


"""simple docstring"""







def 					a__			(				SCREAMING_SNAKE_CASE    :    List[Any]				):


  '''simple docstring'''







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

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

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

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

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

  return "".join(__A				)  # return Postfix as str
def 					a__			(				SCREAMING_SNAKE_CASE    :    List[Any]				):


  '''simple docstring'''







  lowerCAmelCase     :     Optional[Any]								=							list(infix[::-1]				)  # reverse the infix equation

  for i in range(len(__A				)				):
    if infix[i] == "(":
      lowerCAmelCase     :     Dict								=							")"  # change "(" to ")"
    elif infix[i] == ")":
      lowerCAmelCase     :     str								=							"("  # change ")" to "("

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


if __name__ == "__main__":
     lowerCAmelCase__      				=   input('''\nEnter an Infix Equation = ''')  # Input an Infix equation
     lowerCAmelCase__      				=   "".join(Infix.split())  # Remove spaces from the input
     print('''\n\t''', Infix, '''(Infix) -> ''', infix_2_prefix(Infix), '''(Prefix)''')







'''simple docstring'''







import warnings

from ...configuration_utils import PretrainedConfig
from ...utils import logging


lowercase    :							int      =					logging.get_logger(__name__)

lowercase    :							Union[str, Any]      =					{
    "xlnet-base-cased": "https://huggingface.co/xlnet-base-cased/resolve/main/config.json",
    "xlnet-large-cased": "https://huggingface.co/xlnet-large-cased/resolve/main/config.json",
}


class 						__UpperCAmelCase      (					_lowerCamelCase						):
							__lowercase      		=       """xlnet"""
							__lowercase      		=       ["""mems"""]
							__lowercase      		=       {
							    """n_token""": """vocab_size""",  # Backward compatibility
							    """hidden_size""": """d_model""",
							    """num_attention_heads""": """n_head""",
							    """num_hidden_layers""": """n_layer""",
							}


							def __init__(       self    ,   lowerCAmelCase_=3_20_00    ,   lowerCAmelCase_=10_24    ,   lowerCAmelCase_=24    ,   lowerCAmelCase_=16    ,   lowerCAmelCase_=40_96    ,   lowerCAmelCase_="gelu"    ,   lowerCAmelCase_=True    ,   lowerCAmelCase_="bi"    ,   lowerCAmelCase_=0.02    ,   lowerCAmelCase_=1E-12    ,   lowerCAmelCase_=0.1    ,   lowerCAmelCase_=5_12    ,   lowerCAmelCase_=None    ,   lowerCAmelCase_=True    ,   lowerCAmelCase_=False    ,   lowerCAmelCase_=False    ,   lowerCAmelCase_=-1    ,   lowerCAmelCase_=False    ,   lowerCAmelCase_="last"    ,   lowerCAmelCase_=True    ,   lowerCAmelCase_="tanh"    ,   lowerCAmelCase_=0.1    ,   lowerCAmelCase_=5    ,   lowerCAmelCase_=5    ,   lowerCAmelCase_=5    ,   lowerCAmelCase_=1    ,   lowerCAmelCase_=2    ,   **lowerCAmelCase_    ,   ):





								"""simple docstring"""






								_snake_case   						=		vocab_size
								_snake_case   						=		d_model
								_snake_case   						=		n_layer
								_snake_case   						=		n_head
								if d_model % n_head != 0:
									raise ValueError(F'\'d_model % n_head\' ({d_model % n_head}) should be equal to 0'  )
								if "d_head" in kwargs:
									if kwargs["d_head"] != d_model // n_head:
										raise ValueError(
										    F'`d_head` ({kwargs["d_head"]}) should be equal to `d_model // n_head` ({d_model // n_head})'  )
								_snake_case   						=		d_model // n_head
								_snake_case   						=		ff_activation
								_snake_case   						=		d_inner
								_snake_case   						=		untie_r
								_snake_case   						=		attn_type

								_snake_case   						=		initializer_range
								_snake_case   						=		layer_norm_eps

								_snake_case   						=		dropout
								_snake_case   						=		mem_len
								_snake_case   						=		reuse_len
								_snake_case   						=		bi_data
								_snake_case   						=		clamp_len
								_snake_case   						=		same_length

								_snake_case   						=		summary_type
								_snake_case   						=		summary_use_proj
								_snake_case   						=		summary_activation
								_snake_case   						=		summary_last_dropout
								_snake_case   						=		start_n_top
								_snake_case   						=		end_n_top

								_snake_case   						=		bos_token_id
								_snake_case   						=		pad_token_id
								_snake_case   						=		eos_token_id

								if "use_cache" in kwargs:
									warnings.warn(
									    'The `use_cache` argument is deprecated and will be removed in a future version, use `use_mems_eval`'
									    ' instead.'    ,   lowerCAmelCase_    ,   )
									_snake_case   						=		kwargs['use_cache']

								_snake_case   						=		use_mems_eval
								_snake_case   						=		use_mems_train
								super().__init__(pad_token_id=lowerCAmelCase_    ,   bos_token_id=lowerCAmelCase_    ,   eos_token_id=lowerCAmelCase_    ,   **lowerCAmelCase_  )


							@property
							def  lowerCamelCase				(       self  ):





								"""simple docstring"""






								logger.info(F'The model {self.model_type} is one of the few models that has no sequence length limit.'  )
								return -1




							@max_position_embeddings.setter
							def  lowerCamelCase				(       self    ,   lowerCAmelCase_  ):





								"""simple docstring"""






								raise NotImplementedError(
								    F'The model {self.model_type} is one of the few models that has no sequence length limit.'  )

