code: '''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      SCREAMING_SNAKE_CASE_  (		snake_case__     ,						snake_case__							)  ->			int:
  							# Initialize PyTorch model
  							lowerCAmelCase				=	CanineConfig()
  							lowerCAmelCase				=	CanineModel(snake_case__							)
  							model.eval()
  
  							print(f"Building PyTorch model from configuration: {config}"							)
  
  							# Load weights from tf checkpoint
  							load_tf_weights_in_canine(snake_case__     ,						snake_case__     ,						snake_case__							)
  
  							# Save pytorch-model (weights and configuration)
  							print(f"Save PyTorch model to {pytorch_dump_path}"							)
  							model.save_pretrained(snake_case__							)
  
  							# Save tokenizer files
  							lowerCAmelCase				=	CanineTokenizer()
  							print(f"Save tokenizer files to {pytorch_dump_path}"							)
  							tokenizer.save_pretrained(snake_case__							)
  
  
  if __name__ == "__main__":
  	lowercase__    :       int						=			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.''',
  	)
  	lowercase__    :       Dict						=			parser.parse_args()
  	convert_tf_checkpoint_to_pytorch(args.tf_checkpoint_path, args.pytorch_dump_path)
  
  
  
  
style_context: def      SCREAMING_SNAKE_CASE_  (		snake_case__     ,						snake_case__							)  ->			int:
  							return (input_a, input_a).count(0							) % 2
  
  def      SCREAMING_SNAKE_CASE_  (		)  ->			None:
  							assert xor_gate(0     ,						0							) == 0
  							assert xor_gate(0     ,						1							) == 1
  							assert xor_gate(1     ,						0							) == 1
  							assert xor_gate(1     ,						1							) == 0
  
  
  if __name__ == "__main__":
  	print(xor_gate(0, 0))
  	print(xor_gate(0, 1))
  
  
  
  