

import math
import os
import sys




def 			UpperCAmelCase__				(			_A      : str							):





  '''simple docstring'''







  a__  =''''''
  try:
    with open(_A	,      '''rb'''							) as binary_file:
      a__  =binary_file.read()
    for dat in data:
      a__  =F"""{dat:08b}"""
      result += curr_byte
    return result
  except OSError:
    print('''File not accessible'''							)
    sys.exit()




def 			UpperCAmelCase__				(			_A      : dict[str, str]	,      _A      : str	,      _A      : int	,      _A      : str							):





  '''simple docstring'''







  lexicon.pop(_A							)
  a__  =last_match_id

  if math.loga(_A							).is_integer():
    for curr_key in lexicon:
      a__  ='''0''' + lexicon[curr_key]

  a__  =bin(_A							)[2:]




def 			UpperCAmelCase__				(			_A      : str							):





  '''simple docstring'''







  a__  ={'''0''': '''0''', '''1''': '''1'''}
  a__,      a__  ='''''', ''''''
  a__  =len(_A							)

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

    a__  =lexicon[curr_string]
    result += last_match_id
    add_key_to_lexicon(_A	,      _A	,      _A	,      _A							)
    index += 1
    a__  =''''''

  while curr_string != "" and curr_string not in lexicon:
    curr_string += "0"

  if curr_string != "":
    a__  =lexicon[curr_string]
    result += last_match_id

  return result




def 			UpperCAmelCase__				(			_A      : str	,      _A      : str							):





  '''simple docstring'''







  a__  =os.path.getsize(_A							)
  a__  =bin(_A							)[2:]
  a__  =len(_A							)

  return "0" * (length_length - 1) + file_length_binary + compressed




def 			UpperCAmelCase__				(			_A      : str	,      _A      : str							):





  '''simple docstring'''







  a__  =8
  try:
    with open(_A	,      '''wb'''							) as opened_file:
      a__  =[
          to_write[i : i + byte_length]
          for i in range(0	,      len(_A							)	,      _A							)
      ]

      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:
        opened_file.write(int(_A	,      2							).to_bytes(1	,      byteorder='''big'''							)							)
  except OSError:
    print('''File not accessible'''							)
    sys.exit()




def 			UpperCAmelCase__				(			_A      : str	,      _A      : str							):





  '''simple docstring'''







  a__  =read_file_binary(_A							)
  a__  =compress_data(_A							)
  a__  =add_file_length(_A	,      _A							)
  write_file_binary(_A	,      _A							)


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



from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


lowerCamelCase           =					{
    '''configuration_mvp''': ['''MVP_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''MvpConfig''', '''MvpOnnxConfig'''],
    '''tokenization_mvp''': ['''MvpTokenizer'''],
}

try:
       if not is_tokenizers_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       lowerCamelCase           =					['''MvpTokenizerFast''']

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       lowerCamelCase           =					[
           '''MVP_PRETRAINED_MODEL_ARCHIVE_LIST''',
           '''MvpForCausalLM''',
           '''MvpForConditionalGeneration''',
           '''MvpForQuestionAnswering''',
           '''MvpForSequenceClassification''',
           '''MvpModel''',
           '''MvpPreTrainedModel''',
       ]

if TYPE_CHECKING:
       from .configuration_mvp import MVP_PRETRAINED_CONFIG_ARCHIVE_MAP, MvpConfig, MvpOnnxConfig
       from .tokenization_mvp import MvpTokenizer

       try:
              if not is_tokenizers_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .tokenization_mvp_fast import MvpTokenizerFast

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_mvp import (
                  MVP_PRETRAINED_MODEL_ARCHIVE_LIST,
                  MvpForCausalLM,
                  MvpForConditionalGeneration,
                  MvpForQuestionAnswering,
                  MvpForSequenceClassification,
                  MvpModel,
                  MvpPreTrainedModel,
              )

else:
       import sys

       lowerCamelCase           =					_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)
