code: def __init__(self, model, params, c, batch, input_names):
      super(AttackModule, self).__init__()
  
      self.model = model
      self.params = params
      self.c = c
      self.batch = batch
      self.input_names = input_names
  
      self.attack_loss = AttackLoss(
          c,
          attack_idx=self.params.attack_idx,
          device=self.params.device,
          target_items=self.params.target_items,
      )
  
      # Initialize perturbation: batch x context length x target dim
      self.perturbation = nn.Parameter(
          torch.zeros_like(batch["past_target_cdf"]), requires_grad=True
      )
      self.perturbation.to(self.params.device)
  
imports: import torch
  import torch.nn
  import torch.optim
  from tqdm.auto import tqdm
  from typing import List
  from sparse_layer import SparseNet
label_desc: Use image node_id 1 to create a new AttackModule object from inherited base classes: nn with example: obj = AttackModule(model, params, c, batch, input_names)