code: def forward(self, x):
      b, c, _, _ = x.size()
      y = self.avg_pool(x)
      y = y.view([int(b), -1])
      y = self.fc(y)
      y = y.view([int(b), int(c), 1, 1])
      return x * y
  
imports: import numpy
  import torch
  from torch import nn
  from torch.autograd import Variable
  from torchvision.models import ResNet
  from pytorch2keras.converter import pytorch_to_keras
label_desc: Use image node_id 2 for calling the SELayer obj's underlying member method code with example usage: obj.forward(x) and returns: unknown