



from collections import OrderedDict
from typing import Mapping

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


a			:     Tuple     = logging.get_logger(__name__)

a			:     int     = {
    '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							(      _lowerCAmelCase				):
			A					=  '''flaubert'''
			A					=  {
			    '''hidden_size''': '''emb_dim''',
			    '''num_attention_heads''': '''n_heads''',
			    '''num_hidden_layers''': '''n_layers''',
			    '''n_words''': '''vocab_size''',  # For backward compatibility
			}

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

						if "n_words" in kwargs:
									UpperCAmelCase_:		List[str]       			=    kwargs["""n_words"""]

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







class 							_a							(      _lowerCAmelCase				):

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











import decimal







def    lowerCAmelCase_  ():





			"""simple docstring"""


			UpperCAmelCase_:		Union[str, Any]       			=    0
			UpperCAmelCase_:		Optional[Any]       			=    decimal.Context(prec=1_0_5     )
			for i in range(2		,	1_0_0     ):
						UpperCAmelCase_:		str       			=    decimal.Decimal(lowerCAmelCase__     )
						UpperCAmelCase_:		Any       			=    number.sqrt(lowerCAmelCase__     )
						if len(str(lowerCAmelCase__     )     ) > 1:
									answer += int(str(lowerCAmelCase__     )[0]     )
									UpperCAmelCase_:		str       			=    str(lowerCAmelCase__     )[2:1_0_1]
									answer += sum(int(lowerCAmelCase__     ) for x in sqrt_number_str     )
			return answer


if __name__ == "__main__":
	import doctest

	doctest.testmod()
	print(F'''{solution() = }''')






