"""simple docstring"""






import warnings

from ...utils import is_sklearn_available, requires_backends


if is_sklearn_available():
       from scipy.stats import pearsonr, spearmanr
       from sklearn.metrics import fa_score, matthews_corrcoef


__lowerCAmelCase       :			List[str]   	=(
    """This metric will be removed from the library soon, metrics should be handled with the 🤗 Evaluate """
    """library. You can have a look at this example script for pointers: """
    """https://github.com/huggingface/transformers/blob/main/examples/pytorch/text-classification/run_glue.py"""
)


def      UpperCAmelCase__			(							lowerCAmelCase__	:Dict   ,						lowerCAmelCase__	:Optional[Any]						)					->       Dict:
      '''simple docstring'''


      warnings.warn(lowerCAmelCase__   ,						lowerCAmelCase__						)
      requires_backends(lowerCAmelCase__   ,						"""sklearn"""						)
      return (preds == labels).mean()


def      UpperCAmelCase__			(							lowerCAmelCase__	:Union[str, Any]   ,						lowerCAmelCase__	:Optional[Any]						)					->       Tuple:
      '''simple docstring'''


      warnings.warn(lowerCAmelCase__   ,						lowerCAmelCase__						)
      requires_backends(lowerCAmelCase__   ,						"""sklearn"""						)
      lowercase								=      simple_accuracy(lowerCAmelCase__   ,						lowerCAmelCase__						)
      lowercase								=      fa_score(y_true=lowerCAmelCase__   ,						y_pred=lowerCAmelCase__						)
      return {
          "acc": acc,
          "f1": fa,
          "acc_and_f1": (acc + fa) / 2,
      }


def      UpperCAmelCase__			(							lowerCAmelCase__	:List[Any]   ,						lowerCAmelCase__	:List[Any]						)					->       Union[str, Any]:
      '''simple docstring'''


      warnings.warn(lowerCAmelCase__   ,						lowerCAmelCase__						)
      requires_backends(lowerCAmelCase__   ,						"""sklearn"""						)
      lowercase								=      pearsonr(lowerCAmelCase__   ,						lowerCAmelCase__						)[0]
      lowercase								=      spearmanr(lowerCAmelCase__   ,						lowerCAmelCase__						)[0]
      return {
          "pearson": pearson_corr,
          "spearmanr": spearman_corr,
          "corr": (pearson_corr + spearman_corr) / 2,
      }


def      UpperCAmelCase__			(							lowerCAmelCase__	:List[str]   ,						lowerCAmelCase__	:Any   ,						lowerCAmelCase__	:Any						)					->       Dict:
      '''simple docstring'''


      warnings.warn(lowerCAmelCase__   ,						lowerCAmelCase__						)
      requires_backends(lowerCAmelCase__   ,						"""sklearn"""						)
      assert len(lowerCAmelCase__						) == len(lowerCAmelCase__						), f'Predictions and labels have mismatched lengths {len(lowerCAmelCase__						)} and {len(lowerCAmelCase__						)}'
      if task_name == "cola":
            return {"mcc": matthews_corrcoef(lowerCAmelCase__   ,						lowerCAmelCase__						)}
      elif task_name == "sst-2":
            return {"acc": simple_accuracy(lowerCAmelCase__   ,						lowerCAmelCase__						)}
      elif task_name == "mrpc":
            return acc_and_fa(lowerCAmelCase__   ,						lowerCAmelCase__						)
      elif task_name == "sts-b":
            return pearson_and_spearman(lowerCAmelCase__   ,						lowerCAmelCase__						)
      elif task_name == "qqp":
            return acc_and_fa(lowerCAmelCase__   ,						lowerCAmelCase__						)
      elif task_name == "mnli":
            return {"mnli/acc": simple_accuracy(lowerCAmelCase__   ,						lowerCAmelCase__						)}
      elif task_name == "mnli-mm":
            return {"mnli-mm/acc": simple_accuracy(lowerCAmelCase__   ,						lowerCAmelCase__						)}
      elif task_name == "qnli":
            return {"acc": simple_accuracy(lowerCAmelCase__   ,						lowerCAmelCase__						)}
      elif task_name == "rte":
            return {"acc": simple_accuracy(lowerCAmelCase__   ,						lowerCAmelCase__						)}
      elif task_name == "wnli":
            return {"acc": simple_accuracy(lowerCAmelCase__   ,						lowerCAmelCase__						)}
      elif task_name == "hans":
            return {"acc": simple_accuracy(lowerCAmelCase__   ,						lowerCAmelCase__						)}
      else:
            raise KeyError(lowerCAmelCase__						)






def      UpperCAmelCase__			(							lowerCAmelCase__	:int   ,						lowerCAmelCase__	:Any   ,						lowerCAmelCase__	:Any						)					->       Union[str, Any]:
      '''simple docstring'''


      warnings.warn(lowerCAmelCase__   ,						lowerCAmelCase__						)
      requires_backends(lowerCAmelCase__   ,						"""sklearn"""						)
      if len(lowerCAmelCase__						) != len(lowerCAmelCase__						):
            raise ValueError(f'Predictions and labels have mismatched lengths {len(lowerCAmelCase__						)} and {len(lowerCAmelCase__						)}'						)
      if task_name == "xnli":
            return {"acc": simple_accuracy(lowerCAmelCase__   ,						lowerCAmelCase__						)}
      else:
            raise KeyError(lowerCAmelCase__						)




"""simple docstring"""






from copy import deepcopy





class 					_A		:

      def __init__(		self						,			__lowerCAmelCase = None						,			__lowerCAmelCase = None		):







            """simple docstring"""



            if arr is None and size is not None:
                  lowercase								=      size
                  lowercase								=      [0] * size
            elif arr is not None:
                  self.init(__lowerCAmelCase		)
            else:
                  raise ValueError("""Either arr or size must be specified"""		)

      def 							A__			(		self						,			__lowerCAmelCase		):







            """simple docstring"""



            lowercase								=      len(__lowerCAmelCase		)
            lowercase								=      deepcopy(__lowerCAmelCase		)
            for i in range(1						,			self.size		):
                  lowercase								=      self.next_(__lowerCAmelCase		)
                  if j < self.size:
                        self.tree[j] += self.tree[i]

      def 							A__			(		self		):







            """simple docstring"""



            lowercase								=      self.tree[:]
            for i in range(self.size - 1						,			0						,			-1		):
                  lowercase								=      self.next_(__lowerCAmelCase		)
                  if j < self.size:
                        arr[j] -= arr[i]
            return arr

      @staticmethod
      def 							A__			(		__lowerCAmelCase		):







            """simple docstring"""



            return index + (index & (-index))

      @staticmethod
      def 							A__			(		__lowerCAmelCase		):







            """simple docstring"""



            return index - (index & (-index))

      def 							A__			(		self						,			__lowerCAmelCase						,			__lowerCAmelCase		):







            """simple docstring"""



            if index == 0:
                  self.tree[0] += value
                  return
            while index < self.size:
                  self.tree[index] += value
                  lowercase								=      self.next_(__lowerCAmelCase		)

      def 							A__			(		self						,			__lowerCAmelCase						,			__lowerCAmelCase		):







            """simple docstring"""



            self.add(__lowerCAmelCase						,			value - self.get(__lowerCAmelCase		)		)

      def 							A__			(		self						,			__lowerCAmelCase		):







            """simple docstring"""



            if right == 0:
                  return 0
            lowercase								=      self.tree[0]
            right -= 1  # make right inclusive
            while right > 0:
                  result += self.tree[right]
                  lowercase								=      self.prev(__lowerCAmelCase		)
            return result

      def 							A__			(		self						,			__lowerCAmelCase						,			__lowerCAmelCase		):







            """simple docstring"""



            return self.prefix(__lowerCAmelCase		) - self.prefix(__lowerCAmelCase		)

      def 							A__			(		self						,			__lowerCAmelCase		):







            """simple docstring"""



            return self.query(__lowerCAmelCase						,			index + 1		)







      def 							A__			(		self						,			__lowerCAmelCase		):







            """simple docstring"""



            value -= self.tree[0]
            if value < 0:
                  return -1

            lowercase								=      1  # Largest power of 2 <= size
            while j * 2 < self.size:
                  j *= 2

            lowercase								=      0

            while j > 0:
                  if i + j < self.size and self.tree[i + j] <= value:
                        value -= self.tree[i + j]
                        i += j
                  j //= 2
            return i


if __name__ == "__main__":
       import doctest

       doctest.testmod()



