

"""simple docstring"""




from typing import List, Optional

import numpy as np

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





class  lowerCamelCase    (SCREAMING_SNAKE_CASE__      ):
			lowerCamelCase__ :		int       		=				'EncodecFeatureExtractor'
			lowerCamelCase__ :		str       		=				('T5Tokenizer', 'T5TokenizerFast')

			def __init__(       self					:    List[Any]     ,					__UpperCAmelCase					:    List[Any]     ,					__UpperCAmelCase					:    Union[str, Any]							) ->     Tuple:
						super().__init__(A_     ,					A_							)
						SCREAMING_SNAKE_CASE__										=   self.feature_extractor
						SCREAMING_SNAKE_CASE__										=   False

			def        SCREAMING_SNAKE_CASE					(       self					:    Tuple     ,					__UpperCAmelCase					:    Dict=None     ,					__UpperCAmelCase					:    Dict=None     ,					__UpperCAmelCase					:    List[Any]=True							) ->     List[Any]:
						return self.tokenizer.get_decoder_prompt_ids(task=A_     ,					language=A_     ,					no_timestamps=A_							)

			def __call__(       self					:    List[Any]     ,					*__UpperCAmelCase					:    List[Any]     ,					**__UpperCAmelCase					:    Tuple							) ->     Optional[Any]:




						if self._in_target_context_manager:
									return self.current_processor(*A_     ,					**A_							)

						SCREAMING_SNAKE_CASE__										=   kwargs.pop("""audio"""     ,					A_							)
						SCREAMING_SNAKE_CASE__										=   kwargs.pop("""sampling_rate"""     ,					A_							)
						SCREAMING_SNAKE_CASE__										=   kwargs.pop("""text"""     ,					A_							)
						if len(A_							) > 0:
									SCREAMING_SNAKE_CASE__										=   args[0]
									SCREAMING_SNAKE_CASE__										=   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:
									SCREAMING_SNAKE_CASE__										=   self.tokenizer(A_     ,					**A_							)

						if audio is not None:
									SCREAMING_SNAKE_CASE__										=   self.feature_extractor(A_     ,					*A_     ,					sampling_rate=A_     ,					**A_							)

						if audio is None:
									return inputs

						elif text is None:
									return audio_inputs

						else:
									SCREAMING_SNAKE_CASE__										=   audio_inputs['''input_values''']
									if "padding_mask" in audio_inputs:
												SCREAMING_SNAKE_CASE__										=   audio_inputs['''padding_mask''']
									return inputs

			def        SCREAMING_SNAKE_CASE					(       self					:    Optional[Any]     ,					*__UpperCAmelCase					:    Dict     ,					**__UpperCAmelCase					:    Tuple							) ->     Union[str, Any]:
						SCREAMING_SNAKE_CASE__										=   kwargs.pop("""audio"""     ,					A_							)
						SCREAMING_SNAKE_CASE__										=   kwargs.pop("""padding_mask"""     ,					A_							)

						if len(A_							) > 0:
									SCREAMING_SNAKE_CASE__										=   args[0]
									SCREAMING_SNAKE_CASE__										=   args[1:]

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

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





			def        SCREAMING_SNAKE_CASE					(       self					:    List[str]     ,					__UpperCAmelCase					:    int     ,					__UpperCAmelCase					:    Optional[int] = None							) ->     List[np.ndarray]:
						SCREAMING_SNAKE_CASE__										=   to_numpy(A_							)
						SCREAMING_SNAKE_CASE__										=   audio_values.shape

						if padding_mask is None:
									return list(A_							)

						SCREAMING_SNAKE_CASE__										=   to_numpy(A_							)

						# 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)
						SCREAMING_SNAKE_CASE__										=   seq_len - padding_mask.shape[-1]
						SCREAMING_SNAKE_CASE__										=   1 - self.feature_extractor.padding_value
						SCREAMING_SNAKE_CASE__										=   np.pad(A_     ,					((0, 0), (0, difference))     ,					"""constant"""     ,					constant_values=A_							)

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

						return audio_values




"""simple docstring"""




import math
import sys




def 			_lowerCAmelCase		(		_UpperCamelCase    ):






  """simple docstring"""



  _lowercase:      Any   			=  ''''''
  try:
    with open(_UpperCamelCase			,					'''rb'''    ) as binary_file:
      _lowercase:      Dict   			=  binary_file.read()
    for dat in data:
      _lowercase:      List[str]   			=  f'''{dat:08b}'''
      result += curr_byte
    return result
  except OSError:
    print('''File not accessible'''    )
    sys.exit()




def 			_lowerCAmelCase		(		_UpperCamelCase    ):






  """simple docstring"""



  _lowercase:      Any   			=  {'''0''': '''0''', '''1''': '''1'''}
  _lowercase			,					_lowercase:      Optional[int]   			=  '''''', ''''''
  _lowercase:      Dict   			=  len(_UpperCamelCase    )

  for i in range(len(_UpperCamelCase    )    ):
    curr_string += data_bits[i]
    if curr_string not in lexicon:
      continue

    _lowercase:      Any   			=  lexicon[curr_string]
    result += last_match_id
    _lowercase:      Optional[int]   			=  last_match_id + '''0'''

    if math.loga(_UpperCamelCase    ).is_integer():
      _lowercase:      str   			=  {}
      for curr_key in list(_UpperCamelCase    ):
        _lowercase:      List[Any]   			=  lexicon.pop(_UpperCamelCase    )
      _lowercase:      Tuple   			=  new_lex

    _lowercase:      List[Any]   			=  last_match_id + '''1'''
    index += 1
    _lowercase:      List[Any]   			=  ''''''
  return result




def 			_lowerCAmelCase		(		_UpperCamelCase			,					_UpperCamelCase    ):






  """simple docstring"""



  _lowercase:      Optional[Any]   			=  8
  try:
    with open(_UpperCamelCase			,					'''wb'''    ) as opened_file:
      _lowercase:      List[Any]   			=  [
          to_write[i : i + byte_length]
          for i in range(0			,					len(_UpperCamelCase    )			,					_UpperCamelCase    )
      ]

      if len(result_byte_array[-1]    ) % byte_length == 0:
        result_byte_array.append('''10000000'''    )
      else:
        result_byte_array[-1] += "1" + "0" * (
            byte_length - len(result_byte_array[-1]    ) - 1
        )

      for elem in result_byte_array[:-1]:
        opened_file.write(int(_UpperCamelCase			,					2    ).to_bytes(1			,					byteorder='''big'''    )    )
  except OSError:
    print('''File not accessible'''    )
    sys.exit()




def 			_lowerCAmelCase		(		_UpperCamelCase    ):






  """simple docstring"""



  _lowercase:      Any   			=  0
  for letter in data_bits:
    if letter == "1":
      break
    counter += 1

  _lowercase:      List[str]   			=  data_bits[counter:]
  _lowercase:      Union[str, Any]   			=  data_bits[counter + 1 :]
  return data_bits




def 			_lowerCAmelCase		(		_UpperCamelCase			,					_UpperCamelCase    ):






  """simple docstring"""



  _lowercase:      Tuple   			=  read_file_binary(_UpperCamelCase    )
  _lowercase:      Optional[Any]   			=  remove_prefix(_UpperCamelCase    )
  _lowercase:      Dict   			=  decompress_data(_UpperCamelCase    )
  write_file_binary(_UpperCamelCase			,					_UpperCamelCase    )


if __name__ == "__main__":
  compress(sys.argv[1], sys.argv[2])
