def 				__lowerCamelCase		(						lowerCAmelCase__     ):

       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]
       lowerCAmelCase__					     = grid[0]

       for row_n in range(1     ,  len(_lowerCAmelCase     )     ):
              lowerCAmelCase__					     = grid[row_n]
              lowerCAmelCase__					     = fill_row(_lowerCAmelCase     ,  _lowerCAmelCase     )
              lowerCAmelCase__					     = grid[row_n]

       return grid[-1][-1]






def 				__lowerCamelCase		(						lowerCAmelCase__     ,  lowerCAmelCase__     ):
       current_row[0] += row_above[0]
       for cell_n in range(1     ,  len(_lowerCAmelCase     )     ):
              current_row[cell_n] += min(current_row[cell_n - 1]     ,  row_above[cell_n]     )

       return current_row


if __name__ == "__main__":
    import doctest

    doctest.testmod()

from collections import OrderedDict
from typing import Mapping

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


lowerCAmelCase__     						=			logging.get_logger(__name__)

lowerCAmelCase__     						=			{
    '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     a_			(						SCREAMING_SNAKE_CASE						):






 '''simple docstring'''






 UpperCAmelCase_     			= 'xlm-roberta-xl'




 def __init__(      self :  int      ,   lowercase__ :  Optional[int]=250_880      ,   lowercase__ :  Union[str, Any]=2_560      ,   lowercase__ :  int=36      ,   lowercase__ :  int=32      ,   lowercase__ :  List[Any]=10_240      ,   lowercase__ :  Union[str, Any]="gelu"      ,   lowercase__ :  Dict=0.1      ,   lowercase__ :  Any=0.1      ,   lowercase__ :  Any=514      ,   lowercase__ :  Optional[int]=1      ,   lowercase__ :  Any=0.02      ,   lowercase__ :  List[str]=1e-05      ,   lowercase__ :  Dict=1      ,   lowercase__ :  Union[str, Any]=0      ,   lowercase__ :  Dict=2      ,   lowercase__ :  str="absolute"      ,   lowercase__ :  Dict=True      ,   lowercase__ :  List[Any]=None      ,   **lowercase__ :  Optional[Any]      ,   ):







        '''simple docstring'''



        super().__init__(pad_token_id=lowercase__      ,   bos_token_id=lowercase__      ,   eos_token_id=lowercase__      ,   **lowercase__)
        lowerCAmelCase__					     = vocab_size
        lowerCAmelCase__					     = hidden_size
        lowerCAmelCase__					     = num_hidden_layers
        lowerCAmelCase__					     = num_attention_heads
        lowerCAmelCase__					     = hidden_act
        lowerCAmelCase__					     = intermediate_size
        lowerCAmelCase__					     = hidden_dropout_prob
        lowerCAmelCase__					     = attention_probs_dropout_prob
        lowerCAmelCase__					     = max_position_embeddings
        lowerCAmelCase__					     = type_vocab_size
        lowerCAmelCase__					     = initializer_range
        lowerCAmelCase__					     = layer_norm_eps
        lowerCAmelCase__					     = position_embedding_type
        lowerCAmelCase__					     = use_cache
        lowerCAmelCase__					     = classifier_dropout






class     a_			(						SCREAMING_SNAKE_CASE						):






 '''simple docstring'''






 @property
 def 		__snake_case						(      self :  int):







        '''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),
            ])
