code: def __init__(
      self,
      implicit_quantile_function,
      taus,
      nn_output,
      predicted_quantiles,
      validate_args=None,
  ):
      self.predicted_quantiles = predicted_quantiles[0]
      self.taus = taus
      self.quantile_function = implicit_quantile_function
      self.input_data = nn_output
  
      super(ImplicitQuantile, self).__init__(
          batch_shape=self.predicted_quantiles.shape,
          validate_args=validate_args,
      )
  
file_path: gluonts/src/gluonts/nursery/robust-mts-attack/pts/distributions/implicit_quantile.py
imports: import torch
  from torch.distributions import Distribution, TransformedDistribution, AffineTransform
label_desc: Use image node_id 1 to create a new ImplicitQuantile object from inherited base classes: Distribution with example: obj = ImplicitQuantile(implicit_quantile_function, taus, nn_output, predicted_quantiles, validate_args)