


'''simple docstring'''



from typing import List, Optional

import numpy as np

from ...processing_utils import ProcessorMixin
from ...utils import to_numpy



class      a    (		_a	):


     """simple docstring"""






     SCREAMING_SNAKE_CASE	:			Tuple							       =       "EncodecFeatureExtractor"
     SCREAMING_SNAKE_CASE	:			Dict							       =       ("T5Tokenizer", "T5TokenizerFast")

     def __init__(    self					:		Union[str, Any]							,			snake_case					:		List[Any]							,			snake_case					:		Optional[int]      )						->							Union[str, Any]:
          super().__init__(snake_case							,			snake_case      )
          __UpperCAmelCase     :			List[Any]  							=      self.feature_extractor
          __UpperCAmelCase     :			Optional[int]  							=      False

     def 			lowerCamelCase__			(    self					:		int							,			snake_case					:		Optional[Any]=None							,			snake_case					:		Optional[Any]=None							,			snake_case					:		int=True      )						->							Dict:
          return self.tokenizer.get_decoder_prompt_ids(task=snake_case							,			language=snake_case							,			no_timestamps=snake_case      )

     def __call__(    self					:		str							,			*snake_case					:		Dict							,			**snake_case					:		Tuple      )						->							int:
          # For backward compatibility
          if self._in_target_context_manager:
               return self.current_processor(*snake_case							,			**snake_case      )

          __UpperCAmelCase     :			Optional[Any]  							=      kwargs.pop('''audio'''							,			snake_case      )
          __UpperCAmelCase     :			List[str]  							=      kwargs.pop('''sampling_rate'''							,			snake_case      )
          __UpperCAmelCase     :			List[str]  							=      kwargs.pop('''text'''							,			snake_case      )
          if len(snake_case      ) > 0:
               __UpperCAmelCase     :			int  							=      args[0]
               __UpperCAmelCase     :			Optional[Any]  							=      args[1:]

          if audio is None and text is None:
               raise ValueError('''You need to specify either an `audio` or `text` input to process.'''      )

          if text is not None:
               __UpperCAmelCase     :			Any  							=      self.tokenizer(snake_case							,			**snake_case      )

          if audio is not None:
               __UpperCAmelCase     :			List[str]  							=      self.feature_extractor(snake_case							,			*snake_case							,			sampling_rate=snake_case							,			**snake_case      )

          if audio is None:
               return inputs

          elif text is None:
               return audio_inputs

          else:
               __UpperCAmelCase     :			List[str]  							=      audio_inputs['''input_values''']
               if "padding_mask" in audio_inputs:
                    __UpperCAmelCase     :			List[Any]  							=      audio_inputs['''padding_mask''']
               return inputs

     def 			lowerCamelCase__			(    self					:		Tuple							,			*snake_case					:		int							,			**snake_case					:		Tuple      )						->							List[str]:
          __UpperCAmelCase     :			str  							=      kwargs.pop('''audio'''							,			snake_case      )
          __UpperCAmelCase     :			int  							=      kwargs.pop('''padding_mask'''							,			snake_case      )

          if len(snake_case      ) > 0:
               __UpperCAmelCase     :			Dict  							=      args[0]
               __UpperCAmelCase     :			Optional[int]  							=      args[1:]

          if audio_values is not None:
               return self._decode_audio(snake_case							,			padding_mask=snake_case      )
          else:
               return self.tokenizer.batch_decode(*snake_case							,			**snake_case      )

     def 			lowerCamelCase__			(    self					:		Union[str, Any]							,			*snake_case					:		int							,			**snake_case					:		Union[str, Any]      )						->							Tuple:
          return self.tokenizer.decode(*snake_case							,			**snake_case      )






     def 			lowerCamelCase__			(    self					:		List[Any]							,			snake_case					:		Optional[Any]							,			snake_case					:		Optional = None      )						->							List[np.ndarray]:
          __UpperCAmelCase     :			Optional[int]  							=      to_numpy(snake_case      )
          __UpperCAmelCase     :			Dict  							=      audio_values.shape

          if padding_mask is None:
               return list(snake_case      )

          __UpperCAmelCase     :			Optional[Any]  							=      to_numpy(snake_case      )

          # match the sequence length of the padding mask to the generated audio arrays by padding with the **non-padding**
          # token (so that the generated audio values are **not** treated as padded tokens)
          __UpperCAmelCase     :			List[Any]  							=      seq_len - padding_mask.shape[-1]
          __UpperCAmelCase     :			Dict  							=      1 - self.feature_extractor.padding_value
          __UpperCAmelCase     :			str  							=      np.pad(snake_case							,			((0, 0), (0, difference))							,			'''constant'''							,			constant_values=snake_case      )

          __UpperCAmelCase     :			Any  							=      audio_values.tolist()
          for i in range(snake_case      ):
               __UpperCAmelCase     :			str  							=      np.asarray(audio_values[i]      )[
                   padding_mask[i][None, :] != self.feature_extractor.padding_value
               ]
               __UpperCAmelCase     :			str  							=      sliced_audio.reshape(snake_case							,			-1      )

          return audio_values



'''simple docstring'''



from argparse import ArgumentParser

from .env import EnvironmentCommand




def      _a     (						):





     '''simple docstring'''






     __UpperCAmelCase     :			Optional[Any]  							=      ArgumentParser('''Diffusers CLI tool'''      , usage='''diffusers-cli <command> [<args>]'''  )
     __UpperCAmelCase     :			Union[str, Any]  							=      parser.add_subparsers(help='''diffusers-cli command helpers'''  )

     # Register commands
     EnvironmentCommand.register_subcommand(_lowercase  )

     # Let's go
     __UpperCAmelCase     :			Union[str, Any]  							=      parser.parse_args()

     if not hasattr(_lowercase      , '''func'''  ):
          parser.print_help()
          exit(1  )

     # Run
     __UpperCAmelCase     :			Any  							=      args.func(_lowercase  )
     service.run()


if __name__ == "__main__":
      main()