code: def forward(self, x):  # skipcq: PYL-W0221
      weight = self.weight_generator(x)
      loss = self.classifier(x)
      logits = torch.sum(weight * loss, dim=[2, 3]) / (
          torch.sum(weight, dim=[2, 3]) + 1e-6
      )
      return logits
  
imports: from typing import Union, Dict
  import torch
  import torch.nn.functional
  from torch.nn.modules.module import _IncompatibleKeys
  from torch import Tensor, nn
label_desc: Use image node_id 2 for calling the MILCustomPoolingModule obj's underlying member method code with example usage: obj.forward(x) and returns: logits