






import argparse

import torch

from transformers import RoFormerConfig, RoFormerForMaskedLM, load_tf_weights_in_roformer
from transformers.utils import logging


logging.set_verbosity_info()


def __A					(   __lowerCAmelCase				,	__lowerCAmelCase				,	__lowerCAmelCase			)->						Union[str, Any]:





						"""simple docstring"""



						_UpperCAmelCase             =    RoFormerConfig.from_json_file(__lowerCAmelCase			)
						print(F"""Building PyTorch model from configuration: {config}"""			)
						_UpperCAmelCase             =    RoFormerForMaskedLM(__lowerCAmelCase			)

						# Load weights from tf checkpoint
						load_tf_weights_in_roformer(__lowerCAmelCase				,	__lowerCAmelCase				,	__lowerCAmelCase			)

						# Save pytorch-model
						print(F"""Save PyTorch model to {pytorch_dump_path}"""			)
						torch.save(model.state_dict()				,	__lowerCAmelCase				,	_use_new_zipfile_serialization=__lowerCAmelCase			)


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 path.'''
		)
		parser.add_argument(
		    '''--bert_config_file''',
		    default=None,
		    type=str,
		    required=True,
		    help=(
		        '''The config json file corresponding to the pre-trained BERT model. \n'''
		        '''This specifies the model architecture.'''
		    ),
		)
		parser.add_argument(
		    '''--pytorch_dump_path''', default=None, type=str, required=True, help='''Path to the output PyTorch model.'''
		)
		_a   			=						parser.parse_args()
		convert_tf_checkpoint_to_pytorch(args.tf_checkpoint_path, args.bert_config_file, args.pytorch_dump_path)








from itertools import combinations_with_replacement


def __A					(   __lowerCAmelCase = 100			)->						int:





						"""simple docstring"""



						_UpperCAmelCase             =    [*list(range(1				,	21			)			), 25]
						_UpperCAmelCase             =    [2 * x for x in range(1				,	21			)] + [50]
						_UpperCAmelCase             =    [3 * x for x in range(1				,	21			)]
						_UpperCAmelCase             =    singles + doubles + triples + [0]

						_UpperCAmelCase             =    0
						_UpperCAmelCase             =    42
						_UpperCAmelCase             =    42
						_UpperCAmelCase             =    42
						_UpperCAmelCase             =    42

						for double in doubles:
												for throwa, throwa in combinations_with_replacement(__lowerCAmelCase				,	2			):
																		_UpperCAmelCase             =    double + throwa + throwa
																		if checkout_total < limit:
																								num_checkouts += 1

						return num_checkouts


if __name__ == "__main__":
		print(F'''{solution() = }''')
