"""simple docstring"""






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			   = {
    "facebook/xlm-roberta-xl": "https://huggingface.co/facebook/xlm-roberta-xl/resolve/main/config.json",
    "facebook/xlm-roberta-xxl": "https://huggingface.co/facebook/xlm-roberta-xxl/resolve/main/config.json",
    # See all XLM-RoBERTa-XL models at https://huggingface.co/models?filter=xlm-roberta-xl
}


class     UpperCAmelCase						(_UpperCAmelCase  ):



    """simple docstring"""

    _UpperCAmelCase	:Union[str, Any]						    = "xlm-roberta-xl"






    def __init__(   self    ,			_UpperCAmelCase=250880    ,			_UpperCAmelCase=2560    ,			_UpperCAmelCase=36    ,			_UpperCAmelCase=32    ,			_UpperCAmelCase=10240    ,			_UpperCAmelCase="gelu"    ,			_UpperCAmelCase=0.1    ,			_UpperCAmelCase=0.1    ,			_UpperCAmelCase=514    ,			_UpperCAmelCase=1    ,			_UpperCAmelCase=0.02    ,			_UpperCAmelCase=1e-0_5    ,			_UpperCAmelCase=1    ,			_UpperCAmelCase=0    ,			_UpperCAmelCase=2    ,			_UpperCAmelCase="absolute"    ,			_UpperCAmelCase=True    ,			_UpperCAmelCase=None    ,			**_UpperCAmelCase    ,			):
       super().__init__(pad_token_id=_UpperCAmelCase    ,			bos_token_id=_UpperCAmelCase    ,			eos_token_id=_UpperCAmelCase    ,			**_UpperCAmelCase							)
       lowercase__:   Optional[int]					=      vocab_size
       lowercase__:   Union[str, Any]					=      hidden_size
       lowercase__:   List[Any]					=      num_hidden_layers
       lowercase__:   List[Any]					=      num_attention_heads
       lowercase__:   Tuple					=      hidden_act
       lowercase__:   str					=      intermediate_size
       lowercase__:   Optional[int]					=      hidden_dropout_prob
       lowercase__:   List[Any]					=      attention_probs_dropout_prob
       lowercase__:   Dict					=      max_position_embeddings
       lowercase__:   Dict					=      type_vocab_size
       lowercase__:   Optional[int]					=      initializer_range
       lowercase__:   int					=      layer_norm_eps
       lowercase__:   Optional[Any]					=      position_embedding_type
       lowercase__:   List[Any]					=      use_cache
       lowercase__:   Tuple					=      classifier_dropout



class     UpperCAmelCase						(_UpperCAmelCase  ):



    """simple docstring"""

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

"""simple docstring"""






def SCREAMING_SNAKE_CASE__			(   __UpperCAmelCase )  ->  int:

   if not grid or not grid[0]:
      raise TypeError('''The grid does not contain the appropriate information''' )

   for cell_n in range(1       ,    len(grid[0] ) ):
      grid[0][cell_n] += grid[0][cell_n - 1]
   lowercase__:   Tuple					=      grid[0]

   for row_n in range(1       ,    len(__UpperCAmelCase ) ):
      lowercase__:   Tuple					=      grid[row_n]
      lowercase__:   Dict					=      fill_row(__UpperCAmelCase       ,    __UpperCAmelCase )
      lowercase__:   Union[str, Any]					=      grid[row_n]

   return grid[-1][-1]



def SCREAMING_SNAKE_CASE__			(   __UpperCAmelCase       ,    __UpperCAmelCase )  ->  list:
   current_row[0] += row_above[0]
   for cell_n in range(1       ,    len(__UpperCAmelCase ) ):
      current_row[cell_n] += min(current_row[cell_n - 1]       ,    row_above[cell_n] )

   return current_row


if __name__ == "__main__":
       import doctest

       doctest.testmod()
