


'''simple docstring'''
import math
import sys


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


def       _lowercase							(					UpperCamelCase__							:       str      ):
 __A	:		Dict	  =      {'0': '0', '1': '1'}
 __A  ,__A	:		List[str]	  =      '', ''
 __A	:		Optional[int]	  =      len(UpperCamelCase__      )

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

  __A	:		Dict	  =      lexicon[curr_string]
  result += last_match_id
  __A	:		List[str]	  =      last_match_id + '0'

  if math.loga(UpperCamelCase__      ).is_integer():
   __A	:		Optional[Any]	  =      {}
   for curr_key in list(UpperCamelCase__      ):
    __A	:		Optional[Any]	  =      lexicon.pop(UpperCamelCase__      )
   __A	:		Dict	  =      new_lex

  __A	:		Tuple	  =      last_match_id + '1'
  index += 1
  __A	:		Optional[Any]	  =      ''
 return result


def       _lowercase							(					UpperCamelCase__							:       str,					UpperCamelCase__							:       str      ):
 __A	:		List[Any]	  =      8
 try:
  with open(UpperCamelCase__,					'wb'      ) as opened_file:
   __A	:		Optional[int]	  =      [
       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       _lowercase							(					UpperCamelCase__							:       str      ):
 __A	:		int	  =      0
 for letter in data_bits:
  if letter == "1":
   break
  counter += 1

 __A	:		Optional[Any]	  =      data_bits[counter:]
 __A	:		str	  =      data_bits[counter + 1 :]
 return data_bits


def       _lowercase							(					UpperCamelCase__							:       str,					UpperCamelCase__							:       str      ):
 __A	:		Optional[Any]	  =      read_file_binary(UpperCamelCase__      )
 __A	:		List[str]	  =      remove_prefix(UpperCamelCase__      )
 __A	:		List[Any]	  =      decompress_data(UpperCamelCase__      )
 write_file_binary(UpperCamelCase__,					UpperCamelCase__      )


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










'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging


UpperCAmelCase_			:  Optional[int]										=   logging.get_logger(__name__)

UpperCAmelCase_			:  List[str]										=   {
    'google/fnet-base': 'https://huggingface.co/google/fnet-base/resolve/main/config.json',
    'google/fnet-large': 'https://huggingface.co/google/fnet-large/resolve/main/config.json'
    # See all FNet models at https://huggingface.co/models?filter=fnet
}

class     _lowerCamelCase       (     snake_case_					):




 '''simple docstring'''
 __lowercase					:		List[Any]     				=    '''fnet'''


 def __init__(   self   ,   __lowercase=32_000   ,   __lowercase=768   ,   __lowercase=12   ,   __lowercase=3_072   ,   __lowercase="gelu_new"   ,   __lowercase=0.1   ,   __lowercase=512   ,   __lowercase=4   ,   __lowercase=0.0_2   ,   __lowercase=1E-12   ,   __lowercase=False   ,   __lowercase=512   ,   __lowercase=3   ,   __lowercase=1   ,   __lowercase=2   ,   **__lowercase   ,   ):

  """simple docstring"""







  super().__init__(pad_token_id=__lowercase   ,   bos_token_id=__lowercase   ,   eos_token_id=__lowercase   ,   **__lowercase    )

  __A	:		Union[str, Any]	  =      vocab_size
  __A	:		Dict	  =      max_position_embeddings
  __A	:		List[str]	  =      hidden_size
  __A	:		Tuple	  =      num_hidden_layers
  __A	:		Optional[int]	  =      intermediate_size
  __A	:		Dict	  =      hidden_act
  __A	:		List[str]	  =      hidden_dropout_prob
  __A	:		str	  =      initializer_range
  __A	:		Dict	  =      type_vocab_size
  __A	:		int	  =      layer_norm_eps
  __A	:		Tuple	  =      use_tpu_fourier_optimizations
  __A	:		Optional[Any]	  =      tpu_short_seq_length






