



import argparse

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


logging.set_verbosity_info()

def       A_   (						__a  :					List[str]			,		__a  :					Optional[Any]		):

				"""simple docstring"""
				# Initialize PyTorch model
				a__					   =		CanineConfig()
				a__					   =		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
				a__					   =		CanineTokenizer()
				print(F'''Save tokenizer files to {pytorch_dump_path}'''		)
				tokenizer.save_pretrained(__a		)


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








def      SCREAMING_SNAKE_CASE      (   lowerCAmelCase     ,							lowerCAmelCase     ,							lowerCAmelCase       ):
       _UpperCamelCase														=    index
       _UpperCamelCase														=    2 * index + 1
       _UpperCamelCase														=    2 * index + 2
       if left_index < heap_size and unsorted[left_index] > unsorted[largest]:
              _UpperCamelCase														=    left_index

       if right_index < heap_size and unsorted[right_index] > unsorted[largest]:
              _UpperCamelCase														=    right_index

       if largest != index:
              _UpperCamelCase							,		_UpperCamelCase														=    unsorted[index], unsorted[largest]
              heapify(lowerCAmelCase     ,							lowerCAmelCase     ,							lowerCAmelCase       )


def      SCREAMING_SNAKE_CASE      (   lowerCAmelCase       ):
       _UpperCamelCase														=    len(lowerCAmelCase       )
       for i in range(n // 2 - 1     ,							-1     ,							-1       ):
              heapify(lowerCAmelCase     ,							lowerCAmelCase     ,							lowerCAmelCase       )
       for i in range(n - 1     ,							0     ,							-1       ):
              _UpperCamelCase							,		_UpperCamelCase														=    unsorted[i], unsorted[0]
              heapify(lowerCAmelCase     ,							0     ,							lowerCAmelCase       )
       return unsorted


if __name__ == "__main__":
       lowercase     :			Union[str, Any]     						=	input("""Enter numbers separated by a comma:\n""").strip()
       lowercase     :			Dict     						=	[int(item) for item in user_input.split(""",""")]
       print(heap_sort(unsorted))






