





import argparse

import torch

from ...utils import logging
from . import AlbertConfig, AlbertForPreTraining, load_tf_weights_in_albert


logging.set_verbosity_info()







def   __lowerCamelCase   (				__a  :List[str]       ,	__a  :Optional[int]       ,	__a  :List[Any]       )						->							Any:






		"""simple docstring"""

		A__     =  AlbertConfig.from_json_file(__a       )
		print(F'Building PyTorch model from configuration: {config}'       )
		A__     =  AlbertForPreTraining(__a       )

		# Load weights from tf checkpoint
		load_tf_weights_in_albert(__a       ,	__a       ,	__a       )

		# Save pytorch-model
		print(F'Save PyTorch model to {pytorch_dump_path}'       )
		torch.save(model.state_dict()       ,	__a       )


if __name__ == "__main__":
					A       :   List[str]					= 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(
					    '''--albert_config_file''',
					    default=None,
					    type=str,
					    required=True,
					    help=(
					        '''The config json file corresponding to the pre-trained ALBERT 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       :   Optional[Any]					= parser.parse_args()
					convert_tf_checkpoint_to_pytorch(args.tf_checkpoint_path, args.albert_config_file, args.pytorch_dump_path)










def   __lowerCamelCase   (				__a  :str       )						->							bool:






		"""simple docstring"""

		A__     =  0
		for ch in input_str:
				A__     =  ord(__a       )
				A__     =  pow(2       ,	__a       )

				# If we already turned on bit for current character's unicode
				if bitmap >> ch_unicode & 1 == 1:
						return False
				bitmap |= ch_bit_index_on
		return True


if __name__ == "__main__":
					import doctest

					doctest.testmod()



