

import argparse

from transformers import CanineConfig, CanineModel, CanineTokenizer, load_tf_weights_in_canine
from transformers.utils import logging


logging.set_verbosity_info()




def        _lowercase  (					a_					:       str       ,a_					:       Union[str, Any]					)					->						int:




					'''simple docstring'''







					__magic_name__				=     CanineConfig()
					__magic_name__				=     CanineModel(a_					)
					model.eval()

					print(F'Building PyTorch model from configuration: {config}'					)

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

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

					# Save tokenizer files
					__magic_name__				=     CanineTokenizer()
					print(F'Save tokenizer files to {pytorch_dump_path}'					)
					tokenizer.save_pretrained(a_					)


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. 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.",
						)
						A__							=				parser.parse_args()
						convert_tf_checkpoint_to_pytorch(args.tf_checkpoint_path, args.pytorch_dump_path)












'''simple docstring'''







def 					SCREAMING_SNAKE_CASE_			(UpperCamelCase							,     UpperCamelCase = 13 ) ->			str:
							lowerCamelCase__   :      Dict			    =			""""""
							for c in s:
														if "A" <= c <= "Z":
																					out += chr(ord("""A""" ) + (ord(UpperCamelCase ) - ord("""A""" ) + n) % 26 )
														elif "a" <= c <= "z":
																					out += chr(ord("""a""" ) + (ord(UpperCamelCase ) - ord("""a""" ) + n) % 26 )
														else:
																					out += c
							return out





def 					SCREAMING_SNAKE_CASE_			() ->			None:
							lowerCamelCase__   :      Dict			    =			input("""Enter message: """ )

							lowerCamelCase__   :      str			    =			dencrypt(UpperCamelCase							,     13 )
							print("""Encryption:"""							,     UpperCamelCase )

							lowerCamelCase__   :      List[str]			    =			dencrypt(UpperCamelCase							,     13 )
							print("""Decryption: """							,     UpperCamelCase )


if __name__ == "__main__":
			import doctest

			doctest.testmod()
			main()

