





'''simple docstring'''

from typing import TYPE_CHECKING

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


__lowerCAmelCase							:	List[str]			={
    "configuration_squeezebert": [
        "SQUEEZEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "SqueezeBertConfig",
        "SqueezeBertOnnxConfig",
    ],
    "tokenization_squeezebert": ["SqueezeBertTokenizer"],
}

try:
  if not is_tokenizers_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  __lowerCAmelCase							:	Optional[int]			=["SqueezeBertTokenizerFast"]

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  __lowerCAmelCase							:	Dict			=[
      "SQUEEZEBERT_PRETRAINED_MODEL_ARCHIVE_LIST",
      "SqueezeBertForMaskedLM",
      "SqueezeBertForMultipleChoice",
      "SqueezeBertForQuestionAnswering",
      "SqueezeBertForSequenceClassification",
      "SqueezeBertForTokenClassification",
      "SqueezeBertModel",
      "SqueezeBertModule",
      "SqueezeBertPreTrainedModel",
  ]


if TYPE_CHECKING:
  from .configuration_squeezebert import (
      SQUEEZEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
      SqueezeBertConfig,
      SqueezeBertOnnxConfig,
  )
  from .tokenization_squeezebert import SqueezeBertTokenizer

  try:
    if not is_tokenizers_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .tokenization_squeezebert_fast import SqueezeBertTokenizerFast

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_squeezebert import (
        SQUEEZEBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
        SqueezeBertForMaskedLM,
        SqueezeBertForMultipleChoice,
        SqueezeBertForQuestionAnswering,
        SqueezeBertForSequenceClassification,
        SqueezeBertForTokenClassification,
        SqueezeBertModel,
        SqueezeBertModule,
        SqueezeBertPreTrainedModel,
    )

else:
  import sys

  __lowerCAmelCase							:	Any			=_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)










'''simple docstring'''

def 						UpperCamelCase				(							_lowerCamelCase					:					int | float | str       ):
    try:
        A__				=			float(_lowerCamelCase       )
    except ValueError:
        raise ValueError("Please enter a valid number"       )
    A__				=			decimal - int(_lowerCamelCase       )
    if fractional_part == 0:
        return int(_lowerCamelCase       ), 1
    else:
        A__				=			len(str(_lowerCamelCase       ).split("."       )[1]       )
        A__				=			int(decimal * (10**number_of_frac_digits)       )
        A__				=			10**number_of_frac_digits
        A__,	A__				=			denominator, numerator
        while True:
            A__				=			dividend % divisor
            if remainder == 0:
                break
            A__,	A__				=			divisor, remainder
        A__,	A__				=			numerator / divisor, denominator / divisor
        return int(_lowerCamelCase       ), int(_lowerCamelCase       )


if __name__ == "__main__":
  print(f"""{decimal_to_fraction(2) = }""")
  print(f"""{decimal_to_fraction(89.0) = }""")
  print(f"""{decimal_to_fraction("67") = }""")
  print(f"""{decimal_to_fraction("45.0") = }""")
  print(f"""{decimal_to_fraction(1.5) = }""")
  print(f"""{decimal_to_fraction("6.25") = }""")
  print(f"""{decimal_to_fraction("78td") = }""")



