code: def forward(self, x):
      residual = x
      out = self.conv1(x)
      out = self.bn1(out)
      out = self.relu(out)
  
      out = self.conv2(out)
      out = self.bn2(out)
      out = self.se(out)
  
      if self.downsample is not None:
          residual = self.downsample(x)
  
      out += residual
      out = self.relu(out)
  
      return out
  
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 SEBasicBlock obj's underlying member method code with example usage: obj.forward(x) and returns: out