





'''simple docstring'''


from collections import OrderedDict
from typing import Mapping

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


_SCREAMING_SNAKE_CASE			=							logging.get_logger(__name__)

_SCREAMING_SNAKE_CASE			=							{
    "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_						(						__magic_name__						):
 __lowerCamelCase  :							List[str]    					=   "flaubert"
 __lowerCamelCase  :							Any    					=   {
     "hidden_size": "emb_dim",
     "num_attention_heads": "n_heads",
     "num_hidden_layers": "n_layers",
     "n_words": "vocab_size",  # For backward compatibility
 }




 def __init__(		self     ,       _lowerCAmelCase=False     ,       _lowerCAmelCase=0.0     ,       _lowerCAmelCase=30145     ,       _lowerCAmelCase=2048     ,       _lowerCAmelCase=12     ,       _lowerCAmelCase=16     ,       _lowerCAmelCase=0.1     ,       _lowerCAmelCase=0.1     ,       _lowerCAmelCase=True     ,       _lowerCAmelCase=False     ,       _lowerCAmelCase=False     ,       _lowerCAmelCase=False     ,       _lowerCAmelCase=1     ,       _lowerCAmelCase=True     ,       _lowerCAmelCase=512     ,       _lowerCAmelCase=2048**-0.5     ,       _lowerCAmelCase=1E-12     ,       _lowerCAmelCase=0.02     ,       _lowerCAmelCase=0     ,       _lowerCAmelCase=1     ,       _lowerCAmelCase=2     ,       _lowerCAmelCase=3     ,       _lowerCAmelCase=5     ,       _lowerCAmelCase=True     ,       _lowerCAmelCase="first"     ,       _lowerCAmelCase=True     ,       _lowerCAmelCase=None     ,       _lowerCAmelCase=True     ,       _lowerCAmelCase=0.1     ,       _lowerCAmelCase=5     ,       _lowerCAmelCase=5     ,       _lowerCAmelCase=0     ,       _lowerCAmelCase=0     ,       _lowerCAmelCase=2     ,       _lowerCAmelCase=0     ,       **_lowerCAmelCase     ,       )      ->							Union[str, Any]:
     _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=_lowerCAmelCase     ,       bos_token_id=_lowerCAmelCase     ,       **_lowerCAmelCase						)







class 				lowerCAmelCase_						(						__magic_name__						):




 @property
 def 							_snake_case				(		self						)      ->							Mapping[str, Mapping[int, str]]:
     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),
         ]						)









'''simple docstring'''


def 		__a(SCREAMING_SNAKE_CASE_					:   List[Any]						,    SCREAMING_SNAKE_CASE_					:   str      ):



    '''simple docstring'''





    if n < 0:
        return 0
    # table[i] represents the number of ways to get to amount i
    _lowerCAmelCase		     = [0] * (n + 1)

    # There is exactly 1 way to get to zero(You pick no coins).
    _lowerCAmelCase		     = 1

    # Pick all coins one by one and update table[] values
    # after the index greater than or equal to the value of the
    # picked coin
    for coin_val in s:
        for j in range(SCREAMING_SNAKE_CASE_						,    n + 1      ):
            table[j] += table[j - coin_val]

    return table[n]


if __name__ == "__main__":
       import doctest

       doctest.testmod()


