



'''simple docstring'''





def 						__snake_case(				_lowerCAmelCase     ,   _lowerCAmelCase     ,   _lowerCAmelCase		)		-> bool:
      return not any(
          neighbour == 1 and colored_vertices[i] == color
          for i, neighbour in enumerate(_lowerCAmelCase		)		)





def 						__snake_case(				_lowerCAmelCase     ,   _lowerCAmelCase     ,   _lowerCAmelCase     ,   _lowerCAmelCase		)		-> bool:

      # Base Case
      if index == len(_lowerCAmelCase		):
            return True

      # Recursive Step
      for i in range(_lowerCAmelCase		):
            if valid_coloring(graph[index]     ,   _lowerCAmelCase     ,   _lowerCAmelCase		):
                  # Color current vertex
                  snake_case__  :    List[Any]    						=      i
                  # Validate coloring
                  if util_color(_lowerCAmelCase     ,   _lowerCAmelCase     ,   _lowerCAmelCase     ,   index + 1		):
                        return True
                  # Backtrack
                  snake_case__  :    Optional[Any]    						=      -1
      return False





def 						__snake_case(				_lowerCAmelCase     ,   _lowerCAmelCase		)		-> list[int]:
      snake_case__  :    Dict    						=      [-1] * len(_lowerCAmelCase		)

      if util_color(_lowerCAmelCase     ,   _lowerCAmelCase     ,   _lowerCAmelCase     ,   0		):
            return colored_vertices

      return []





'''simple docstring'''





import numpy as np

from transformers import Pipeline





def 						__snake_case(				_lowerCAmelCase		)		-> Optional[int]:
      snake_case__  :    Optional[Any]    						=      np.max(_lowerCAmelCase     ,   axis=-1     ,   keepdims=_lowerCAmelCase		)
      snake_case__  :    List[str]    						=      np.exp(outputs - maxes		)
      return shifted_exp / shifted_exp.sum(axis=-1     ,   keepdims=_lowerCAmelCase		)







class     UpperCAmelCase_       (       _a	):
    """simple docstring"""







    def lowerCamelCase       (    self					:     Optional[Any] ,     **snake_case_					:     int						):
          snake_case__  :    Optional[int]    						=      {}
          if "second_text" in kwargs:
                snake_case__  :    Union[str, Any]    						=      kwargs["""second_text"""]
          return preprocess_kwargs, {}, {}




    def lowerCamelCase       (    self					:     str ,     snake_case_					:     Tuple ,     snake_case_					:     Union[str, Any]=None						):
          return self.tokenizer(snake_case_ ,     text_pair=snake_case_ ,     return_tensors=self.framework						)




    def lowerCamelCase       (    self					:     List[Any] ,     snake_case_					:     Dict						):
          return self.model(**snake_case_						)




    def lowerCamelCase       (    self					:     int ,     snake_case_					:     List[Any]						):
          snake_case__  :    Union[str, Any]    						=      model_outputs.logits[0].numpy()
          snake_case__  :    List[str]    						=      softmax(snake_case_						)

          snake_case__  :    List[str]    						=      np.argmax(snake_case_						)
          snake_case__  :    List[str]    						=      self.model.config.idalabel[best_class]
          snake_case__  :    Optional[int]    						=      probabilities[best_class].item()
          snake_case__  :    str    						=      logits.tolist()
          return {"label": label, "score": score, "logits": logits}
