code: def forward(
      self,
      past_target: torch.Tensor,
      future_target: torch.Tensor = None,
  ) -> torch.Tensor:
      forecasts = super().forward(past_target=past_target)
  
      return forecasts.unsqueeze(1)
  
imports: from typing import List, Tuple
  import numpy
  import torch
  import torch.nn
  import torch.nn.functional
  from gluonts.time_feature import get_seasonality
label_desc: Use image node_id 2 for calling the NBEATSPredictionNetwork obj's underlying member method code with example usage: obj.forward(past_target, future_target) and returns: forecasts