


from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


_A		:					int          =							logging.get_logger(__name__)

_A		:					Dict          =							{
    '''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 							a       (      _UpperCAmelCase ):
     UpperCAmelCase__			:	int       =						"flaubert"
     UpperCAmelCase__			:	List[str]       =						{
         "hidden_size": "emb_dim",
         "num_attention_heads": "n_heads",
         "num_hidden_layers": "n_layers",
         "n_words": "vocab_size",  # For backward compatibility
     }





     def __init__(     self       :					Any     ,						SCREAMING_SNAKE_CASE_       :					Any=False     ,						SCREAMING_SNAKE_CASE_       :					int=0.0     ,						SCREAMING_SNAKE_CASE_       :					List[Any]=30145     ,						SCREAMING_SNAKE_CASE_       :					Optional[Any]=2048     ,						SCREAMING_SNAKE_CASE_       :					Optional[int]=12     ,						SCREAMING_SNAKE_CASE_       :					str=16     ,						SCREAMING_SNAKE_CASE_       :					int=0.1     ,						SCREAMING_SNAKE_CASE_       :					Union[str, Any]=0.1     ,						SCREAMING_SNAKE_CASE_       :					str=True     ,						SCREAMING_SNAKE_CASE_       :					Union[str, Any]=False     ,						SCREAMING_SNAKE_CASE_       :					List[Any]=False     ,						SCREAMING_SNAKE_CASE_       :					Optional[int]=False     ,						SCREAMING_SNAKE_CASE_       :					int=1     ,						SCREAMING_SNAKE_CASE_       :					Optional[Any]=True     ,						SCREAMING_SNAKE_CASE_       :					str=512     ,						SCREAMING_SNAKE_CASE_       :					Tuple=2048**-0.5     ,						SCREAMING_SNAKE_CASE_       :					Any=1E-1_2     ,						SCREAMING_SNAKE_CASE_       :					Optional[int]=0.02     ,						SCREAMING_SNAKE_CASE_       :					Tuple=0     ,						SCREAMING_SNAKE_CASE_       :					Union[str, Any]=1     ,						SCREAMING_SNAKE_CASE_       :					Optional[Any]=2     ,						SCREAMING_SNAKE_CASE_       :					Optional[Any]=3     ,						SCREAMING_SNAKE_CASE_       :					Optional[Any]=5     ,						SCREAMING_SNAKE_CASE_       :					Any=True     ,						SCREAMING_SNAKE_CASE_       :					Union[str, Any]="first"     ,						SCREAMING_SNAKE_CASE_       :					Union[str, Any]=True     ,						SCREAMING_SNAKE_CASE_       :					Any=None     ,						SCREAMING_SNAKE_CASE_       :					Dict=True     ,						SCREAMING_SNAKE_CASE_       :					int=0.1     ,						SCREAMING_SNAKE_CASE_       :					Optional[Any]=5     ,						SCREAMING_SNAKE_CASE_       :					Dict=5     ,						SCREAMING_SNAKE_CASE_       :					Optional[int]=0     ,						SCREAMING_SNAKE_CASE_       :					List[Any]=0     ,						SCREAMING_SNAKE_CASE_       :					int=2     ,						SCREAMING_SNAKE_CASE_       :					Tuple=0     ,						**SCREAMING_SNAKE_CASE_       :					Tuple     ,						):
        __lowerCamelCase:					Tuple	 =						pre_norm
        __lowerCamelCase:					List[str]	 =						layerdrop
        __lowerCamelCase:					List[str]	 =						vocab_size
        __lowerCamelCase:					Tuple	 =						emb_dim
        __lowerCamelCase:					Optional[int]	 =						n_layers
        __lowerCamelCase:					int	 =						n_heads
        __lowerCamelCase:					Tuple	 =						dropout
        __lowerCamelCase:					int	 =						attention_dropout
        __lowerCamelCase:					Dict	 =						gelu_activation
        __lowerCamelCase:					int	 =						sinusoidal_embeddings
        __lowerCamelCase:					Union[str, Any]	 =						causal
        __lowerCamelCase:					Dict	 =						asm
        __lowerCamelCase:					List[str]	 =						n_langs
        __lowerCamelCase:					Union[str, Any]	 =						use_lang_emb
        __lowerCamelCase:					Dict	 =						layer_norm_eps
        __lowerCamelCase:					Dict	 =						bos_index
        __lowerCamelCase:					Union[str, Any]	 =						eos_index
        __lowerCamelCase:					int	 =						pad_index
        __lowerCamelCase:					Optional[Any]	 =						unk_index
        __lowerCamelCase:					Any	 =						mask_index
        __lowerCamelCase:					Any	 =						is_encoder
        __lowerCamelCase:					Tuple	 =						max_position_embeddings
        __lowerCamelCase:					str	 =						embed_init_std
        __lowerCamelCase:					List[Any]	 =						init_std
        __lowerCamelCase:					Optional[Any]	 =						summary_type
        __lowerCamelCase:					Optional[Any]	 =						summary_use_proj
        __lowerCamelCase:					Optional[Any]	 =						summary_activation
        __lowerCamelCase:					List[str]	 =						summary_proj_to_labels
        __lowerCamelCase:					Union[str, Any]	 =						summary_first_dropout
        __lowerCamelCase:					int	 =						start_n_top
        __lowerCamelCase:					Tuple	 =						end_n_top
        __lowerCamelCase:					Optional[int]	 =						mask_token_id
        __lowerCamelCase:					Any	 =						lang_id

        if "n_words" in kwargs:
           __lowerCamelCase:					Optional[Any]	 =						kwargs["""n_words"""]

        super().__init__(pad_token_id=SCREAMING_SNAKE_CASE_     ,						bos_token_id=SCREAMING_SNAKE_CASE_     ,						**SCREAMING_SNAKE_CASE_				)



class 							a       (      _UpperCAmelCase ):





     @property
     def 			SCREAMING_SNAKE_CASE__							(     self       :					Any				):
        if self.task == "multiple-choice":
           __lowerCamelCase:					List[str]	 =						{0: """batch""", 1: """choice""", 2: """sequence"""}
        else:
           __lowerCamelCase:					int	 =						{0: """batch""", 1: """sequence"""}
        return OrderedDict(
            [
                ("""input_ids""", dynamic_axis),
                ("""attention_mask""", dynamic_axis),
            ]				)






import sys



def      __lowerCAmelCase    (				snake_case						:     int    ,   snake_case						:     list[int]			)							->				int:
   if not numbers:
      return 0
   if target == 0 and target in numbers:
      return 0
   if not isinstance(snake_case    ,   (list, tuple)			) or not all(
       isinstance(snake_case    ,   snake_case			) for number in numbers			):
      raise ValueError("""numbers must be an iterable of integers"""			)

   __lowerCamelCase:					Union[str, Any]	 =						0
   __lowerCamelCase:					str	 =						sys.maxsize

   while right < len(snake_case			):
      curr_sum += numbers[right]
      while curr_sum >= target and left <= right:
         __lowerCamelCase:					str	 =						min(snake_case    ,   right - left + 1			)
         curr_sum -= numbers[left]
         left += 1
      right += 1

   return 0 if min_len == sys.maxsize else min_len


