'''simple docstring'''

import argparse

from transformers import CanineConfig, CanineModel, CanineTokenizer, load_tf_weights_in_canine
from transformers.utils import logging


logging.set_verbosity_info()



def  _lowerCAmelCase				(				__a			,      __a      )  ->      Union[str, Any]:
     '''simple docstring'''







     _UpperCamelCase  :str       =CanineConfig()
     _UpperCamelCase  :str       =CanineModel(__a      )
     model.eval()

     print(F'''Building PyTorch model from configuration: {config}'''      )

     # Load weights from tf checkpoint
     load_tf_weights_in_canine(__a			,      __a			,      __a      )

     # Save pytorch-model (weights and configuration)
     print(F'''Save PyTorch model to {pytorch_dump_path}'''      )
     model.save_pretrained(__a      )

     # Save tokenizer files
     _UpperCamelCase  :Tuple       =CanineTokenizer()
     print(F'''Save tokenizer files to {pytorch_dump_path}'''      )
     tokenizer.save_pretrained(__a      )


if __name__ == "__main__":
      _lowerCamelCase :				List[str]														= argparse.ArgumentParser()
      # Required parameters
      parser.add_argument(
          """--tf_checkpoint_path""",
          default=None,
          type=str,
          required=True,
          help="""Path to the TensorFlow checkpoint. Should end with model.ckpt""",
      )
      parser.add_argument(
          """--pytorch_dump_path""",
          default=None,
          type=str,
          required=True,
          help="""Path to a folder where the PyTorch model will be placed.""",
      )
      _lowerCamelCase :				Dict														= parser.parse_args()
      convert_tf_checkpoint_to_pytorch(args.tf_checkpoint_path, args.pytorch_dump_path)






from .balanced_parentheses import balanced_parentheses
from .stack import Stack







def      A__				(       SCREAMING_SNAKE_CASE__)  ->       int:
  return {"+": 1, "-": 1, "*": 2, "/": 2, "^": 3}.get(SCREAMING_SNAKE_CASE__   ,   -1)







def      A__				(       SCREAMING_SNAKE_CASE__)  ->       str:
  if not balanced_parentheses(SCREAMING_SNAKE_CASE__):
    raise ValueError("""Mismatched parentheses""")
  __snake_case:		Stack[str]					    =		Stack()
  __snake_case:		Any					    =		[]
  for char in expression_str:
    if char.isalpha() or char.isdigit():
      postfix.append(SCREAMING_SNAKE_CASE__)
    elif char == "(":
      stack.push(SCREAMING_SNAKE_CASE__)
    elif char == ")":
      while not stack.is_empty() and stack.peek() != "(":
        postfix.append(stack.pop())
      stack.pop()
    else:
      while not stack.is_empty() and precedence(SCREAMING_SNAKE_CASE__) <= precedence(stack.peek()):
        postfix.append(stack.pop())
      stack.push(SCREAMING_SNAKE_CASE__)
  while not stack.is_empty():
    postfix.append(stack.pop())
  return " ".join(SCREAMING_SNAKE_CASE__)


if __name__ == "__main__":
      from doctest import testmod

      testmod()
      __UpperCAmelCase			:  Optional[int]										=				"a+b*(c^d-e)^(f+g*h)-i"

      print("Infix to Postfix Notation demonstration:\n")
      print("Infix notation: " + expression)
      print("Postfix notation: " + infix_to_postfix(expression))






