
"""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  (		UpperCamelCase__				,     UpperCamelCase__      ):


	"""simple docstring"""






	_UpperCAmelCase =						CanineConfig()
	_UpperCAmelCase =						CanineModel(UpperCamelCase__      )
	model.eval()

	print(f"Building PyTorch model from configuration: {config}"      )

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

	# Save pytorch-model (weights and configuration)
	print(f"Save PyTorch model to {pytorch_dump_path}"      )
	model.save_pretrained(UpperCamelCase__      )

	# Save tokenizer files
	_UpperCAmelCase =						CanineTokenizer()
	print(f"Save tokenizer files to {pytorch_dump_path}"      )
	tokenizer.save_pretrained(UpperCamelCase__      )


if __name__ == "__main__":
			__magic_name__		       =				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.''',
			)
			__magic_name__		       =				parser.parse_args()
			convert_tf_checkpoint_to_pytorch(args.tf_checkpoint_path, args.pytorch_dump_path)






"""simple docstring"""
def     __lowerCamelCase  (		UpperCamelCase__      ):


	"""simple docstring"""






	if not isinstance(UpperCamelCase__				,     UpperCamelCase__      ):
		raise TypeError("recursive_lucas_number accepts only integer arguments."      )
	if n_th_number == 0:
		return 2
	if n_th_number == 1:
		return 1

	return recursive_lucas_number(n_th_number - 1      ) + recursive_lucas_number(
	    n_th_number - 2      )




def     __lowerCamelCase  (		UpperCamelCase__      ):


	"""simple docstring"""






	if not isinstance(UpperCamelCase__				,     UpperCamelCase__      ):
		raise TypeError("dynamic_lucas_number accepts only integer arguments."      )
	_UpperCAmelCase ,      _UpperCAmelCase =						2, 1
	for _ in range(UpperCamelCase__      ):
		_UpperCAmelCase ,      _UpperCAmelCase =						b, a + b
	return a


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

			testmod()
			__magic_name__		       =				int(input('''Enter the number of terms in lucas series:\n''').strip())
			print('''Using recursive function to calculate lucas series:''')
			print(''' '''.join(str(recursive_lucas_number(i)) for i in range(n)))
			print('''\nUsing dynamic function to calculate lucas series:''')
			print(''' '''.join(str(dynamic_lucas_number(i)) for i in range(n)))




