
'''simple docstring'''
#
# Sort large text files in a minimum amount of memory
#
import argparse
import os






class      snake_case__    :







		"""simple docstring"""

		lowerCamelCase							=		"""block_{0}.dat"""



		def __init__(	self							:       List[str]   ,     UpperCamelCase__							:       str	)		->       Union[str, Any]:






				"""simple docstring"""







				snake_case   :    Optional[int]			       =		filename
				snake_case   :    Any			       =		[]



		def 	lowerCAmelCase							(	self							:       Any   ,     UpperCamelCase__							:       int   ,     UpperCamelCase__							:       str	)		->       Dict:






				"""simple docstring"""







				snake_case   :    str			       =		self.BLOCK_FILENAME_FORMAT.format(UpperCamelCase__	)
				with open(UpperCamelCase__   ,     '''w'''	) as file:
						file.write(UpperCamelCase__	)
				self.block_filenames.append(UpperCamelCase__	)



		def 	lowerCAmelCase							(	self							:       Optional[Any]	)		->       Optional[int]:






				"""simple docstring"""







				return self.block_filenames



		def 	lowerCAmelCase							(	self							:       Optional[int]   ,     UpperCamelCase__							:       Union[str, Any]   ,     UpperCamelCase__							:       Optional[Any]=None	)		->       Dict:






				"""simple docstring"""







				snake_case   :    Optional[Any]			       =		0
				with open(self.filename	) as file:
						while True:
								snake_case   :    List[str]			       =		file.readlines(UpperCamelCase__	)

								if lines == []:
										break

								if sort_key is None:
										lines.sort()
								else:
										lines.sort(key=UpperCamelCase__	)

								self.write_block(''''''.join(UpperCamelCase__	)   ,     UpperCamelCase__	)
								i += 1



		def 	lowerCAmelCase							(	self							:       Dict	)		->       Optional[Any]:






				"""simple docstring"""







				map(os.remove   ,     self.block_filenames	)







class      snake_case__    :







		"""simple docstring"""

		def 	lowerCAmelCase							(	self							:       str   ,     UpperCamelCase__							:       Optional[int]	)		->       Dict:






				"""simple docstring"""







				snake_case   :    str			       =		-1
				snake_case   :    Optional[Any]			       =		None

				for i in range(len(UpperCamelCase__	)	):
						if min_str is None or choices[i] < min_str:
								snake_case   :    Union[str, Any]			       =		i

				return min_index







class      snake_case__    :







		"""simple docstring"""

		def __init__(	self							:       str   ,     UpperCamelCase__							:       Tuple	)		->       Dict:






				"""simple docstring"""







				snake_case   :    Dict			       =		files
				snake_case   :    Optional[Any]			       =		set()
				snake_case   :    Tuple			       =		len(UpperCamelCase__	)
				snake_case   :    List[Any]			       =		{i: None for i in range(self.num_buffers	)}



		def 	lowerCAmelCase							(	self							:       Tuple	)		->       int:






				"""simple docstring"""







				return {
				    i: self.buffers[i] for i in range(self.num_buffers	) if i not in self.empty
				}



		def 	lowerCAmelCase							(	self							:       List[str]	)		->       int:






				"""simple docstring"""







				for i in range(self.num_buffers	):
						if self.buffers[i] is None and i not in self.empty:
								snake_case   :    Optional[Any]			       =		self.files[i].readline()

								if self.buffers[i] == "":
										self.empty.add(UpperCamelCase__	)
										self.files[i].close()

				if len(self.empty	) == self.num_buffers:
						return False

				return True



		def 	lowerCAmelCase							(	self							:       Optional[Any]   ,     UpperCamelCase__							:       Any	)		->       str:






				"""simple docstring"""







				snake_case   :    List[Any]			       =		self.buffers[index]
				snake_case   :    Optional[int]			       =		None

				return value







class      snake_case__    :







		"""simple docstring"""

		def __init__(	self							:       List[Any]   ,     UpperCamelCase__							:       Optional[Any]	)		->       Optional[Any]:






				"""simple docstring"""







				snake_case   :    Optional[int]			       =		merge_strategy



		def 	lowerCAmelCase							(	self							:       str   ,     UpperCamelCase__							:       Optional[int]   ,     UpperCamelCase__							:       int   ,     UpperCamelCase__							:       Dict	)		->       Tuple:






				"""simple docstring"""







				snake_case   :    List[Any]			       =		FilesArray(self.get_file_handles(UpperCamelCase__   ,     UpperCamelCase__	)	)
				with open(UpperCamelCase__   ,     '''w'''   ,     UpperCamelCase__	) as outfile:
						while buffers.refresh():
								snake_case   :    List[Any]			       =		self.merge_strategy.select(buffers.get_dict()	)
								outfile.write(buffers.unshift(UpperCamelCase__	)	)



		def 	lowerCAmelCase							(	self							:       List[str]   ,     UpperCamelCase__							:       Tuple   ,     UpperCamelCase__							:       str	)		->       int:






				"""simple docstring"""







				snake_case   :    str			       =		{}

				for i in range(len(UpperCamelCase__	)	):
						snake_case   :    Any			       =		open(filenames[i]   ,     '''r'''   ,     UpperCamelCase__	)  # noqa: UP015

				return files







class      snake_case__    :







		"""simple docstring"""

		def __init__(	self							:       Any   ,     UpperCamelCase__							:       Any	)		->       Optional[Any]:






				"""simple docstring"""







				snake_case   :    Optional[Any]			       =		block_size



		def 	lowerCAmelCase							(	self							:       Dict   ,     UpperCamelCase__							:       int   ,     UpperCamelCase__							:       Tuple=None	)		->       Optional[Any]:






				"""simple docstring"""







				snake_case   :    List[str]			       =		self.get_number_blocks(UpperCamelCase__   ,     self.block_size	)
				snake_case   :    Optional[Any]			       =		FileSplitter(UpperCamelCase__	)
				splitter.split(self.block_size   ,     UpperCamelCase__	)

				snake_case   :    Optional[Any]			       =		FileMerger(NWayMerge()	)
				snake_case   :    Any			       =		self.block_size / (num_blocks + 1)
				merger.merge(splitter.get_block_filenames()   ,     filename + '''.out'''   ,     UpperCamelCase__	)

				splitter.cleanup()



		def 	lowerCAmelCase							(	self							:       Optional[Any]   ,     UpperCamelCase__							:       List[str]   ,     UpperCamelCase__							:       Dict	)		->       List[Any]:






				"""simple docstring"""







				return (os.stat(UpperCamelCase__	).st_size / block_size) + 1







def 					_UpperCamelCase		(    SCREAMING_SNAKE_CASE__       )   ->				List[Any]:


		'''simple docstring'''


		if string[-1].lower() == "k":
				return int(string[:-1]       ) * 1024
		elif string[-1].lower() == "m":
				return int(string[:-1]       ) * 1024 * 1024
		elif string[-1].lower() == "g":
				return int(string[:-1]       ) * 1024 * 1024 * 1024
		else:
				return int(SCREAMING_SNAKE_CASE__       )




def 					_UpperCamelCase		(    )   ->				Optional[int]:


		'''simple docstring'''


		snake_case   :    Tuple			       =		argparse.ArgumentParser()
		parser.add_argument(
		    '''-m'''      ,    '''--mem'''      ,    help='''amount of memory to use for sorting'''      ,    default='''100M'''       )
		parser.add_argument(
		    '''filename'''      ,    metavar='''<filename>'''      ,    nargs=1      ,    help='''name of file to sort'''       )
		snake_case   :    Any			       =		parser.parse_args()

		snake_case   :    int			       =		ExternalSort(parse_memory(args.mem       )       )
		sorter.sort(args.filename[0]       )


if __name__ == "__main__":
						main()









"""simple docstring"""
import warnings
from contextlib import contextmanager

from ...processing_utils import ProcessorMixin







class 	a				(					a__   ):
 snake_case__    	=    '''AutoFeatureExtractor'''
 snake_case__    	=    '''Speech2Text2Tokenizer'''



 def __init__(			self							,    _snake_case							,    _snake_case			):







  """simple docstring"""






  super().__init__(_snake_case							,    _snake_case			)
  lowerCAmelCase  							=      self.feature_extractor
  lowerCAmelCase  							=      False



 def __call__(			self							,    *_snake_case							,    **_snake_case			):







  """simple docstring"""






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

  if "raw_speech" in kwargs:
   warnings.warn('Using `raw_speech` as a keyword argument is deprecated. Use `audio` instead.'			)
   lowerCAmelCase  							=      kwargs.pop('raw_speech'			)
  else:
   lowerCAmelCase  							=      kwargs.pop('audio'							,    _snake_case			)
  lowerCAmelCase  							=      kwargs.pop('sampling_rate'							,    _snake_case			)
  lowerCAmelCase  							=      kwargs.pop('text'							,    _snake_case			)
  if len(_snake_case			) > 0:
   lowerCAmelCase  							=      args[0]
   lowerCAmelCase  							=      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 audio is not None:
   lowerCAmelCase  							=      self.feature_extractor(_snake_case							,    *_snake_case							,    sampling_rate=_snake_case							,    **_snake_case			)
  if text is not None:
   lowerCAmelCase  							=      self.tokenizer(_snake_case							,    **_snake_case			)

  if text is None:
   return inputs
  elif audio is None:
   return encodings
  else:
   lowerCAmelCase  							=      encodings['input_ids']
   return inputs



 def 					UpperCamelCase__   (			self							,    *_snake_case							,    **_snake_case			):







  """simple docstring"""






  return self.tokenizer.batch_decode(*_snake_case							,    **_snake_case			)



 def 					UpperCamelCase__   (			self							,    *_snake_case							,    **_snake_case			):







  """simple docstring"""






  return self.tokenizer.decode(*_snake_case							,    **_snake_case			)



 @contextmanager
 def 					UpperCamelCase__   (			self			):







  """simple docstring"""






  warnings.warn(
      '`as_target_processor` is deprecated and will be removed in v5 of Transformers. You can process your '
      'labels by using the argument `text` of the regular `__call__` method (either in the same call as '
      'your audio inputs, or in a separate call.'			)
  lowerCAmelCase  							=      True
  lowerCAmelCase  							=      self.tokenizer
  yield
  lowerCAmelCase  							=      self.feature_extractor
  lowerCAmelCase  							=      False





