



"""simple docstring"""





from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


lowerCamelCase  			=		{
    """configuration_longformer""": [
        """LONGFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """LongformerConfig""",
        """LongformerOnnxConfig""",
    ],
    """tokenization_longformer""": ["""LongformerTokenizer"""],
}

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

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  lowerCamelCase  			=		[
      """LONGFORMER_PRETRAINED_MODEL_ARCHIVE_LIST""",
      """LongformerForMaskedLM""",
      """LongformerForMultipleChoice""",
      """LongformerForQuestionAnswering""",
      """LongformerForSequenceClassification""",
      """LongformerForTokenClassification""",
      """LongformerModel""",
      """LongformerPreTrainedModel""",
      """LongformerSelfAttention""",
  ]

try:
  if not is_tf_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  lowerCamelCase  			=		[
      """TF_LONGFORMER_PRETRAINED_MODEL_ARCHIVE_LIST""",
      """TFLongformerForMaskedLM""",
      """TFLongformerForMultipleChoice""",
      """TFLongformerForQuestionAnswering""",
      """TFLongformerForSequenceClassification""",
      """TFLongformerForTokenClassification""",
      """TFLongformerModel""",
      """TFLongformerPreTrainedModel""",
      """TFLongformerSelfAttention""",
  ]


if TYPE_CHECKING:
  from .configuration_longformer import (
      LONGFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
      LongformerConfig,
      LongformerOnnxConfig,
  )
  from .tokenization_longformer import LongformerTokenizer

  try:
    if not is_tokenizers_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .tokenization_longformer_fast import LongformerTokenizerFast

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_longformer import (
        LONGFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
        LongformerForMaskedLM,
        LongformerForMultipleChoice,
        LongformerForQuestionAnswering,
        LongformerForSequenceClassification,
        LongformerForTokenClassification,
        LongformerModel,
        LongformerPreTrainedModel,
        LongformerSelfAttention,
    )

  try:
    if not is_tf_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_tf_longformer import (
        TF_LONGFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
        TFLongformerForMaskedLM,
        TFLongformerForMultipleChoice,
        TFLongformerForQuestionAnswering,
        TFLongformerForSequenceClassification,
        TFLongformerForTokenClassification,
        TFLongformerModel,
        TFLongformerPreTrainedModel,
        TFLongformerSelfAttention,
    )

else:
  import sys

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







__lowercase				      =						"""Alexander Joslin"""

import operator as op

from .stack import Stack







def 							_lowerCamelCase   (			SCREAMING_SNAKE_CASE   ):
      '''simple docstring'''







      A_							       =		{'''*''': op.mul, '''/''': op.truediv, '''+''': op.add, '''-''': op.sub}

      A_							       =		Stack()
      A_							       =		Stack()

      for i in equation:
            if i.isdigit():
                  # RULE 1
                  operand_stack.push(int(SCREAMING_SNAKE_CASE   )   )
            elif i in operators:
                  # RULE 2
                  operator_stack.push(SCREAMING_SNAKE_CASE   )
            elif i == ")":
                  # RULE 4
                  A_							       =		operator_stack.peek()
                  operator_stack.pop()
                  A_							       =		operand_stack.peek()
                  operand_stack.pop()
                  A_							       =		operand_stack.peek()
                  operand_stack.pop()

                  A_							       =		operators[opr](SCREAMING_SNAKE_CASE		,				SCREAMING_SNAKE_CASE   )
                  operand_stack.push(SCREAMING_SNAKE_CASE   )

    # RULE 5
      return operand_stack.peek()


if __name__ == "__main__":
      __lowercase				      =						"""(5 + ((4 * 2) * (2 + 3)))"""
      # answer = 45
      print(f'{equation} = {dijkstras_two_stack_algorithm(equation)}')





