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   UpperCamelCase__     (		lowercase__  :     Optional[int]       ,     lowercase__  :     Dict   ):
  		# Initialize PyTorch model
  		snake_case		:						Optional[int]								=				CanineConfig()
  		snake_case		:						Any								=				CanineModel(lowercase__   )
  		model.eval()
  
  		print(F'''Building PyTorch model from configuration: {config}'''   )
  
  		# Load weights from tf checkpoint
  		load_tf_weights_in_canine(lowercase__       ,     lowercase__       ,     lowercase__   )
  
  		# Save pytorch-model (weights and configuration)
  		print(F'''Save PyTorch model to {pytorch_dump_path}'''   )
  		model.save_pretrained(lowercase__   )
  
  		# Save tokenizer files
  		snake_case		:						Tuple								=				CanineTokenizer()
  		print(F'''Save tokenizer files to {pytorch_dump_path}'''   )
  		tokenizer.save_pretrained(lowercase__   )
  
  
  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)
  
  
style_context: 
  
  
  
  
  """simple docstring"""
  
  import random
  
  
  
  def   UpperCamelCase__     (		lowercase__  :     Union[str, Any]   ):
  
  		def is_sorted(lowercase__  :     int   ):
  				for i in range(len(lowercase__   ) - 1   ):
  						if collection[i] > collection[i + 1]:
  								return False
  				return True
  
  		while not is_sorted(lowercase__   ):
  				random.shuffle(lowercase__   )
  		return collection
  
  
  if __name__ == "__main__":
  							__A 		=			input("Enter numbers separated by a comma:\n").strip()
  							__A 		=			[int(item) for item in user_input.split(",")]
  							print(bogo_sort(unsorted))
  
  