





'''simple docstring'''




from typing import TYPE_CHECKING

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


lowercase__       : 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:
  lowercase__       : Optional[int]         =       ['''SqueezeBertTokenizerFast''']

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  lowercase__       : List[str]         =       [
      '''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

  lowercase__       : List[str]         =       _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)




"""simple docstring"""







from __future__ import annotations

def       _lowerCamelCase				(							UpperCAmelCase_ :       float,	UpperCAmelCase_ :       float,	UpperCAmelCase_ :       float,	)	-> tuple:






	"""simple docstring"""





	if (electron_conc, hole_conc, intrinsic_conc).count(0     ) != 1:
		raise ValueError("You cannot supply more or less than 2 values"     )
	elif electron_conc < 0:
		raise ValueError("Electron concentration cannot be negative in a semiconductor"     )
	elif hole_conc < 0:
		raise ValueError("Hole concentration cannot be negative in a semiconductor"     )
	elif intrinsic_conc < 0:
		raise ValueError(
		    "Intrinsic concentration cannot be negative in a semiconductor"     )
	elif electron_conc == 0:
		return (
		    "electron_conc",
		    intrinsic_conc**2 / hole_conc,
		)
	elif hole_conc == 0:
		return (
		    "hole_conc",
		    intrinsic_conc**2 / electron_conc,
		)
	elif intrinsic_conc == 0:
		return (
		    "intrinsic_conc",
		    (electron_conc * hole_conc) ** 0.5,
		)
	else:
		return (-1, -1)


if __name__ == "__main__":
			import doctest

			doctest.testmod()




