code: 
  
  from collections import OrderedDict
  from typing import Mapping
  
  from ...configuration_utils import PretrainedConfig
  from ...onnx import OnnxConfig
  from ...utils import logging
  
  
  _A							    =	logging.get_logger(__name__)
  
  _A							    =	{
      """flaubert/flaubert_small_cased""": """https://huggingface.co/flaubert/flaubert_small_cased/resolve/main/config.json""",
      """flaubert/flaubert_base_uncased""": """https://huggingface.co/flaubert/flaubert_base_uncased/resolve/main/config.json""",
      """flaubert/flaubert_base_cased""": """https://huggingface.co/flaubert/flaubert_base_cased/resolve/main/config.json""",
      """flaubert/flaubert_large_cased""": """https://huggingface.co/flaubert/flaubert_large_cased/resolve/main/config.json""",
  }
  
  
  class 							_lowerCAmelCase		(     UpperCamelCase__	):
  				lowerCamelCase__									=    "flaubert"
  				lowerCamelCase__									=    {
  				    "hidden_size": "emb_dim",
  				    "num_attention_heads": "n_heads",
  				    "num_hidden_layers": "n_layers",
  				    "n_words": "vocab_size",  # For backward compatibility
  				}
  
  
  
  
  				def __init__( self		,		snake_case_=False		,		snake_case_=0.0		,		snake_case_=30_145		,		snake_case_=2_048		,		snake_case_=12		,		snake_case_=16		,		snake_case_=0.1		,		snake_case_=0.1		,		snake_case_=True		,		snake_case_=False		,		snake_case_=False		,		snake_case_=False		,		snake_case_=1		,		snake_case_=True		,		snake_case_=512		,		snake_case_=2_048**-0.5		,		snake_case_=1E-1_2		,		snake_case_=0.02		,		snake_case_=0		,		snake_case_=1		,		snake_case_=2		,		snake_case_=3		,		snake_case_=5		,		snake_case_=True		,		snake_case_="first"		,		snake_case_=True		,		snake_case_=None		,		snake_case_=True		,		snake_case_=0.1		,		snake_case_=5		,		snake_case_=5		,		snake_case_=0		,		snake_case_=0		,		snake_case_=2		,		snake_case_=0		,		**snake_case_		,		)    ->      Optional[Any]:
  											SCREAMING_SNAKE_CASE			: Optional[int]	     =pre_norm
  											SCREAMING_SNAKE_CASE			: Optional[Any]	     =layerdrop
  											SCREAMING_SNAKE_CASE			: List[Any]	     =vocab_size
  											SCREAMING_SNAKE_CASE			: Optional[Any]	     =emb_dim
  											SCREAMING_SNAKE_CASE			: Tuple	     =n_layers
  											SCREAMING_SNAKE_CASE			: Optional[Any]	     =n_heads
  											SCREAMING_SNAKE_CASE			: Tuple	     =dropout
  											SCREAMING_SNAKE_CASE			: Tuple	     =attention_dropout
  											SCREAMING_SNAKE_CASE			: Union[str, Any]	     =gelu_activation
  											SCREAMING_SNAKE_CASE			: List[Any]	     =sinusoidal_embeddings
  											SCREAMING_SNAKE_CASE			: Tuple	     =causal
  											SCREAMING_SNAKE_CASE			: int	     =asm
  											SCREAMING_SNAKE_CASE			: Union[str, Any]	     =n_langs
  											SCREAMING_SNAKE_CASE			: List[str]	     =use_lang_emb
  											SCREAMING_SNAKE_CASE			: int	     =layer_norm_eps
  											SCREAMING_SNAKE_CASE			: List[Any]	     =bos_index
  											SCREAMING_SNAKE_CASE			: int	     =eos_index
  											SCREAMING_SNAKE_CASE			: int	     =pad_index
  											SCREAMING_SNAKE_CASE			: List[Any]	     =unk_index
  											SCREAMING_SNAKE_CASE			: str	     =mask_index
  											SCREAMING_SNAKE_CASE			: Any	     =is_encoder
  											SCREAMING_SNAKE_CASE			: str	     =max_position_embeddings
  											SCREAMING_SNAKE_CASE			: List[str]	     =embed_init_std
  											SCREAMING_SNAKE_CASE			: List[str]	     =init_std
  											SCREAMING_SNAKE_CASE			: str	     =summary_type
  											SCREAMING_SNAKE_CASE			: str	     =summary_use_proj
  											SCREAMING_SNAKE_CASE			: Optional[Any]	     =summary_activation
  											SCREAMING_SNAKE_CASE			: Dict	     =summary_proj_to_labels
  											SCREAMING_SNAKE_CASE			: Optional[int]	     =summary_first_dropout
  											SCREAMING_SNAKE_CASE			: str	     =start_n_top
  											SCREAMING_SNAKE_CASE			: List[str]	     =end_n_top
  											SCREAMING_SNAKE_CASE			: Tuple	     =mask_token_id
  											SCREAMING_SNAKE_CASE			: List[Any]	     =lang_id
  
  											if "n_words" in kwargs:
  																		SCREAMING_SNAKE_CASE			: Tuple	     =kwargs['''n_words''']
  
  											super().__init__(pad_token_id=UpperCamelCase_		,		bos_token_id=UpperCamelCase_		,		**UpperCamelCase_							)
  
  
  
  
  
  
  
  class 							_lowerCAmelCase		(     UpperCamelCase__	):
  
  
  
  
  				@property
  				def     __a		( self							)    ->      int:
  											if self.task == "multiple-choice":
  																		SCREAMING_SNAKE_CASE			: str	     ={0: '''batch''', 1: '''choice''', 2: '''sequence'''}
  											else:
  																		SCREAMING_SNAKE_CASE			: Any	     ={0: '''batch''', 1: '''sequence'''}
  											return OrderedDict(
  											    [
  											        ('''input_ids''', dynamic_axis),
  											        ('''attention_mask''', dynamic_axis),
  											    ]							)
  
  
  
  
  
  
  
style_context: 
  
  
  
  
  from __future__ import annotations
  def 						lowerCAmelCase_       (	__a	,	__a	,	__a	,	__a )       ->			None:
  
  
  
  
  
  							"""simple docstring"""
  
  
  
  
  
  							SCREAMING_SNAKE_CASE     ,							SCREAMING_SNAKE_CASE			: Any	     =m - 1, 0
  							while i >= 0 and j < n:
  														if key == mat[i][j]:
  																					print(f'Key {key} found at row- {i + 1} column- {j + 1}' )
  																					return
  														if key < mat[i][j]:
  																					i -= 1
  														else:
  																					j += 1
  							print(f'Key {key} not found' )
  def 						lowerCAmelCase_       (	)       ->			None:
  
  
  
  
  
  							"""simple docstring"""
  
  
  
  
  
  							SCREAMING_SNAKE_CASE			: int	     =[[2, 5, 7], [4, 8, 13], [9, 11, 15], [12, 17, 20]]
  							SCREAMING_SNAKE_CASE			: List[str]	     =int(input('''Enter the element to be searched:''' ) )
  							print(__a )
  							search_in_a_sorted_matrix(__a	,	len(__a )	,	len(mat[0] )	,	__a )
  
  
  if __name__ == "__main__":
  							import doctest
  
  							doctest.testmod()
  							main()
  
  
  
  
  
  
  