code: def __init__(
      self,
      base_distribution: MQF2Distribution,
      transforms: List[AffineTransform],
      is_energy_score: bool = True,
      validate_args: bool = False,
  ) -> None:
      super().__init__(
          base_distribution, transforms, validate_args=validate_args
      )
      self.is_energy_score = is_energy_score
  
imports: from typing import Dict, List, Optional, Tuple, cast
  import torch
  from torch.distributions import AffineTransform, TransformedDistribution
  from torch.distributions.normal import Normal
  from gluonts.core.component import validated
  from gluonts.itertools import prod
  from gluonts.torch.distributions import DistributionOutput
  from gluonts.torch.model.mqf2.module import PICNN
label_desc: Use image node_id 1 to create a new TransformedMQF2Distribution object from inherited base classes: TransformedDistribution with example: obj = TransformedMQF2Distribution(base_distribution, transforms, is_energy_score, validate_args)