



import argparse
import json

from transformers import GPTNeoConfig, GPTNeoForCausalLM, load_tf_weights_in_gpt_neo
from transformers.utils import logging


logging.set_verbosity_info()


def 						_UpperCAmelCase							( snake_case      ,		snake_case      ,		snake_case     ):





					"""simple docstring"""

					_lowerCAmelCase         =       json.load(open(_UpperCAmelCase      ,		"""r"""     )     )
					_lowerCAmelCase         =       GPTNeoConfig(
					    hidden_size=config_json["""n_embd"""]      ,		num_layers=config_json["""n_layer"""]      ,		num_heads=config_json["""n_head"""]      ,		attention_types=config_json["""attention_types"""]      ,		max_position_embeddings=config_json["""n_positions"""]      ,		resid_dropout=config_json["""res_dropout"""]      ,		embed_dropout=config_json["""embed_dropout"""]      ,		attention_dropout=config_json["""attn_dropout"""]      ,		)
					print(F'Building PyTorch model from configuration: {config}'     )
					_lowerCAmelCase         =       GPTNeoForCausalLM(_UpperCAmelCase     )

					# Load weights from tf checkpoint
					load_tf_weights_in_gpt_neo(_UpperCAmelCase      ,		_UpperCAmelCase      ,		_UpperCAmelCase     )

					# Save pytorch-model
					print(F'Save PyTorch model to {pytorch_dump_path}'     )
					model.save_pretrained(_UpperCAmelCase     )


if __name__ == "__main__":
	A__       =			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(
	    """--config_file""",
	    default=None,
	    type=str,
	    required=True,
	    help=(
	        """The config json file corresponding to the pre-trained mesh-tf 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."""
	)
	A__       =			parser.parse_args()
	convert_tf_checkpoint_to_pytorch(args.tf_checkpoint_path, args.config_file, args.pytorch_dump_path)









"""simple docstring"""

def 		lowercase_   (		_UpperCAmelCase	,   _UpperCAmelCase						):




	"""simple docstring"""






	return a + b


if __name__ == "__main__":
		_lowerCamelCase	:      Tuple   =							5
		_lowerCamelCase	:      Union[str, Any]   =							6
		print(f'The sum of {a} + {b} is {add(a, b)}')





