





import argparse

from transformers import ConvBertConfig, ConvBertModel, TFConvBertModel, load_tf_weights_in_convbert
from transformers.utils import logging


logging.set_verbosity_info()







def      A__				(       SCREAMING_SNAKE_CASE__   ,   SCREAMING_SNAKE_CASE__   ,   SCREAMING_SNAKE_CASE__)  ->       Optional[int]:
  __snake_case:		int					    =		ConvBertConfig.from_json_file(SCREAMING_SNAKE_CASE__)
  __snake_case:		str					    =		ConvBertModel(SCREAMING_SNAKE_CASE__)

  __snake_case:		Optional[Any]					    =		load_tf_weights_in_convbert(SCREAMING_SNAKE_CASE__   ,   SCREAMING_SNAKE_CASE__   ,   SCREAMING_SNAKE_CASE__)
  model.save_pretrained(SCREAMING_SNAKE_CASE__)

  __snake_case:		Tuple					    =		TFConvBertModel.from_pretrained(SCREAMING_SNAKE_CASE__   ,   from_pt=SCREAMING_SNAKE_CASE__)
  tf_model.save_pretrained(SCREAMING_SNAKE_CASE__)


if __name__ == "__main__":
      __UpperCAmelCase			:  Any										=				argparse.ArgumentParser()
      # Required parameters
      parser.add_argument(
          "--tf_checkpoint_path", default=None, type=str, required=True, help="Path to the TensorFlow checkpoint path."
      )
      parser.add_argument(
          "--convbert_config_file",
          default=None,
          type=str,
          required=True,
          help=(
              "The config json file corresponding to the pre-trained ConvBERT model. \n"
              "This specifies the model architecture."
          ),
      )
      parser.add_argument(
          "--pytorch_dump_path", default=None, type=str, required=True, help="Path to the output PyTorch model."
      )
      __UpperCAmelCase			:  Any										=				parser.parse_args()
      convert_orig_tfa_checkpoint_to_pytorch(args.tf_checkpoint_path, args.convbert_config_file, 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))






