






import argparse

from transformers import TaConfig, TaForConditionalGeneration, load_tf_weights_in_ta
from transformers.utils import logging


logging.set_verbosity_info()
def      lowerCamelCase					(						a_ ,						a_ ,						a_	)	->			Optional[int]:
							# Initialise PyTorch model
							lowerCAmelCase_										=     TaConfig.from_json_file(a_	)
							print(F'''Building PyTorch model from configuration: {config}'''	)
							lowerCAmelCase_										=     TaForConditionalGeneration(a_	)

							# Load weights from tf checkpoint
							load_tf_weights_in_ta(a_ ,						a_ ,						a_	)

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


if __name__ == "__main__":
		lowerCamelCase_						     =  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 T5 model. \nThis specifies the model architecture."""
		    ),
		)
		parser.add_argument(
		    """--pytorch_dump_path""", default=None, type=str, required=True, help="""Path to the output PyTorch model."""
		)
		lowerCamelCase_						     =  parser.parse_args()
		convert_tf_checkpoint_to_pytorch(args.tf_checkpoint_path, args.config_file, args.pytorch_dump_path)











from transformers import HfArgumentParser, PyTorchBenchmark, PyTorchBenchmarkArguments
def      lowerCamelCase					(						)	->			Union[str, Any]:
							lowerCAmelCase_										=     HfArgumentParser(a_	)
							try:
														lowerCAmelCase_										=     parser.parse_args_into_dataclasses()[0]
							except ValueError as e:
														lowerCAmelCase_										=     'Arg --no_{0} is no longer used, please use --no-{0} instead.'
														lowerCAmelCase_										=     ' '.join(str(a_	).split(' '	)[:-1]	)
														lowerCAmelCase_										=     ''
														lowerCAmelCase_										=     eval(str(a_	).split(' '	)[-1]	)
														lowerCAmelCase_										=     []
														for arg in depreciated_args:
																					# arg[2:] removes '--'
																					if arg[2:] in PyTorchBenchmarkArguments.deprecated_args:
																												# arg[5:] removes '--no_'
																												full_error_msg += arg_error_msg.format(arg[5:]	)
																					else:
																												wrong_args.append(a_	)
														if len(a_	) > 0:
																					lowerCAmelCase_										=     full_error_msg + begin_error_msg + str(a_	)
														raise ValueError(a_	)

							lowerCAmelCase_										=     PyTorchBenchmark(args=a_	)
							benchmark.run()


if __name__ == "__main__":
		main()



