



'''simple docstring'''



import argparse

import torch

from transformers import RemBertConfig, RemBertModel, load_tf_weights_in_rembert
from transformers.utils import logging


logging.set_verbosity_info()



def   __lowerCAmelCase					(							lowerCamelCase   :						Any				,		lowerCamelCase   :						Dict				,		lowerCamelCase   :						int					):






	'''simple docstring'''




	__lowerCAmelCase												=  RemBertConfig.from_json_file(lowerCamelCase					)
	print("Building PyTorch model from configuration: {}".format(str(lowerCamelCase					)					)					)
	__lowerCAmelCase												=  RemBertModel(lowerCamelCase					)

	# Load weights from tf checkpoint
	load_tf_weights_in_rembert(lowerCamelCase				,		lowerCamelCase				,		lowerCamelCase					)

	# Save pytorch-model
	print("Save PyTorch model to {}".format(lowerCamelCase					)					)
	torch.save(model.state_dict()				,		lowerCamelCase					)


if __name__ == "__main__":
	lowerCAmelCase	:		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(
	    '''--rembert_config_file''',
	    default=None,
	    type=str,
	    required=True,
	    help=(
	        '''The config json file corresponding to the pre-trained RemBERT 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.'''
	)
	lowerCAmelCase	:		List[str]				=   parser.parse_args()
	convert_rembert_tf_checkpoint_to_pytorch(args.tf_checkpoint_path, args.rembert_config_file, args.pytorch_dump_path)




'''simple docstring'''



from ...configuration_utils import PretrainedConfig
from ...utils import logging


lowerCAmelCase	:		Optional[Any]				=   logging.get_logger(__name__)

lowerCAmelCase	:		Optional[int]				=   {
    '''facebook/dpr-ctx_encoder-single-nq-base''': (
        '''https://huggingface.co/facebook/dpr-ctx_encoder-single-nq-base/resolve/main/config.json'''
    ),
    '''facebook/dpr-question_encoder-single-nq-base''': (
        '''https://huggingface.co/facebook/dpr-question_encoder-single-nq-base/resolve/main/config.json'''
    ),
    '''facebook/dpr-reader-single-nq-base''': (
        '''https://huggingface.co/facebook/dpr-reader-single-nq-base/resolve/main/config.json'''
    ),
    '''facebook/dpr-ctx_encoder-multiset-base''': (
        '''https://huggingface.co/facebook/dpr-ctx_encoder-multiset-base/resolve/main/config.json'''
    ),
    '''facebook/dpr-question_encoder-multiset-base''': (
        '''https://huggingface.co/facebook/dpr-question_encoder-multiset-base/resolve/main/config.json'''
    ),
    '''facebook/dpr-reader-multiset-base''': (
        '''https://huggingface.co/facebook/dpr-reader-multiset-base/resolve/main/config.json'''
    ),
}






class 					UpperCAmelCase__	(		UpperCamelCase__ ):
					a      :     Optional[Any]        =							"""dpr"""



					def __init__(    self			,				UpperCamelCase=3_0522			,				UpperCamelCase=768			,				UpperCamelCase=12			,				UpperCamelCase=12			,				UpperCamelCase=3072			,				UpperCamelCase="gelu"			,				UpperCamelCase=0.1			,				UpperCamelCase=0.1			,				UpperCamelCase=512			,				UpperCamelCase=2			,				UpperCamelCase=0.02			,				UpperCamelCase=1E-12			,				UpperCamelCase=0			,				UpperCamelCase="absolute"			,				UpperCamelCase = 0			,				**UpperCamelCase			,				)     ->			Tuple:
						super().__init__(pad_token_id=UpperCamelCase			,				**UpperCamelCase     )

						__lowerCAmelCase												=  vocab_size
						__lowerCAmelCase												=  hidden_size
						__lowerCAmelCase												=  num_hidden_layers
						__lowerCAmelCase												=  num_attention_heads
						__lowerCAmelCase												=  hidden_act
						__lowerCAmelCase												=  intermediate_size
						__lowerCAmelCase												=  hidden_dropout_prob
						__lowerCAmelCase												=  attention_probs_dropout_prob
						__lowerCAmelCase												=  max_position_embeddings
						__lowerCAmelCase												=  type_vocab_size
						__lowerCAmelCase												=  initializer_range
						__lowerCAmelCase												=  layer_norm_eps
						__lowerCAmelCase												=  projection_dim
						__lowerCAmelCase												=  position_embedding_type