





import argparse

import torch

from transformers import GPTaConfig, GPTaModel, load_tf_weights_in_gpta
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging


logging.set_verbosity_info()


def 		_SCREAMING_SNAKE_CASE     ( lowerCAmelCase__							,lowerCAmelCase__							,lowerCAmelCase__						):
		# Construct model
		if gpta_config_file == "":
				lowerCamelCase_	:     int 						=      GPTaConfig()
		else:
				lowerCamelCase_	:     Union[str, Any] 						=      GPTaConfig.from_json_file(lowerCAmelCase__						)
		lowerCamelCase_	:     Tuple 						=      GPTaModel(lowerCAmelCase__						)

		# Load weights from numpy
		load_tf_weights_in_gpta(lowerCAmelCase__							,lowerCAmelCase__							,lowerCAmelCase__						)

		# Save pytorch-model
		lowerCamelCase_	:     Tuple 						=      pytorch_dump_folder_path + '/' + WEIGHTS_NAME
		lowerCamelCase_	:     List[str] 						=      pytorch_dump_folder_path + '/' + CONFIG_NAME
		print(F"Save PyTorch model to {pytorch_weights_dump_path}"						)
		torch.save(model.state_dict()							,lowerCAmelCase__						)
		print(F"Save configuration file to {pytorch_config_dump_path}"						)
		with open(lowerCAmelCase__							,'w'							,encoding='utf-8'						) as f:
				f.write(config.to_json_string()						)


if __name__ == "__main__":
		_lowercase		:  Dict			       =argparse.ArgumentParser()
		# Required parameters
		parser.add_argument(
		    """--gpt2_checkpoint_path""", default=None, type=str, required=True, help="""Path to the TensorFlow checkpoint path."""
		)
		parser.add_argument(
		    """--pytorch_dump_folder_path""", default=None, type=str, required=True, help="""Path to the output PyTorch model."""
		)
		parser.add_argument(
		    """--gpt2_config_file""",
		    default="""""",
		    type=str,
		    help=(
		        """An optional config json file corresponding to the pre-trained OpenAI model. \n"""
		        """This specifies the model architecture."""
		    ),
		)
		_lowercase		:  str			       =parser.parse_args()
		convert_gpta_checkpoint_to_pytorch(args.gpta_checkpoint_path, args.gpta_config_file, args.pytorch_dump_folder_path)







def 		_SCREAMING_SNAKE_CASE     ( lowerCAmelCase__						):
		lowerCamelCase_	:     Union[str, Any] 						=      []
		lowerCamelCase_	:     Tuple 						=      []
		lowerCamelCase_	:     Dict 						=      {
		    '^': 3,
		    '*': 2,
		    '/': 2,
		    '%': 2,
		    '+': 1,
		    '-': 1,
		}  # Priority of each operator
		lowerCamelCase_	:     Optional[int] 						=      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 		_SCREAMING_SNAKE_CASE     ( lowerCAmelCase__						):
		lowerCamelCase_	:     Dict 						=      list(infix[::-1]						)  # reverse the infix equation

		for i in range(len(lowerCAmelCase__						)						):
				if infix[i] == "(":
						lowerCamelCase_	:     str 						=      ')'  # change "(" to ")"
				elif infix[i] == ")":
						lowerCamelCase_	:     Optional[Any] 						=      '('  # change ")" to "("

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


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