/operations/*}",
                    },
                    {
                        "method": "delete",
                        "uri": "/ui/{name=projects/*/locations/*/indexEndpoints/*/operations/*}",
                    },
                    {
                        "method": "delete",
                        "uri": "/ui/{name=projects/*/locations/*/metadataStores/*/operations/*}",
                    },
                    {
                        "method": "delete",
                        "uri": "/ui/{name=projects/*/locations/*/metadataStores/*/artifacts/*/operations/*}",
                    },
                    {
                        "method": "delete",
                        "uri": "/ui/{name=projects/*/locations/*/metadataStores/*/contexts/*/operations/*}",
                    },
                    {
                        "method": "delete",
                        "uri": "/ui/{name=projects/*/locations/*/metadataStores/*/executions/*/operations/*}",
                    },
                    {
                        "method": "delete",
                        "uri": "/ui/{name=projects/*/locations/*/modelDeploymentMonitoringJobs/*/operations/*}",
                    },
                    {
                        "method": "delete",
                        "uri": "/ui/{name=projects/*/locations/*/modelMonitors/*/operations/*}",
                    },
                    {
                        "method": "delete",
                        "uri": "/ui/{name=projects/*/locations/*/migratableResources/*/operations/*}",
                    },
                    {
                        "method": "delete",
                        "uri": "/ui/{name=projects/*/locations/*/models/*/operations/*}",
                    },
                    {
                        "method": "delete",
                        "uri": "/ui/{name=projects/*/locations/*/models/*/evaluations/*/operations/*}",
                    },
                    {
                        "method": "delete",
                        "uri": "/ui/{name=projects/*/locations/*/notebookExecutionJobs/*/operations/*}",
                    },
                    {
                        "method": "delete",
                        "uri": "/ui/{name=projects/*/locations/*/notebookRuntimes/*/operations/*}",
                    },
                    {
                        "method": "delete",
                        "uri": "/ui/{name=projects/*/locations/*/notebookRuntimeTemplates/*/operations/*}",
                    },
                    {
                        "method": "delete",
                        "uri": "/ui/{name=projects/*/locations/*/persistentResources/*/operations/*}",
                    },
                    {
                        "method": "delete",
                        "uri": "/ui/{name=projects/*/locations/*/studies/*/operations/*}",
                    },
                    {
                        "method": "delete",
                        "uri": "/ui/{name=projects/*/locations/*/studies/*/trials/*/operations/*}",
                    },
                    {
                        "method": "delete",
                        "uri": "/ui/{name=projects/*/locations/*/trainingPipelines/*/operations/*}",
                    },
                    {
                        "method": "delete",
                        "uri": "/ui/{name=projects/*/locations/*/pipelineJobs/*/operations/*}",
                    },
                    {
                        "method": "delete",
                        "uri": "/ui/{name=projects/*/locations/*/schedules/*/operations/*}",
                    },
                    {
                        "method": "delete",
                        "uri": "/ui/{name=projects/*/locations/*/specialistPools/*/operations/*}",
                    },
                    {
                        "method": "delete",
                        "uri": "/ui/{name=projects/*/locations/*/ragEngineConfig/operations/*}",
                    },
                    {
                        "method": "delete",
                        "uri": "/ui/{name=projects/*/locations/*/tensorboards/*/operations/*}",
                    },
                    {
                        "method": "delete",
                        "uri": "/ui/{name=projects/*/locations/*/tensorboards/*/experiments/*/operations/*}",
                    },
                    {
                        "method": "delete",
                        "uri": "/ui/{name=projects/*/locations/*/tensorboards/*/experiments/*/runs/*/operations/*}",
                    },
                    {
                        "method": "delete",
                        "uri": "/ui/{name=projects/*/locations/*/tensorboards/*/experiments/*/runs/*/timeSeries/*/operations/*}",
                    },
                    {
                        "method": "delete",
                        "uri": "/ui/{name=projects/*/locations/*/featureOnlineStores/*/operations/*}",
                    },
                    {
                        "method": "delete",
                        "uri": "/ui/{name=projects/*/locations/*/featureGroups/*/operations/*}",
                    },
                    {
                        "method": "delete",
                        "uri": "/ui/{name=projects/*/locations/*/featureGroups/*/features/*/operations/*}",
                    },
                    {
                        "method": "delete",
                        "uri": "/ui/{name=projects/*/locations/*/featureGroups/*/featureMonitors/*/operations/*}",
                    },
                    {
                        "method": "delete",
                        "uri": "/ui/{name=projects/*/locations/*/featureOnlineStores/*/featureViews/*/operations/*}",
                    },
                    {
                        "method": "delete",
                        "uri": "/v1/{name=projects/*/locations/*/operations/*}",
                    },
                    {
                        "method": "delete",
                        "uri": "/v1/{name=projects/*/locations/*/datasets/*/operations/*}",
                    },
                    {
                        "method": "delete",
                        "uri": "/v1/{name=projects/*/locations/*/datasets/*/dataItems/*/operations/*}",
                    },
                    {
                        "method": "delete",
                        "uri": "/v1/{name=projects/*/locations/*/datasets/*/savedQueries/*/operations/*}",
                    },
                    {
                        "method": "delete",
                        "uri": "/v1/{name=projects/*/locations/*/datasets/*/annotationSpecs/*/operations/*}",
                    },
                    {
                        "method": "delete",
                        "uri": "/v1/{name=projects/*/locations/*/datasets/*/dataItems/*/annotations/*/operations/*}",
                    },
                    {
                        "method": "delete",
                        "uri": "/v1/{name=projects/*/locations/*/deploymentResourcePools/*/operations/*}",
                    },
                    {
                        "method": "delete",
                        "uri": "/v1/{name=projects/*/locations/*/endpoints/*/operations/*}",
                    },
                    {
                        "method": "delete",
                        "uri": "/v1/{name=projects/*/locations/*/featurestores/*/operations/*}",
                    },
                    {
                        "method": "delete",
                        "uri": "/v1/{name=projects/*/locations/*/featurestores/*/entityTypes/*/operations/*}",
                    },
                    {
                        "method": "delete",
                        "uri": "/v1/{name=projects/*/locations/*/featurestores/*/entityTypes/*/features/*/operations/*}",
                    },
                    {
                        "method": "delete",
                        "uri": "/v1/{name=projects/*/locations/*/customJobs/*/operations/*}",
                    },
                    {
                        "method": "delete",
                        "uri": "/v1/{name=projects/*/locations/*/dataLabelingJobs/*/operations/*}",
                    },
                    {
                        "method": "delete",
                        "uri": "/v1/{name=projects/*/locations/*/hyperparameterTuningJobs/*/operations/*}",
                    },
                    {
                        "method": "delete",
                        "uri": "/v1/{name=projects/*/locations/*/indexes/*/operations/*}",
                    },
                    {
                        "method": "delete",
                        "uri": "/v1/{name=projects/*/locations/*/indexEndpoints/*/operations/*}",
                    },
                    {
                        "method": "delete",
                        "uri": "/v1/{name=projects/*/locations/*/metadataStores/*/operations/*}",
                    },
                    {
                        "method": "delete",
                        "uri": "/v1/{name=projects/*/locations/*/metadataStores/*/artifacts/*/operations/*}",
                    },
                    {
                        "method": "delete",
                        "uri": "/v1/{name=projects/*/locations/*/metadataStores/*/contexts/*/operations/*}",
                    },
                    {
                        "method": "delete",
                        "uri": "/v1/{name=projects/*/locations/*/metadataStores/*/executions/*/operations/*}",
                    },
                    {
                        "method": "delete",
                        "uri": "/v1/{name=projects/*/locations/*/modelDeploymentMonitoringJobs/*/operations/*}",
                    },
                    {
                        "method": "delete",
                        "uri": "/v1/{name=projects/*/locations/*/migratableResources/*/operations/*}",
                    },
                    {
                        "method": "delete",
                        "uri": "/v1/{name=projects/*/locations/*/models/*/operations/*}",
                    },
                    {
                        "method": "delete",
                        "uri": "/v1/{name=projects/*/locations/*/models/*/evaluations/*/operations/*}",
                    },
                    {
                        "method": "delete",
                        "uri": "/v1/{name=projects/*/locations/*/notebookExecutionJobs/*/operations/*}",
                    },
                    {
                        "method": "delete",
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                    {
                        "method": "get",
                        "uri": "/v1/{name=projects/*/locations/*/featurestores/*/entityTypes/*/features/*}/operations",
                    },
                    {
                        "method": "get",
                        "uri": "/v1/{name=projects/*/locations/*/customJobs/*}/operations",
                    },
                    {
                        "method": "get",
                        "uri": "/v1/{name=projects/*/locations/*/dataLabelingJobs/*}/operations",
                    },
                    {
                        "method": "get",
                        "uri": "/v1/{name=projects/*/locations/*/hyperparameterTuningJobs/*}/operations",
                    },
                    {
                        "method": "get",
                        "uri": "/v1/{name=projects/*/locations/*/tuningJobs/*}/operations",
                    },
                    {
                        "method": "get",
                        "uri": "/v1/{name=projects/*/locations/*/indexes/*}/operations",
                    },
                    {
                        "method": "get",
                        "uri": "/v1/{name=projects/*/locations/*/indexEndpoints/*}/operations",
                    },
                    {
                        "method": "get",
                        "uri": "/v1/{name=projects/*/locations/*/metadataStores/*}/operations",
                    },
                    {
                        "method": "get",
                        "uri": "/v1/{name=projects/*/locations/*/metadataStores/*/artifacts/*}/operations",
                    },
                    {
                        "method": "get",
                        "uri": "/v1/{name=projects/*/locations/*/metadataStores/*/contexts/*}/operations",
                    },
                    {
                        "method": "get",
                        "uri": "/v1/{name=projects/*/locations/*/metadataStores/*/executions/*}/operations",
                    },
                    {
                        "method": "get",
                        "uri": "/v1/{name=projects/*/locations/*/modelDeploymentMonitoringJobs/*}/operations",
                    },
                    {
                        "method": "get",
                        "uri": "/v1/{name=projects/*/locations/*/migratableResources/*}/operations",
                    },
                    {
                        "method": "get",
                        "uri": "/v1/{name=projects/*/locations/*/models/*}/operations",
                    },
                    {
                        "method": "get",
                        "uri": "/v1/{name=projects/*/locations/*/models/*/evaluations/*}/operations",
                    },
                    {
                        "method": "get",
                        "uri": "/v1/{name=projects/*/locations/*/notebookExecutionJobs/*}/operations",
                    },
                    {
                        "method": "get",
                        "uri": "/v1/{name=projects/*/locations/*/notebookRuntimes/*}/operations",
                    },
                    {
                        "method": "get",
                        "uri": "/v1/{name=projects/*/locations/*/notebookRuntimeTemplates/*}/operations",
                    },
                    {
                        "method": "get",
                        "uri": "/v1/{name=projects/*/locations/*/reasoningEngines/*}/operations",
                    },
                    {
                        "method": "get",
                        "uri": "/v1/{name=projects/*/locations/*/reasoningEngines/*/sessions/*}/operations",
                    },
                    {
                        "method": "get",
                        "uri": "/v1/{name=projects/*/locations/*/studies/*}/operations",
                    },
                    {
                        "method": "get",
                        "uri": "/v1/{name=projects/*/locations/*/studies/*/trials/*}/operations",
                    },
                    {
                        "method": "get",
                        "uri": "/v1/{name=projects/*/locations/*/trainingPipelines/*}/operations",
                    },
                    {
                        "method": "get",
                        "uri": "/v1/{name=projects/*/locations/*/persistentResources/*}/operations",
                    },
                    {
                        "method": "get",
                        "uri": "/v1/{name=projects/*/locations/*/pipelineJobs/*}/operations",
                    },
                    {
                        "method": "get",
                        "uri": "/v1/{name=projects/*/locations/*/ragEngineConfig}/operations",
                    },
                    {
                        "method": "get",
                        "uri": "/v1/{name=projects/*/locations/*/ragCorpora/*}/operations",
                    },
                    {
                        "method": "get",
                        "uri": "/v1/{name=projects/*/locations/*/ragCorpora/*/ragFiles/*}/operations",
                    },
                    {
                        "method": "get",
                        "uri": "/v1/{name=projects/*/locations/*/schedules/*}/operations",
                    },
                    {
                        "method": "get",
                        "uri": "/v1/{name=projects/*/locations/*/specialistPools/*}/operations",
                    },
                    {
                        "method": "get",
                        "uri": "/v1/{name=projects/*/locations/*/tensorboards/*}/operations",
                    },
                    {
                        "method": "get",
                        "uri": "/v1/{name=projects/*/locations/*/tensorboards/*/experiments/*}/operations",
                    },
                    {
                        "method": "get",
                        "uri": "/v1/{name=projects/*/locations/*/tensorboards/*/experiments/*/runs/*}/operations",
                    },
                    {
                        "method": "get",
                        "uri": "/v1/{name=projects/*/locations/*/tensorboards/*/experiments/*/runs/*/timeSeries/*}/operations",
                    },
                    {
                        "method": "get",
                        "uri": "/v1/{name=projects/*/locations/*/featureOnlineStores/*/operations/*}:wait",
                    },
                    {
                        "method": "get",
                        "uri": "/v1/{name=projects/*/locations/*/featureOnlineStores/*/featureViews/*/operations/*}:wait",
                    },
                    {
                        "method": "get",
                        "uri": "/v1/{name=projects/*/locations/*/featureGroups/*/operations/*}:wait",
                    },
                    {
                        "method": "get",
                        "uri": "/v1/{name=projects/*/locations/*/featureGroups/*/features/*/operations/*}:wait",
                    },
                    {
                        "method": "get",
                        "uri": "/v1/{name=reasoningEngines/*/sessions/*}/operations",
                    },
                ],
                "google.longrunning.Operations.WaitOperation": [
                    {
                        "method": "post",
                        "uri": "/ui/{name=projects/*/locations/*/operations/*}:wait",
                    },
                    {
                        "method": "post",
                        "uri": "/ui/{name=projects/*/locations/*/agents/*/operations/*}:wait",
                    },
                    {
                        "method": "post",
                        "uri": "/ui/{name=projects/*/locations/*/apps/*/operations/*}:wait",
                    },
                    {
                        "method": "post",
                        "uri": "/ui/{name=projects/*/locations/*/datasets/*/operations/*}:wait",
                    },
                    {
                        "method": "post",
                        "uri": "/ui/{name=projects/*/locations/*/datasets/*/dataItems/*/operations/*}:wait",
                    },
                    {
                        "method": "post",
                        "uri": "/ui/{name=projects/*/locations/*/datasets/*/savedQueries/*/operations/*}:wait",
                    },
                    {
                        "method": "post",
                        "uri": "/ui/{name=projects/*/locations/*/datasets/*/annotationSpecs/*/operations/*}:wait",
                    },
                    {
                        "method": "post",
                        "uri": "/ui/{name=projects/*/locations/*/datasets/*/dataItems/*/annotations/*/operations/*}:wait",
                    },
                    {
                        "method": "post",
                        "uri": "/ui/{name=projects/*/locations/*/deploymentResourcePools/*/operations/*}:wait",
                    },
                    {
                        "method": "post",
                        "uri": "/ui/{name=projects/*/locations/*/edgeDevices/*/operations/*}:wait",
                    },
                    {
                        "method": "post",
                        "uri": "/ui/{name=projects/*/locations/*/endpoints/*/operations/*}:wait",
                    },
                    {
                        "method": "post",
                        "uri": "/ui/{name=projects/*/locations/*/extensionControllers/*/operations/*}:wait",
                    },
                    {
                        "method": "post",
                        "uri": "/ui/{name=projects/*/locations/*/extensions/*/operations/*}:wait",
                    },
                    {
                        "method": "post",
                        "uri": "/ui/{name=projects/*/locations/*/featurestores/*/operations/*}:wait",
                    },
                    {
                        "method": "post",
                        "uri": "/ui/{name=projects/*/locations/*/featurestores/*/entityTypes/*/operations/*}:wait",
                    },
                    {
                        "method": "post",
                        "uri": "/ui/{name=projects/*/locations/*/featurestores/*/entityTypes/*/features/*/operations/*}:wait",
                    },
                    {
                        "method": "post",
                        "uri": "/ui/{name=projects/*/locations/*/customJobs/*/operations/*}:wait",
                    },
                    {
                        "method": "post",
                        "uri": "/ui/{name=projects/*/locations/*/dataLabelingJobs/*/operations/*}:wait",
                    },
                    {
                        "method": "post",
                        "uri": "/ui/{name=projects/*/locations/*/hyperparameterTuningJobs/*/operations/*}:wait",
                    },
                    {
                        "method": "post",
                        "uri": "/ui/{name=projects/*/locations/*/tuningJobs/*/operations/*}:wait",
                    },
                    {
                        "method": "post",
                        "uri": "/ui/{name=projects/*/locations/*/indexes/*/operations/*}:wait",
                    },
                    {
                        "method": "post",
                        "uri": "/ui/{name=projects/*/locations/*/indexEndpoints/*/operations/*}:wait",
                    },
                    {
                        "method": "post",
                        "uri": "/ui/{name=projects/*/locations/*/metadataStores/*/operations/*}:wait",
                    },
                    {
                        "method": "post",
                        "uri": "/ui/{name=projects/*/locations/*/metadataStores/*/artifacts/*/operations/*}:wait",
                    },
                    {
                        "method": "post",
                        "uri": "/ui/{name=projects/*/locations/*/metadataStores/*/contexts/*/operations/*}:wait",
                    },
                    {
                        "method": "post",
                        "uri": "/ui/{name=projects/*/locations/*/metadataStores/*/executions/*/operations/*}:wait",
                    },
                    {
                        "method": "post",
                        "uri": "/ui/{name=projects/*/locations/*/modelDeploymentMonitoringJobs/*/operations/*}:wait",
                    },
                    {
                        "method": "post",
                        "uri": "/ui/{name=projects/*/locations/*/modelMonitors/*/operations/*}:wait",
                    },
                    {
                        "method": "post",
                        "uri": "/ui/{name=projects/*/locations/*/migratableResources/*/operations/*}:wait",
                    },
                    {
                        "method": "post",
                        "uri": "/ui/{name=projects/*/locations/*/models/*/operations/*}:wait",
                    },
                    {
                        "method": "post",
                        "uri": "/ui/{name=projects/*/locations/*/models/*/evaluations/*/operations/*}:wait",
                    },
                    {
                        "method": "post",
                        "uri": "/ui/{name=projects/*/locations/*/notebookExecutionJobs/*/operations/*}:wait",
                    },
                    {
                        "method": "post",
                        "uri": "/ui/{name=projects/*/locations/*/notebookRuntimes/*/operations/*}:wait",
                    },
                    {
                        "method": "post",
                        "uri": "/ui/{name=projects/*/locations/*/notebookRuntimeTemplates/*/operations/*}:wait",
                    },
                    {
                        "method": "post",
                        "uri": "/ui/{name=projects/*/locations/*/studies/*/operations/*}:wait",
                    },
                    {
                        "method": "post",
                        "uri": "/ui/{name=projects/*/locations/*/studies/*/trials/*/operations/*}:wait",
                    },
                    {
                        "method": "post",
                        "uri": "/ui/{name=projects/*/locations/*/trainingPipelines/*/operations/*}:wait",
                    },
                    {
                        "method": "post",
                        "uri": "/ui/{name=projects/*/locations/*/persistentResources/*/operations/*}:wait",
                    },
                    {
                        "method": "post",
                        "uri": "/ui/{name=projects/*/locations/*/pipelineJobs/*/operations/*}:wait",
                    },
                    {
                        "method": "post",
                        "uri": "/ui/{name=projects/*/locations/*/schedules/*/operations/*}:wait",
                    },
                    {
                        "method": "post",
                        "uri": "/ui/{name=projects/*/locations/*/specialistPools/*/operations/*}:wait",
                    },
                    {
                        "method": "post",
                        "uri": "/ui/{name=projects/*/locations/*/ragEngineConfig/operations/*}:wait",
                    },
                    {
                        "method": "post",
                        "uri": "/ui/{name=projects/*/locations/*/tensorboards/*/operations/*}:wait",
                    },
                    {
                        "method": "post",
                        "uri": "/ui/{name=projects/*/locations/*/tensorboards/*/experiments/*/operations/*}:wait",
                    },
                    {
                        "method": "post",
                        "uri": "/ui/{name=projects/*/locations/*/tensorboards/*/experiments/*/runs/*/operations/*}:wait",
                    },
                    {
                        "method": "post",
                        "uri": "/ui/{name=projects/*/locations/*/tensorboards/*/experiments/*/runs/*/timeSeries/*/operations/*}:wait",
                    },
                    {
                        "method": "post",
                        "uri": "/ui/{name=projects/*/locations/*/featureOnlineStores/*/operations/*}:wait",
                    },
                    {
                        "method": "post",
                        "uri": "/ui/{name=projects/*/locations/*/featureOnlineStores/*/featureViews/*/operations/*}:wait",
                    },
                    {
                        "method": "post",
                        "uri": "/ui/{name=projects/*/locations/*/featureGroups/*/operations/*}:wait",
                    },
                    {
                        "method": "post",
                        "uri": "/ui/{name=projects/*/locations/*/featureGroups/*/features/*/operations/*}:wait",
                    },
                    {
                        "method": "post",
                        "uri": "/ui/{name=projects/*/locations/*/featureGroups/*/featureMonitors/*/operations/*}:wait",
                    },
                    {
                        "method": "post",
                        "uri": "/v1/{name=projects/*/locations/*/operations/*}:wait",
                    },
                    {
                        "method": "post",
                        "uri": "/v1/{name=projects/*/locations/*/datasets/*/operations/*}:wait",
                    },
                    {
                        "method": "post",
                        "uri": "/v1/{name=projects/*/locations/*/datasets/*/dataItems/*/operations/*}:wait",
                    },
                    {
                        "method": "post",
                        "uri": "/v1/{name=projects/*/locations/*/datasets/*/savedQueries/*/operations/*}:wait",
                    },
                    {
                        "method": "post",
                        "uri": "/v1/{name=projects/*/locations/*/datasets/*/annotationSpecs/*/operations/*}:wait",
                    },
                    {
                        "method": "post",
                        "uri": "/v1/{name=projects/*/locations/*/datasets/*/dataItems/*/annotations/*/operations/*}:wait",
                    },
                    {
                        "method": "post",
                        "uri": "/v1/{name=projects/*/locations/*/deploymentResourcePools/*/operations/*}:wait",
                    },
                    {
                        "method": "post",
                        "uri": "/v1/{name=projects/*/locations/*/endpoints/*/operations/*}:wait",
                    },
                    {
                        "method": "post",
                        "uri": "/v1/{name=projects/*/locations/*/featurestores/*/operations/*}:wait",
                    },
                    {
                        "method": "post",
                        "uri": "/v1/{name=projects/*/locations/*/featurestores/*/entityTypes/*/operations/*}:wait",
                    },
                    {
                        "method": "post",
                        "uri": "/v1/{name=projects/*/locations/*/featurestores/*/entityTypes/*/features/*/operations/*}:wait",
                    },
                    {
                        "method": "post",
                        "uri": "/v1/{name=projects/*/locations/*/customJobs/*/operations/*}:wait",
                    },
                    {
                        "method": "post",
                        "uri": "/v1/{name=projects/*/locations/*/dataLabelingJobs/*/operations/*}:wait",
                    },
                    {
                        "method": "post",
                        "uri": "/v1/{name=projects/*/locations/*/hyperparameterTuningJobs/*/operations/*}:wait",
                    },
                    {
                        "method": "post",
                        "uri": "/v1/{name=projects/*/locations/*/indexes/*/operations/*}:wait",
                    },
                    {
                        "method": "post",
                        "uri": "/v1/{name=projects/*/locations/*/indexEndpoints/*/operations/*}:wait",
                    },
                    {
                        "method": "post",
                        "uri": "/v1/{name=projects/*/locations/*/metadataStores/*/operations/*}:wait",
                    },
                    {
                        "method": "post",
                        "uri": "/v1/{name=projects/*/locations/*/metadataStores/*/artifacts/*/operations/*}:wait",
                    },
                    {
                        "method": "post",
                        "uri": "/v1/{name=projects/*/locations/*/metadataStores/*/contexts/*/operations/*}:wait",
                    },
                    {
                        "method": "post",
                        "uri": "/v1/{name=projects/*/locations/*/metadataStores/*/executions/*/operations/*}:wait",
                    },
                    {
                        "method": "post",
                        "uri": "/v1/{name=projects/*/locations/*/modelDeploymentMonitoringJobs/*/operations/*}:wait",
                    },
                    {
                        "method": "post",
                        "uri": "/v1/{name=projects/*/locations/*/migratableResources/*/operations/*}:wait",
                    },
                    {
                        "method": "post",
                        "uri": "/v1/{name=projects/*/locations/*/models/*/operations/*}:wait",
                    },
                    {
                        "method": "post",
                        "uri": "/v1/{name=projects/*/locations/*/models/*/evaluations/*/operations/*}:wait",
                    },
                    {
                        "method": "post",
                        "uri": "/v1/{name=projects/*/locations/*/notebookExecutionJobs/*/operations/*}:wait",
                    },
                    {
                        "method": "post",
                        "uri": "/v1/{name=projects/*/locations/*/notebookRuntimes/*/operations/*}:wait",
                    },
                    {
                        "method": "post",
                        "uri": "/v1/{name=projects/*/locations/*/notebookRuntimeTemplates/*/operations/*}:wait",
                    },
                    {
                        "method": "post",
                        "uri": "/v1/{name=projects/*/locations/*/ragEngineConfig/operations/*}:wait",
                    },
                    {
                        "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/*/reasoningEngines/*/sessions/*/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",
                    },
                    {
                        "method": "post",
                        "uri": "/v1/{name=reasoningEngines/*/sessions/*/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 _CreateDataset(
        _BaseDatasetServiceRestTransport._BaseCreateDataset, DatasetServiceRestStub
    ):
        def __hash__(self):
            return hash("DatasetServiceRestTransport.CreateDataset")

        @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: dataset_service.CreateDatasetRequest,
            *,
            retry: OptionalRetry = gapic_v1.method.DEFAULT,
            timeout: Optional[float] = None,
            metadata: Sequence[Tuple[str, Union[str, bytes]]] = (),
        ) -> operations_pb2.Operation:
            r"""Call the create dataset method over HTTP.

            Args:
                request (~.dataset_service.CreateDatasetRequest):
                    The request object. Request message for
                [DatasetService.CreateDataset][google.cloud.aiplatform.v1.DatasetService.CreateDataset].
                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 = (
                _BaseDatasetServiceRestTransport._BaseCreateDataset._get_http_options()
            )

            request, metadata = self._interceptor.pre_create_dataset(request, metadata)
            transcoded_request = _BaseDatasetServiceRestTransport._BaseCreateDataset._get_transcoded_request(
                http_options, request
            )

            body = _BaseDatasetServiceRestTransport._BaseCreateDataset._get_request_body_json(
                transcoded_request
            )

            # Jsonify the query params
            query_params = _BaseDatasetServiceRestTransport._BaseCreateDataset._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.DatasetServiceClient.CreateDataset",
                    extra={
                        "serviceName": "google.cloud.aiplatform.v1.DatasetService",
                        "rpcName": "CreateDataset",
                        "httpRequest": http_request,
                        "metadata": http_request["headers"],
                    },
                )

            # Send the request
            response = DatasetServiceRestTransport._CreateDataset._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_create_dataset(resp)
            response_metadata = [(k, str(v)) for k, v in response.headers.items()]
            resp, _ = self._interceptor.post_create_dataset_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.DatasetServiceClient.create_dataset",
                    extra={
                        "serviceName": "google.cloud.aiplatform.v1.DatasetService",
                        "rpcName": "CreateDataset",
                        "metadata": http_response["headers"],
                        "httpResponse": http_response,
                    },
                )
            return resp

    class _CreateDatasetVersion(
        _BaseDatasetServiceRestTransport._BaseCreateDatasetVersion,
        DatasetServiceRestStub,
    ):
        def __hash__(self):
            return hash("DatasetServiceRestTransport.CreateDatasetVersion")

        @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: dataset_service.CreateDatasetVersionRequest,
            *,
            retry: OptionalRetry = gapic_v1.method.DEFAULT,
            timeout: Optional[float] = None,
            metadata: Sequence[Tuple[str, Union[str, bytes]]] = (),
        ) -> operations_pb2.Operation:
            r"""Call the create dataset version method over HTTP.

            Args:
                request (~.dataset_service.CreateDatasetVersionRequest):
                    The request object. Request message for
                [DatasetService.CreateDatasetVersion][google.cloud.aiplatform.v1.DatasetService.CreateDatasetVersion].
                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 = (
                _BaseDatasetServiceRestTransport._BaseCreateDatasetVersion._get_http_options()
            )

            request, metadata = self._interceptor.pre_create_dataset_version(
                request, metadata
            )
            transcoded_request = _BaseDatasetServiceRestTransport._BaseCreateDatasetVersion._get_transcoded_request(
                http_options, request
            )

            body = _BaseDatasetServiceRestTransport._BaseCreateDatasetVersion._get_request_body_json(
                transcoded_request
            )

            # Jsonify the query params
            query_params = _BaseDatasetServiceRestTransport._BaseCreateDatasetVersion._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.DatasetServiceClient.CreateDatasetVersion",
                    extra={
                        "serviceName": "google.cloud.aiplatform.v1.DatasetService",
                        "rpcName": "CreateDatasetVersion",
                        "httpRequest": http_request,
                        "metadata": http_request["headers"],
                    },
                )

            # Send the request
            response = DatasetServiceRestTransport._CreateDatasetVersion._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_create_dataset_version(resp)
            response_metadata = [(k, str(v)) for k, v in response.headers.items()]
            resp, _ = self._interceptor.post_create_dataset_version_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.DatasetServiceClient.create_dataset_version",
                    extra={
                        "serviceName": "google.cloud.aiplatform.v1.DatasetService",
                        "rpcName": "CreateDatasetVersion",
                        "metadata": http_response["headers"],
                        "httpResponse": http_response,
                    },
                )
            return resp

    class _DeleteDataset(
        _BaseDatasetServiceRestTransport._BaseDeleteDataset, DatasetServiceRestStub
    ):
        def __hash__(self):
            return hash("DatasetServiceRestTransport.DeleteDataset")

        @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: dataset_service.DeleteDatasetRequest,
            *,
            retry: OptionalRetry = gapic_v1.method.DEFAULT,
            timeout: Optional[float] = None,
            metadata: Sequence[Tuple[str, Union[str, bytes]]] = (),
        ) -> operations_pb2.Operation:
            r"""Call the delete dataset method over HTTP.

            Args:
                request (~.dataset_service.DeleteDatasetRequest):
                    The request object. Request message for
                [DatasetService.DeleteDataset][google.cloud.aiplatform.v1.DatasetService.DeleteDataset].
                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 = (
                _BaseDatasetServiceRestTransport._BaseDeleteDataset._get_http_options()
            )

            request, metadata = self._interceptor.pre_delete_dataset(request, metadata)
            transcoded_request = _BaseDatasetServiceRestTransport._BaseDeleteDataset._get_transcoded_request(
                http_options, request
            )

            # Jsonify the query params
            query_params = _BaseDatasetServiceRestTransport._BaseDeleteDataset._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.DatasetServiceClient.DeleteDataset",
                    extra={
                        "serviceName": "google.cloud.aiplatform.v1.DatasetService",
                        "rpcName": "DeleteDataset",
                        "httpRequest": http_request,
                        "metadata": http_request["headers"],
                    },
                )

            # Send the request
            response = DatasetServiceRestTransport._DeleteDataset._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_dataset(resp)
            response_metadata = [(k, str(v)) for k, v in response.headers.items()]
            resp, _ = self._interceptor.post_delete_dataset_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.DatasetServiceClient.delete_dataset",
                    extra={
                        "serviceName": "google.cloud.aiplatform.v1.DatasetService",
                        "rpcName": "DeleteDataset",
                        "metadata": http_response["headers"],
                        "httpResponse": http_response,
                    },
                )
            return resp

    class _DeleteDatasetVersion(
        _BaseDatasetServiceRestTransport._BaseDeleteDatasetVersion,
        DatasetServiceRestStub,
    ):
        def __hash__(self):
            return hash("DatasetServiceRestTransport.DeleteDatasetVersion")

        @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: dataset_service.DeleteDatasetVersionRequest,
            *,
            retry: OptionalRetry = gapic_v1.method.DEFAULT,
            timeout: Optional[float] = None,
            metadata: Sequence[Tuple[str, Union[str, bytes]]] = (),
        ) -> operations_pb2.Operation:
            r"""Call the delete dataset version method over HTTP.

            Args:
                request (~.dataset_service.DeleteDatasetVersionRequest):
                    The request object. Request message for
                [DatasetService.DeleteDatasetVersion][google.cloud.aiplatform.v1.DatasetService.DeleteDatasetVersion].
                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 = (
                _BaseDatasetServiceRestTransport._BaseDeleteDatasetVersion._get_http_options()
            )

            request, metadata = self._interceptor.pre_delete_dataset_version(
                request, metadata
            )
            transcoded_request = _BaseDatasetServiceRestTransport._BaseDeleteDatasetVersion._get_transcoded_request(
                http_options, request
            )

            # Jsonify the query params
            query_params = _BaseDatasetServiceRestTransport._BaseDeleteDatasetVersion._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.DatasetServiceClient.DeleteDatasetVersion",
                    extra={
                        "serviceName": "google.cloud.aiplatform.v1.DatasetService",
                        "rpcName": "DeleteDatasetVersion",
                        "httpRequest": http_request,
                        "metadata": http_request["headers"],
                    },
                )

            # Send the request
            response = DatasetServiceRestTransport._DeleteDatasetVersion._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_dataset_version(resp)
            response_metadata = [(k, str(v)) for k, v in response.headers.items()]
            resp, _ = self._interceptor.post_delete_dataset_version_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.DatasetServiceClient.delete_dataset_version",
                    extra={
                        "serviceName": "google.cloud.aiplatform.v1.DatasetService",
                        "rpcName": "DeleteDatasetVersion",
                        "metadata": http_response["headers"],
                        "httpResponse": http_response,
                    },
                )
            return resp

    class _DeleteSavedQuery(
        _BaseDatasetServiceRestTransport._BaseDeleteSavedQuery, DatasetServiceRestStub
    ):
        def __hash__(self):
            return hash("DatasetServiceRestTransport.DeleteSavedQuery")

        @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: dataset_service.DeleteSavedQueryRequest,
            *,
            retry: OptionalRetry = gapic_v1.method.DEFAULT,
            timeout: Optional[float] = None,
            metadata: Sequence[Tuple[str, Union[str, bytes]]] = (),
        ) -> operations_pb2.Operation:
            r"""Call the delete saved query method over HTTP.

            Args:
                request (~.dataset_service.DeleteSavedQueryRequest):
                    The request object. Request message for
                [DatasetService.DeleteSavedQuery][google.cloud.aiplatform.v1.DatasetService.DeleteSavedQuery].
                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 = (
                _BaseDatasetServiceRestTransport._BaseDeleteSavedQuery._get_http_options()
            )

            request, metadata = self._interceptor.pre_delete_saved_query(
                request, metadata
            )
            transcoded_request = _BaseDatasetServiceRestTransport._BaseDeleteSavedQuery._get_transcoded_request(
                http_options, request
            )

            # Jsonify the query params
            query_params = _BaseDatasetServiceRestTransport._BaseDeleteSavedQuery._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.DatasetServiceClient.DeleteSavedQuery",
                    extra={
                        "serviceName": "google.cloud.aiplatform.v1.DatasetService",
                        "rpcName": "DeleteSavedQuery",
                        "httpRequest": http_request,
                        "metadata": http_request["headers"],
                    },
                )

            # Send the request
            response = DatasetServiceRestTransport._DeleteSavedQuery._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_saved_query(resp)
            response_metadata = [(k, str(v)) for k, v in response.headers.items()]
            resp, _ = self._interceptor.post_delete_saved_query_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.DatasetServiceClient.delete_saved_query",
                    extra={
                        "serviceName": "google.cloud.aiplatform.v1.DatasetService",
                        "rpcName": "DeleteSavedQuery",
                        "metadata": http_response["headers"],
                        "httpResponse": http_response,
                    },
                )
            return resp

    class _ExportData(
        _BaseDatasetServiceRestTransport._BaseExportData, DatasetServiceRestStub
    ):
        def __hash__(self):
            return hash("DatasetServiceRestTransport.ExportData")

        @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: dataset_service.ExportDataRequest,
            *,
            retry: OptionalRetry = gapic_v1.method.DEFAULT,
            timeout: Optional[float] = None,
            metadata: Sequence[Tuple[str, Union[str, bytes]]] = (),
        ) -> operations_pb2.Operation:
            r"""Call the export data method over HTTP.

            Args:
                request (~.dataset_service.ExportDataRequest):
                    The request object. Request message for
                [DatasetService.ExportData][google.cloud.aiplatform.v1.DatasetService.ExportData].
                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 = (
                _BaseDatasetServiceRestTransport._BaseExportData._get_http_options()
            )

            request, metadata = self._interceptor.pre_export_data(request, metadata)
            transcoded_request = _BaseDatasetServiceRestTransport._BaseExportData._get_transcoded_request(
                http_options, request
            )

            body = (
                _BaseDatasetServiceRestTransport._BaseExportData._get_request_body_json(
                    transcoded_request
                )
            )

            # Jsonify the query params
            query_params = (
                _BaseDatasetServiceRestTransport._BaseExportData._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.DatasetServiceClient.ExportData",
                    extra={
                        "serviceName": "google.cloud.aiplatform.v1.DatasetService",
                        "rpcName": "ExportData",
                        "httpRequest": http_request,
                        "metadata": http_request["headers"],
                    },
                )

            # Send the request
            response = DatasetServiceRestTransport._ExportData._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_export_data(resp)
            response_metadata = [(k, str(v)) for k, v in response.headers.items()]
            resp, _ = self._interceptor.post_export_data_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.DatasetServiceClient.export_data",
                    extra={
                        "serviceName": "google.cloud.aiplatform.v1.DatasetService",
                        "rpcName": "ExportData",
                        "metadata": http_response["headers"],
                        "httpResponse": http_response,
                    },
                )
            return resp

    class _GetAnnotationSpec(
        _BaseDatasetServiceRestTransport._BaseGetAnnotationSpec, DatasetServiceRestStub
    ):
        def __hash__(self):
            return hash("DatasetServiceRestTransport.GetAnnotationSpec")

        @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: dataset_service.GetAnnotationSpecRequest,
            *,
            retry: OptionalRetry = gapic_v1.method.DEFAULT,
            timeout: Optional[float] = None,
            metadata: Sequence[Tuple[str, Union[str, bytes]]] = (),
        ) -> annotation_spec.AnnotationSpec:
            r"""Call the get annotation spec method over HTTP.

            Args:
                request (~.dataset_service.GetAnnotationSpecRequest):
                    The request object. Request message for
                [DatasetService.GetAnnotationSpec][google.cloud.aiplatform.v1.DatasetService.GetAnnotationSpec].
                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:
                ~.annotation_spec.AnnotationSpec:
                    Identifies a concept with which
                DataItems may be annotated with.

            """

            http_options = (
                _BaseDatasetServiceRestTransport._BaseGetAnnotationSpec._get_http_options()
            )

            request, metadata = self._interceptor.pre_get_annotation_spec(
                request, metadata
            )
            transcoded_request = _BaseDatasetServiceRestTransport._BaseGetAnnotationSpec._get_transcoded_request(
                http_options, request
            )

            # Jsonify the query params
            query_params = _BaseDatasetServiceRestTransport._BaseGetAnnotationSpec._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.DatasetServiceClient.GetAnnotationSpec",
                    extra={
                        "serviceName": "google.cloud.aiplatform.v1.DatasetService",
                        "rpcName": "GetAnnotationSpec",
                        "httpRequest": http_request,
                        "metadata": http_request["headers"],
                    },
                )

            # Send the request
            response = DatasetServiceRestTransport._GetAnnotationSpec._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 = annotation_spec.AnnotationSpec()
            pb_resp = annotation_spec.AnnotationSpec.pb(resp)

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

            resp = self._interceptor.post_get_annotation_spec(resp)
            response_metadata = [(k, str(v)) for k, v in response.headers.items()]
            resp, _ = self._interceptor.post_get_annotation_spec_with_metadata(
                resp, response_metadata
            )
            if CLIENT_LOGGING_SUPPORTED and _LOGGER.isEnabledFor(
                logging.DEBUG
            ):  # pragma: NO COVER
                try:
                    response_payload = annotation_spec.AnnotationSpec.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.DatasetServiceClient.get_annotation_spec",
                    extra={
                        "serviceName": "google.cloud.aiplatform.v1.DatasetService",
                        "rpcName": "GetAnnotationSpec",
                        "metadata": http_response["headers"],
                        "httpResponse": http_response,
                    },
                )
            return resp

    class _GetDataset(
        _BaseDatasetServiceRestTransport._BaseGetDataset, DatasetServiceRestStub
    ):
        def __hash__(self):
            return hash("DatasetServiceRestTransport.GetDataset")

        @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: dataset_service.GetDatasetRequest,
            *,
            retry: OptionalRetry = gapic_v1.method.DEFAULT,
            timeout: Optional[float] = None,
            metadata: Sequence[Tuple[str, Union[str, bytes]]] = (),
        ) -> dataset.Dataset:
            r"""Call the get dataset method over HTTP.

            Args:
                request (~.dataset_service.GetDatasetRequest):
                    The request object. Request message for
                [DatasetService.GetDataset][google.cloud.aiplatform.v1.DatasetService.GetDataset].
                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:
                ~.dataset.Dataset:
                    A collection of DataItems and
                Annotations on them.

            """

            http_options = (
                _BaseDatasetServiceRestTransport._BaseGetDataset._get_http_options()
            )

            request, metadata = self._interceptor.pre_get_dataset(request, metadata)
            transcoded_request = _BaseDatasetServiceRestTransport._BaseGetDataset._get_transcoded_request(
                http_options, request
            )

            # Jsonify the query params
            query_params = (
                _BaseDatasetServiceRestTransport._BaseGetDataset._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.DatasetServiceClient.GetDataset",
                    extra={
                        "serviceName": "google.cloud.aiplatform.v1.DatasetService",
                        "rpcName": "GetDataset",
                        "httpRequest": http_request,
                        "metadata": http_request["headers"],
                    },
                )

            # Send the request
            response = DatasetServiceRestTransport._GetDataset._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 = dataset.Dataset()
            pb_resp = dataset.Dataset.pb(resp)

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

            resp = self._interceptor.post_get_dataset(resp)
            response_metadata = [(k, str(v)) for k, v in response.headers.items()]
            resp, _ = self._interceptor.post_get_dataset_with_metadata(
                resp, response_metadata
            )
            if CLIENT_LOGGING_SUPPORTED and _LOGGER.isEnabledFor(
                logging.DEBUG
            ):  # pragma: NO COVER
                try:
                    response_payload = dataset.Dataset.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.DatasetServiceClient.get_dataset",
                    extra={
                        "serviceName": "google.cloud.aiplatform.v1.DatasetService",
                        "rpcName": "GetDataset",
                        "metadata": http_response["headers"],
                        "httpResponse": http_response,
                    },
                )
            return resp

    class _GetDatasetVersion(
        _BaseDatasetServiceRestTransport._BaseGetDatasetVersion, DatasetServiceRestStub
    ):
        def __hash__(self):
            return hash("DatasetServiceRestTransport.GetDatasetVersion")

        @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: dataset_service.GetDatasetVersionRequest,
            *,
            retry: OptionalRetry = gapic_v1.method.DEFAULT,
            timeout: Optional[float] = None,
            metadata: Sequence[Tuple[str, Union[str, bytes]]] = (),
        ) -> dataset_version.DatasetVersion:
            r"""Call the get dataset version method over HTTP.

            Args:
                request (~.dataset_service.GetDatasetVersionRequest):
                    The request object. Request message for
                [DatasetService.GetDatasetVersion][google.cloud.aiplatform.v1.DatasetService.GetDatasetVersion].
                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:
                ~.dataset_version.DatasetVersion:
                    Describes the dataset version.
            """

            http_options = (
                _BaseDatasetServiceRestTransport._BaseGetDatasetVersion._get_http_options()
            )

            request, metadata = self._interceptor.pre_get_dataset_version(
                request, metadata
            )
            transcoded_request = _BaseDatasetServiceRestTransport._BaseGetDatasetVersion._get_transcoded_request(
                http_options, request
            )

            # Jsonify the query params
            query_params = _BaseDatasetServiceRestTransport._BaseGetDatasetVersion._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.DatasetServiceClient.GetDatasetVersion",
                    extra={
                        "serviceName": "google.cloud.aiplatform.v1.DatasetService",
                        "rpcName": "GetDatasetVersion",
                        "httpRequest": http_request,
                        "metadata": http_request["headers"],
                    },
                )

            # Send the request
            response = DatasetServiceRestTransport._GetDatasetVersion._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 = dataset_version.DatasetVersion()
            pb_resp = dataset_version.DatasetVersion.pb(resp)

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

            resp = self._interceptor.post_get_dataset_version(resp)
            response_metadata = [(k, str(v)) for k, v in response.headers.items()]
            resp, _ = self._interceptor.post_get_dataset_version_with_metadata(
                resp, response_metadata
            )
            if CLIENT_LOGGING_SUPPORTED and _LOGGER.isEnabledFor(
                logging.DEBUG
            ):  # pragma: NO COVER
                try:
                    response_payload = dataset_version.DatasetVersion.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.DatasetServiceClient.get_dataset_version",
                    extra={
                        "serviceName": "google.cloud.aiplatform.v1.DatasetService",
                        "rpcName": "GetDatasetVersion",
                        "metadata": http_response["headers"],
                        "httpResponse": http_response,
                    },
                )
            return resp

    class _ImportData(
        _BaseDatasetServiceRestTransport._BaseImportData, DatasetServiceRestStub
    ):
        def __hash__(self):
            return hash("DatasetServiceRestTransport.ImportData")

        @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: dataset_service.ImportDataRequest,
            *,
            retry: OptionalRetry = gapic_v1.method.DEFAULT,
            timeout: Optional[float] = None,
            metadata: Sequence[Tuple[str, Union[str, bytes]]] = (),
        ) -> operations_pb2.Operation:
            r"""Call the import data method over HTTP.

            Args:
                request (~.dataset_service.ImportDataRequest):
                    The request object. Request message for
                [DatasetService.ImportData][google.cloud.aiplatform.v1.DatasetService.ImportData].
                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 = (
                _BaseDatasetServiceRestTransport._BaseImportData._get_http_options()
            )

            request, metadata = self._interceptor.pre_import_data(request, metadata)
            transcoded_request = _BaseDatasetServiceRestTransport._BaseImportData._get_transcoded_request(
                http_options, request
            )

            body = (
                _BaseDatasetServiceRestTransport._BaseImportData._get_request_body_json(
                    transcoded_request
                )
            )

            # Jsonify the query params
            query_params = (
                _BaseDatasetServiceRestTransport._BaseImportData._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.DatasetServiceClient.ImportData",
                    extra={
                        "serviceName": "google.cloud.aiplatform.v1.DatasetService",
                        "rpcName": "ImportData",
                        "httpRequest": http_request,
                        "metadata": http_request["headers"],
                    },
                )

            # Send the request
            response = DatasetServiceRestTransport._ImportData._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_import_data(resp)
            response_metadata = [(k, str(v)) for k, v in response.headers.items()]
            resp, _ = self._interceptor.post_import_data_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.DatasetServiceClient.import_data",
                    extra={
                        "serviceName": "google.cloud.aiplatform.v1.DatasetService",
                        "rpcName": "ImportData",
                        "metadata": http_response["headers"],
                        "httpResponse": http_response,
                    },
                )
            return resp

    class _ListAnnotations(
        _BaseDatasetServiceRestTransport._BaseListAnnotations, DatasetServiceRestStub
    ):
        def __hash__(self):
            return hash("DatasetServiceRestTransport.ListAnnotations")

        @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: dataset_service.ListAnnotationsRequest,
            *,
            retry: OptionalRetry = gapic_v1.method.DEFAULT,
            timeout: Optional[float] = None,
            metadata: Sequence[Tuple[str, Union[str, bytes]]] = (),
        ) -> dataset_service.ListAnnotationsResponse:
            r"""Call the list annotations method over HTTP.

            Args:
                request (~.dataset_service.ListAnnotationsRequest):
                    The request object. Request message for
                [DatasetService.ListAnnotations][google.cloud.aiplatform.v1.DatasetService.ListAnnotations].
                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:
                ~.dataset_service.ListAnnotationsResponse:
                    Response message for
                [DatasetService.ListAnnotations][google.cloud.aiplatform.v1.DatasetService.ListAnnotations].

            """

            http_options = (
                _BaseDatasetServiceRestTransport._BaseListAnnotations._get_http_options()
            )

            request, metadata = self._interceptor.pre_list_annotations(
                request, metadata
            )
            transcoded_request = _BaseDatasetServiceRestTransport._BaseListAnnotations._get_transcoded_request(
                http_options, request
            )

            # Jsonify the query params
            query_params = _BaseDatasetServiceRestTransport._BaseListAnnotations._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.DatasetServiceClient.ListAnnotations",
                    extra={
                        "serviceName": "google.cloud.aiplatform.v1.DatasetService",
                        "rpcName": "ListAnnotations",
                        "httpRequest": http_request,
                        "metadata": http_request["headers"],
                    },
                )

            # Send the request
            response = DatasetServiceRestTransport._ListAnnotations._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 = dataset_service.ListAnnotationsResponse()
            pb_resp = dataset_service.ListAnnotationsResponse.pb(resp)

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

            resp = self._interceptor.post_list_annotations(resp)
            response_metadata = [(k, str(v)) for k, v in response.headers.items()]
            resp, _ = self._interceptor.post_list_annotations_with_metadata(
                resp, response_metadata
            )
            if CLIENT_LOGGING_SUPPORTED and _LOGGER.isEnabledFor(
                logging.DEBUG
            ):  # pragma: NO COVER
                try:
                    response_payload = dataset_service.ListAnnotationsResponse.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.DatasetServiceClient.list_annotations",
                    extra={
                        "serviceName": "google.cloud.aiplatform.v1.DatasetService",
                        "rpcName": "ListAnnotations",
                        "metadata": http_response["headers"],
                        "httpResponse": http_response,
                    },
                )
            return resp

    class _ListDataItems(
        _BaseDatasetServiceRestTransport._BaseListDataItems, DatasetServiceRestStub
    ):
        def __hash__(self):
            return hash("DatasetServiceRestTransport.ListDataItems")

        @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: dataset_service.ListDataItemsRequest,
            *,
            retry: OptionalRetry = gapic_v1.method.DEFAULT,
            timeout: Optional[float] = None,
            metadata: Sequence[Tuple[str, Union[str, bytes]]] = (),
        ) -> dataset_service.ListDataItemsResponse:
            r"""Call the list data items method over HTTP.

            Args:
                request (~.dataset_service.ListDataItemsRequest):
                    The request object. Request message for
                [DatasetService.ListDataItems][google.cloud.aiplatform.v1.DatasetService.ListDataItems].
                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:
                ~.dataset_service.ListDataItemsResponse:
                    Response message for
                [DatasetService.ListDataItems][google.cloud.aiplatform.v1.DatasetService.ListDataItems].

            """

            http_options = (
                _BaseDatasetServiceRestTransport._BaseListDataItems._get_http_options()
            )

            request, metadata = self._interceptor.pre_list_data_items(request, metadata)
            transcoded_request = _BaseDatasetServiceRestTransport._BaseListDataItems._get_transcoded_request(
                http_options, request
            )

            # Jsonify the query params
            query_params = _BaseDatasetServiceRestTransport._BaseListDataItems._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.DatasetServiceClient.ListDataItems",
                    extra={
                        "serviceName": "google.cloud.aiplatform.v1.DatasetService",
                        "rpcName": "ListDataItems",
                        "httpRequest": http_request,
                        "metadata": http_request["headers"],
                    },
                )

            # Send the request
            response = DatasetServiceRestTransport._ListDataItems._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 = dataset_service.ListDataItemsResponse()
            pb_resp = dataset_service.ListDataItemsResponse.pb(resp)

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

            resp = self._interceptor.post_list_data_items(resp)
            response_metadata = [(k, str(v)) for k, v in response.headers.items()]
            resp, _ = self._interceptor.post_list_data_items_with_metadata(
                resp, response_metadata
            )
            if CLIENT_LOGGING_SUPPORTED and _LOGGER.isEnabledFor(
                logging.DEBUG
            ):  # pragma: NO COVER
                try:
                    response_payload = dataset_service.ListDataItemsResponse.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.DatasetServiceClient.list_data_items",
                    extra={
                        "serviceName": "google.cloud.aiplatform.v1.DatasetService",
                        "rpcName": "ListDataItems",
                        "metadata": http_response["headers"],
                        "httpResponse": http_response,
                    },
                )
            return resp

    class _ListDatasets(
        _BaseDatasetServiceRestTransport._BaseListDatasets, DatasetServiceRestStub
    ):
        def __hash__(self):
            return hash("DatasetServiceRestTransport.ListDatasets")

        @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: dataset_service.ListDatasetsRequest,
            *,
            retry: OptionalRetry = gapic_v1.method.DEFAULT,
            timeout: Optional[float] = None,
            metadata: Sequence[Tuple[str, Union[str, bytes]]] = (),
        ) -> dataset_service.ListDatasetsResponse:
            r"""Call the list datasets method over HTTP.

            Args:
                request (~.dataset_service.ListDatasetsRequest):
                    The request object. Request message for
                [DatasetService.ListDatasets][google.cloud.aiplatform.v1.DatasetService.ListDatasets].
                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:
                ~.dataset_service.ListDatasetsResponse:
                    Response message for
                [DatasetService.ListDatasets][google.cloud.aiplatform.v1.DatasetService.ListDatasets].

            """

            http_options = (
                _BaseDatasetServiceRestTransport._BaseListDatasets._get_http_options()
            )

            request, metadata = self._interceptor.pre_list_datasets(request, metadata)
            transcoded_request = _BaseDatasetServiceRestTransport._BaseListDatasets._get_transcoded_request(
                http_options, request
            )

            # Jsonify the query params
            query_params = _BaseDatasetServiceRestTransport._BaseListDatasets._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.DatasetServiceClient.ListDatasets",
                    extra={
                        "serviceName": "google.cloud.aiplatform.v1.DatasetService",
                        "rpcName": "ListDatasets",
                        "httpRequest": http_request,
                        "metadata": http_request["headers"],
                    },
                )

            # Send the request
            response = DatasetServiceRestTransport._ListDatasets._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 = dataset_service.ListDatasetsResponse()
            pb_resp = dataset_service.ListDatasetsResponse.pb(resp)

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

            resp = self._interceptor.post_list_datasets(resp)
            response_metadata = [(k, str(v)) for k, v in response.headers.items()]
            resp, _ = self._interceptor.post_list_datasets_with_metadata(
                resp, response_metadata
            )
            if CLIENT_LOGGING_SUPPORTED and _LOGGER.isEnabledFor(
                logging.DEBUG
            ):  # pragma: NO COVER
                try:
                    response_payload = dataset_service.ListDatasetsResponse.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.DatasetServiceClient.list_datasets",
                    extra={
                        "serviceName": "google.cloud.aiplatform.v1.DatasetService",
                        "rpcName": "ListDatasets",
                        "metadata": http_response["headers"],
                        "httpResponse": http_response,
                    },
                )
            return resp

    class _ListDatasetVersions(
        _BaseDatasetServiceRestTransport._BaseListDatasetVersions,
        DatasetServiceRestStub,
    ):
        def __hash__(self):
            return hash("DatasetServiceRestTransport.ListDatasetVersions")

        @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: dataset_service.ListDatasetVersionsRequest,
            *,
            retry: OptionalRetry = gapic_v1.method.DEFAULT,
            timeout: Optional[float] = None,
            metadata: Sequence[Tuple[str, Union[str, bytes]]] = (),
        ) -> dataset_service.ListDatasetVersionsResponse:
            r"""Call the list dataset versions method over HTTP.

            Args:
                request (~.dataset_service.ListDatasetVersionsRequest):
                    The request object. Request message for
                [DatasetService.ListDatasetVersions][google.cloud.aiplatform.v1.DatasetService.ListDatasetVersions].
                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:
                ~.dataset_service.ListDatasetVersionsResponse:
                    Response message for
                [DatasetService.ListDatasetVersions][google.cloud.aiplatform.v1.DatasetService.ListDatasetVersions].

            """

            http_options = (
                _BaseDatasetServiceRestTransport._BaseListDatasetVersions._get_http_options()
            )

            request, metadata = self._interceptor.pre_list_dataset_versions(
                request, metadata
            )
            transcoded_request = _BaseDatasetServiceRestTransport._BaseListDatasetVersions._get_transcoded_request(
                http_options, request
            )

            # Jsonify the query params
            query_params = _BaseDatasetServiceRestTransport._BaseListDatasetVersions._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.DatasetServiceClient.ListDatasetVersions",
                    extra={
                        "serviceName": "google.cloud.aiplatform.v1.DatasetService",
                        "rpcName": "ListDatasetVersions",
                        "httpRequest": http_request,
                        "metadata": http_request["headers"],
                    },
                )

            # Send the request
            response = DatasetServiceRestTransport._ListDatasetVersions._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 = dataset_service.ListDatasetVersionsResponse()
            pb_resp = dataset_service.ListDatasetVersionsResponse.pb(resp)

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

            resp = self._interceptor.post_list_dataset_versions(resp)
            response_metadata = [(k, str(v)) for k, v in response.headers.items()]
            resp, _ = self._interceptor.post_list_dataset_versions_with_metadata(
                resp, response_metadata
            )
            if CLIENT_LOGGING_SUPPORTED and _LOGGER.isEnabledFor(
                logging.DEBUG
            ):  # pragma: NO COVER
                try:
                    response_payload = (
                        dataset_service.ListDatasetVersionsResponse.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.DatasetServiceClient.list_dataset_versions",
                    extra={
                        "serviceName": "google.cloud.aiplatform.v1.DatasetService",
                        "rpcName": "ListDatasetVersions",
                        "metadata": http_response["headers"],
                        "httpResponse": http_response,
                    },
                )
            return resp

    class _ListSavedQueries(
        _BaseDatasetServiceRestTransport._BaseListSavedQueries, DatasetServiceRestStub
    ):
        def __hash__(self):
            return hash("DatasetServiceRestTransport.ListSavedQueries")

        @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: dataset_service.ListSavedQueriesRequest,
            *,
            retry: OptionalRetry = gapic_v1.method.DEFAULT,
            timeout: Optional[float] = None,
            metadata: Sequence[Tuple[str, Union[str, bytes]]] = (),
        ) -> dataset_service.ListSavedQueriesResponse:
            r"""Call the list saved queries method over HTTP.

            Args:
                request (~.dataset_service.ListSavedQueriesRequest):
                    The request object. Request message for
                [DatasetService.ListSavedQueries][google.cloud.aiplatform.v1.DatasetService.ListSavedQueries].
                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:
                ~.dataset_service.ListSavedQueriesResponse:
                    Response message for
                [DatasetService.ListSavedQueries][google.cloud.aiplatform.v1.DatasetService.ListSavedQueries].

            """

            http_options = (
                _BaseDatasetServiceRestTransport._BaseListSavedQueries._get_http_options()
            )

            request, metadata = self._interceptor.pre_list_saved_queries(
                request, metadata
            )
            transcoded_request = _BaseDatasetServiceRestTransport._BaseListSavedQueries._get_transcoded_request(
                http_options, request
            )

            # Jsonify the query params
            query_params = _BaseDatasetServiceRestTransport._BaseListSavedQueries._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.DatasetServiceClient.ListSavedQueries",
                    extra={
                        "serviceName": "google.cloud.aiplatform.v1.DatasetService",
                        "rpcName": "ListSavedQueries",
                        "httpRequest": http_request,
                        "metadata": http_request["headers"],
                    },
                )

            # Send the request
            response = DatasetServiceRestTransport._ListSavedQueries._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 = dataset_service.ListSavedQueriesResponse()
            pb_resp = dataset_service.ListSavedQueriesResponse.pb(resp)

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

            resp = self._interceptor.post_list_saved_queries(resp)
            response_metadata = [(k, str(v)) for k, v in response.headers.items()]
            resp, _ = self._interceptor.post_list_saved_queries_with_metadata(
                resp, response_metadata
            )
            if CLIENT_LOGGING_SUPPORTED and _LOGGER.isEnabledFor(
                logging.DEBUG
            ):  # pragma: NO COVER
                try:
                    response_payload = dataset_service.ListSavedQueriesResponse.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.DatasetServiceClient.list_saved_queries",
                    extra={
                        "serviceName": "google.cloud.aiplatform.v1.DatasetService",
                        "rpcName": "ListSavedQueries",
                        "metadata": http_response["headers"],
                        "httpResponse": http_response,
                    },
                )
            return resp

    class _RestoreDatasetVersion(
        _BaseDatasetServiceRestTransport._BaseRestoreDatasetVersion,
        DatasetServiceRestStub,
    ):
        def __hash__(self):
            return hash("DatasetServiceRestTransport.RestoreDatasetVersion")

        @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: dataset_service.RestoreDatasetVersionRequest,
            *,
            retry: OptionalRetry = gapic_v1.method.DEFAULT,
            timeout: Optional[float] = None,
            metadata: Sequence[Tuple[str, Union[str, bytes]]] = (),
        ) -> operations_pb2.Operation:
            r"""Call the restore dataset version method over HTTP.

            Args:
                request (~.dataset_service.RestoreDatasetVersionRequest):
                    The request object. Request message for
                [DatasetService.RestoreDatasetVersion][google.cloud.aiplatform.v1.DatasetService.RestoreDatasetVersion].
                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 = (
                _BaseDatasetServiceRestTransport._BaseRestoreDatasetVersion._get_http_options()
            )

            request, metadata = self._interceptor.pre_restore_dataset_version(
                request, metadata
            )
            transcoded_request = _BaseDatasetServiceRestTransport._BaseRestoreDatasetVersion._get_transcoded_request(
                http_options, request
            )

            # Jsonify the query params
            query_params = _BaseDatasetServiceRestTransport._BaseRestoreDatasetVersion._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.DatasetServiceClient.RestoreDatasetVersion",
                    extra={
                        "serviceName": "google.cloud.aiplatform.v1.DatasetService",
                        "rpcName": "RestoreDatasetVersion",
                        "httpRequest": http_request,
                        "metadata": http_request["headers"],
                    },
                )

            # Send the request
            response = DatasetServiceRestTransport._RestoreDatasetVersion._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_restore_dataset_version(resp)
            response_metadata = [(k, str(v)) for k, v in response.headers.items()]
            resp, _ = self._interceptor.post_restore_dataset_version_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.DatasetServiceClient.restore_dataset_version",
                    extra={
                        "serviceName": "google.cloud.aiplatform.v1.DatasetService",
                        "rpcName": "RestoreDatasetVersion",
                        "metadata": http_response["headers"],
                        "httpResponse": http_response,
                    },
                )
            return resp

    class _SearchDataItems(
        _BaseDatasetServiceRestTransport._BaseSearchDataItems, DatasetServiceRestStub
    ):
        def __hash__(self):
            return hash("DatasetServiceRestTransport.SearchDataItems")

        @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: dataset_service.SearchDataItemsRequest,
            *,
            retry: OptionalRetry = gapic_v1.method.DEFAULT,
            timeout: Optional[float] = None,
            metadata: Sequence[Tuple[str, Union[str, bytes]]] = (),
        ) -> dataset_service.SearchDataItemsResponse:
            r"""Call the search data items method over HTTP.

            Args:
                request (~.dataset_service.SearchDataItemsRequest):
                    The request object. Request message for
                [DatasetService.SearchDataItems][google.cloud.aiplatform.v1.DatasetService.SearchDataItems].
                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:
                ~.dataset_service.SearchDataItemsResponse:
                    Response message for
                [DatasetService.SearchDataItems][google.cloud.aiplatform.v1.DatasetService.SearchDataItems].

            """

            http_options = (
                _BaseDatasetServiceRestTransport._BaseSearchDataItems._get_http_options()
            )

            request, metadata = self._interceptor.pre_search_data_items(
                request, metadata
            )
            transcoded_request = _BaseDatasetServiceRestTransport._BaseSearchDataItems._get_transcoded_request(
                http_options, request
            )

            # Jsonify the query params
            query_params = _BaseDatasetServiceRestTransport._BaseSearchDataItems._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.DatasetServiceClient.SearchDataItems",
                    extra={
                        "serviceName": "google.cloud.aiplatform.v1.DatasetService",
                        "rpcName": "SearchDataItems",
                        "httpRequest": http_request,
                        "metadata": http_request["headers"],
                    },
                )

            # Send the request
            response = DatasetServiceRestTransport._SearchDataItems._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 = dataset_service.SearchDataItemsResponse()
            pb_resp = dataset_service.SearchDataItemsResponse.pb(resp)

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

            resp = self._interceptor.post_search_data_items(resp)
            response_metadata = [(k, str(v)) for k, v in response.headers.items()]
            resp, _ = self._interceptor.post_search_data_items_with_metadata(
                resp, response_metadata
            )
            if CLIENT_LOGGING_SUPPORTED and _LOGGER.isEnabledFor(
                logging.DEBUG
            ):  # pragma: NO COVER
                try:
                    response_payload = dataset_service.SearchDataItemsResponse.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.DatasetServiceClient.search_data_items",
                    extra={
                        "serviceName": "google.cloud.aiplatform.v1.DatasetService",
                        "rpcName": "SearchDataItems",
                        "metadata": http_response["headers"],
                        "httpResponse": http_response,
                    },
                )
            return resp

    class _UpdateDataset(
        _BaseDatasetServiceRestTransport._BaseUpdateDataset, DatasetServiceRestStub
    ):
        def __hash__(self):
            return hash("DatasetServiceRestTransport.UpdateDataset")

        @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: dataset_service.UpdateDatasetRequest,
            *,
            retry: OptionalRetry = gapic_v1.method.DEFAULT,
            timeout: Optional[float] = None,
            metadata: Sequence[Tuple[str, Union[str, bytes]]] = (),
        ) -> gca_dataset.Dataset:
            r"""Call the update dataset method over HTTP.

            Args:
                request (~.dataset_service.UpdateDatasetRequest):
                    The request object. Request message for
                [DatasetService.UpdateDataset][google.cloud.aiplatform.v1.DatasetService.UpdateDataset].
                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_dataset.Dataset:
                    A collection of DataItems and
                Annotations on them.

            """

            http_options = (
                _BaseDatasetServiceRestTransport._BaseUpdateDataset._get_http_options()
            )

            request, metadata = self._interceptor.pre_update_dataset(request, metadata)
            transcoded_request = _BaseDatasetServiceRestTransport._BaseUpdateDataset._get_transcoded_request(
                http_options, request
            )

            body = _BaseDatasetServiceRestTransport._BaseUpdateDataset._get_request_body_json(
                transcoded_request
            )

            # Jsonify the query params
            query_params = _BaseDatasetServiceRestTransport._BaseUpdateDataset._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.DatasetServiceClient.UpdateDataset",
                    extra={
                        "serviceName": "google.cloud.aiplatform.v1.DatasetService",
                        "rpcName": "UpdateDataset",
                        "httpRequest": http_request,
                        "metadata": http_request["headers"],
                    },
                )

            # Send the request
            response = DatasetServiceRestTransport._UpdateDataset._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_dataset.Dataset()
            pb_resp = gca_dataset.Dataset.pb(resp)

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

            resp = self._interceptor.post_update_dataset(resp)
            response_metadata = [(k, str(v)) for k, v in response.headers.items()]
            resp, _ = self._interceptor.post_update_dataset_with_metadata(
                resp, response_metadata
            )
            if CLIENT_LOGGING_SUPPORTED and _LOGGER.isEnabledFor(
                logging.DEBUG
            ):  # pragma: NO COVER
                try:
                    response_payload = gca_dataset.Dataset.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.DatasetServiceClient.update_dataset",
                    extra={
                        "serviceName": "google.cloud.aiplatform.v1.DatasetService",
                        "rpcName": "UpdateDataset",
                        "metadata": http_response["headers"],
                        "httpResponse": http_response,
                    },
                )
            return resp

    class _UpdateDatasetVersion(
        _BaseDatasetServiceRestTransport._BaseUpdateDatasetVersion,
        DatasetServiceRestStub,
    ):
        def __hash__(self):
            return hash("DatasetServiceRestTransport.UpdateDatasetVersion")

        @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: dataset_service.UpdateDatasetVersionRequest,
            *,
            retry: OptionalRetry = gapic_v1.method.DEFAULT,
            timeout: Optional[float] = None,
            metadata: Sequence[Tuple[str, Union[str, bytes]]] = (),
        ) -> gca_dataset_version.DatasetVersion:
            r"""Call the update dataset version method over HTTP.

            Args:
                request (~.dataset_service.UpdateDatasetVersionRequest):
                    The request object. Request message for
                [DatasetService.UpdateDatasetVersion][google.cloud.aiplatform.v1.DatasetService.UpdateDatasetVersion].
                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_dataset_version.DatasetVersion:
                    Describes the dataset version.
            """

            http_options = (
                _BaseDatasetServiceRestTransport._BaseUpdateDatasetVersion._get_http_options()
            )

            request, metadata = self._interceptor.pre_update_dataset_version(
                request, metadata
            )
            transcoded_request = _BaseDatasetServiceRestTransport._BaseUpdateDatasetVersion._get_transcoded_request(
                http_options, request
            )

            body = _BaseDatasetServiceRestTransport._BaseUpdateDatasetVersion._get_request_body_json(
                transcoded_request
            )

            # Jsonify the query params
            query_params = _BaseDatasetServiceRestTransport._BaseUpdateDatasetVersion._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.DatasetServiceClient.UpdateDatasetVersion",
                    extra={
                        "serviceName": "google.cloud.aiplatform.v1.DatasetService",
                        "rpcName": "UpdateDatasetVersion",
                        "httpRequest": http_request,
                        "metadata": http_request["headers"],
                    },
                )

            # Send the request
            response = DatasetServiceRestTransport._UpdateDatasetVersion._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_dataset_version.DatasetVersion()
            pb_resp = gca_dataset_version.DatasetVersion.pb(resp)

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

            resp = self._interceptor.post_update_dataset_version(resp)
            response_metadata = [(k, str(v)) for k, v in response.headers.items()]
            resp, _ = self._interceptor.post_update_dataset_version_with_metadata(
                resp, response_metadata
            )
            if CLIENT_LOGGING_SUPPORTED and _LOGGER.isEnabledFor(
                logging.DEBUG
            ):  # pragma: NO COVER
                try:
                    response_payload = gca_dataset_version.DatasetVersion.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.DatasetServiceClient.update_dataset_version",
                    extra={
                        "serviceName": "google.cloud.aiplatform.v1.DatasetService",
                        "rpcName": "UpdateDatasetVersion",
                        "metadata": http_response["headers"],
                        "httpResponse": http_response,
                    },
                )
            return resp

    @property
    def create_dataset(
        self,
    ) -> Callable[[dataset_service.CreateDatasetRequest], 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._CreateDataset(self._session, self._host, self._interceptor)  # type: ignore

    @property
    def create_dataset_version(
        self,
    ) -> Callable[
        [dataset_service.CreateDatasetVersionRequest], 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._CreateDatasetVersion(self._session, self._host, self._interceptor)  # type: ignore

    @property
    def delete_dataset(
        self,
    ) -> Callable[[dataset_service.DeleteDatasetRequest], 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._DeleteDataset(self._session, self._host, self._interceptor)  # type: ignore

    @property
    def delete_dataset_version(
        self,
    ) -> Callable[
        [dataset_service.DeleteDatasetVersionRequest], 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._DeleteDatasetVersion(self._session, self._host, self._interceptor)  # type: ignore

    @property
    def delete_saved_query(
        self,
    ) -> Callable[[dataset_service.DeleteSavedQueryRequest], 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._DeleteSavedQuery(self._session, self._host, self._interceptor)  # type: ignore

    @property
    def export_data(
        self,
    ) -> Callable[[dataset_service.ExportDataRequest], 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._ExportData(self._session, self._host, self._interceptor)  # type: ignore

    @property
    def get_annotation_spec(
        self,
    ) -> Callable[
        [dataset_service.GetAnnotationSpecRequest], annotation_spec.AnnotationSpec
    ]:
        # 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._GetAnnotationSpec(self._session, self._host, self._interceptor)  # type: ignore

    @property
    def get_dataset(
        self,
    ) -> Callable[[dataset_service.GetDatasetRequest], dataset.Dataset]:
        # 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._GetDataset(self._session, self._host, self._interceptor)  # type: ignore

    @property
    def get_dataset_version(
        self,
    ) -> Callable[
        [dataset_service.GetDatasetVersionRequest], dataset_version.DatasetVersion
    ]:
        # 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._GetDatasetVersion(self._session, self._host, self._interceptor)  # type: ignore

    @property
    def import_data(
        self,
    ) -> Callable[[dataset_service.ImportDataRequest], 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._ImportData(self._session, self._host, self._interceptor)  # type: ignore

    @property
    def list_annotations(
        self,
    ) -> Callable[
        [dataset_service.ListAnnotationsRequest],
        dataset_service.ListAnnotationsResponse,
    ]:
        # 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._ListAnnotations(self._session, self._host, self._interceptor)  # type: ignore

    @property
    def list_data_items(
        self,
    ) -> Callable[
        [dataset_service.ListDataItemsRequest], dataset_service.ListDataItemsResponse
    ]:
        # 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._ListDataItems(self._session, self._host, self._interceptor)  # type: ignore

    @property
    def list_datasets(
        self,
    ) -> Callable[
        [dataset_service.ListDatasetsRequest], dataset_service.ListDatasetsResponse
    ]:
        # 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._ListDatasets(self._session, self._host, self._interceptor)  # type: ignore

    @property
    def list_dataset_versions(
        self,
    ) -> Callable[
        [dataset_service.ListDatasetVersionsRequest],
        dataset_service.ListDatasetVersionsResponse,
    ]:
        # 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._ListDatasetVersions(self._session, self._host, self._interceptor)  # type: ignore

    @property
    def list_saved_queries(
        self,
    ) -> Callable[
        [dataset_service.ListSavedQueriesRequest],
        dataset_service.ListSavedQueriesResponse,
    ]:
        # 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._ListSavedQueries(self._session, self._host, self._interceptor)  # type: ignore

    @property
    def restore_dataset_version(
        self,
    ) -> Callable[
        [dataset_service.RestoreDatasetVersionRequest], 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._RestoreDatasetVersion(self._session, self._host, self._interceptor)  # type: ignore

    @property
    def search_data_items(
        self,
    ) -> Callable[
        [dataset_service.SearchDataItemsRequest],
        dataset_service.SearchDataItemsResponse,
    ]:
        # 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._SearchDataItems(self._session, self._host, self._interceptor)  # type: ignore

    @property
    def update_dataset(
        self,
    ) -> Callable[[dataset_service.UpdateDatasetRequest], gca_dataset.Dataset]:
        # 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._UpdateDataset(self._session, self._host, self._interceptor)  # type: ignore

    @property
    def update_dataset_version(
        self,
    ) -> Callable[
        [dataset_service.UpdateDatasetVersionRequest],
        gca_dataset_version.DatasetVersion,
    ]:
        # 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._UpdateDatasetVersion(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(
        _BaseDatasetServiceRestTransport._BaseGetLocation, DatasetServiceRestStub
    ):
        def __hash__(self):
            return hash("DatasetServiceRestTransport.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 = (
                _BaseDatasetServiceRestTransport._BaseGetLocation._get_http_options()
            )

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

            # Jsonify the query params
            query_params = _BaseDatasetServiceRestTransport._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.DatasetServiceClient.GetLocation",
                    extra={
                        "serviceName": "google.cloud.aiplatform.v1.DatasetService",
                        "rpcName": "GetLocation",
                        "httpRequest": http_request,
                        "metadata": http_request["headers"],
                    },
                )

            # Send the request
            response = DatasetServiceRestTransport._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.DatasetServiceAsyncClient.GetLocation",
                    extra={
                        "serviceName": "google.cloud.aiplatform.v1.DatasetService",
                        "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(
        _BaseDatasetServiceRestTransport._BaseListLocations, DatasetServiceRestStub
    ):
        def __hash__(self):
            return hash("DatasetServiceRestTransport.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 = (
                _BaseDatasetServiceRestTransport._BaseListLocations._get_http_options()
            )

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

            # Jsonify the query params
            query_params = _BaseDatasetServiceRestTransport._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.DatasetServiceClient.ListLocations",
                    extra={
                        "serviceName": "google.cloud.aiplatform.v1.DatasetService",
                        "rpcName": "ListLocations",
                        "httpRequest": http_request,
                        "metadata": http_request["headers"],
                    },
                )

            # Send the request
            response = DatasetServiceRestTransport._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.DatasetServiceAsyncClient.ListLocations",
                    extra={
                        "serviceName": "google.cloud.aiplatform.v1.DatasetService",
                        "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(
        _BaseDatasetServiceRestTransport._BaseGetIamPolicy, DatasetServiceRestStub
    ):
        def __hash__(self):
            return hash("DatasetServiceRestTransport.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 = (
                _BaseDatasetServiceRestTransport._BaseGetIamPolicy._get_http_options()
            )

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

            # Jsonify the query params
            query_params = _BaseDatasetServiceRestTransport._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.DatasetServiceClient.GetIamPolicy",
                    extra={
                        "serviceName": "google.cloud.aiplatform.v1.DatasetService",
                        "rpcName": "GetIamPolicy",
                        "httpRequest": http_request,
                        "metadata": http_request["headers"],
                    },
                )

            # Send the request
            response = DatasetServiceRestTransport._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.DatasetServiceAsyncClient.GetIamPolicy",
                    extra={
                        "serviceName": "google.cloud.aiplatform.v1.DatasetService",
                        "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(
        _BaseDatasetServiceRestTransport._BaseSetIamPolicy, DatasetServiceRestStub
    ):
        def __hash__(self):
            return hash("DatasetServiceRestTransport.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 = (
                _BaseDatasetServiceRestTransport._BaseSetIamPolicy._get_http_options()
            )

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

            body = _BaseDatasetServiceRestTransport._BaseSetIamPolicy._get_request_body_json(
                transcoded_request
            )

            # Jsonify the query params
            query_params = _BaseDatasetServiceRestTransport._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.DatasetServiceClient.SetIamPolicy",
                    extra={
                        "serviceName": "google.cloud.aiplatform.v1.DatasetService",
                        "rpcName": "SetIamPolicy",
                        "httpRequest": http_request,
                        "metadata": http_request["headers"],
                    },
                )

            # Send the request
            response = DatasetServiceRestTransport._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.DatasetServiceAsyncClient.SetIamPolicy",
                    extra={
                        "serviceName": "google.cloud.aiplatform.v1.DatasetService",
                        "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(
        _BaseDatasetServiceRestTransport._BaseTestIamPermissions, DatasetServiceRestStub
    ):
        def __hash__(self):
            return hash("DatasetServiceRestTransport.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 = (
                _BaseDatasetServiceRestTransport._BaseTestIamPermissions._get_http_options()
            )

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

            # Jsonify the query params
            query_params = _BaseDatasetServiceRestTransport._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.DatasetServiceClient.TestIamPermissions",
                    extra={
                        "serviceName": "google.cloud.aiplatform.v1.DatasetService",
                        "rpcName": "TestIamPermissions",
                        "httpRequest": http_request,
                        "metadata": http_request["headers"],
                    },
                )

            # Send the request
            response = DatasetServiceRestTransport._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.DatasetServiceAsyncClient.TestIamPermissions",
                    extra={
                        "serviceName": "google.cloud.aiplatform.v1.DatasetService",
                        "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(
        _BaseDatasetServiceRestTransport._BaseCancelOperation, DatasetServiceRestStub
    ):
        def __hash__(self):
            return hash("DatasetServiceRestTransport.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 = (
                _BaseDatasetServiceRestTransport._BaseCancelOperation._get_http_options()
            )

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

            # Jsonify the query params
            query_params = _BaseDatasetServiceRestTransport._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.DatasetServiceClient.CancelOperation",
                    extra={
                        "serviceName": "google.cloud.aiplatform.v1.DatasetService",
                        "rpcName": "CancelOperation",
                        "httpRequest": http_request,
                        "metadata": http_request["headers"],
                    },
                )

            # Send the request
            response = DatasetServiceRestTransport._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(
        _BaseDatasetServiceRestTransport._BaseDeleteOperation, DatasetServiceRestStub
    ):
        def __hash__(self):
            return hash("DatasetServiceRestTransport.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 = (
                _BaseDatasetServiceRestTransport._BaseDeleteOperation._get_http_options()
            )

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

            # Jsonify the query params
            query_params = _BaseDatasetServiceRestTransport._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.DatasetServiceClient.DeleteOperation",
                    extra={
                        "serviceName": "google.cloud.aiplatform.v1.DatasetService",
                        "rpcName": "DeleteOperation",
                        "httpRequest": http_request,
                        "metadata": http_request["headers"],
                    },
                )

            # Send the request
            response = DatasetServiceRestTransport._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(
        _BaseDatasetServiceRestTransport._BaseGetOperation, DatasetServiceRestStub
    ):
        def __hash__(self):
            return hash("DatasetServiceRestTransport.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 = (
                _BaseDatasetServiceRestTransport._BaseGetOperation._get_http_options()
            )

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

            # Jsonify the query params
            query_params = _BaseDatasetServiceRestTransport._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.DatasetServiceClient.GetOperation",
                    extra={
                        "serviceName": "google.cloud.aiplatform.v1.DatasetService",
                        "rpcName": "GetOperation",
                        "httpRequest": http_request,
                        "metadata": http_request["headers"],
                    },
                )

            # Send the request
            response = DatasetServiceRestTransport._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.DatasetServiceAsyncClient.GetOperation",
                    extra={
                        "serviceName": "google.cloud.aiplatform.v1.DatasetService",
                        "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(
        _BaseDatasetServiceRestTransport._BaseListOperations, DatasetServiceRestStub
    ):
        def __hash__(self):
            return hash("DatasetServiceRestTransport.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 = (
                _BaseDatasetServiceRestTransport._BaseListOperations._get_http_options()
            )

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

            # Jsonify the query params
            query_params = _BaseDatasetServiceRestTransport._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.DatasetServiceClient.ListOperations",
                    extra={
                        "serviceName": "google.cloud.aiplatform.v1.DatasetService",
                        "rpcName": "ListOperations",
                        "httpRequest": http_request,
                        "metadata": http_request["headers"],
                    },
                )

            # Send the request
            response = DatasetServiceRestTransport._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.DatasetServiceAsyncClient.ListOperations",
                    extra={
                        "serviceName": "google.cloud.aiplatform.v1.DatasetService",
                        "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(
        _BaseDatasetServiceRestTransport._BaseWaitOperation, DatasetServiceRestStub
    ):
        def __hash__(self):
            return hash("DatasetServiceRestTransport.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 = (
                _BaseDatasetServiceRestTransport._BaseWaitOperation._get_http_options()
            )

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

            # Jsonify the query params
            query_params = _BaseDatasetServiceRestTransport._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.DatasetServiceClient.WaitOperation",
                    extra={
                        "serviceName": "google.cloud.aiplatform.v1.DatasetService",
                        "rpcName": "WaitOperation",
                        "httpRequest": http_request,
                        "metadata": http_request["headers"],
                    },
                )

            # Send the request
            response = DatasetServiceRestTransport._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.DatasetServiceAsyncClient.WaitOperation",
                    extra={
                        "serviceName": "google.cloud.aiplatform.v1.DatasetService",
                        "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__ = ("DatasetServiceRestTransport",)
