code: def log_prob(self, x):
      scale = 1.0
      for transform in reversed(self.transforms):
          assert isinstance(
              transform, AffineTransform
          ), "Not an AffineTransform"
          x = transform.inv(x)
          scale *= transform.scale
      p = self.base_dist.log_prob(x)
      return p * scale
  
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 2 for calling the TransformedImplicitQuantile obj's underlying member method code with example usage: obj.log_prob(x) and returns: unknown