


'''simple docstring'''






import operator as op






def 		_A			(lowerCAmelCase__					:Tuple						)				->					Dict:




     '''simple docstring'''



     _a      =							[]
     _a      =							lambda lowerCAmelCase__			,  lowerCAmelCase__						: int(x / y						)  # noqa: E731 integer division operation
     _a      =							{
         '^': op.pow,
         '*': op.mul,
         '/': div,
         '+': op.add,
         '-': op.sub,
     }  # operators & their respective operation

     # print table header
     print('Symbol'.center(8						)			,  'Action'.center(12						)			,  'Stack'			,  sep=' | '						)
     print('-' * (30 + len(lowerCAmelCase__						))						)

     for x in post_fix:
          if x.isdigit():  # if x in digit
               stack.append(lowerCAmelCase__						)  # append x to stack
               # output in tabular format
               print(x.rjust(8						)			,  ('push(' + x + ')').ljust(12						)			,  ','.join(lowerCAmelCase__						)			,  sep=' | '						)
          else:
               _a      =							stack.pop()  # pop stack
               # output in tabular format
               print(''.rjust(8						)			,  ('pop(' + b + ')').ljust(12						)			,  ','.join(lowerCAmelCase__						)			,  sep=' | '						)

               _a      =							stack.pop()  # pop stack
               # output in tabular format
               print(''.rjust(8						)			,  ('pop(' + a + ')').ljust(12						)			,  ','.join(lowerCAmelCase__						)			,  sep=' | '						)

               stack.append(
                   str(opr[x](int(lowerCAmelCase__						)			,  int(lowerCAmelCase__						)						)						)						)  # evaluate the 2 values popped from stack & push result to stack
               # output in tabular format
               print(
                   x.rjust(8						)			,  ('push(' + a + x + b + ')').ljust(12						)			,  ','.join(lowerCAmelCase__						)			,  sep=' | '			,  )

     return int(stack[0]						)


if __name__ == "__main__":
 a_   :      Dict				    =      input("\n\nEnter a Postfix Equation (space separated) = ").split(" ")
 print("\n\tResult = ", solve(Postfix))





'''simple docstring'''






from typing import TYPE_CHECKING

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


a_   :      List[Any]				    =      {"configuration_gpt_neox": ["GPT_NEOX_PRETRAINED_CONFIG_ARCHIVE_MAP", "GPTNeoXConfig"]}

try:
 if not is_tokenizers_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 a_   :      List[str]				    =      ["GPTNeoXTokenizerFast"]

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 a_   :      List[Any]				    =      [
     "GPT_NEOX_PRETRAINED_MODEL_ARCHIVE_LIST",
     "GPTNeoXForCausalLM",
     "GPTNeoXForQuestionAnswering",
     "GPTNeoXForSequenceClassification",
     "GPTNeoXForTokenClassification",
     "GPTNeoXLayer",
     "GPTNeoXModel",
     "GPTNeoXPreTrainedModel",
 ]


if TYPE_CHECKING:
 from .configuration_gpt_neox import GPT_NEOX_PRETRAINED_CONFIG_ARCHIVE_MAP, GPTNeoXConfig

 try:
  if not is_tokenizers_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .tokenization_gpt_neox_fast import GPTNeoXTokenizerFast

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_gpt_neox import (
      GPT_NEOX_PRETRAINED_MODEL_ARCHIVE_LIST,
      GPTNeoXForCausalLM,
      GPTNeoXForQuestionAnswering,
      GPTNeoXForSequenceClassification,
      GPTNeoXForTokenClassification,
      GPTNeoXLayer,
      GPTNeoXModel,
      GPTNeoXPreTrainedModel,
  )


else:
 import sys

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

