code: def quantile_error(
      preds: Tensor, target: Tensor, percentage: float
  ) -> Tensor:
      diff = target - preds
      weight = pt.where(
          condition=diff > 0,
          input=diff.new_tensor(percentage),
          other=diff.new_tensor(percentage - 1),
      )
      return diff * weight
  
file_path: gluonts/src/gluonts/nursery/daf/tslib/metrics/metrics.py
imports: import torch
  from torch import Tensor, BoolTensor
  from torch.nn.functional import l1_loss, mse_loss
  from torch.distributions import Distribution, Normal
label_desc: Use image node_id 1 for calling a global function with example usage: quantile_error(preds, target, percentage) and returns: unknown