code: 
  
  
  from ...configuration_utils import PretrainedConfig
  from ...utils import logging
  
  
  UpperCAmelCase      :						Optional[int]    =		logging.get_logger(__name__)
  
  UpperCAmelCase      :						Dict    =		{
      "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					(       a_     ):
  
  
  
  		"""simple docstring"""
  
  		UpperCamelCase    :				Union[str, Any] 					=		"reformer"
  		UpperCamelCase    :				List[Any] 					=		["past_buckets_states"]
  		UpperCamelCase    :				Union[str, Any] 					=		{}
  
  
  
  
  
  
  
  		def __init__(   self		,			A=64		,			A=["local", "lsh", "local", "lsh", "local", "lsh"]		,			A=1.0		,			A=True		,			A=[64, 64]		,			A=[64, 1_92]		,			A=0		,			A=2		,			A=5_12		,			A=None		,			A="relu"		,			A=0.05		,			A=2_56		,			A=0.02		,			A=False		,			A=1e-1_2		,			A=1		,			A=0		,			A=0.05		,			A=64		,			A=64		,			A=0.0		,			A=1		,			A=0		,			A=40_96		,			A=12		,			A=None		,			A=1		,			A=0		,			A=3_20		,			A=False		,			A=True		,			A=None		,			**A		,			)     ->   Union[str, Any]:
  
  
  
  
  
  
  
  					'''simple docstring'''
  
  
  
  
  
  
  
  					lowerCamelCase								=     hash_seed
  					lowerCamelCase								=     vocab_size
  					lowerCamelCase								=     attention_head_size
  					lowerCamelCase								=     hidden_size
  					lowerCamelCase								=     num_attention_heads
  					lowerCamelCase								=     num_hashes
  					lowerCamelCase								=     len(A  )
  					lowerCamelCase								=     tuple(A  ) if isinstance(A		,			A  ) else num_buckets
  					lowerCamelCase								=     lsh_attn_chunk_length
  					lowerCamelCase								=     local_attn_chunk_length
  					lowerCamelCase								=     lsh_num_chunks_after
  					lowerCamelCase								=     lsh_num_chunks_before
  					lowerCamelCase								=     local_num_chunks_after
  					lowerCamelCase								=     local_num_chunks_before
  					lowerCamelCase								=     hidden_act
  					lowerCamelCase								=     feed_forward_size
  					lowerCamelCase								=     hidden_dropout_prob
  					lowerCamelCase								=     lsh_attention_probs_dropout_prob
  					lowerCamelCase								=     local_attention_probs_dropout_prob
  					lowerCamelCase								=     max_position_embeddings
  					lowerCamelCase								=     initializer_range
  					lowerCamelCase								=     layer_norm_eps
  					lowerCamelCase								=     axial_pos_embds
  					lowerCamelCase								=     tuple(A  )
  					lowerCamelCase								=     tuple(A  )
  					lowerCamelCase								=     axial_norm_std
  					lowerCamelCase								=     chunk_size_lm_head
  					lowerCamelCase								=     attn_layers
  					lowerCamelCase								=     use_cache
  					lowerCamelCase								=     classifier_dropout
  					super().__init__(
  					    pad_token_id=A		,			eos_token_id=A		,			is_decoder=A		,			tie_word_embeddings=A		,			**A		,			)
  
  
style_context: 
  
  
  import abc
  import copy
  import dataclasses
  from dataclasses import dataclass
  from typing import ClassVar, Dict, Type, TypeVar
  
  from ..features import Features
  
  
  UpperCAmelCase      :						List[Any]    =		TypeVar("T", bound="TaskTemplate")
  
  
  
  
  
  
  
  @dataclass(frozen=a_     )
  class 					__lowercase					(       abc.ABC     ):
  
  
  
  		"""simple docstring"""
  
  		UpperCamelCase    :				str
  		UpperCamelCase    :				ClassVar[Features]
  		UpperCamelCase    :				ClassVar[Features]
  
  
  
  
  
  
  
  		def 				__A      (   self		,			A  )     ->   T:
  
  
  
  
  
  
  
  					'''simple docstring'''
  
  
  
  
  
  
  
  					return copy.deepcopy(self  )
  
  
  
  
  
  
  
  		@property
  		def 				__A      (   self  )     ->   Features:
  
  
  
  
  
  
  
  					'''simple docstring'''
  
  
  
  
  
  
  
  					return Features(**self.input_schema		,			**self.label_schema  )
  
  
  
  
  
  
  
  		@property
  		@abc.abstractmethod
  		def 				__A      (   self  )     ->   Dict[str, str]:
  
  
  
  
  
  
  
  					'''simple docstring'''
  
  
  
  
  
  
  
  					raise NotImplementedError
  
  
  
  
  
  
  
  		@classmethod
  		def 				__A      (   cls		,			A  )     ->   T:
  
  
  
  
  
  
  
  					'''simple docstring'''
  
  
  
  
  
  
  
  					lowerCamelCase								=     {f.name for f in dataclasses.fields(cls  )}
  					return cls(**{k: v for k, v in template_dict.items() if k in field_names}  )
  
  