





def        __lowercase       (				_SCREAMING_SNAKE_CASE     )			->       str:


      '''simple docstring'''


      if not all(char in """01""" for char in bin_string     ):
            raise ValueError("""Non-binary value was passed to the function"""     )
      if not bin_string:
            raise ValueError("""Empty string was passed to the function"""     )
      SCREAMING_SNAKE_CASE		=						""
      while len(_lowerCAmelCase     ) % 3 != 0:
            SCREAMING_SNAKE_CASE		=						"0" + bin_string
      SCREAMING_SNAKE_CASE		=						[
          bin_string[index : index + 3]
          for index in range(len(_lowerCAmelCase     )     )
          if index % 3 == 0
      ]
      for bin_group in bin_string_in_3_list:
            SCREAMING_SNAKE_CASE		=						0
            for index, val in enumerate(_lowerCAmelCase     ):
                  oct_val += int(2 ** (2 - index) * int(_lowerCAmelCase     )     )
            oct_string += str(_lowerCAmelCase     )
      return oct_string


if __name__ == "__main__":
      from doctest import testmod

      testmod()









from typing import TYPE_CHECKING

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


SCREAMING_SNAKE_CASE_						       =	{
    """configuration_mvp""": ["""MVP_PRETRAINED_CONFIG_ARCHIVE_MAP""", """MvpConfig""", """MvpOnnxConfig"""],
    """tokenization_mvp""": ["""MvpTokenizer"""],
}

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

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      SCREAMING_SNAKE_CASE_						       =	[
          """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

      SCREAMING_SNAKE_CASE_						       =	_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)


