code: 
  
  
  
  
  
  '''simple docstring'''
  
  
  from ...configuration_utils import PretrainedConfig
  from ...utils import logging
  
  
  _lowerCamelCase				    =       logging.get_logger(__name__)
  
  _lowerCamelCase				    =       {
      'facebook/opt-125m': 'https://huggingface.co/facebook/opt-125m/blob/main/config.json',
      'facebook/opt-350m': 'https://huggingface.co/facebook/opt-350m/blob/main/config.json',
      'facebook/opt-1.3b': 'https://huggingface.co/facebook/opt-1.3b/blob/main/config.json',
      'facebook/opt-2.7b': 'https://huggingface.co/facebook/opt-2.7b/blob/main/config.json',
      'facebook/opt-6.7b': 'https://huggingface.co/facebook/opt-6.7b/blob/main/config.json',
      'facebook/opt-13b': 'https://huggingface.co/facebook/opt-13b/blob/main/config.json',
  }
  
  
  
  class 							__UpperCAmelCase  (       A__						):
  
  
  
  
  
  
  
  		'''simple docstring'''
  
  
  
  
  
  
  
  		__lowerCAmelCase 				=    '''opt'''
  		__lowerCAmelCase 				=    ['''past_key_values''']
  
  
  
  
  
  
  
  		def __init__(self						:      List[str]      ,      _lowerCAmelCase						:      Union[str, Any]=5_0272      ,      _lowerCAmelCase						:      Optional[int]=768      ,      _lowerCAmelCase						:      int=12      ,      _lowerCAmelCase						:      Optional[int]=3072      ,      _lowerCAmelCase						:      str=2048      ,      _lowerCAmelCase						:      Dict=True      ,      _lowerCAmelCase						:      List[Any]=False      ,      _lowerCAmelCase						:      Union[str, Any]=None      ,      _lowerCAmelCase						:      Any=0.1      ,      _lowerCAmelCase						:      Optional[int]=0.0      ,      _lowerCAmelCase						:      str=12      ,      _lowerCAmelCase						:      Optional[Any]="relu"      ,      _lowerCAmelCase						:      Optional[Any]=0.0      ,      _lowerCAmelCase						:      int=0.02      ,      _lowerCAmelCase						:      int=True      ,      _lowerCAmelCase						:      Optional[int]=1      ,      _lowerCAmelCase						:      int=2      ,      _lowerCAmelCase						:      Dict=2      ,      _lowerCAmelCase						:      Union[str, Any]=True      ,      _lowerCAmelCase						:      List[str]=True      ,      **_lowerCAmelCase						:      int      ,      ):
  			super().__init__(
  			    pad_token_id=_lowerCAmelCase      ,      bos_token_id=_lowerCAmelCase      ,      eos_token_id=_lowerCAmelCase      ,      **_lowerCAmelCase      ,      )
  			A							  =      vocab_size
  			A							  =      max_position_embeddings
  			A							  =      num_attention_heads
  			A							  =      word_embed_proj_dim if word_embed_proj_dim is not None else hidden_size
  			A							  =      ffn_dim
  			A							  =      hidden_size
  			A							  =      num_hidden_layers
  			A							  =      dropout
  			A							  =      attention_dropout
  			A							  =      activation_function
  			A							  =      init_std
  			A							  =      layerdrop
  			A							  =      use_cache
  			A							  =      do_layer_norm_before
  			# We keep these variables at `True` for backward compatibility.
  			A							  =      enable_bias
  			A							  =      layer_norm_elementwise_affine
  
  			# Note that the only purpose of `_remove_final_layer_norm` is to keep backward compatibility
  			# with checkpoints that have been fine-tuned before transformers v4.20.1
  			# see https://github.com/facebookresearch/metaseq/pull/164
  			A							  =      _remove_final_layer_norm
  
  
style_context: 
  
  
  
  
  
  '''simple docstring'''
  
  
  from __future__ import annotations
  
  
  
  class 							__UpperCAmelCase  :
  
  
  
  
  
  
  
  		'''simple docstring'''
  
  
  
  
  
  
  
  		def __init__(self						:      Any      ,      _lowerCAmelCase						:      int      ):
  			A							  =      value
  			A							  =      None
  			A							  =      None
  
  
  
  
  
  
  class 							__UpperCAmelCase  :
  
  
  
  
  
  
  
  		'''simple docstring'''
  
  
  
  
  
  
  
  		__lowerCAmelCase 				=    42
  
  
  
  
  
  
  
  		def __init__(self						:      List[str]      ):
  			A							  =      0
  
  
  
  
  
  
  
  		def        A     (self						:      Dict      ,      _lowerCAmelCase						:      Node | None      ,      _lowerCAmelCase						:      int      ):
  			if node is None:
  				return
  
  			if path_sum == self.target:
  				self.paths += 1
  
  			if node.left:
  				self.depth_first_search(node.left      ,      path_sum + node.left.value      )
  			if node.right:
  				self.depth_first_search(node.right      ,      path_sum + node.right.value      )
  
  
  
  
  
  
  
  		def        A     (self						:      Optional[Any]      ,      _lowerCAmelCase						:      Node | None      ,      _lowerCAmelCase						:      int | None = None      ):
  			if node is None:
  				return 0
  			if target is not None:
  				A							  =      target
  
  			self.depth_first_search(_lowerCAmelCase      ,      node.value      )
  			self.path_sum(node.left      )
  			self.path_sum(node.right      )
  
  			return self.paths
  
  
  if __name__ == "__main__":
  				import doctest
  
  				doctest.testmod()
  
  