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  """This module contains a Google Text to Speech operator."""
  
  from tempfile import NamedTemporaryFile
  from typing import TYPE_CHECKING, Dict, Optional, Sequence, Union
  
  from google.api_core.retry import Retry
  from google.cloud.texttospeech_v1.types import AudioConfig, SynthesisInput, VoiceSelectionParams
  
  from airflow.exceptions import AirflowException
  from airflow.models import BaseOperator
  from airflow.providers.google.cloud.hooks.gcs import GCSHook
  from airflow.providers.google.cloud.hooks.text_to_speech import CloudTextToSpeechHook
  
  if TYPE_CHECKING:
      from airflow.utils.context import Context
  
  
  class CloudTextToSpeechSynthesizeOperator(BaseOperator):
      """
      Synthesizes text to speech and stores it in Google Cloud Storage
  
      .. seealso::
          For more information on how to use this operator, take a look at the guide:
          :ref:`howto/operator:CloudTextToSpeechSynthesizeOperator`
  
      :param input_data: text input to be synthesized. See more:
          https://googleapis.github.io/google-cloud-python/latest/texttospeech/gapic/v1/types.html#google.cloud.texttospeech_v1.types.SynthesisInput
      :type input_data: dict or google.cloud.texttospeech_v1.types.SynthesisInput
      :param voice: configuration of voice to be used in synthesis. See more:
          https://googleapis.github.io/google-cloud-python/latest/texttospeech/gapic/v1/types.html#google.cloud.texttospeech_v1.types.VoiceSelectionParams
      :type voice: dict or google.cloud.texttospeech_v1.types.VoiceSelectionParams
      :param audio_config: configuration of the synthesized audio. See more:
          https://googleapis.github.io/google-cloud-python/latest/texttospeech/gapic/v1/types.html#google.cloud.texttospeech_v1.types.AudioConfig
      :type audio_config: dict or google.cloud.texttospeech_v1.types.AudioConfig
      :param target_bucket_name: name of the GCS bucket in which output file should be stored
      :type target_bucket_name: str
      :param target_filename: filename of the output file.
      :type target_filename: str
      :param project_id: Optional, Google Cloud Project ID where the Compute
          Engine Instance exists. If set to None or missing, the default project_id from the Google Cloud
          connection is used.
      :type project_id: str
      :param gcp_conn_id: Optional, The connection ID used to connect to Google Cloud.
          Defaults to 'google_cloud_default'.
      :type gcp_conn_id: str
      :param retry: (Optional) A retry object used to retry requests. If None is specified,
              requests will not be retried.
      :type retry: google.api_core.retry.Retry
      :param timeout: (Optional) The amount of time, in seconds, to wait for the request to complete.
          Note that if retry is specified, the timeout applies to each individual attempt.
      :type timeout: float
      :param impersonation_chain: Optional service account to impersonate using short-term
          credentials, or chained list of accounts required to get the access_token
          of the last account in the list, which will be impersonated in the request.
          If set as a string, the account must grant the originating account
          the Service Account Token Creator IAM role.
          If set as a sequence, the identities from the list must grant
          Service Account Token Creator IAM role to the directly preceding identity, with first
          account from the list granting this role to the originating account (templated).
      :type impersonation_chain: Union[str, Sequence[str]]
      """
  
      # [START gcp_text_to_speech_synthesize_template_fields]
      template_fields = (
          "input_data",
          "voice",
          "audio_config",
          "project_id",
          "gcp_conn_id",
          "target_bucket_name",
          "target_filename",
          "impersonation_chain",
      )
      # [END gcp_text_to_speech_synthesize_template_fields]
  
      def __init__(
          self,
          *,
          input_data: Union[Dict, SynthesisInput],
          voice: Union[Dict, VoiceSelectionParams],
          audio_config: Union[Dict, AudioConfig],
          target_bucket_name: str,
          target_filename: str,
          project_id: Optional[str] = None,
          gcp_conn_id: str = "google_cloud_default",
          retry: Optional[Retry] = None,
          timeout: Optional[float] = None,
          impersonation_chain: Optional[Union[str, Sequence[str]]] = None,
          **kwargs,
      ) -> None:
          self.input_data = input_data
          self.voice = voice
          self.audio_config = audio_config
          self.target_bucket_name = target_bucket_name
          self.target_filename = target_filename
          self.project_id = project_id
          self.gcp_conn_id = gcp_conn_id
          self.retry = retry
          self.timeout = timeout
          self._validate_inputs()
          self.impersonation_chain = impersonation_chain
          super().__init__(**kwargs)
  
      def _validate_inputs(self) -> None:
          for parameter in [
              "input_data",
              "voice",
              "audio_config",
              "target_bucket_name",
              "target_filename",
          ]:
              if getattr(self, parameter) == "":
                  raise AirflowException(f"The required parameter '{parameter}' is empty")
  
      def execute(self, context: 'Context') -> None:
          hook = CloudTextToSpeechHook(
              gcp_conn_id=self.gcp_conn_id,
              impersonation_chain=self.impersonation_chain,
          )
          result = hook.synthesize_speech(
              input_data=self.input_data,
              voice=self.voice,
              audio_config=self.audio_config,
              retry=self.retry,
              timeout=self.timeout,
          )
          with NamedTemporaryFile() as temp_file:
              temp_file.write(result.audio_content)
              cloud_storage_hook = GCSHook(
                  gcp_conn_id=self.gcp_conn_id,
                  impersonation_chain=self.impersonation_chain,
              )
              cloud_storage_hook.upload(
                  bucket_name=self.target_bucket_name, object_name=self.target_filename, filename=temp_file.name
              )
  