code: def forward(
      self, past_target: torch.Tensor, future_target: torch.Tensor
  ) -> torch.Tensor:
      distr = self.get_distr(past_target)
  
      # (batch_size, prediction_length, target_dim)
      loss = -distr.log_prob(future_target)
  
      return loss.mean()
  
file_path: gluonts/src/gluonts/nursery/robust-mts-attack/pts/model/simple_feedforward/simple_feedforward_network.py
imports: from typing import List
  import torch
  import torch.nn
  from torch.distributions import Distribution
  from gluonts.core.component import validated
  from gluonts.torch.modules.distribution_output import DistributionOutput
  from gluonts.torch.modules.lambda_layer import LambdaLayer
  from pts.modules import MeanScaler, NOPScaler
label_desc: Use image node_id 1 for calling the SimpleFeedForwardTrainingNetwork obj's underlying member method code with example usage: obj.forward(past_target, future_target) and returns: loss