code: def __init__(self, quantile_levels, alpha=0.01):
      super(HuberPinballLoss, self).__init__()
      if quantile_levels is not None:
          self.quantile_levels = (
              torch.Tensor(quantile_levels).contiguous().reshape(1, -1)
          )
      else:
          self.quantile_levels = None
      self.alpha = alpha
  
file_path: autogluon/tabular/src/autogluon/tabular/models/fastainn/quantile_helpers.py
imports: import numpy
  import torch
  import torch.nn
  from sklearn.isotonic import IsotonicRegression
label_desc: Use image node_id 1 to create a new HuberPinballLoss object from inherited base classes: nn with example: obj = HuberPinballLoss(quantile_levels, alpha)