




import argparse

import torch

from transformers import ElectraConfig, ElectraForMaskedLM, ElectraForPreTraining, load_tf_weights_in_electra
from transformers.utils import logging


logging.set_verbosity_info()







def  lowerCAmelCase  (	UpperCAmelCase,	UpperCAmelCase,	UpperCAmelCase,	UpperCAmelCase       )  ->Tuple:






					"""simple docstring"""






					__magic_name__					:							List[Any]		   =							ElectraConfig.from_json_file(UpperCAmelCase       )
					print(F'''Building PyTorch model from configuration: {config}'''       )

					if discriminator_or_generator == "discriminator":
										__magic_name__					:							Union[str, Any]		   =							ElectraForPreTraining(UpperCAmelCase       )
					elif discriminator_or_generator == "generator":
										__magic_name__					:							str		   =							ElectraForMaskedLM(UpperCAmelCase       )
					else:
										raise ValueError('''The discriminator_or_generator argument should be either \'discriminator\' or \'generator\''''       )

					# Load weights from tf checkpoint
					load_tf_weights_in_electra(
					    UpperCAmelCase,	UpperCAmelCase,	UpperCAmelCase,	discriminator_or_generator=UpperCAmelCase       )

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


if __name__ == "__main__":
				lowercase_		=							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.'''
				)
				parser.add_argument(
				    '''--discriminator_or_generator''',
				    default=None,
				    type=str,
				    required=True,
				    help=(
				        '''Whether to export the generator or the discriminator. Should be a string, either \'discriminator\' or '''
				        '''\'generator\'.'''
				    ),
				)
				lowercase_		=							parser.parse_args()
				convert_tf_checkpoint_to_pytorch(
				    args.tf_checkpoint_path, args.config_file, args.pytorch_dump_path, args.discriminator_or_generator
				)







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


lowerCAmelCase__       :	Any     				=logging.get_logger(__name__)

lowerCAmelCase__       :	Union[str, Any]     				={
    'google/reformer-crime-and-punishment': (
        'https://huggingface.co/google/reformer-crime-and-punishment/resolve/main/config.json'
    ),
    'google/reformer-enwik8': 'https://huggingface.co/google/reformer-enwik8/resolve/main/config.json',
}







class      __lowercase  (__SCREAMING_SNAKE_CASE   ):





							"""simple docstring"""







							_UpperCAmelCase     =		"""reformer"""
							_UpperCAmelCase     =		["""past_buckets_states"""]
							_UpperCAmelCase     =		{}






							def __init__(	self       ,		lowerCAmelCase__=6_4       ,		lowerCAmelCase__=["local", "lsh", "local", "lsh", "local", "lsh"]       ,		lowerCAmelCase__=1.0       ,		lowerCAmelCase__=True       ,		lowerCAmelCase__=[6_4, 6_4]       ,		lowerCAmelCase__=[6_4, 1_9_2]       ,		lowerCAmelCase__=0       ,		lowerCAmelCase__=2       ,		lowerCAmelCase__=5_1_2       ,		lowerCAmelCase__=None       ,		lowerCAmelCase__="relu"       ,		lowerCAmelCase__=0.05       ,		lowerCAmelCase__=2_5_6       ,		lowerCAmelCase__=0.02       ,		lowerCAmelCase__=False       ,		lowerCAmelCase__=1E-12       ,		lowerCAmelCase__=1       ,		lowerCAmelCase__=0       ,		lowerCAmelCase__=0.05       ,		lowerCAmelCase__=6_4       ,		lowerCAmelCase__=6_4       ,		lowerCAmelCase__=0.0       ,		lowerCAmelCase__=1       ,		lowerCAmelCase__=0       ,		lowerCAmelCase__=4_0_9_6       ,		lowerCAmelCase__=1_2       ,		lowerCAmelCase__=None       ,		lowerCAmelCase__=1       ,		lowerCAmelCase__=0       ,		lowerCAmelCase__=3_2_0       ,		lowerCAmelCase__=False       ,		lowerCAmelCase__=True       ,		lowerCAmelCase__=None       ,		**lowerCAmelCase__       ,		):





										"""simple docstring"""




										SCREAMING_SNAKE_CASE_						:			str       						= hash_seed
										SCREAMING_SNAKE_CASE_						:			Union[str, Any]       						= vocab_size
										SCREAMING_SNAKE_CASE_						:			Any       						= attention_head_size
										SCREAMING_SNAKE_CASE_						:			List[Any]       						= hidden_size
										SCREAMING_SNAKE_CASE_						:			Optional[Any]       						= num_attention_heads
										SCREAMING_SNAKE_CASE_						:			Any       						= num_hashes
										SCREAMING_SNAKE_CASE_						:			int       						= len(lowerCAmelCase__    )
										SCREAMING_SNAKE_CASE_						:			str       						= tuple(lowerCAmelCase__    ) if isinstance(lowerCAmelCase__       ,		lowerCAmelCase__    ) else num_buckets
										SCREAMING_SNAKE_CASE_						:			int       						= lsh_attn_chunk_length
										SCREAMING_SNAKE_CASE_						:			List[str]       						= local_attn_chunk_length
										SCREAMING_SNAKE_CASE_						:			Tuple       						= lsh_num_chunks_after
										SCREAMING_SNAKE_CASE_						:			str       						= lsh_num_chunks_before
										SCREAMING_SNAKE_CASE_						:			List[Any]       						= local_num_chunks_after
										SCREAMING_SNAKE_CASE_						:			Any       						= local_num_chunks_before
										SCREAMING_SNAKE_CASE_						:			Any       						= hidden_act
										SCREAMING_SNAKE_CASE_						:			Dict       						= feed_forward_size
										SCREAMING_SNAKE_CASE_						:			Optional[int]       						= hidden_dropout_prob
										SCREAMING_SNAKE_CASE_						:			Tuple       						= lsh_attention_probs_dropout_prob
										SCREAMING_SNAKE_CASE_						:			Any       						= local_attention_probs_dropout_prob
										SCREAMING_SNAKE_CASE_						:			str       						= max_position_embeddings
										SCREAMING_SNAKE_CASE_						:			Optional[int]       						= initializer_range
										SCREAMING_SNAKE_CASE_						:			Optional[Any]       						= layer_norm_eps
										SCREAMING_SNAKE_CASE_						:			List[str]       						= axial_pos_embds
										SCREAMING_SNAKE_CASE_						:			List[str]       						= tuple(lowerCAmelCase__    )
										SCREAMING_SNAKE_CASE_						:			Tuple       						= tuple(lowerCAmelCase__    )
										SCREAMING_SNAKE_CASE_						:			Dict       						= axial_norm_std
										SCREAMING_SNAKE_CASE_						:			Any       						= chunk_size_lm_head
										SCREAMING_SNAKE_CASE_						:			int       						= attn_layers
										SCREAMING_SNAKE_CASE_						:			Union[str, Any]       						= use_cache
										SCREAMING_SNAKE_CASE_						:			Tuple       						= classifier_dropout
										super().__init__(
										    pad_token_id=lowerCAmelCase__       ,		eos_token_id=lowerCAmelCase__       ,		is_decoder=lowerCAmelCase__       ,		tie_word_embeddings=lowerCAmelCase__       ,		**lowerCAmelCase__       ,		)





