code: 
  
  
  from collections import OrderedDict
  from typing import Mapping
  
  from ...configuration_utils import PretrainedConfig
  from ...onnx import OnnxConfig
  from ...utils import logging
  
  
  UpperCAmelCase      :						Any    =		logging.get_logger(__name__)
  
  UpperCAmelCase      :						Any    =		{
      "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 					__lowercase					(       a_     ):
  
  
  
  		"""simple docstring"""
  
  		UpperCamelCase    :				Any 					=		"flaubert"
  		UpperCamelCase    :				Dict 					=		{
  		    "hidden_size": "emb_dim",
  		    "num_attention_heads": "n_heads",
  		    "num_hidden_layers": "n_layers",
  		    "n_words": "vocab_size",  # For backward compatibility
  		}
  
  
  
  
  
  
  
  		def __init__(   self		,			A=False		,			A=0.0		,			A=3_01_45		,			A=20_48		,			A=12		,			A=16		,			A=0.1		,			A=0.1		,			A=True		,			A=False		,			A=False		,			A=False		,			A=1		,			A=True		,			A=5_12		,			A=20_48**-0.5		,			A=1e-1_2		,			A=0.02		,			A=0		,			A=1		,			A=2		,			A=3		,			A=5		,			A=True		,			A="first"		,			A=True		,			A=None		,			A=True		,			A=0.1		,			A=5		,			A=5		,			A=0		,			A=0		,			A=2		,			A=0		,			**A		,			)     ->   int:
  
  
  
  
  
  
  
  					'''simple docstring'''
  
  
  
  
  
  
  
  					lowerCamelCase								=     pre_norm
  					lowerCamelCase								=     layerdrop
  					lowerCamelCase								=     vocab_size
  					lowerCamelCase								=     emb_dim
  					lowerCamelCase								=     n_layers
  					lowerCamelCase								=     n_heads
  					lowerCamelCase								=     dropout
  					lowerCamelCase								=     attention_dropout
  					lowerCamelCase								=     gelu_activation
  					lowerCamelCase								=     sinusoidal_embeddings
  					lowerCamelCase								=     causal
  					lowerCamelCase								=     asm
  					lowerCamelCase								=     n_langs
  					lowerCamelCase								=     use_lang_emb
  					lowerCamelCase								=     layer_norm_eps
  					lowerCamelCase								=     bos_index
  					lowerCamelCase								=     eos_index
  					lowerCamelCase								=     pad_index
  					lowerCamelCase								=     unk_index
  					lowerCamelCase								=     mask_index
  					lowerCamelCase								=     is_encoder
  					lowerCamelCase								=     max_position_embeddings
  					lowerCamelCase								=     embed_init_std
  					lowerCamelCase								=     init_std
  					lowerCamelCase								=     summary_type
  					lowerCamelCase								=     summary_use_proj
  					lowerCamelCase								=     summary_activation
  					lowerCamelCase								=     summary_proj_to_labels
  					lowerCamelCase								=     summary_first_dropout
  					lowerCamelCase								=     start_n_top
  					lowerCamelCase								=     end_n_top
  					lowerCamelCase								=     mask_token_id
  					lowerCamelCase								=     lang_id
  
  					if "n_words" in kwargs:
  								lowerCamelCase								=     kwargs["""n_words"""]
  
  					super().__init__(pad_token_id=A		,			bos_token_id=A		,			**A  )
  
  
  
  
  
  
  
  class 					__lowercase					(       a_     ):
  
  
  
  		"""simple docstring"""
  
  		@property
  		def 				__A      (   self  )     ->   Mapping[str, Mapping[int, str]]:
  
  
  
  
  
  
  
  					'''simple docstring'''
  
  
  
  
  
  
  
  					if self.task == "multiple-choice":
  								lowerCamelCase								=     {0: """batch""", 1: """choice""", 2: """sequence"""}
  					else:
  								lowerCamelCase								=     {0: """batch""", 1: """sequence"""}
  					return OrderedDict(
  					    [
  					        ("""input_ids""", dynamic_axis),
  					        ("""attention_mask""", dynamic_axis),
  					    ]  )
  
  
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}  )
  
  