




def 						lowerCAmelCase		(		_lowerCAmelCase							:   Tuple	):




 """simple docstring"""







 UpperCAmelCase__							 =						[]
 UpperCAmelCase__							 =						[]
 UpperCAmelCase__							 =						{
     "^": 3,
     "*": 2,
     "/": 2,
     "%": 2,
     "+": 1,
     "-": 1,
 }  # Priority of each operator
 UpperCAmelCase__							 =						len(_lowerCAmelCase	) if (len(_lowerCAmelCase	) > 7) else 7

 # Print table header for output
 print(
     "Symbol".center(8	)						,							"Stack".center(_lowerCAmelCase	)						,							"Postfix".center(_lowerCAmelCase	)						,							sep=" | "						,							)
 print("-" * (print_width * 3 + 7)	)

 for x in infix:
  if x.isalpha() or x.isdigit():
   post_fix.append(_lowerCAmelCase	)  # if x is Alphabet / Digit, add it to Postfix
  elif x == "(":
   stack.append(_lowerCAmelCase	)  # if x is "(" push to Stack
  elif x == ")":  # if x is ")" pop stack until "(" is encountered
   while stack[-1] != "(":
    post_fix.append(stack.pop()	)  # Pop stack & add the content to Postfix
   stack.pop()
  else:
   if len(_lowerCAmelCase	) == 0:
    stack.append(_lowerCAmelCase	)  # If stack is empty, push x to stack
   else:  # while priority of x is not > priority of element in the stack
    while len(_lowerCAmelCase	) > 0 and priority[x] <= priority[stack[-1]]:
     post_fix.append(stack.pop()	)  # pop stack & add to Postfix
    stack.append(_lowerCAmelCase	)  # push x to stack

  print(
      x.center(8	)						,							("".join(_lowerCAmelCase	)).ljust(_lowerCAmelCase	)						,							("".join(_lowerCAmelCase	)).ljust(_lowerCAmelCase	)						,							sep=" | "						,							)  # Output in tabular format

 while len(_lowerCAmelCase	) > 0:  # while stack is not empty
  post_fix.append(stack.pop()	)  # pop stack & add to Postfix
  print(
      " ".center(8	)						,							("".join(_lowerCAmelCase	)).ljust(_lowerCAmelCase	)						,							("".join(_lowerCAmelCase	)).ljust(_lowerCAmelCase	)						,							sep=" | "						,							)  # Output in tabular format

 return "".join(_lowerCAmelCase	)  # return Postfix as str



def 						lowerCAmelCase		(		_lowerCAmelCase							:   Any	):




 """simple docstring"""







 UpperCAmelCase__							 =						list(infix[::-1]	)  # reverse the infix equation

 for i in range(len(_lowerCAmelCase	)	):
  if infix[i] == "(":
   UpperCAmelCase__							 =						")"  # change "(" to ")"
  elif infix[i] == ")":
   UpperCAmelCase__							 =						"("  # change ")" to "("

 return (infix_2_postfix("".join(_lowerCAmelCase	)	))[
     ::-1
 ]  # call infix_2_postfix on Infix, return reverse of Postfix


if __name__ == "__main__":
  _lowerCAmelCase						:   Optional[int]		=   input("\nEnter an Infix Equation = ")  # Input an Infix equation
  _lowerCAmelCase						:   Optional[Any]		=   "".join(Infix.split())  # Remove spaces from the input
  print("\n\t", Infix, "(Infix) -> ", infix_2_prefix(Infix), "(Prefix)")











from typing import TYPE_CHECKING

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


_lowerCAmelCase						:   Optional[int]		=   {
    "configuration_gpt_neo": ["GPT_NEO_PRETRAINED_CONFIG_ARCHIVE_MAP", "GPTNeoConfig", "GPTNeoOnnxConfig"],
}

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  _lowerCAmelCase						:   List[str]		=   [
      "GPT_NEO_PRETRAINED_MODEL_ARCHIVE_LIST",
      "GPTNeoForCausalLM",
      "GPTNeoForQuestionAnswering",
      "GPTNeoForSequenceClassification",
      "GPTNeoForTokenClassification",
      "GPTNeoModel",
      "GPTNeoPreTrainedModel",
      "load_tf_weights_in_gpt_neo",
  ]

try:
  if not is_flax_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  _lowerCAmelCase						:   Tuple		=   [
      "FlaxGPTNeoForCausalLM",
      "FlaxGPTNeoModel",
      "FlaxGPTNeoPreTrainedModel",
  ]


if TYPE_CHECKING:
  from .configuration_gpt_neo import GPT_NEO_PRETRAINED_CONFIG_ARCHIVE_MAP, GPTNeoConfig, GPTNeoOnnxConfig

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_gpt_neo import (
        GPT_NEO_PRETRAINED_MODEL_ARCHIVE_LIST,
        GPTNeoForCausalLM,
        GPTNeoForQuestionAnswering,
        GPTNeoForSequenceClassification,
        GPTNeoForTokenClassification,
        GPTNeoModel,
        GPTNeoPreTrainedModel,
        load_tf_weights_in_gpt_neo,
    )

  try:
    if not is_flax_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_flax_gpt_neo import FlaxGPTNeoForCausalLM, FlaxGPTNeoModel, FlaxGPTNeoPreTrainedModel


else:
  import sys

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





