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


UpperCAmelCase      		=					logging.get_logger(__name__)

UpperCAmelCase      		=					{
    '''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  __lowerCAmelCase	(							a_    ):



 '''simple docstring'''
 _lowerCamelCase    :						Dict					     =			'reformer'
 _lowerCamelCase    :						List[Any]					     =			['past_buckets_states']
 _lowerCamelCase    :						Any					     =			{}

 def __init__(      self							:		List[str]							,      lowerCamelCase							:		List[str]=6_4							,      lowerCamelCase							:		Any=["local", "lsh", "local", "lsh", "local", "lsh"]							,      lowerCamelCase							:		Optional[Any]=1.0							,      lowerCamelCase							:		Union[str, Any]=True							,      lowerCamelCase							:		Union[str, Any]=[6_4, 6_4]							,      lowerCamelCase							:		List[Any]=[6_4, 1_9_2]							,      lowerCamelCase							:		Any=0							,      lowerCamelCase							:		Union[str, Any]=2							,      lowerCamelCase							:		List[Any]=5_1_2							,      lowerCamelCase							:		str=None							,      lowerCamelCase							:		Dict="relu"							,      lowerCamelCase							:		Optional[Any]=0.0_5							,      lowerCamelCase							:		Dict=2_5_6							,      lowerCamelCase							:		str=0.0_2							,      lowerCamelCase							:		Optional[Any]=False							,      lowerCamelCase							:		Optional[int]=1e-12							,      lowerCamelCase							:		Tuple=1							,      lowerCamelCase							:		Union[str, Any]=0							,      lowerCamelCase							:		str=0.0_5							,      lowerCamelCase							:		Tuple=6_4							,      lowerCamelCase							:		Union[str, Any]=6_4							,      lowerCamelCase							:		Optional[int]=0.0							,      lowerCamelCase							:		List[Any]=1							,      lowerCamelCase							:		Optional[Any]=0							,      lowerCamelCase							:		Dict=4_0_9_6							,      lowerCamelCase							:		Optional[int]=1_2							,      lowerCamelCase							:		List[Any]=None							,      lowerCamelCase							:		int=1							,      lowerCamelCase							:		Union[str, Any]=0							,      lowerCamelCase							:		int=3_2_0							,      lowerCamelCase							:		Optional[Any]=False							,      lowerCamelCase							:		Tuple=True							,      lowerCamelCase							:		int=None							,      **lowerCamelCase							:		Any							,      )			->				str:
        _UpperCamelCase  :							List[str]	    =	hash_seed
        _UpperCamelCase  :							List[str]	    =	vocab_size
        _UpperCamelCase  :							List[str]	    =	attention_head_size
        _UpperCamelCase  :							int	    =	hidden_size
        _UpperCamelCase  :							Optional[int]	    =	num_attention_heads
        _UpperCamelCase  :							Optional[int]	    =	num_hashes
        _UpperCamelCase  :							Optional[int]	    =	len(lowerCamelCase	)
        _UpperCamelCase  :							Union[str, Any]	    =	tuple(lowerCamelCase	) if isinstance(lowerCamelCase							,      lowerCamelCase	) else num_buckets
        _UpperCamelCase  :							Optional[int]	    =	lsh_attn_chunk_length
        _UpperCamelCase  :							str	    =	local_attn_chunk_length
        _UpperCamelCase  :							Union[str, Any]	    =	lsh_num_chunks_after
        _UpperCamelCase  :							Dict	    =	lsh_num_chunks_before
        _UpperCamelCase  :							Optional[int]	    =	local_num_chunks_after
        _UpperCamelCase  :							Any	    =	local_num_chunks_before
        _UpperCamelCase  :							Optional[int]	    =	hidden_act
        _UpperCamelCase  :							str	    =	feed_forward_size
        _UpperCamelCase  :							Optional[Any]	    =	hidden_dropout_prob
        _UpperCamelCase  :							List[str]	    =	lsh_attention_probs_dropout_prob
        _UpperCamelCase  :							str	    =	local_attention_probs_dropout_prob
        _UpperCamelCase  :							Union[str, Any]	    =	max_position_embeddings
        _UpperCamelCase  :							List[Any]	    =	initializer_range
        _UpperCamelCase  :							int	    =	layer_norm_eps
        _UpperCamelCase  :							List[str]	    =	axial_pos_embds
        _UpperCamelCase  :							List[str]	    =	tuple(lowerCamelCase	)
        _UpperCamelCase  :							Any	    =	tuple(lowerCamelCase	)
        _UpperCamelCase  :							Optional[Any]	    =	axial_norm_std
        _UpperCamelCase  :							Optional[int]	    =	chunk_size_lm_head
        _UpperCamelCase  :							Dict	    =	attn_layers
        _UpperCamelCase  :							Union[str, Any]	    =	use_cache
        _UpperCamelCase  :							Optional[int]	    =	classifier_dropout
        super().__init__(
            pad_token_id=lowerCamelCase							,      eos_token_id=lowerCamelCase							,      is_decoder=lowerCamelCase							,      tie_word_embeddings=lowerCamelCase							,      **lowerCamelCase							,      )




'''simple docstring'''




from typing import Optional, Tuple

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_openai import OpenAIGPTTokenizer


__snake_case  : Union[str, Any]		       =    logging.get_logger(__name__)

__snake_case  : Union[str, Any]		       =    {'vocab_file': 'vocab.json', 'merges_file': 'merges.txt', 'tokenizer_file': 'tokenizer.json'}

__snake_case  : List[str]		       =    {
    'vocab_file': {'openai-gpt': 'https://huggingface.co/openai-gpt/resolve/main/vocab.json'},
    'merges_file': {'openai-gpt': 'https://huggingface.co/openai-gpt/resolve/main/merges.txt'},
    'tokenizer_file': {'openai-gpt': 'https://huggingface.co/openai-gpt/resolve/main/tokenizer.json'},
}

__snake_case  : Optional[int]		       =    {
    'openai-gpt': 512,
}




class       __UpperCAmelCase							(							_UpperCamelCase	):





       '''simple docstring'''



       __lowercase   :   int  					=							VOCAB_FILES_NAMES
       __lowercase   :   int  					=							PRETRAINED_VOCAB_FILES_MAP
       __lowercase   :   str  					=							PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
       __lowercase   :   Optional[Any]  					=							['input_ids', 'attention_mask']
       __lowercase   :   List[Any]  					=							OpenAIGPTTokenizer

       def __init__( self       ,	_SCREAMING_SNAKE_CASE=None       ,	_SCREAMING_SNAKE_CASE=None       ,	_SCREAMING_SNAKE_CASE=None       ,	_SCREAMING_SNAKE_CASE="<unk>"       ,	**_SCREAMING_SNAKE_CASE					)						->	Optional[Any]:
           super().__init__(_SCREAMING_SNAKE_CASE       ,	_SCREAMING_SNAKE_CASE       ,	tokenizer_file=_SCREAMING_SNAKE_CASE       ,	unk_token=_SCREAMING_SNAKE_CASE       ,	**_SCREAMING_SNAKE_CASE					)

       @property
       def    __A			( self					)						->	Optional[Any]:
           return True

       def    __A			( self       ,	_SCREAMING_SNAKE_CASE       ,	_SCREAMING_SNAKE_CASE = None					)						->	Tuple[str]:
           A_      =  self._tokenizer.model.save(_SCREAMING_SNAKE_CASE       ,	name=_SCREAMING_SNAKE_CASE					)
           return tuple(_SCREAMING_SNAKE_CASE					)






