


'''simple docstring'''



import argparse

import torch

from transformers import LxmertConfig, LxmertForPreTraining, load_tf_weights_in_lxmert
from transformers.utils import logging


logging.set_verbosity_info()


def 				lowerCamelCase__				(	A       :      Any				,       A       :      List[str]				,       A       :      Optional[Any]					):




						'''simple docstring'''






						UpperCAmelCase					    =     LxmertConfig.from_json_file(A					)
						print(f"""Building PyTorch model from configuration: {config}"""					)
						UpperCAmelCase					    =     LxmertForPreTraining(A					)

						# Load weights from tf checkpoint
						load_tf_weights_in_lxmert(A				,       A				,       A					)

						# Save pytorch-model
						print(f"""Save PyTorch model to {pytorch_dump_path}"""					)
						torch.save(model.state_dict()				,       A					)


if __name__ == "__main__":
	_lowercase      :      Tuple            =					argparse.ArgumentParser()
	# Required parameters
	parser.add_argument(
	    """--tf_checkpoint_path""", default=None, type=str, required=True, help="""Path to the TensorFlow checkpoint path."""
	)
	parser.add_argument(
	    """--config_file""",
	    default=None,
	    type=str,
	    required=True,
	    help="""The config json file corresponding to the pre-trained model. \nThis specifies the model architecture.""",
	)
	parser.add_argument(
	    """--pytorch_dump_path""", default=None, type=str, required=True, help="""Path to the output PyTorch model."""
	)
	_lowercase      :      Dict            =					parser.parse_args()
	convert_tf_checkpoint_to_pytorch(args.tf_checkpoint_path, args.config_file, args.pytorch_dump_path)









'''simple docstring'''



from __future__ import annotations

from collections import namedtuple
from dataclasses import dataclass






@dataclass
class 	UpperCamelCase__:
				__magic_name__    :				int
				__magic_name__    :				TreeNode | None  		=	None
				__magic_name__    :				TreeNode | None  		=	None







_lowercase      :      Tuple            =					namedtuple("""CoinsDistribResult""", """moves excess""")


def 				lowerCamelCase__				(	A       :      TreeNode | None					):




						'''simple docstring'''






						if root is None:
												return 0

						# Validation
						def count_nodes(A       :      TreeNode | None					) -> int:
												if node is None:
																		return 0

												return count_nodes(node.left					) + count_nodes(node.right					) + 1

						def count_coins(A       :      TreeNode | None					) -> int:
												if node is None:
																		return 0

												return count_coins(node.left					) + count_coins(node.right					) + node.data

						if count_nodes(A					) != count_coins(A					):
												raise ValueError('''The nodes number should be same as the number of coins'''					)

						# Main calculation
						def get_distrib(A       :      TreeNode | None					) -> CoinsDistribResult:

												if node is None:
																		return CoinsDistribResult(0				,       1					)

												UpperCAmelCase    ,    UpperCAmelCase					    =     get_distrib(node.left					)
												UpperCAmelCase    ,    UpperCAmelCase					    =     get_distrib(node.right					)

												UpperCAmelCase					    =     1 - left_distrib_excess
												UpperCAmelCase					    =     1 - right_distrib_excess

												UpperCAmelCase					    =     (
												    left_distrib_moves
												    + right_distrib_moves
												    + abs(A					)
												    + abs(A					)
												)
												UpperCAmelCase					    =     node.data - coins_to_left - coins_to_right

												return CoinsDistribResult(A				,       A					)

						return get_distrib(A					)[0]


if __name__ == "__main__":
	import doctest

	doctest.testmod()





