text: # -*- coding: utf-8 -*-
  # Copyright 2020 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.
  #
  from collections import OrderedDict
  from distutils import util
  import os
  import re
  from typing import Callable, Dict, Optional, Iterable, Sequence, Tuple, Type, Union
  import pkg_resources
  
  from google.api_core import client_options as client_options_lib  # type: ignore
  from google.api_core import exceptions as core_exceptions  # type: ignore
  from google.api_core import gapic_v1  # type: ignore
  from google.api_core import retry as retries  # type: ignore
  from google.auth import credentials as ga_credentials  # type: ignore
  from google.auth.transport import mtls  # type: ignore
  from google.auth.transport.grpc import SslCredentials  # type: ignore
  from google.auth.exceptions import MutualTLSChannelError  # type: ignore
  from google.oauth2 import service_account  # type: ignore
  
  from google.api_core import operation as gac_operation  # type: ignore
  from google.api_core import operation_async  # type: ignore
  from google.cloud.aiplatform_v1beta1.services.tensorboard_service import pagers
  from google.cloud.aiplatform_v1beta1.types import encryption_spec
  from google.cloud.aiplatform_v1beta1.types import operation as gca_operation
  from google.cloud.aiplatform_v1beta1.types import tensorboard
  from google.cloud.aiplatform_v1beta1.types import tensorboard as gca_tensorboard
  from google.cloud.aiplatform_v1beta1.types import tensorboard_data
  from google.cloud.aiplatform_v1beta1.types import tensorboard_experiment
  from google.cloud.aiplatform_v1beta1.types import (
      tensorboard_experiment as gca_tensorboard_experiment,
  )
  from google.cloud.aiplatform_v1beta1.types import tensorboard_run
  from google.cloud.aiplatform_v1beta1.types import tensorboard_run as gca_tensorboard_run
  from google.cloud.aiplatform_v1beta1.types import tensorboard_service
  from google.cloud.aiplatform_v1beta1.types import tensorboard_time_series
  from google.cloud.aiplatform_v1beta1.types import (
      tensorboard_time_series as gca_tensorboard_time_series,
  )
  from google.protobuf import empty_pb2  # type: ignore
  from google.protobuf import field_mask_pb2  # type: ignore
  from google.protobuf import timestamp_pb2  # type: ignore
  from .transports.base import TensorboardServiceTransport, DEFAULT_CLIENT_INFO
  from .transports.grpc import TensorboardServiceGrpcTransport
  from .transports.grpc_asyncio import TensorboardServiceGrpcAsyncIOTransport
  
  
  class TensorboardServiceClientMeta(type):
      """Metaclass for the TensorboardService client.
  
      This provides class-level methods for building and retrieving
      support objects (e.g. transport) without polluting the client instance
      objects.
      """
  
      _transport_registry = (
          OrderedDict()
      )  # type: Dict[str, Type[TensorboardServiceTransport]]
      _transport_registry["grpc"] = TensorboardServiceGrpcTransport
      _transport_registry["grpc_asyncio"] = TensorboardServiceGrpcAsyncIOTransport
  
      def get_transport_class(
          cls, label: str = None,
      ) -> Type[TensorboardServiceTransport]:
          """Returns an appropriate transport class.
  
          Args:
              label: The name of the desired transport. If none is
                  provided, then the first transport in the registry is used.
  
          Returns:
              The transport class to use.
          """
          # If a specific transport is requested, return that one.
          if label:
              return cls._transport_registry[label]
  
          # No transport is requested; return the default (that is, the first one
          # in the dictionary).
          return next(iter(cls._transport_registry.values()))
  
  
  class TensorboardServiceClient(metaclass=TensorboardServiceClientMeta):
      """TensorboardService"""
  
      @staticmethod
      def _get_default_mtls_endpoint(api_endpoint):
          """Converts api endpoint to mTLS endpoint.
  
          Convert "*.sandbox.googleapis.com" and "*.googleapis.com" to
          "*.mtls.sandbox.googleapis.com" and "*.mtls.googleapis.com" respectively.
          Args:
              api_endpoint (Optional[str]): the api endpoint to convert.
          Returns:
              str: converted mTLS api endpoint.
          """
          if not api_endpoint:
              return api_endpoint
  
          mtls_endpoint_re = re.compile(
              r"(?P<name>[^.]+)(?P<mtls>\.mtls)?(?P<sandbox>\.sandbox)?(?P<googledomain>\.googleapis\.com)?"
          )
  
          m = mtls_endpoint_re.match(api_endpoint)
          name, mtls, sandbox, googledomain = m.groups()
          if mtls or not googledomain:
              return api_endpoint
  
          if sandbox:
              return api_endpoint.replace(
                  "sandbox.googleapis.com", "mtls.sandbox.googleapis.com"
              )
  
          return api_endpoint.replace(".googleapis.com", ".mtls.googleapis.com")
  
      DEFAULT_ENDPOINT = "aiplatform.googleapis.com"
      DEFAULT_MTLS_ENDPOINT = _get_default_mtls_endpoint.__func__(  # type: ignore
          DEFAULT_ENDPOINT
      )
  
      @classmethod
      def from_service_account_info(cls, info: dict, *args, **kwargs):
          """Creates an instance of this client using the provided credentials
              info.
  
          Args:
              info (dict): The service account private key info.
              args: Additional arguments to pass to the constructor.
              kwargs: Additional arguments to pass to the constructor.
  
          Returns:
              TensorboardServiceClient: The constructed client.
          """
          credentials = service_account.Credentials.from_service_account_info(info)
          kwargs["credentials"] = credentials
          return cls(*args, **kwargs)
  
      @classmethod
      def from_service_account_file(cls, filename: str, *args, **kwargs):
          """Creates an instance of this client using the provided credentials
              file.
  
          Args:
              filename (str): The path to the service account private key json
                  file.
              args: Additional arguments to pass to the constructor.
              kwargs: Additional arguments to pass to the constructor.
  
          Returns:
              TensorboardServiceClient: The constructed client.
          """
          credentials = service_account.Credentials.from_service_account_file(filename)
          kwargs["credentials"] = credentials
          return cls(*args, **kwargs)
  
      from_service_account_json = from_service_account_file
  
      @property
      def transport(self) -> TensorboardServiceTransport:
          """Returns the transport used by the client instance.
  
          Returns:
              TensorboardServiceTransport: The transport used by the client
                  instance.
          """
          return self._transport
  
      @staticmethod
      def tensorboard_path(project: str, location: str, tensorboard: str,) -> str:
          """Returns a fully-qualified tensorboard string."""
          return "projects/{project}/locations/{location}/tensorboards/{tensorboard}".format(
              project=project, location=location, tensorboard=tensorboard,
          )
  
      @staticmethod
      def parse_tensorboard_path(path: str) -> Dict[str, str]:
          """Parses a tensorboard path into its component segments."""
          m = re.match(
              r"^projects/(?P<project>.+?)/locations/(?P<location>.+?)/tensorboards/(?P<tensorboard>.+?)$",
              path,
          )
          return m.groupdict() if m else {}
  
      @staticmethod
      def tensorboard_experiment_path(
          project: str, location: str, tensorboard: str, experiment: str,
      ) -> str:
          """Returns a fully-qualified tensorboard_experiment string."""
          return "projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}".format(
              project=project,
              location=location,
              tensorboard=tensorboard,
              experiment=experiment,
          )
  
      @staticmethod
      def parse_tensorboard_experiment_path(path: str) -> Dict[str, str]:
          """Parses a tensorboard_experiment path into its component segments."""
          m = re.match(
              r"^projects/(?P<project>.+?)/locations/(?P<location>.+?)/tensorboards/(?P<tensorboard>.+?)/experiments/(?P<experiment>.+?)$",
              path,
          )
          return m.groupdict() if m else {}
  
      @staticmethod
      def tensorboard_run_path(
          project: str, location: str, tensorboard: str, experiment: str, run: str,
      ) -> str:
          """Returns a fully-qualified tensorboard_run string."""
          return "projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}".format(
              project=project,
              location=location,
              tensorboard=tensorboard,
              experiment=experiment,
              run=run,
          )
  
      @staticmethod
      def parse_tensorboard_run_path(path: str) -> Dict[str, str]:
          """Parses a tensorboard_run path into its component segments."""
          m = re.match(
              r"^projects/(?P<project>.+?)/locations/(?P<location>.+?)/tensorboards/(?P<tensorboard>.+?)/experiments/(?P<experiment>.+?)/runs/(?P<run>.+?)$",
              path,
          )
          return m.groupdict() if m else {}
  
      @staticmethod
      def tensorboard_time_series_path(
          project: str,
          location: str,
          tensorboard: str,
          experiment: str,
          run: str,
          time_series: str,
      ) -> str:
          """Returns a fully-qualified tensorboard_time_series string."""
          return "projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}/timeSeries/{time_series}".format(
              project=project,
              location=location,
              tensorboard=tensorboard,
              experiment=experiment,
              run=run,
              time_series=time_series,
          )
  
      @staticmethod
      def parse_tensorboard_time_series_path(path: str) -> Dict[str, str]:
          """Parses a tensorboard_time_series path into its component segments."""
          m = re.match(
              r"^projects/(?P<project>.+?)/locations/(?P<location>.+?)/tensorboards/(?P<tensorboard>.+?)/experiments/(?P<experiment>.+?)/runs/(?P<run>.+?)/timeSeries/(?P<time_series>.+?)$",
              path,
          )
          return m.groupdict() if m else {}
  
      @staticmethod
      def common_billing_account_path(billing_account: str,) -> str:
          """Returns a fully-qualified billing_account string."""
          return "billingAccounts/{billing_account}".format(
              billing_account=billing_account,
          )
  
      @staticmethod
      def parse_common_billing_account_path(path: str) -> Dict[str, str]:
          """Parse a billing_account path into its component segments."""
          m = re.match(r"^billingAccounts/(?P<billing_account>.+?)$", path)
          return m.groupdict() if m else {}
  
      @staticmethod
      def common_folder_path(folder: str,) -> str:
          """Returns a fully-qualified folder string."""
          return "folders/{folder}".format(folder=folder,)
  
      @staticmethod
      def parse_common_folder_path(path: str) -> Dict[str, str]:
          """Parse a folder path into its component segments."""
          m = re.match(r"^folders/(?P<folder>.+?)$", path)
          return m.groupdict() if m else {}
  
      @staticmethod
      def common_organization_path(organization: str,) -> str:
          """Returns a fully-qualified organization string."""
          return "organizations/{organization}".format(organization=organization,)
  
      @staticmethod
      def parse_common_organization_path(path: str) -> Dict[str, str]:
          """Parse a organization path into its component segments."""
          m = re.match(r"^organizations/(?P<organization>.+?)$", path)
          return m.groupdict() if m else {}
  
      @staticmethod
      def common_project_path(project: str,) -> str:
          """Returns a fully-qualified project string."""
          return "projects/{project}".format(project=project,)
  
      @staticmethod
      def parse_common_project_path(path: str) -> Dict[str, str]:
          """Parse a project path into its component segments."""
          m = re.match(r"^projects/(?P<project>.+?)$", path)
          return m.groupdict() if m else {}
  
      @staticmethod
      def common_location_path(project: str, location: str,) -> str:
          """Returns a fully-qualified location string."""
          return "projects/{project}/locations/{location}".format(
              project=project, location=location,
          )
  
      @staticmethod
      def parse_common_location_path(path: str) -> Dict[str, str]:
          """Parse a location path into its component segments."""
          m = re.match(r"^projects/(?P<project>.+?)/locations/(?P<location>.+?)$", path)
          return m.groupdict() if m else {}
  
      def __init__(
          self,
          *,
          credentials: Optional[ga_credentials.Credentials] = None,
          transport: Union[str, TensorboardServiceTransport, None] = None,
          client_options: Optional[client_options_lib.ClientOptions] = None,
          client_info: gapic_v1.client_info.ClientInfo = DEFAULT_CLIENT_INFO,
      ) -> None:
          """Instantiates the tensorboard service client.
  
          Args:
              credentials (Optional[google.auth.credentials.Credentials]): The
                  authorization credentials to attach to requests. These
                  credentials identify the application to the service; if none
                  are specified, the client will attempt to ascertain the
                  credentials from the environment.
              transport (Union[str, TensorboardServiceTransport]): The
                  transport to use. If set to None, a transport is chosen
                  automatically.
              client_options (google.api_core.client_options.ClientOptions): Custom options for the
                  client. It won't take effect if a ``transport`` instance is provided.
                  (1) The ``api_endpoint`` property can be used to override the
                  default endpoint provided by the client. GOOGLE_API_USE_MTLS_ENDPOINT
                  environment variable can also be used to override the endpoint:
                  "always" (always use the default mTLS endpoint), "never" (always
                  use the default regular endpoint) and "auto" (auto switch to the
                  default mTLS endpoint if client certificate is present, this is
                  the default value). However, the ``api_endpoint`` property takes
                  precedence if provided.
                  (2) If GOOGLE_API_USE_CLIENT_CERTIFICATE environment variable
                  is "true", then the ``client_cert_source`` property can be used
                  to provide client certificate for mutual TLS transport. If
                  not provided, the default SSL client certificate will be used if
                  present. If GOOGLE_API_USE_CLIENT_CERTIFICATE is "false" or not
                  set, no client certificate will be used.
              client_info (google.api_core.gapic_v1.client_info.ClientInfo):
                  The client info used to send a user-agent string along with
                  API requests. If ``None``, then default info will be used.
                  Generally, you only need to set this if you're developing
                  your own client library.
  
          Raises:
              google.auth.exceptions.MutualTLSChannelError: If mutual TLS transport
                  creation failed for any reason.
          """
          if isinstance(client_options, dict):
              client_options = client_options_lib.from_dict(client_options)
          if client_options is None:
              client_options = client_options_lib.ClientOptions()
  
          # Create SSL credentials for mutual TLS if needed.
          use_client_cert = bool(
              util.strtobool(os.getenv("GOOGLE_API_USE_CLIENT_CERTIFICATE", "false"))
          )
  
          client_cert_source_func = None
          is_mtls = False
          if use_client_cert:
              if client_options.client_cert_source:
                  is_mtls = True
                  client_cert_source_func = client_options.client_cert_source
              else:
                  is_mtls = mtls.has_default_client_cert_source()
                  if is_mtls:
                      client_cert_source_func = mtls.default_client_cert_source()
                  else:
                      client_cert_source_func = None
  
          # Figure out which api endpoint to use.
          if client_options.api_endpoint is not None:
              api_endpoint = client_options.api_endpoint
          else:
              use_mtls_env = os.getenv("GOOGLE_API_USE_MTLS_ENDPOINT", "auto")
              if use_mtls_env == "never":
                  api_endpoint = self.DEFAULT_ENDPOINT
              elif use_mtls_env == "always":
                  api_endpoint = self.DEFAULT_MTLS_ENDPOINT
              elif use_mtls_env == "auto":
                  if is_mtls:
                      api_endpoint = self.DEFAULT_MTLS_ENDPOINT
                  else:
                      api_endpoint = self.DEFAULT_ENDPOINT
              else:
                  raise MutualTLSChannelError(
                      "Unsupported GOOGLE_API_USE_MTLS_ENDPOINT value. Accepted "
                      "values: never, auto, always"
                  )
  
          # Save or instantiate the transport.
          # Ordinarily, we provide the transport, but allowing a custom transport
          # instance provides an extensibility point for unusual situations.
          if isinstance(transport, TensorboardServiceTransport):
              # transport is a TensorboardServiceTransport instance.
              if credentials or client_options.credentials_file:
                  raise ValueError(
                      "When providing a transport instance, "
                      "provide its credentials directly."
                  )
              if client_options.scopes:
                  raise ValueError(
                      "When providing a transport instance, provide its scopes "
                      "directly."
                  )
              self._transport = transport
          else:
              Transport = type(self).get_transport_class(transport)
              self._transport = Transport(
                  credentials=credentials,
                  credentials_file=client_options.credentials_file,
                  host=api_endpoint,
                  scopes=client_options.scopes,
                  client_cert_source_for_mtls=client_cert_source_func,
                  quota_project_id=client_options.quota_project_id,
                  client_info=client_info,
                  always_use_jwt_access=(
                      Transport == type(self).get_transport_class("grpc")
                      or Transport == type(self).get_transport_class("grpc_asyncio")
                  ),
              )
  
      def create_tensorboard(
          self,
          request: tensorboard_service.CreateTensorboardRequest = None,
          *,
          parent: str = None,
          tensorboard: gca_tensorboard.Tensorboard = None,
          retry: retries.Retry = gapic_v1.method.DEFAULT,
          timeout: float = None,
          metadata: Sequence[Tuple[str, str]] = (),
      ) -> gac_operation.Operation:
          r"""Creates a Tensorboard.
  
          Args:
              request (google.cloud.aiplatform_v1beta1.types.CreateTensorboardRequest):
                  The request object. Request message for
                  [TensorboardService.CreateTensorboard][google.cloud.aiplatform.v1beta1.TensorboardService.CreateTensorboard].
              parent (str):
                  Required. The resource name of the Location to create
                  the Tensorboard in. Format:
                  ``projects/{project}/locations/{location}``
  
                  This corresponds to the ``parent`` field
                  on the ``request`` instance; if ``request`` is provided, this
                  should not be set.
              tensorboard (google.cloud.aiplatform_v1beta1.types.Tensorboard):
                  Required. The Tensorboard to create.
                  This corresponds to the ``tensorboard`` field
                  on the ``request`` instance; if ``request`` is provided, this
                  should not be set.
              retry (google.api_core.retry.Retry): Designation of what errors, if any,
                  should be retried.
              timeout (float): The timeout for this request.
              metadata (Sequence[Tuple[str, str]]): Strings which should be
                  sent along with the request as metadata.
  
          Returns:
              google.api_core.operation.Operation:
                  An object representing a long-running operation.
  
                  The result type for the operation will be :class:`google.cloud.aiplatform_v1beta1.types.Tensorboard` Tensorboard is a physical database that stores users' training metrics.
                     A default Tensorboard is provided in each region of a
                     GCP project. If needed users can also create extra
                     Tensorboards in their projects.
  
          """
          # Create or coerce a protobuf request object.
          # Sanity check: If we got a request object, we should *not* have
          # gotten any keyword arguments that map to the request.
          has_flattened_params = any([parent, tensorboard])
          if request is not None and has_flattened_params:
              raise ValueError(
                  "If the `request` argument is set, then none of "
                  "the individual field arguments should be set."
              )
  
          # Minor optimization to avoid making a copy if the user passes
          # in a tensorboard_service.CreateTensorboardRequest.
          # There's no risk of modifying the input as we've already verified
          # there are no flattened fields.
          if not isinstance(request, tensorboard_service.CreateTensorboardRequest):
              request = tensorboard_service.CreateTensorboardRequest(request)
              # If we have keyword arguments corresponding to fields on the
              # request, apply these.
              if parent is not None:
                  request.parent = parent
              if tensorboard is not None:
                  request.tensorboard = tensorboard
  
          # Wrap the RPC method; this adds retry and timeout information,
          # and friendly error handling.
          rpc = self._transport._wrapped_methods[self._transport.create_tensorboard]
  
          # Certain fields should be provided within the metadata header;
          # add these here.
          metadata = tuple(metadata) + (
              gapic_v1.routing_header.to_grpc_metadata((("parent", request.parent),)),
          )
  
          # Send the request.
          response = rpc(request, retry=retry, timeout=timeout, metadata=metadata,)
  
          # Wrap the response in an operation future.
          response = gac_operation.from_gapic(
              response,
              self._transport.operations_client,
              gca_tensorboard.Tensorboard,
              metadata_type=tensorboard_service.CreateTensorboardOperationMetadata,
          )
  
          # Done; return the response.
          return response
  
      def get_tensorboard(
          self,
          request: tensorboard_service.GetTensorboardRequest = None,
          *,
          name: str = None,
          retry: retries.Retry = gapic_v1.method.DEFAULT,
          timeout: float = None,
          metadata: Sequence[Tuple[str, str]] = (),
      ) -> tensorboard.Tensorboard:
          r"""Gets a Tensorboard.
  
          Args:
              request (google.cloud.aiplatform_v1beta1.types.GetTensorboardRequest):
                  The request object. Request message for
                  [TensorboardService.GetTensorboard][google.cloud.aiplatform.v1beta1.TensorboardService.GetTensorboard].
              name (str):
                  Required. The name of the Tensorboard resource. Format:
                  ``projects/{project}/locations/{location}/tensorboards/{tensorboard}``
  
                  This corresponds to the ``name`` field
                  on the ``request`` instance; if ``request`` is provided, this
                  should not be set.
              retry (google.api_core.retry.Retry): Designation of what errors, if any,
                  should be retried.
              timeout (float): The timeout for this request.
              metadata (Sequence[Tuple[str, str]]): Strings which should be
                  sent along with the request as metadata.
  
          Returns:
              google.cloud.aiplatform_v1beta1.types.Tensorboard:
                  Tensorboard is a physical database
                  that stores users' training metrics. A
                  default Tensorboard is provided in each
                  region of a GCP project. If needed users
                  can also create extra Tensorboards in
                  their projects.
  
          """
          # Create or coerce a protobuf request object.
          # Sanity check: If we got a request object, we should *not* have
          # gotten any keyword arguments that map to the request.
          has_flattened_params = any([name])
          if request is not None and has_flattened_params:
              raise ValueError(
                  "If the `request` argument is set, then none of "
                  "the individual field arguments should be set."
              )
  
          # Minor optimization to avoid making a copy if the user passes
          # in a tensorboard_service.GetTensorboardRequest.
          # There's no risk of modifying the input as we've already verified
          # there are no flattened fields.
          if not isinstance(request, tensorboard_service.GetTensorboardRequest):
              request = tensorboard_service.GetTensorboardRequest(request)
              # If we have keyword arguments corresponding to fields on the
              # request, apply these.
              if name is not None:
                  request.name = name
  
          # Wrap the RPC method; this adds retry and timeout information,
          # and friendly error handling.
          rpc = self._transport._wrapped_methods[self._transport.get_tensorboard]
  
          # Certain fields should be provided within the metadata header;
          # add these here.
          metadata = tuple(metadata) + (
              gapic_v1.routing_header.to_grpc_metadata((("name", request.name),)),
          )
  
          # Send the request.
          response = rpc(request, retry=retry, timeout=timeout, metadata=metadata,)
  
          # Done; return the response.
          return response
  
      def update_tensorboard(
          self,
          request: tensorboard_service.UpdateTensorboardRequest = None,
          *,
          tensorboard: gca_tensorboard.Tensorboard = None,
          update_mask: field_mask_pb2.FieldMask = None,
          retry: retries.Retry = gapic_v1.method.DEFAULT,
          timeout: float = None,
          metadata: Sequence[Tuple[str, str]] = (),
      ) -> gac_operation.Operation:
          r"""Updates a Tensorboard.
  
          Args:
              request (google.cloud.aiplatform_v1beta1.types.UpdateTensorboardRequest):
                  The request object. Request message for
                  [TensorboardService.UpdateTensorboard][google.cloud.aiplatform.v1beta1.TensorboardService.UpdateTensorboard].
              tensorboard (google.cloud.aiplatform_v1beta1.types.Tensorboard):
                  Required. The Tensorboard's ``name`` field is used to
                  identify the Tensorboard to be updated. Format:
                  ``projects/{project}/locations/{location}/tensorboards/{tensorboard}``
  
                  This corresponds to the ``tensorboard`` field
                  on the ``request`` instance; if ``request`` is provided, this
                  should not be set.
              update_mask (google.protobuf.field_mask_pb2.FieldMask):
                  Required. Field mask is used to specify the fields to be
                  overwritten in the Tensorboard resource by the update.
                  The fields specified in the update_mask are relative to
                  the resource, not the full request. A field will be
                  overwritten if it is in the mask. If the user does not
                  provide a mask then all fields will be overwritten if
                  new values are specified.
  
                  This corresponds to the ``update_mask`` field
                  on the ``request`` instance; if ``request`` is provided, this
                  should not be set.
              retry (google.api_core.retry.Retry): Designation of what errors, if any,
                  should be retried.
              timeout (float): The timeout for this request.
              metadata (Sequence[Tuple[str, str]]): Strings which should be
                  sent along with the request as metadata.
  
          Returns:
              google.api_core.operation.Operation:
                  An object representing a long-running operation.
  
                  The result type for the operation will be :class:`google.cloud.aiplatform_v1beta1.types.Tensorboard` Tensorboard is a physical database that stores users' training metrics.
                     A default Tensorboard is provided in each region of a
                     GCP project. If needed users can also create extra
                     Tensorboards in their projects.
  
          """
          # Create or coerce a protobuf request object.
          # Sanity check: If we got a request object, we should *not* have
          # gotten any keyword arguments that map to the request.
          has_flattened_params = any([tensorboard, update_mask])
          if request is not None and has_flattened_params:
              raise ValueError(
                  "If the `request` argument is set, then none of "
                  "the individual field arguments should be set."
              )
  
          # Minor optimization to avoid making a copy if the user passes
          # in a tensorboard_service.UpdateTensorboardRequest.
          # There's no risk of modifying the input as we've already verified
          # there are no flattened fields.
          if not isinstance(request, tensorboard_service.UpdateTensorboardRequest):
              request = tensorboard_service.UpdateTensorboardRequest(request)
              # If we have keyword arguments corresponding to fields on the
              # request, apply these.
              if tensorboard is not None:
                  request.tensorboard = tensorboard
              if update_mask is not None:
                  request.update_mask = update_mask
  
          # Wrap the RPC method; this adds retry and timeout information,
          # and friendly error handling.
          rpc = self._transport._wrapped_methods[self._transport.update_tensorboard]
  
          # Certain fields should be provided within the metadata header;
          # add these here.
          metadata = tuple(metadata) + (
              gapic_v1.routing_header.to_grpc_metadata(
                  (("tensorboard.name", request.tensorboard.name),)
              ),
          )
  
          # Send the request.
          response = rpc(request, retry=retry, timeout=timeout, metadata=metadata,)
  
          # Wrap the response in an operation future.
          response = gac_operation.from_gapic(
              response,
              self._transport.operations_client,
              gca_tensorboard.Tensorboard,
              metadata_type=tensorboard_service.UpdateTensorboardOperationMetadata,
          )
  
          # Done; return the response.
          return response
  
      def list_tensorboards(
          self,
          request: tensorboard_service.ListTensorboardsRequest = None,
          *,
          parent: str = None,
          retry: retries.Retry = gapic_v1.method.DEFAULT,
          timeout: float = None,
          metadata: Sequence[Tuple[str, str]] = (),
      ) -> pagers.ListTensorboardsPager:
          r"""Lists Tensorboards in a Location.
  
          Args:
              request (google.cloud.aiplatform_v1beta1.types.ListTensorboardsRequest):
                  The request object. Request message for
                  [TensorboardService.ListTensorboards][google.cloud.aiplatform.v1beta1.TensorboardService.ListTensorboards].
              parent (str):
                  Required. The resource name of the Location to list
                  Tensorboards. Format:
                  ``projects/{project}/locations/{location}``
  
                  This corresponds to the ``parent`` field
                  on the ``request`` instance; if ``request`` is provided, this
                  should not be set.
              retry (google.api_core.retry.Retry): Designation of what errors, if any,
                  should be retried.
              timeout (float): The timeout for this request.
              metadata (Sequence[Tuple[str, str]]): Strings which should be
                  sent along with the request as metadata.
  
          Returns:
              google.cloud.aiplatform_v1beta1.services.tensorboard_service.pagers.ListTensorboardsPager:
                  Response message for
                  [TensorboardService.ListTensorboards][google.cloud.aiplatform.v1beta1.TensorboardService.ListTensorboards].
  
                  Iterating over this object will yield results and
                  resolve additional pages automatically.
  
          """
          # Create or coerce a protobuf request object.
          # Sanity check: If we got a request object, we should *not* have
          # gotten any keyword arguments that map to the request.
          has_flattened_params = any([parent])
          if request is not None and has_flattened_params:
              raise ValueError(
                  "If the `request` argument is set, then none of "
                  "the individual field arguments should be set."
              )
  
          # Minor optimization to avoid making a copy if the user passes
          # in a tensorboard_service.ListTensorboardsRequest.
          # There's no risk of modifying the input as we've already verified
          # there are no flattened fields.
          if not isinstance(request, tensorboard_service.ListTensorboardsRequest):
              request = tensorboard_service.ListTensorboardsRequest(request)
              # If we have keyword arguments corresponding to fields on the
              # request, apply these.
              if parent is not None:
                  request.parent = parent
  
          # Wrap the RPC method; this adds retry and timeout information,
          # and friendly error handling.
          rpc = self._transport._wrapped_methods[self._transport.list_tensorboards]
  
          # Certain fields should be provided within the metadata header;
          # add these here.
          metadata = tuple(metadata) + (
              gapic_v1.routing_header.to_grpc_metadata((("parent", request.parent),)),
          )
  
          # Send the request.
          response = rpc(request, retry=retry, timeout=timeout, metadata=metadata,)
  
          # This method is paged; wrap the response in a pager, which provides
          # an `__iter__` convenience method.
          response = pagers.ListTensorboardsPager(
              method=rpc, request=request, response=response, metadata=metadata,
          )
  
          # Done; return the response.
          return response
  
      def delete_tensorboard(
          self,
          request: tensorboard_service.DeleteTensorboardRequest = None,
          *,
          name: str = None,
          retry: retries.Retry = gapic_v1.method.DEFAULT,
          timeout: float = None,
          metadata: Sequence[Tuple[str, str]] = (),
      ) -> gac_operation.Operation:
          r"""Deletes a Tensorboard.
  
          Args:
              request (google.cloud.aiplatform_v1beta1.types.DeleteTensorboardRequest):
                  The request object. Request message for
                  [TensorboardService.DeleteTensorboard][google.cloud.aiplatform.v1beta1.TensorboardService.DeleteTensorboard].
              name (str):
                  Required. The name of the Tensorboard to be deleted.
                  Format:
                  ``projects/{project}/locations/{location}/tensorboards/{tensorboard}``
  
                  This corresponds to the ``name`` field
                  on the ``request`` instance; if ``request`` is provided, this
                  should not be set.
              retry (google.api_core.retry.Retry): Designation of what errors, if any,
                  should be retried.
              timeout (float): The timeout for this request.
              metadata (Sequence[Tuple[str, str]]): Strings which should be
                  sent along with the request as metadata.
  
          Returns:
              google.api_core.operation.Operation:
                  An object representing a long-running operation.
  
                  The result type for the operation will be :class:`google.protobuf.empty_pb2.Empty` A generic empty message that you can re-use to avoid defining duplicated
                     empty messages in your APIs. A typical example is to
                     use it as the request or the response type of an API
                     method. For instance:
  
                        service Foo {
                           rpc Bar(google.protobuf.Empty) returns
                           (google.protobuf.Empty);
  
                        }
  
                     The JSON representation for Empty is empty JSON
                     object {}.
  
          """
          # Create or coerce a protobuf request object.
          # Sanity check: If we got a request object, we should *not* have
          # gotten any keyword arguments that map to the request.
          has_flattened_params = any([name])
          if request is not None and has_flattened_params:
              raise ValueError(
                  "If the `request` argument is set, then none of "
                  "the individual field arguments should be set."
              )
  
          # Minor optimization to avoid making a copy if the user passes
          # in a tensorboard_service.DeleteTensorboardRequest.
          # There's no risk of modifying the input as we've already verified
          # there are no flattened fields.
          if not isinstance(request, tensorboard_service.DeleteTensorboardRequest):
              request = tensorboard_service.DeleteTensorboardRequest(request)
              # If we have keyword arguments corresponding to fields on the
              # request, apply these.
              if name is not None:
                  request.name = name
  
          # Wrap the RPC method; this adds retry and timeout information,
          # and friendly error handling.
          rpc = self._transport._wrapped_methods[self._transport.delete_tensorboard]
  
          # Certain fields should be provided within the metadata header;
          # add these here.
          metadata = tuple(metadata) + (
              gapic_v1.routing_header.to_grpc_metadata((("name", request.name),)),
          )
  
          # Send the request.
          response = rpc(request, retry=retry, timeout=timeout, metadata=metadata,)
  
          # Wrap the response in an operation future.
          response = gac_operation.from_gapic(
              response,
              self._transport.operations_client,
              empty_pb2.Empty,
              metadata_type=gca_operation.DeleteOperationMetadata,
          )
  
          # Done; return the response.
          return response
  
      def create_tensorboard_experiment(
          self,
          request: tensorboard_service.CreateTensorboardExperimentRequest = None,
          *,
          parent: str = None,
          tensorboard_experiment: gca_tensorboard_experiment.TensorboardExperiment = None,
          tensorboard_experiment_id: str = None,
          retry: retries.Retry = gapic_v1.method.DEFAULT,
          timeout: float = None,
          metadata: Sequence[Tuple[str, str]] = (),
      ) -> gca_tensorboard_experiment.TensorboardExperiment:
          r"""Creates a TensorboardExperiment.
  
          Args:
              request (google.cloud.aiplatform_v1beta1.types.CreateTensorboardExperimentRequest):
                  The request object. Request message for
                  [TensorboardService.CreateTensorboardExperiment][google.cloud.aiplatform.v1beta1.TensorboardService.CreateTensorboardExperiment].
              parent (str):
                  Required. The resource name of the Tensorboard to create
                  the TensorboardExperiment in. Format:
                  ``projects/{project}/locations/{location}/tensorboards/{tensorboard}``
  
                  This corresponds to the ``parent`` field
                  on the ``request`` instance; if ``request`` is provided, this
                  should not be set.
              tensorboard_experiment (google.cloud.aiplatform_v1beta1.types.TensorboardExperiment):
                  The TensorboardExperiment to create.
                  This corresponds to the ``tensorboard_experiment`` field
                  on the ``request`` instance; if ``request`` is provided, this
                  should not be set.
              tensorboard_experiment_id (str):
                  Required. The ID to use for the Tensorboard experiment,
                  which will become the final component of the Tensorboard
                  experiment's resource name.
  
                  This value should be 1-128 characters, and valid
                  characters are /[a-z][0-9]-/.
  
                  This corresponds to the ``tensorboard_experiment_id`` field
                  on the ``request`` instance; if ``request`` is provided, this
                  should not be set.
              retry (google.api_core.retry.Retry): Designation of what errors, if any,
                  should be retried.
              timeout (float): The timeout for this request.
              metadata (Sequence[Tuple[str, str]]): Strings which should be
                  sent along with the request as metadata.
  
          Returns:
              google.cloud.aiplatform_v1beta1.types.TensorboardExperiment:
                  A TensorboardExperiment is a group of
                  TensorboardRuns, that are typically the
                  results of a training job run, in a
                  Tensorboard.
  
          """
          # Create or coerce a protobuf request object.
          # Sanity check: If we got a request object, we should *not* have
          # gotten any keyword arguments that map to the request.
          has_flattened_params = any(
              [parent, tensorboard_experiment, tensorboard_experiment_id]
          )
          if request is not None and has_flattened_params:
              raise ValueError(
                  "If the `request` argument is set, then none of "
                  "the individual field arguments should be set."
              )
  
          # Minor optimization to avoid making a copy if the user passes
          # in a tensorboard_service.CreateTensorboardExperimentRequest.
          # There's no risk of modifying the input as we've already verified
          # there are no flattened fields.
          if not isinstance(
              request, tensorboard_service.CreateTensorboardExperimentRequest
          ):
              request = tensorboard_service.CreateTensorboardExperimentRequest(request)
              # If we have keyword arguments corresponding to fields on the
              # request, apply these.
              if parent is not None:
                  request.parent = parent
              if tensorboard_experiment is not None:
                  request.tensorboard_experiment = tensorboard_experiment
              if tensorboard_experiment_id is not None:
                  request.tensorboard_experiment_id = tensorboard_experiment_id
  
          # Wrap the RPC method; this adds retry and timeout information,
          # and friendly error handling.
          rpc = self._transport._wrapped_methods[
              self._transport.create_tensorboard_experiment
          ]
  
          # Certain fields should be provided within the metadata header;
          # add these here.
          metadata = tuple(metadata) + (
              gapic_v1.routing_header.to_grpc_metadata((("parent", request.parent),)),
          )
  
          # Send the request.
          response = rpc(request, retry=retry, timeout=timeout, metadata=metadata,)
  
          # Done; return the response.
          return response
  
      def get_tensorboard_experiment(
          self,
          request: tensorboard_service.GetTensorboardExperimentRequest = None,
          *,
          name: str = None,
          retry: retries.Retry = gapic_v1.method.DEFAULT,
          timeout: float = None,
          metadata: Sequence[Tuple[str, str]] = (),
      ) -> tensorboard_experiment.TensorboardExperiment:
          r"""Gets a TensorboardExperiment.
  
          Args:
              request (google.cloud.aiplatform_v1beta1.types.GetTensorboardExperimentRequest):
                  The request object. Request message for
                  [TensorboardService.GetTensorboardExperiment][google.cloud.aiplatform.v1beta1.TensorboardService.GetTensorboardExperiment].
              name (str):
                  Required. The name of the TensorboardExperiment
                  resource. Format:
                  ``projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}``
  
                  This corresponds to the ``name`` field
                  on the ``request`` instance; if ``request`` is provided, this
                  should not be set.
              retry (google.api_core.retry.Retry): Designation of what errors, if any,
                  should be retried.
              timeout (float): The timeout for this request.
              metadata (Sequence[Tuple[str, str]]): Strings which should be
                  sent along with the request as metadata.
  
          Returns:
              google.cloud.aiplatform_v1beta1.types.TensorboardExperiment:
                  A TensorboardExperiment is a group of
                  TensorboardRuns, that are typically the
                  results of a training job run, in a
                  Tensorboard.
  
          """
          # Create or coerce a protobuf request object.
          # Sanity check: If we got a request object, we should *not* have
          # gotten any keyword arguments that map to the request.
          has_flattened_params = any([name])
          if request is not None and has_flattened_params:
              raise ValueError(
                  "If the `request` argument is set, then none of "
                  "the individual field arguments should be set."
              )
  
          # Minor optimization to avoid making a copy if the user passes
          # in a tensorboard_service.GetTensorboardExperimentRequest.
          # There's no risk of modifying the input as we've already verified
          # there are no flattened fields.
          if not isinstance(request, tensorboard_service.GetTensorboardExperimentRequest):
              request = tensorboard_service.GetTensorboardExperimentRequest(request)
              # If we have keyword arguments corresponding to fields on the
              # request, apply these.
              if name is not None:
                  request.name = name
  
          # Wrap the RPC method; this adds retry and timeout information,
          # and friendly error handling.
          rpc = self._transport._wrapped_methods[
              self._transport.get_tensorboard_experiment
          ]
  
          # Certain fields should be provided within the metadata header;
          # add these here.
          metadata = tuple(metadata) + (
              gapic_v1.routing_header.to_grpc_metadata((("name", request.name),)),
          )
  
          # Send the request.
          response = rpc(request, retry=retry, timeout=timeout, metadata=metadata,)
  
          # Done; return the response.
          return response
  
      def update_tensorboard_experiment(
          self,
          request: tensorboard_service.UpdateTensorboardExperimentRequest = None,
          *,
          tensorboard_experiment: gca_tensorboard_experiment.TensorboardExperiment = None,
          update_mask: field_mask_pb2.FieldMask = None,
          retry: retries.Retry = gapic_v1.method.DEFAULT,
          timeout: float = None,
          metadata: Sequence[Tuple[str, str]] = (),
      ) -> gca_tensorboard_experiment.TensorboardExperiment:
          r"""Updates a TensorboardExperiment.
  
          Args:
              request (google.cloud.aiplatform_v1beta1.types.UpdateTensorboardExperimentRequest):
                  The request object. Request message for
                  [TensorboardService.UpdateTensorboardExperiment][google.cloud.aiplatform.v1beta1.TensorboardService.UpdateTensorboardExperiment].
              tensorboard_experiment (google.cloud.aiplatform_v1beta1.types.TensorboardExperiment):
                  Required. The TensorboardExperiment's ``name`` field is
                  used to identify the TensorboardExperiment to be
                  updated. Format:
                  ``projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}``
  
                  This corresponds to the ``tensorboard_experiment`` field
                  on the ``request`` instance; if ``request`` is provided, this
                  should not be set.
              update_mask (google.protobuf.field_mask_pb2.FieldMask):
                  Required. Field mask is used to specify the fields to be
                  overwritten in the TensorboardExperiment resource by the
                  update. The fields specified in the update_mask are
                  relative to the resource, not the full request. A field
                  will be overwritten if it is in the mask. If the user
                  does not provide a mask then all fields will be
                  overwritten if new values are specified.
  
                  This corresponds to the ``update_mask`` field
                  on the ``request`` instance; if ``request`` is provided, this
                  should not be set.
              retry (google.api_core.retry.Retry): Designation of what errors, if any,
                  should be retried.
              timeout (float): The timeout for this request.
              metadata (Sequence[Tuple[str, str]]): Strings which should be
                  sent along with the request as metadata.
  
          Returns:
              google.cloud.aiplatform_v1beta1.types.TensorboardExperiment:
                  A TensorboardExperiment is a group of
                  TensorboardRuns, that are typically the
                  results of a training job run, in a
                  Tensorboard.
  
          """
          # Create or coerce a protobuf request object.
          # Sanity check: If we got a request object, we should *not* have
          # gotten any keyword arguments that map to the request.
          has_flattened_params = any([tensorboard_experiment, update_mask])
          if request is not None and has_flattened_params:
              raise ValueError(
                  "If the `request` argument is set, then none of "
                  "the individual field arguments should be set."
              )
  
          # Minor optimization to avoid making a copy if the user passes
          # in a tensorboard_service.UpdateTensorboardExperimentRequest.
          # There's no risk of modifying the input as we've already verified
          # there are no flattened fields.
          if not isinstance(
              request, tensorboard_service.UpdateTensorboardExperimentRequest
          ):
              request = tensorboard_service.UpdateTensorboardExperimentRequest(request)
              # If we have keyword arguments corresponding to fields on the
              # request, apply these.
              if tensorboard_experiment is not None:
                  request.tensorboard_experiment = tensorboard_experiment
              if update_mask is not None:
                  request.update_mask = update_mask
  
          # Wrap the RPC method; this adds retry and timeout information,
          # and friendly error handling.
          rpc = self._transport._wrapped_methods[
              self._transport.update_tensorboard_experiment
          ]
  
          # Certain fields should be provided within the metadata header;
          # add these here.
          metadata = tuple(metadata) + (
              gapic_v1.routing_header.to_grpc_metadata(
                  (("tensorboard_experiment.name", request.tensorboard_experiment.name),)
              ),
          )
  
          # Send the request.
          response = rpc(request, retry=retry, timeout=timeout, metadata=metadata,)
  
          # Done; return the response.
          return response
  
      def list_tensorboard_experiments(
          self,
          request: tensorboard_service.ListTensorboardExperimentsRequest = None,
          *,
          parent: str = None,
          retry: retries.Retry = gapic_v1.method.DEFAULT,
          timeout: float = None,
          metadata: Sequence[Tuple[str, str]] = (),
      ) -> pagers.ListTensorboardExperimentsPager:
          r"""Lists TensorboardExperiments in a Location.
  
          Args:
              request (google.cloud.aiplatform_v1beta1.types.ListTensorboardExperimentsRequest):
                  The request object. Request message for
                  [TensorboardService.ListTensorboardExperiments][google.cloud.aiplatform.v1beta1.TensorboardService.ListTensorboardExperiments].
              parent (str):
                  Required. The resource name of the
                  Tensorboard to list
                  TensorboardExperiments. Format:
                  'projects/{project}/locations/{location}/tensorboards/{tensorboard}'
  
                  This corresponds to the ``parent`` field
                  on the ``request`` instance; if ``request`` is provided, this
                  should not be set.
              retry (google.api_core.retry.Retry): Designation of what errors, if any,
                  should be retried.
              timeout (float): The timeout for this request.
              metadata (Sequence[Tuple[str, str]]): Strings which should be
                  sent along with the request as metadata.
  
          Returns:
              google.cloud.aiplatform_v1beta1.services.tensorboard_service.pagers.ListTensorboardExperimentsPager:
                  Response message for
                  [TensorboardService.ListTensorboardExperiments][google.cloud.aiplatform.v1beta1.TensorboardService.ListTensorboardExperiments].
  
                  Iterating over this object will yield results and
                  resolve additional pages automatically.
  
          """
          # Create or coerce a protobuf request object.
          # Sanity check: If we got a request object, we should *not* have
          # gotten any keyword arguments that map to the request.
          has_flattened_params = any([parent])
          if request is not None and has_flattened_params:
              raise ValueError(
                  "If the `request` argument is set, then none of "
                  "the individual field arguments should be set."
              )
  
          # Minor optimization to avoid making a copy if the user passes
          # in a tensorboard_service.ListTensorboardExperimentsRequest.
          # There's no risk of modifying the input as we've already verified
          # there are no flattened fields.
          if not isinstance(
              request, tensorboard_service.ListTensorboardExperimentsRequest
          ):
              request = tensorboard_service.ListTensorboardExperimentsRequest(request)
              # If we have keyword arguments corresponding to fields on the
              # request, apply these.
              if parent is not None:
                  request.parent = parent
  
          # Wrap the RPC method; this adds retry and timeout information,
          # and friendly error handling.
          rpc = self._transport._wrapped_methods[
              self._transport.list_tensorboard_experiments
          ]
  
          # Certain fields should be provided within the metadata header;
          # add these here.
          metadata = tuple(metadata) + (
              gapic_v1.routing_header.to_grpc_metadata((("parent", request.parent),)),
          )
  
          # Send the request.
          response = rpc(request, retry=retry, timeout=timeout, metadata=metadata,)
  
          # This method is paged; wrap the response in a pager, which provides
          # an `__iter__` convenience method.
          response = pagers.ListTensorboardExperimentsPager(
              method=rpc, request=request, response=response, metadata=metadata,
          )
  
          # Done; return the response.
          return response
  
      def delete_tensorboard_experiment(
          self,
          request: tensorboard_service.DeleteTensorboardExperimentRequest = None,
          *,
          name: str = None,
          retry: retries.Retry = gapic_v1.method.DEFAULT,
          timeout: float = None,
          metadata: Sequence[Tuple[str, str]] = (),
      ) -> gac_operation.Operation:
          r"""Deletes a TensorboardExperiment.
  
          Args:
              request (google.cloud.aiplatform_v1beta1.types.DeleteTensorboardExperimentRequest):
                  The request object. Request message for
                  [TensorboardService.DeleteTensorboardExperiment][google.cloud.aiplatform.v1beta1.TensorboardService.DeleteTensorboardExperiment].
              name (str):
                  Required. The name of the TensorboardExperiment to be
                  deleted. Format:
                  ``projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}``
  
                  This corresponds to the ``name`` field
                  on the ``request`` instance; if ``request`` is provided, this
                  should not be set.
              retry (google.api_core.retry.Retry): Designation of what errors, if any,
                  should be retried.
              timeout (float): The timeout for this request.
              metadata (Sequence[Tuple[str, str]]): Strings which should be
                  sent along with the request as metadata.
  
          Returns:
              google.api_core.operation.Operation:
                  An object representing a long-running operation.
  
                  The result type for the operation will be :class:`google.protobuf.empty_pb2.Empty` A generic empty message that you can re-use to avoid defining duplicated
                     empty messages in your APIs. A typical example is to
                     use it as the request or the response type of an API
                     method. For instance:
  
                        service Foo {
                           rpc Bar(google.protobuf.Empty) returns
                           (google.protobuf.Empty);
  
                        }
  
                     The JSON representation for Empty is empty JSON
                     object {}.
  
          """
          # Create or coerce a protobuf request object.
          # Sanity check: If we got a request object, we should *not* have
          # gotten any keyword arguments that map to the request.
          has_flattened_params = any([name])
          if request is not None and has_flattened_params:
              raise ValueError(
                  "If the `request` argument is set, then none of "
                  "the individual field arguments should be set."
              )
  
          # Minor optimization to avoid making a copy if the user passes
          # in a tensorboard_service.DeleteTensorboardExperimentRequest.
          # There's no risk of modifying the input as we've already verified
          # there are no flattened fields.
          if not isinstance(
              request, tensorboard_service.DeleteTensorboardExperimentRequest
          ):
              request = tensorboard_service.DeleteTensorboardExperimentRequest(request)
              # If we have keyword arguments corresponding to fields on the
              # request, apply these.
              if name is not None:
                  request.name = name
  
          # Wrap the RPC method; this adds retry and timeout information,
          # and friendly error handling.
          rpc = self._transport._wrapped_methods[
              self._transport.delete_tensorboard_experiment
          ]
  
          # Certain fields should be provided within the metadata header;
          # add these here.
          metadata = tuple(metadata) + (
              gapic_v1.routing_header.to_grpc_metadata((("name", request.name),)),
          )
  
          # Send the request.
          response = rpc(request, retry=retry, timeout=timeout, metadata=metadata,)
  
          # Wrap the response in an operation future.
          response = gac_operation.from_gapic(
              response,
              self._transport.operations_client,
              empty_pb2.Empty,
              metadata_type=gca_operation.DeleteOperationMetadata,
          )
  
          # Done; return the response.
          return response
  
      def create_tensorboard_run(
          self,
          request: tensorboard_service.CreateTensorboardRunRequest = None,
          *,
          parent: str = None,
          tensorboard_run: gca_tensorboard_run.TensorboardRun = None,
          tensorboard_run_id: str = None,
          retry: retries.Retry = gapic_v1.method.DEFAULT,
          timeout: float = None,
          metadata: Sequence[Tuple[str, str]] = (),
      ) -> gca_tensorboard_run.TensorboardRun:
          r"""Creates a TensorboardRun.
  
          Args:
              request (google.cloud.aiplatform_v1beta1.types.CreateTensorboardRunRequest):
                  The request object. Request message for
                  [TensorboardService.CreateTensorboardRun][google.cloud.aiplatform.v1beta1.TensorboardService.CreateTensorboardRun].
              parent (str):
                  Required. The resource name of the TensorboardExperiment
                  to create the TensorboardRun in. Format:
                  ``projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}``
  
                  This corresponds to the ``parent`` field
                  on the ``request`` instance; if ``request`` is provided, this
                  should not be set.
              tensorboard_run (google.cloud.aiplatform_v1beta1.types.TensorboardRun):
                  Required. The TensorboardRun to
                  create.
  
                  This corresponds to the ``tensorboard_run`` field
                  on the ``request`` instance; if ``request`` is provided, this
                  should not be set.
              tensorboard_run_id (str):
                  Required. The ID to use for the Tensorboard run, which
                  will become the final component of the Tensorboard run's
                  resource name.
  
                  This value should be 1-128 characters, and valid
                  characters are /[a-z][0-9]-/.
  
                  This corresponds to the ``tensorboard_run_id`` field
                  on the ``request`` instance; if ``request`` is provided, this
                  should not be set.
              retry (google.api_core.retry.Retry): Designation of what errors, if any,
                  should be retried.
              timeout (float): The timeout for this request.
              metadata (Sequence[Tuple[str, str]]): Strings which should be
                  sent along with the request as metadata.
  
          Returns:
              google.cloud.aiplatform_v1beta1.types.TensorboardRun:
                  TensorboardRun maps to a specific
                  execution of a training job with a given
                  set of hyperparameter values, model
                  definition, dataset, etc
  
          """
          # Create or coerce a protobuf request object.
          # Sanity check: If we got a request object, we should *not* have
          # gotten any keyword arguments that map to the request.
          has_flattened_params = any([parent, tensorboard_run, tensorboard_run_id])
          if request is not None and has_flattened_params:
              raise ValueError(
                  "If the `request` argument is set, then none of "
                  "the individual field arguments should be set."
              )
  
          # Minor optimization to avoid making a copy if the user passes
          # in a tensorboard_service.CreateTensorboardRunRequest.
          # There's no risk of modifying the input as we've already verified
          # there are no flattened fields.
          if not isinstance(request, tensorboard_service.CreateTensorboardRunRequest):
              request = tensorboard_service.CreateTensorboardRunRequest(request)
              # If we have keyword arguments corresponding to fields on the
              # request, apply these.
              if parent is not None:
                  request.parent = parent
              if tensorboard_run is not None:
                  request.tensorboard_run = tensorboard_run
              if tensorboard_run_id is not None:
                  request.tensorboard_run_id = tensorboard_run_id
  
          # Wrap the RPC method; this adds retry and timeout information,
          # and friendly error handling.
          rpc = self._transport._wrapped_methods[self._transport.create_tensorboard_run]
  
          # Certain fields should be provided within the metadata header;
          # add these here.
          metadata = tuple(metadata) + (
              gapic_v1.routing_header.to_grpc_metadata((("parent", request.parent),)),
          )
  
          # Send the request.
          response = rpc(request, retry=retry, timeout=timeout, metadata=metadata,)
  
          # Done; return the response.
          return response
  
      def batch_create_tensorboard_runs(
          self,
          request: tensorboard_service.BatchCreateTensorboardRunsRequest = None,
          *,
          parent: str = None,
          requests: Sequence[tensorboard_service.CreateTensorboardRunRequest] = None,
          retry: retries.Retry = gapic_v1.method.DEFAULT,
          timeout: float = None,
          metadata: Sequence[Tuple[str, str]] = (),
      ) -> tensorboard_service.BatchCreateTensorboardRunsResponse:
          r"""Batch create TensorboardRuns.
  
          Args:
              request (google.cloud.aiplatform_v1beta1.types.BatchCreateTensorboardRunsRequest):
                  The request object. Request message for
                  [TensorboardService.BatchCreateTensorboardRuns][google.cloud.aiplatform.v1beta1.TensorboardService.BatchCreateTensorboardRuns].
              parent (str):
                  Required. The resource name of the TensorboardExperiment
                  to create the TensorboardRuns in. Format:
                  ``projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}``
                  The parent field in the CreateTensorboardRunRequest
                  messages must match this field.
  
                  This corresponds to the ``parent`` field
                  on the ``request`` instance; if ``request`` is provided, this
                  should not be set.
              requests (Sequence[google.cloud.aiplatform_v1beta1.types.CreateTensorboardRunRequest]):
                  Required. The request message
                  specifying the TensorboardRuns to
                  create. A maximum of 1000
                  TensorboardRuns can be created in a
                  batch.
  
                  This corresponds to the ``requests`` field
                  on the ``request`` instance; if ``request`` is provided, this
                  should not be set.
              retry (google.api_core.retry.Retry): Designation of what errors, if any,
                  should be retried.
              timeout (float): The timeout for this request.
              metadata (Sequence[Tuple[str, str]]): Strings which should be
                  sent along with the request as metadata.
  
          Returns:
              google.cloud.aiplatform_v1beta1.types.BatchCreateTensorboardRunsResponse:
                  Response message for
                  [TensorboardService.BatchCreateTensorboardRuns][google.cloud.aiplatform.v1beta1.TensorboardService.BatchCreateTensorboardRuns].
  
          """
          # Create or coerce a protobuf request object.
          # Sanity check: If we got a request object, we should *not* have
          # gotten any keyword arguments that map to the request.
          has_flattened_params = any([parent, requests])
          if request is not None and has_flattened_params:
              raise ValueError(
                  "If the `request` argument is set, then none of "
                  "the individual field arguments should be set."
              )
  
          # Minor optimization to avoid making a copy if the user passes
          # in a tensorboard_service.BatchCreateTensorboardRunsRequest.
          # There's no risk of modifying the input as we've already verified
          # there are no flattened fields.
          if not isinstance(
              request, tensorboard_service.BatchCreateTensorboardRunsRequest
          ):
              request = tensorboard_service.BatchCreateTensorboardRunsRequest(request)
              # If we have keyword arguments corresponding to fields on the
              # request, apply these.
              if parent is not None:
                  request.parent = parent
              if requests is not None:
                  request.requests = requests
  
          # Wrap the RPC method; this adds retry and timeout information,
          # and friendly error handling.
          rpc = self._transport._wrapped_methods[
              self._transport.batch_create_tensorboard_runs
          ]
  
          # Certain fields should be provided within the metadata header;
          # add these here.
          metadata = tuple(metadata) + (
              gapic_v1.routing_header.to_grpc_metadata((("parent", request.parent),)),
          )
  
          # Send the request.
          response = rpc(request, retry=retry, timeout=timeout, metadata=metadata,)
  
          # Done; return the response.
          return response
  
      def get_tensorboard_run(
          self,
          request: tensorboard_service.GetTensorboardRunRequest = None,
          *,
          name: str = None,
          retry: retries.Retry = gapic_v1.method.DEFAULT,
          timeout: float = None,
          metadata: Sequence[Tuple[str, str]] = (),
      ) -> tensorboard_run.TensorboardRun:
          r"""Gets a TensorboardRun.
  
          Args:
              request (google.cloud.aiplatform_v1beta1.types.GetTensorboardRunRequest):
                  The request object. Request message for
                  [TensorboardService.GetTensorboardRun][google.cloud.aiplatform.v1beta1.TensorboardService.GetTensorboardRun].
              name (str):
                  Required. The name of the TensorboardRun resource.
                  Format:
                  ``projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}``
  
                  This corresponds to the ``name`` field
                  on the ``request`` instance; if ``request`` is provided, this
                  should not be set.
              retry (google.api_core.retry.Retry): Designation of what errors, if any,
                  should be retried.
              timeout (float): The timeout for this request.
              metadata (Sequence[Tuple[str, str]]): Strings which should be
                  sent along with the request as metadata.
  
          Returns:
              google.cloud.aiplatform_v1beta1.types.TensorboardRun:
                  TensorboardRun maps to a specific
                  execution of a training job with a given
                  set of hyperparameter values, model
                  definition, dataset, etc
  
          """
          # Create or coerce a protobuf request object.
          # Sanity check: If we got a request object, we should *not* have
          # gotten any keyword arguments that map to the request.
          has_flattened_params = any([name])
          if request is not None and has_flattened_params:
              raise ValueError(
                  "If the `request` argument is set, then none of "
                  "the individual field arguments should be set."
              )
  
          # Minor optimization to avoid making a copy if the user passes
          # in a tensorboard_service.GetTensorboardRunRequest.
          # There's no risk of modifying the input as we've already verified
          # there are no flattened fields.
          if not isinstance(request, tensorboard_service.GetTensorboardRunRequest):
              request = tensorboard_service.GetTensorboardRunRequest(request)
              # If we have keyword arguments corresponding to fields on the
              # request, apply these.
              if name is not None:
                  request.name = name
  
          # Wrap the RPC method; this adds retry and timeout information,
          # and friendly error handling.
          rpc = self._transport._wrapped_methods[self._transport.get_tensorboard_run]
  
          # Certain fields should be provided within the metadata header;
          # add these here.
          metadata = tuple(metadata) + (
              gapic_v1.routing_header.to_grpc_metadata((("name", request.name),)),
          )
  
          # Send the request.
          response = rpc(request, retry=retry, timeout=timeout, metadata=metadata,)
  
          # Done; return the response.
          return response
  
      def update_tensorboard_run(
          self,
          request: tensorboard_service.UpdateTensorboardRunRequest = None,
          *,
          tensorboard_run: gca_tensorboard_run.TensorboardRun = None,
          update_mask: field_mask_pb2.FieldMask = None,
          retry: retries.Retry = gapic_v1.method.DEFAULT,
          timeout: float = None,
          metadata: Sequence[Tuple[str, str]] = (),
      ) -> gca_tensorboard_run.TensorboardRun:
          r"""Updates a TensorboardRun.
  
          Args:
              request (google.cloud.aiplatform_v1beta1.types.UpdateTensorboardRunRequest):
                  The request object. Request message for
                  [TensorboardService.UpdateTensorboardRun][google.cloud.aiplatform.v1beta1.TensorboardService.UpdateTensorboardRun].
              tensorboard_run (google.cloud.aiplatform_v1beta1.types.TensorboardRun):
                  Required. The TensorboardRun's ``name`` field is used to
                  identify the TensorboardRun to be updated. Format:
                  ``projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}``
  
                  This corresponds to the ``tensorboard_run`` field
                  on the ``request`` instance; if ``request`` is provided, this
                  should not be set.
              update_mask (google.protobuf.field_mask_pb2.FieldMask):
                  Required. Field mask is used to specify the fields to be
                  overwritten in the TensorboardRun resource by the
                  update. The fields specified in the update_mask are
                  relative to the resource, not the full request. A field
                  will be overwritten if it is in the mask. If the user
                  does not provide a mask then all fields will be
                  overwritten if new values are specified.
  
                  This corresponds to the ``update_mask`` field
                  on the ``request`` instance; if ``request`` is provided, this
                  should not be set.
              retry (google.api_core.retry.Retry): Designation of what errors, if any,
                  should be retried.
              timeout (float): The timeout for this request.
              metadata (Sequence[Tuple[str, str]]): Strings which should be
                  sent along with the request as metadata.
  
          Returns:
              google.cloud.aiplatform_v1beta1.types.TensorboardRun:
                  TensorboardRun maps to a specific
                  execution of a training job with a given
                  set of hyperparameter values, model
                  definition, dataset, etc
  
          """
          # Create or coerce a protobuf request object.
          # Sanity check: If we got a request object, we should *not* have
          # gotten any keyword arguments that map to the request.
          has_flattened_params = any([tensorboard_run, update_mask])
          if request is not None and has_flattened_params:
              raise ValueError(
                  "If the `request` argument is set, then none of "
                  "the individual field arguments should be set."
              )
  
          # Minor optimization to avoid making a copy if the user passes
          # in a tensorboard_service.UpdateTensorboardRunRequest.
          # There's no risk of modifying the input as we've already verified
          # there are no flattened fields.
          if not isinstance(request, tensorboard_service.UpdateTensorboardRunRequest):
              request = tensorboard_service.UpdateTensorboardRunRequest(request)
              # If we have keyword arguments corresponding to fields on the
              # request, apply these.
              if tensorboard_run is not None:
                  request.tensorboard_run = tensorboard_run
              if update_mask is not None:
                  request.update_mask = update_mask
  
          # Wrap the RPC method; this adds retry and timeout information,
          # and friendly error handling.
          rpc = self._transport._wrapped_methods[self._transport.update_tensorboard_run]
  
          # Certain fields should be provided within the metadata header;
          # add these here.
          metadata = tuple(metadata) + (
              gapic_v1.routing_header.to_grpc_metadata(
                  (("tensorboard_run.name", request.tensorboard_run.name),)
              ),
          )
  
          # Send the request.
          response = rpc(request, retry=retry, timeout=timeout, metadata=metadata,)
  
          # Done; return the response.
          return response
  
      def list_tensorboard_runs(
          self,
          request: tensorboard_service.ListTensorboardRunsRequest = None,
          *,
          parent: str = None,
          retry: retries.Retry = gapic_v1.method.DEFAULT,
          timeout: float = None,
          metadata: Sequence[Tuple[str, str]] = (),
      ) -> pagers.ListTensorboardRunsPager:
          r"""Lists TensorboardRuns in a Location.
  
          Args:
              request (google.cloud.aiplatform_v1beta1.types.ListTensorboardRunsRequest):
                  The request object. Request message for
                  [TensorboardService.ListTensorboardRuns][google.cloud.aiplatform.v1beta1.TensorboardService.ListTensorboardRuns].
              parent (str):
                  Required. The resource name of the
                  TensorboardExperiment to list
                  TensorboardRuns. Format:
                  'projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}'
  
                  This corresponds to the ``parent`` field
                  on the ``request`` instance; if ``request`` is provided, this
                  should not be set.
              retry (google.api_core.retry.Retry): Designation of what errors, if any,
                  should be retried.
              timeout (float): The timeout for this request.
              metadata (Sequence[Tuple[str, str]]): Strings which should be
                  sent along with the request as metadata.
  
          Returns:
              google.cloud.aiplatform_v1beta1.services.tensorboard_service.pagers.ListTensorboardRunsPager:
                  Response message for
                  [TensorboardService.ListTensorboardRuns][google.cloud.aiplatform.v1beta1.TensorboardService.ListTensorboardRuns].
  
                  Iterating over this object will yield results and
                  resolve additional pages automatically.
  
          """
          # Create or coerce a protobuf request object.
          # Sanity check: If we got a request object, we should *not* have
          # gotten any keyword arguments that map to the request.
          has_flattened_params = any([parent])
          if request is not None and has_flattened_params:
              raise ValueError(
                  "If the `request` argument is set, then none of "
                  "the individual field arguments should be set."
              )
  
          # Minor optimization to avoid making a copy if the user passes
          # in a tensorboard_service.ListTensorboardRunsRequest.
          # There's no risk of modifying the input as we've already verified
          # there are no flattened fields.
          if not isinstance(request, tensorboard_service.ListTensorboardRunsRequest):
              request = tensorboard_service.ListTensorboardRunsRequest(request)
              # If we have keyword arguments corresponding to fields on the
              # request, apply these.
              if parent is not None:
                  request.parent = parent
  
          # Wrap the RPC method; this adds retry and timeout information,
          # and friendly error handling.
          rpc = self._transport._wrapped_methods[self._transport.list_tensorboard_runs]
  
          # Certain fields should be provided within the metadata header;
          # add these here.
          metadata = tuple(metadata) + (
              gapic_v1.routing_header.to_grpc_metadata((("parent", request.parent),)),
          )
  
          # Send the request.
          response = rpc(request, retry=retry, timeout=timeout, metadata=metadata,)
  
          # This method is paged; wrap the response in a pager, which provides
          # an `__iter__` convenience method.
          response = pagers.ListTensorboardRunsPager(
              method=rpc, request=request, response=response, metadata=metadata,
          )
  
          # Done; return the response.
          return response
  
      def delete_tensorboard_run(
          self,
          request: tensorboard_service.DeleteTensorboardRunRequest = None,
          *,
          name: str = None,
          retry: retries.Retry = gapic_v1.method.DEFAULT,
          timeout: float = None,
          metadata: Sequence[Tuple[str, str]] = (),
      ) -> gac_operation.Operation:
          r"""Deletes a TensorboardRun.
  
          Args:
              request (google.cloud.aiplatform_v1beta1.types.DeleteTensorboardRunRequest):
                  The request object. Request message for
                  [TensorboardService.DeleteTensorboardRun][google.cloud.aiplatform.v1beta1.TensorboardService.DeleteTensorboardRun].
              name (str):
                  Required. The name of the TensorboardRun to be deleted.
                  Format:
                  ``projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}``
  
                  This corresponds to the ``name`` field
                  on the ``request`` instance; if ``request`` is provided, this
                  should not be set.
              retry (google.api_core.retry.Retry): Designation of what errors, if any,
                  should be retried.
              timeout (float): The timeout for this request.
              metadata (Sequence[Tuple[str, str]]): Strings which should be
                  sent along with the request as metadata.
  
          Returns:
              google.api_core.operation.Operation:
                  An object representing a long-running operation.
  
                  The result type for the operation will be :class:`google.protobuf.empty_pb2.Empty` A generic empty message that you can re-use to avoid defining duplicated
                     empty messages in your APIs. A typical example is to
                     use it as the request or the response type of an API
                     method. For instance:
  
                        service Foo {
                           rpc Bar(google.protobuf.Empty) returns
                           (google.protobuf.Empty);
  
                        }
  
                     The JSON representation for Empty is empty JSON
                     object {}.
  
          """
          # Create or coerce a protobuf request object.
          # Sanity check: If we got a request object, we should *not* have
          # gotten any keyword arguments that map to the request.
          has_flattened_params = any([name])
          if request is not None and has_flattened_params:
              raise ValueError(
                  "If the `request` argument is set, then none of "
                  "the individual field arguments should be set."
              )
  
          # Minor optimization to avoid making a copy if the user passes
          # in a tensorboard_service.DeleteTensorboardRunRequest.
          # There's no risk of modifying the input as we've already verified
          # there are no flattened fields.
          if not isinstance(request, tensorboard_service.DeleteTensorboardRunRequest):
              request = tensorboard_service.DeleteTensorboardRunRequest(request)
              # If we have keyword arguments corresponding to fields on the
              # request, apply these.
              if name is not None:
                  request.name = name
  
          # Wrap the RPC method; this adds retry and timeout information,
          # and friendly error handling.
          rpc = self._transport._wrapped_methods[self._transport.delete_tensorboard_run]
  
          # Certain fields should be provided within the metadata header;
          # add these here.
          metadata = tuple(metadata) + (
              gapic_v1.routing_header.to_grpc_metadata((("name", request.name),)),
          )
  
          # Send the request.
          response = rpc(request, retry=retry, timeout=timeout, metadata=metadata,)
  
          # Wrap the response in an operation future.
          response = gac_operation.from_gapic(
              response,
              self._transport.operations_client,
              empty_pb2.Empty,
              metadata_type=gca_operation.DeleteOperationMetadata,
          )
  
          # Done; return the response.
          return response
  
      def batch_create_tensorboard_time_series(
          self,
          request: tensorboard_service.BatchCreateTensorboardTimeSeriesRequest = None,
          *,
          parent: str = None,
          requests: Sequence[
              tensorboard_service.CreateTensorboardTimeSeriesRequest
          ] = None,
          retry: retries.Retry = gapic_v1.method.DEFAULT,
          timeout: float = None,
          metadata: Sequence[Tuple[str, str]] = (),
      ) -> tensorboard_service.BatchCreateTensorboardTimeSeriesResponse:
          r"""Batch create TensorboardTimeSeries that belong to a
          TensorboardExperiment.
  
          Args:
              request (google.cloud.aiplatform_v1beta1.types.BatchCreateTensorboardTimeSeriesRequest):
                  The request object. Request message for
                  [TensorboardService.BatchCreateTensorboardTimeSeries][google.cloud.aiplatform.v1beta1.TensorboardService.BatchCreateTensorboardTimeSeries].
              parent (str):
                  Required. The resource name of the TensorboardExperiment
                  to create the TensorboardTimeSeries in. Format:
                  ``projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}``
                  The TensorboardRuns referenced by the parent fields in
                  the CreateTensorboardTimeSeriesRequest messages must be
                  sub resources of this TensorboardExperiment.
  
                  This corresponds to the ``parent`` field
                  on the ``request`` instance; if ``request`` is provided, this
                  should not be set.
              requests (Sequence[google.cloud.aiplatform_v1beta1.types.CreateTensorboardTimeSeriesRequest]):
                  Required. The request message
                  specifying the TensorboardTimeSeries to
                  create. A maximum of 1000
                  TensorboardTimeSeries can be created in
                  a batch.
  
                  This corresponds to the ``requests`` field
                  on the ``request`` instance; if ``request`` is provided, this
                  should not be set.
              retry (google.api_core.retry.Retry): Designation of what errors, if any,
                  should be retried.
              timeout (float): The timeout for this request.
              metadata (Sequence[Tuple[str, str]]): Strings which should be
                  sent along with the request as metadata.
  
          Returns:
              google.cloud.aiplatform_v1beta1.types.BatchCreateTensorboardTimeSeriesResponse:
                  Response message for
                  [TensorboardService.BatchCreateTensorboardTimeSeries][google.cloud.aiplatform.v1beta1.TensorboardService.BatchCreateTensorboardTimeSeries].
  
          """
          # Create or coerce a protobuf request object.
          # Sanity check: If we got a request object, we should *not* have
          # gotten any keyword arguments that map to the request.
          has_flattened_params = any([parent, requests])
          if request is not None and has_flattened_params:
              raise ValueError(
                  "If the `request` argument is set, then none of "
                  "the individual field arguments should be set."
              )
  
          # Minor optimization to avoid making a copy if the user passes
          # in a tensorboard_service.BatchCreateTensorboardTimeSeriesRequest.
          # There's no risk of modifying the input as we've already verified
          # there are no flattened fields.
          if not isinstance(
              request, tensorboard_service.BatchCreateTensorboardTimeSeriesRequest
          ):
              request = tensorboard_service.BatchCreateTensorboardTimeSeriesRequest(
                  request
              )
              # If we have keyword arguments corresponding to fields on the
              # request, apply these.
              if parent is not None:
                  request.parent = parent
              if requests is not None:
                  request.requests = requests
  
          # Wrap the RPC method; this adds retry and timeout information,
          # and friendly error handling.
          rpc = self._transport._wrapped_methods[
              self._transport.batch_create_tensorboard_time_series
          ]
  
          # Certain fields should be provided within the metadata header;
          # add these here.
          metadata = tuple(metadata) + (
              gapic_v1.routing_header.to_grpc_metadata((("parent", request.parent),)),
          )
  
          # Send the request.
          response = rpc(request, retry=retry, timeout=timeout, metadata=metadata,)
  
          # Done; return the response.
          return response
  
      def create_tensorboard_time_series(
          self,
          request: tensorboard_service.CreateTensorboardTimeSeriesRequest = None,
          *,
          parent: str = None,
          tensorboard_time_series: gca_tensorboard_time_series.TensorboardTimeSeries = None,
          retry: retries.Retry = gapic_v1.method.DEFAULT,
          timeout: float = None,
          metadata: Sequence[Tuple[str, str]] = (),
      ) -> gca_tensorboard_time_series.TensorboardTimeSeries:
          r"""Creates a TensorboardTimeSeries.
  
          Args:
              request (google.cloud.aiplatform_v1beta1.types.CreateTensorboardTimeSeriesRequest):
                  The request object. Request message for
                  [TensorboardService.CreateTensorboardTimeSeries][google.cloud.aiplatform.v1beta1.TensorboardService.CreateTensorboardTimeSeries].
              parent (str):
                  Required. The resource name of the TensorboardRun to
                  create the TensorboardTimeSeries in. Format:
                  ``projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}``
  
                  This corresponds to the ``parent`` field
                  on the ``request`` instance; if ``request`` is provided, this
                  should not be set.
              tensorboard_time_series (google.cloud.aiplatform_v1beta1.types.TensorboardTimeSeries):
                  Required. The TensorboardTimeSeries
                  to create.
  
                  This corresponds to the ``tensorboard_time_series`` field
                  on the ``request`` instance; if ``request`` is provided, this
                  should not be set.
              retry (google.api_core.retry.Retry): Designation of what errors, if any,
                  should be retried.
              timeout (float): The timeout for this request.
              metadata (Sequence[Tuple[str, str]]): Strings which should be
                  sent along with the request as metadata.
  
          Returns:
              google.cloud.aiplatform_v1beta1.types.TensorboardTimeSeries:
                  TensorboardTimeSeries maps to times
                  series produced in training runs
  
          """
          # Create or coerce a protobuf request object.
          # Sanity check: If we got a request object, we should *not* have
          # gotten any keyword arguments that map to the request.
          has_flattened_params = any([parent, tensorboard_time_series])
          if request is not None and has_flattened_params:
              raise ValueError(
                  "If the `request` argument is set, then none of "
                  "the individual field arguments should be set."
              )
  
          # Minor optimization to avoid making a copy if the user passes
          # in a tensorboard_service.CreateTensorboardTimeSeriesRequest.
          # There's no risk of modifying the input as we've already verified
          # there are no flattened fields.
          if not isinstance(
              request, tensorboard_service.CreateTensorboardTimeSeriesRequest
          ):
              request = tensorboard_service.CreateTensorboardTimeSeriesRequest(request)
              # If we have keyword arguments corresponding to fields on the
              # request, apply these.
              if parent is not None:
                  request.parent = parent
              if tensorboard_time_series is not None:
                  request.tensorboard_time_series = tensorboard_time_series
  
          # Wrap the RPC method; this adds retry and timeout information,
          # and friendly error handling.
          rpc = self._transport._wrapped_methods[
              self._transport.create_tensorboard_time_series
          ]
  
          # Certain fields should be provided within the metadata header;
          # add these here.
          metadata = tuple(metadata) + (
              gapic_v1.routing_header.to_grpc_metadata((("parent", request.parent),)),
          )
  
          # Send the request.
          response = rpc(request, retry=retry, timeout=timeout, metadata=metadata,)
  
          # Done; return the response.
          return response
  
      def get_tensorboard_time_series(
          self,
          request: tensorboard_service.GetTensorboardTimeSeriesRequest = None,
          *,
          name: str = None,
          retry: retries.Retry = gapic_v1.method.DEFAULT,
          timeout: float = None,
          metadata: Sequence[Tuple[str, str]] = (),
      ) -> tensorboard_time_series.TensorboardTimeSeries:
          r"""Gets a TensorboardTimeSeries.
  
          Args:
              request (google.cloud.aiplatform_v1beta1.types.GetTensorboardTimeSeriesRequest):
                  The request object. Request message for
                  [TensorboardService.GetTensorboardTimeSeries][google.cloud.aiplatform.v1beta1.TensorboardService.GetTensorboardTimeSeries].
              name (str):
                  Required. The name of the TensorboardTimeSeries
                  resource. Format:
                  ``projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}/timeSeries/{time_series}``
  
                  This corresponds to the ``name`` field
                  on the ``request`` instance; if ``request`` is provided, this
                  should not be set.
              retry (google.api_core.retry.Retry): Designation of what errors, if any,
                  should be retried.
              timeout (float): The timeout for this request.
              metadata (Sequence[Tuple[str, str]]): Strings which should be
                  sent along with the request as metadata.
  
          Returns:
              google.cloud.aiplatform_v1beta1.types.TensorboardTimeSeries:
                  TensorboardTimeSeries maps to times
                  series produced in training runs
  
          """
          # Create or coerce a protobuf request object.
          # Sanity check: If we got a request object, we should *not* have
          # gotten any keyword arguments that map to the request.
          has_flattened_params = any([name])
          if request is not None and has_flattened_params:
              raise ValueError(
                  "If the `request` argument is set, then none of "
                  "the individual field arguments should be set."
              )
  
          # Minor optimization to avoid making a copy if the user passes
          # in a tensorboard_service.GetTensorboardTimeSeriesRequest.
          # There's no risk of modifying the input as we've already verified
          # there are no flattened fields.
          if not isinstance(request, tensorboard_service.GetTensorboardTimeSeriesRequest):
              request = tensorboard_service.GetTensorboardTimeSeriesRequest(request)
              # If we have keyword arguments corresponding to fields on the
              # request, apply these.
              if name is not None:
                  request.name = name
  
          # Wrap the RPC method; this adds retry and timeout information,
          # and friendly error handling.
          rpc = self._transport._wrapped_methods[
              self._transport.get_tensorboard_time_series
          ]
  
          # Certain fields should be provided within the metadata header;
          # add these here.
          metadata = tuple(metadata) + (
              gapic_v1.routing_header.to_grpc_metadata((("name", request.name),)),
          )
  
          # Send the request.
          response = rpc(request, retry=retry, timeout=timeout, metadata=metadata,)
  
          # Done; return the response.
          return response
  
      def update_tensorboard_time_series(
          self,
          request: tensorboard_service.UpdateTensorboardTimeSeriesRequest = None,
          *,
          tensorboard_time_series: gca_tensorboard_time_series.TensorboardTimeSeries = None,
          update_mask: field_mask_pb2.FieldMask = None,
          retry: retries.Retry = gapic_v1.method.DEFAULT,
          timeout: float = None,
          metadata: Sequence[Tuple[str, str]] = (),
      ) -> gca_tensorboard_time_series.TensorboardTimeSeries:
          r"""Updates a TensorboardTimeSeries.
  
          Args:
              request (google.cloud.aiplatform_v1beta1.types.UpdateTensorboardTimeSeriesRequest):
                  The request object. Request message for
                  [TensorboardService.UpdateTensorboardTimeSeries][google.cloud.aiplatform.v1beta1.TensorboardService.UpdateTensorboardTimeSeries].
              tensorboard_time_series (google.cloud.aiplatform_v1beta1.types.TensorboardTimeSeries):
                  Required. The TensorboardTimeSeries' ``name`` field is
                  used to identify the TensorboardTimeSeries to be
                  updated. Format:
                  ``projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}/timeSeries/{time_series}``
  
                  This corresponds to the ``tensorboard_time_series`` field
                  on the ``request`` instance; if ``request`` is provided, this
                  should not be set.
              update_mask (google.protobuf.field_mask_pb2.FieldMask):
                  Required. Field mask is used to specify the fields to be
                  overwritten in the TensorboardTimeSeries resource by the
                  update. The fields specified in the update_mask are
                  relative to the resource, not the full request. A field
                  will be overwritten if it is in the mask. If the user
                  does not provide a mask then all fields will be
                  overwritten if new values are specified.
  
                  This corresponds to the ``update_mask`` field
                  on the ``request`` instance; if ``request`` is provided, this
                  should not be set.
              retry (google.api_core.retry.Retry): Designation of what errors, if any,
                  should be retried.
              timeout (float): The timeout for this request.
              metadata (Sequence[Tuple[str, str]]): Strings which should be
                  sent along with the request as metadata.
  
          Returns:
              google.cloud.aiplatform_v1beta1.types.TensorboardTimeSeries:
                  TensorboardTimeSeries maps to times
                  series produced in training runs
  
          """
          # Create or coerce a protobuf request object.
          # Sanity check: If we got a request object, we should *not* have
          # gotten any keyword arguments that map to the request.
          has_flattened_params = any([tensorboard_time_series, update_mask])
          if request is not None and has_flattened_params:
              raise ValueError(
                  "If the `request` argument is set, then none of "
                  "the individual field arguments should be set."
              )
  
          # Minor optimization to avoid making a copy if the user passes
          # in a tensorboard_service.UpdateTensorboardTimeSeriesRequest.
          # There's no risk of modifying the input as we've already verified
          # there are no flattened fields.
          if not isinstance(
              request, tensorboard_service.UpdateTensorboardTimeSeriesRequest
          ):
              request = tensorboard_service.UpdateTensorboardTimeSeriesRequest(request)
              # If we have keyword arguments corresponding to fields on the
              # request, apply these.
              if tensorboard_time_series is not None:
                  request.tensorboard_time_series = tensorboard_time_series
              if update_mask is not None:
                  request.update_mask = update_mask
  
          # Wrap the RPC method; this adds retry and timeout information,
          # and friendly error handling.
          rpc = self._transport._wrapped_methods[
              self._transport.update_tensorboard_time_series
          ]
  
          # Certain fields should be provided within the metadata header;
          # add these here.
          metadata = tuple(metadata) + (
              gapic_v1.routing_header.to_grpc_metadata(
                  (
                      (
                          "tensorboard_time_series.name",
                          request.tensorboard_time_series.name,
                      ),
                  )
              ),
          )
  
          # Send the request.
          response = rpc(request, retry=retry, timeout=timeout, metadata=metadata,)
  
          # Done; return the response.
          return response
  
      def list_tensorboard_time_series(
          self,
          request: tensorboard_service.ListTensorboardTimeSeriesRequest = None,
          *,
          parent: str = None,
          retry: retries.Retry = gapic_v1.method.DEFAULT,
          timeout: float = None,
          metadata: Sequence[Tuple[str, str]] = (),
      ) -> pagers.ListTensorboardTimeSeriesPager:
          r"""Lists TensorboardTimeSeries in a Location.
  
          Args:
              request (google.cloud.aiplatform_v1beta1.types.ListTensorboardTimeSeriesRequest):
                  The request object. Request message for
                  [TensorboardService.ListTensorboardTimeSeries][google.cloud.aiplatform.v1beta1.TensorboardService.ListTensorboardTimeSeries].
              parent (str):
                  Required. The resource name of the
                  TensorboardRun to list
                  TensorboardTimeSeries. Format:
                  'projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}'
  
                  This corresponds to the ``parent`` field
                  on the ``request`` instance; if ``request`` is provided, this
                  should not be set.
              retry (google.api_core.retry.Retry): Designation of what errors, if any,
                  should be retried.
              timeout (float): The timeout for this request.
              metadata (Sequence[Tuple[str, str]]): Strings which should be
                  sent along with the request as metadata.
  
          Returns:
              google.cloud.aiplatform_v1beta1.services.tensorboard_service.pagers.ListTensorboardTimeSeriesPager:
                  Response message for
                  [TensorboardService.ListTensorboardTimeSeries][google.cloud.aiplatform.v1beta1.TensorboardService.ListTensorboardTimeSeries].
  
                  Iterating over this object will yield results and
                  resolve additional pages automatically.
  
          """
          # Create or coerce a protobuf request object.
          # Sanity check: If we got a request object, we should *not* have
          # gotten any keyword arguments that map to the request.
          has_flattened_params = any([parent])
          if request is not None and has_flattened_params:
              raise ValueError(
                  "If the `request` argument is set, then none of "
                  "the individual field arguments should be set."
              )
  
          # Minor optimization to avoid making a copy if the user passes
          # in a tensorboard_service.ListTensorboardTimeSeriesRequest.
          # There's no risk of modifying the input as we've already verified
          # there are no flattened fields.
          if not isinstance(
              request, tensorboard_service.ListTensorboardTimeSeriesRequest
          ):
              request = tensorboard_service.ListTensorboardTimeSeriesRequest(request)
              # If we have keyword arguments corresponding to fields on the
              # request, apply these.
              if parent is not None:
                  request.parent = parent
  
          # Wrap the RPC method; this adds retry and timeout information,
          # and friendly error handling.
          rpc = self._transport._wrapped_methods[
              self._transport.list_tensorboard_time_series
          ]
  
          # Certain fields should be provided within the metadata header;
          # add these here.
          metadata = tuple(metadata) + (
              gapic_v1.routing_header.to_grpc_metadata((("parent", request.parent),)),
          )
  
          # Send the request.
          response = rpc(request, retry=retry, timeout=timeout, metadata=metadata,)
  
          # This method is paged; wrap the response in a pager, which provides
          # an `__iter__` convenience method.
          response = pagers.ListTensorboardTimeSeriesPager(
              method=rpc, request=request, response=response, metadata=metadata,
          )
  
          # Done; return the response.
          return response
  
      def delete_tensorboard_time_series(
          self,
          request: tensorboard_service.DeleteTensorboardTimeSeriesRequest = None,
          *,
          name: str = None,
          retry: retries.Retry = gapic_v1.method.DEFAULT,
          timeout: float = None,
          metadata: Sequence[Tuple[str, str]] = (),
      ) -> gac_operation.Operation:
          r"""Deletes a TensorboardTimeSeries.
  
          Args:
              request (google.cloud.aiplatform_v1beta1.types.DeleteTensorboardTimeSeriesRequest):
                  The request object. Request message for
                  [TensorboardService.DeleteTensorboardTimeSeries][google.cloud.aiplatform.v1beta1.TensorboardService.DeleteTensorboardTimeSeries].
              name (str):
                  Required. The name of the TensorboardTimeSeries to be
                  deleted. Format:
                  ``projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}/timeSeries/{time_series}``
  
                  This corresponds to the ``name`` field
                  on the ``request`` instance; if ``request`` is provided, this
                  should not be set.
              retry (google.api_core.retry.Retry): Designation of what errors, if any,
                  should be retried.
              timeout (float): The timeout for this request.
              metadata (Sequence[Tuple[str, str]]): Strings which should be
                  sent along with the request as metadata.
  
          Returns:
              google.api_core.operation.Operation:
                  An object representing a long-running operation.
  
                  The result type for the operation will be :class:`google.protobuf.empty_pb2.Empty` A generic empty message that you can re-use to avoid defining duplicated
                     empty messages in your APIs. A typical example is to
                     use it as the request or the response type of an API
                     method. For instance:
  
                        service Foo {
                           rpc Bar(google.protobuf.Empty) returns
                           (google.protobuf.Empty);
  
                        }
  
                     The JSON representation for Empty is empty JSON
                     object {}.
  
          """
          # Create or coerce a protobuf request object.
          # Sanity check: If we got a request object, we should *not* have
          # gotten any keyword arguments that map to the request.
          has_flattened_params = any([name])
          if request is not None and has_flattened_params:
              raise ValueError(
                  "If the `request` argument is set, then none of "
                  "the individual field arguments should be set."
              )
  
          # Minor optimization to avoid making a copy if the user passes
          # in a tensorboard_service.DeleteTensorboardTimeSeriesRequest.
          # There's no risk of modifying the input as we've already verified
          # there are no flattened fields.
          if not isinstance(
              request, tensorboard_service.DeleteTensorboardTimeSeriesRequest
          ):
              request = tensorboard_service.DeleteTensorboardTimeSeriesRequest(request)
              # If we have keyword arguments corresponding to fields on the
              # request, apply these.
              if name is not None:
                  request.name = name
  
          # Wrap the RPC method; this adds retry and timeout information,
          # and friendly error handling.
          rpc = self._transport._wrapped_methods[
              self._transport.delete_tensorboard_time_series
          ]
  
          # Certain fields should be provided within the metadata header;
          # add these here.
          metadata = tuple(metadata) + (
              gapic_v1.routing_header.to_grpc_metadata((("name", request.name),)),
          )
  
          # Send the request.
          response = rpc(request, retry=retry, timeout=timeout, metadata=metadata,)
  
          # Wrap the response in an operation future.
          response = gac_operation.from_gapic(
              response,
              self._transport.operations_client,
              empty_pb2.Empty,
              metadata_type=gca_operation.DeleteOperationMetadata,
          )
  
          # Done; return the response.
          return response
  
      def read_tensorboard_time_series_data(
          self,
          request: tensorboard_service.ReadTensorboardTimeSeriesDataRequest = None,
          *,
          tensorboard_time_series: str = None,
          retry: retries.Retry = gapic_v1.method.DEFAULT,
          timeout: float = None,
          metadata: Sequence[Tuple[str, str]] = (),
      ) -> tensorboard_service.ReadTensorboardTimeSeriesDataResponse:
          r"""Reads a TensorboardTimeSeries' data. Data is returned in
          paginated responses. By default, if the number of data points
          stored is less than 1000, all data will be returned. Otherwise,
          1000 data points will be randomly selected from this time series
          and returned. This value can be changed by changing
          max_data_points.
  
          Args:
              request (google.cloud.aiplatform_v1beta1.types.ReadTensorboardTimeSeriesDataRequest):
                  The request object. Request message for
                  [TensorboardService.ReadTensorboardTimeSeriesData][google.cloud.aiplatform.v1beta1.TensorboardService.ReadTensorboardTimeSeriesData].
              tensorboard_time_series (str):
                  Required. The resource name of the TensorboardTimeSeries
                  to read data from. Format:
                  ``projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}/timeSeries/{time_series}``
  
                  This corresponds to the ``tensorboard_time_series`` field
                  on the ``request`` instance; if ``request`` is provided, this
                  should not be set.
              retry (google.api_core.retry.Retry): Designation of what errors, if any,
                  should be retried.
              timeout (float): The timeout for this request.
              metadata (Sequence[Tuple[str, str]]): Strings which should be
                  sent along with the request as metadata.
  
          Returns:
              google.cloud.aiplatform_v1beta1.types.ReadTensorboardTimeSeriesDataResponse:
                  Response message for
                  [TensorboardService.ReadTensorboardTimeSeriesData][google.cloud.aiplatform.v1beta1.TensorboardService.ReadTensorboardTimeSeriesData].
  
          """
          # Create or coerce a protobuf request object.
          # Sanity check: If we got a request object, we should *not* have
          # gotten any keyword arguments that map to the request.
          has_flattened_params = any([tensorboard_time_series])
          if request is not None and has_flattened_params:
              raise ValueError(
                  "If the `request` argument is set, then none of "
                  "the individual field arguments should be set."
              )
  
          # Minor optimization to avoid making a copy if the user passes
          # in a tensorboard_service.ReadTensorboardTimeSeriesDataRequest.
          # There's no risk of modifying the input as we've already verified
          # there are no flattened fields.
          if not isinstance(
              request, tensorboard_service.ReadTensorboardTimeSeriesDataRequest
          ):
              request = tensorboard_service.ReadTensorboardTimeSeriesDataRequest(request)
              # If we have keyword arguments corresponding to fields on the
              # request, apply these.
              if tensorboard_time_series is not None:
                  request.tensorboard_time_series = tensorboard_time_series
  
          # Wrap the RPC method; this adds retry and timeout information,
          # and friendly error handling.
          rpc = self._transport._wrapped_methods[
              self._transport.read_tensorboard_time_series_data
          ]
  
          # Certain fields should be provided within the metadata header;
          # add these here.
          metadata = tuple(metadata) + (
              gapic_v1.routing_header.to_grpc_metadata(
                  (("tensorboard_time_series", request.tensorboard_time_series),)
              ),
          )
  
          # Send the request.
          response = rpc(request, retry=retry, timeout=timeout, metadata=metadata,)
  
          # Done; return the response.
          return response
  
      def read_tensorboard_blob_data(
          self,
          request: tensorboard_service.ReadTensorboardBlobDataRequest = None,
          *,
          time_series: str = None,
          retry: retries.Retry = gapic_v1.method.DEFAULT,
          timeout: float = None,
          metadata: Sequence[Tuple[str, str]] = (),
      ) -> Iterable[tensorboard_service.ReadTensorboardBlobDataResponse]:
          r"""Gets bytes of TensorboardBlobs.
          This is to allow reading blob data stored in consumer
          project's Cloud Storage bucket without users having to
          obtain Cloud Storage access permission.
  
          Args:
              request (google.cloud.aiplatform_v1beta1.types.ReadTensorboardBlobDataRequest):
                  The request object. Request message for
                  [TensorboardService.ReadTensorboardBlobData][google.cloud.aiplatform.v1beta1.TensorboardService.ReadTensorboardBlobData].
              time_series (str):
                  Required. The resource name of the TensorboardTimeSeries
                  to list Blobs. Format:
                  'projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}/timeSeries/{time_series}'
  
                  This corresponds to the ``time_series`` field
                  on the ``request`` instance; if ``request`` is provided, this
                  should not be set.
              retry (google.api_core.retry.Retry): Designation of what errors, if any,
                  should be retried.
              timeout (float): The timeout for this request.
              metadata (Sequence[Tuple[str, str]]): Strings which should be
                  sent along with the request as metadata.
  
          Returns:
              Iterable[google.cloud.aiplatform_v1beta1.types.ReadTensorboardBlobDataResponse]:
                  Response message for
                  [TensorboardService.ReadTensorboardBlobData][google.cloud.aiplatform.v1beta1.TensorboardService.ReadTensorboardBlobData].
  
          """
          # Create or coerce a protobuf request object.
          # Sanity check: If we got a request object, we should *not* have
          # gotten any keyword arguments that map to the request.
          has_flattened_params = any([time_series])
          if request is not None and has_flattened_params:
              raise ValueError(
                  "If the `request` argument is set, then none of "
                  "the individual field arguments should be set."
              )
  
          # Minor optimization to avoid making a copy if the user passes
          # in a tensorboard_service.ReadTensorboardBlobDataRequest.
          # There's no risk of modifying the input as we've already verified
          # there are no flattened fields.
          if not isinstance(request, tensorboard_service.ReadTensorboardBlobDataRequest):
              request = tensorboard_service.ReadTensorboardBlobDataRequest(request)
              # If we have keyword arguments corresponding to fields on the
              # request, apply these.
              if time_series is not None:
                  request.time_series = time_series
  
          # Wrap the RPC method; this adds retry and timeout information,
          # and friendly error handling.
          rpc = self._transport._wrapped_methods[
              self._transport.read_tensorboard_blob_data
          ]
  
          # Certain fields should be provided within the metadata header;
          # add these here.
          metadata = tuple(metadata) + (
              gapic_v1.routing_header.to_grpc_metadata(
                  (("time_series", request.time_series),)
              ),
          )
  
          # Send the request.
          response = rpc(request, retry=retry, timeout=timeout, metadata=metadata,)
  
          # Done; return the response.
          return response
  
      def write_tensorboard_experiment_data(
          self,
          request: tensorboard_service.WriteTensorboardExperimentDataRequest = None,
          *,
          tensorboard_experiment: str = None,
          write_run_data_requests: Sequence[
              tensorboard_service.WriteTensorboardRunDataRequest
          ] = None,
          retry: retries.Retry = gapic_v1.method.DEFAULT,
          timeout: float = None,
          metadata: Sequence[Tuple[str, str]] = (),
      ) -> tensorboard_service.WriteTensorboardExperimentDataResponse:
          r"""Write time series data points of multiple
          TensorboardTimeSeries in multiple TensorboardRun's. If
          any data fail to be ingested, an error will be returned.
  
          Args:
              request (google.cloud.aiplatform_v1beta1.types.WriteTensorboardExperimentDataRequest):
                  The request object. Request message for
                  [TensorboardService.WriteTensorboardExperimentData][google.cloud.aiplatform.v1beta1.TensorboardService.WriteTensorboardExperimentData].
              tensorboard_experiment (str):
                  Required. The resource name of the TensorboardExperiment
                  to write data to. Format:
                  ``projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}``
  
                  This corresponds to the ``tensorboard_experiment`` field
                  on the ``request`` instance; if ``request`` is provided, this
                  should not be set.
              write_run_data_requests (Sequence[google.cloud.aiplatform_v1beta1.types.WriteTensorboardRunDataRequest]):
                  Required. Requests containing per-run
                  TensorboardTimeSeries data to write.
  
                  This corresponds to the ``write_run_data_requests`` field
                  on the ``request`` instance; if ``request`` is provided, this
                  should not be set.
              retry (google.api_core.retry.Retry): Designation of what errors, if any,
                  should be retried.
              timeout (float): The timeout for this request.
              metadata (Sequence[Tuple[str, str]]): Strings which should be
                  sent along with the request as metadata.
  
          Returns:
              google.cloud.aiplatform_v1beta1.types.WriteTensorboardExperimentDataResponse:
                  Response message for
                  [TensorboardService.WriteTensorboardExperimentData][google.cloud.aiplatform.v1beta1.TensorboardService.WriteTensorboardExperimentData].
  
          """
          # Create or coerce a protobuf request object.
          # Sanity check: If we got a request object, we should *not* have
          # gotten any keyword arguments that map to the request.
          has_flattened_params = any([tensorboard_experiment, write_run_data_requests])
          if request is not None and has_flattened_params:
              raise ValueError(
                  "If the `request` argument is set, then none of "
                  "the individual field arguments should be set."
              )
  
          # Minor optimization to avoid making a copy if the user passes
          # in a tensorboard_service.WriteTensorboardExperimentDataRequest.
          # There's no risk of modifying the input as we've already verified
          # there are no flattened fields.
          if not isinstance(
              request, tensorboard_service.WriteTensorboardExperimentDataRequest
          ):
              request = tensorboard_service.WriteTensorboardExperimentDataRequest(request)
              # If we have keyword arguments corresponding to fields on the
              # request, apply these.
              if tensorboard_experiment is not None:
                  request.tensorboard_experiment = tensorboard_experiment
              if write_run_data_requests is not None:
                  request.write_run_data_requests = write_run_data_requests
  
          # Wrap the RPC method; this adds retry and timeout information,
          # and friendly error handling.
          rpc = self._transport._wrapped_methods[
              self._transport.write_tensorboard_experiment_data
          ]
  
          # Certain fields should be provided within the metadata header;
          # add these here.
          metadata = tuple(metadata) + (
              gapic_v1.routing_header.to_grpc_metadata(
                  (("tensorboard_experiment", request.tensorboard_experiment),)
              ),
          )
  
          # Send the request.
          response = rpc(request, retry=retry, timeout=timeout, metadata=metadata,)
  
          # Done; return the response.
          return response
  
      def write_tensorboard_run_data(
          self,
          request: tensorboard_service.WriteTensorboardRunDataRequest = None,
          *,
          tensorboard_run: str = None,
          time_series_data: Sequence[tensorboard_data.TimeSeriesData] = None,
          retry: retries.Retry = gapic_v1.method.DEFAULT,
          timeout: float = None,
          metadata: Sequence[Tuple[str, str]] = (),
      ) -> tensorboard_service.WriteTensorboardRunDataResponse:
          r"""Write time series data points into multiple
          TensorboardTimeSeries under a TensorboardRun. If any
          data fail to be ingested, an error will be returned.
  
          Args:
              request (google.cloud.aiplatform_v1beta1.types.WriteTensorboardRunDataRequest):
                  The request object. Request message for
                  [TensorboardService.WriteTensorboardRunData][google.cloud.aiplatform.v1beta1.TensorboardService.WriteTensorboardRunData].
              tensorboard_run (str):
                  Required. The resource name of the TensorboardRun to
                  write data to. Format:
                  ``projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}``
  
                  This corresponds to the ``tensorboard_run`` field
                  on the ``request`` instance; if ``request`` is provided, this
                  should not be set.
              time_series_data (Sequence[google.cloud.aiplatform_v1beta1.types.TimeSeriesData]):
                  Required. The TensorboardTimeSeries
                  data to write. Values with in a time
                  series are indexed by their step value.
                  Repeated writes to the same step will
                  overwrite the existing value for that
                  step.
                  The upper limit of data points per write
                  request is 5000.
  
                  This corresponds to the ``time_series_data`` field
                  on the ``request`` instance; if ``request`` is provided, this
                  should not be set.
              retry (google.api_core.retry.Retry): Designation of what errors, if any,
                  should be retried.
              timeout (float): The timeout for this request.
              metadata (Sequence[Tuple[str, str]]): Strings which should be
                  sent along with the request as metadata.
  
          Returns:
              google.cloud.aiplatform_v1beta1.types.WriteTensorboardRunDataResponse:
                  Response message for
                  [TensorboardService.WriteTensorboardRunData][google.cloud.aiplatform.v1beta1.TensorboardService.WriteTensorboardRunData].
  
          """
          # Create or coerce a protobuf request object.
          # Sanity check: If we got a request object, we should *not* have
          # gotten any keyword arguments that map to the request.
          has_flattened_params = any([tensorboard_run, time_series_data])
          if request is not None and has_flattened_params:
              raise ValueError(
                  "If the `request` argument is set, then none of "
                  "the individual field arguments should be set."
              )
  
          # Minor optimization to avoid making a copy if the user passes
          # in a tensorboard_service.WriteTensorboardRunDataRequest.
          # There's no risk of modifying the input as we've already verified
          # there are no flattened fields.
          if not isinstance(request, tensorboard_service.WriteTensorboardRunDataRequest):
              request = tensorboard_service.WriteTensorboardRunDataRequest(request)
              # If we have keyword arguments corresponding to fields on the
              # request, apply these.
              if tensorboard_run is not None:
                  request.tensorboard_run = tensorboard_run
              if time_series_data is not None:
                  request.time_series_data = time_series_data
  
          # Wrap the RPC method; this adds retry and timeout information,
          # and friendly error handling.
          rpc = self._transport._wrapped_methods[
              self._transport.write_tensorboard_run_data
          ]
  
          # Certain fields should be provided within the metadata header;
          # add these here.
          metadata = tuple(metadata) + (
              gapic_v1.routing_header.to_grpc_metadata(
                  (("tensorboard_run", request.tensorboard_run),)
              ),
          )
  
          # Send the request.
          response = rpc(request, retry=retry, timeout=timeout, metadata=metadata,)
  
          # Done; return the response.
          return response
  
      def export_tensorboard_time_series_data(
          self,
          request: tensorboard_service.ExportTensorboardTimeSeriesDataRequest = None,
          *,
          tensorboard_time_series: str = None,
          retry: retries.Retry = gapic_v1.method.DEFAULT,
          timeout: float = None,
          metadata: Sequence[Tuple[str, str]] = (),
      ) -> pagers.ExportTensorboardTimeSeriesDataPager:
          r"""Exports a TensorboardTimeSeries' data. Data is
          returned in paginated responses.
  
          Args:
              request (google.cloud.aiplatform_v1beta1.types.ExportTensorboardTimeSeriesDataRequest):
                  The request object. Request message for
                  [TensorboardService.ExportTensorboardTimeSeriesData][google.cloud.aiplatform.v1beta1.TensorboardService.ExportTensorboardTimeSeriesData].
              tensorboard_time_series (str):
                  Required. The resource name of the TensorboardTimeSeries
                  to export data from. Format:
                  ``projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}/timeSeries/{time_series}``
  
                  This corresponds to the ``tensorboard_time_series`` field
                  on the ``request`` instance; if ``request`` is provided, this
                  should not be set.
              retry (google.api_core.retry.Retry): Designation of what errors, if any,
                  should be retried.
              timeout (float): The timeout for this request.
              metadata (Sequence[Tuple[str, str]]): Strings which should be
                  sent along with the request as metadata.
  
          Returns:
              google.cloud.aiplatform_v1beta1.services.tensorboard_service.pagers.ExportTensorboardTimeSeriesDataPager:
                  Response message for
                  [TensorboardService.ExportTensorboardTimeSeriesData][google.cloud.aiplatform.v1beta1.TensorboardService.ExportTensorboardTimeSeriesData].
  
                  Iterating over this object will yield results and
                  resolve additional pages automatically.
  
          """
          # Create or coerce a protobuf request object.
          # Sanity check: If we got a request object, we should *not* have
          # gotten any keyword arguments that map to the request.
          has_flattened_params = any([tensorboard_time_series])
          if request is not None and has_flattened_params:
              raise ValueError(
                  "If the `request` argument is set, then none of "
                  "the individual field arguments should be set."
              )
  
          # Minor optimization to avoid making a copy if the user passes
          # in a tensorboard_service.ExportTensorboardTimeSeriesDataRequest.
          # There's no risk of modifying the input as we've already verified
          # there are no flattened fields.
          if not isinstance(
              request, tensorboard_service.ExportTensorboardTimeSeriesDataRequest
          ):
              request = tensorboard_service.ExportTensorboardTimeSeriesDataRequest(
                  request
              )
              # If we have keyword arguments corresponding to fields on the
              # request, apply these.
              if tensorboard_time_series is not None:
                  request.tensorboard_time_series = tensorboard_time_series
  
          # Wrap the RPC method; this adds retry and timeout information,
          # and friendly error handling.
          rpc = self._transport._wrapped_methods[
              self._transport.export_tensorboard_time_series_data
          ]
  
          # Certain fields should be provided within the metadata header;
          # add these here.
          metadata = tuple(metadata) + (
              gapic_v1.routing_header.to_grpc_metadata(
                  (("tensorboard_time_series", request.tensorboard_time_series),)
              ),
          )
  
          # Send the request.
          response = rpc(request, retry=retry, timeout=timeout, metadata=metadata,)
  
          # This method is paged; wrap the response in a pager, which provides
          # an `__iter__` convenience method.
          response = pagers.ExportTensorboardTimeSeriesDataPager(
              method=rpc, request=request, response=response, metadata=metadata,
          )
  
          # Done; return the response.
          return response
  
  
  try:
      DEFAULT_CLIENT_INFO = gapic_v1.client_info.ClientInfo(
          gapic_version=pkg_resources.get_distribution(
              "google-cloud-aiplatform",
          ).version,
      )
  except pkg_resources.DistributionNotFound:
      DEFAULT_CLIENT_INFO = gapic_v1.client_info.ClientInfo()
  
  
  __all__ = ("TensorboardServiceClient",)
  