code: def forward(self, *input):
      x1 = self.pre_conv1(input[0])
      x2 = self.pre_conv2(input[1])
      x3 = self.pre_conv3(input[2])
  
      padding, out_padding = get_padding(x1.size(), x2.size(), 2)
      x2 = F.conv_transpose2d(
          x2,
          self.deconv_weight1,
          stride=2,
          padding=padding,
          output_padding=out_padding,
      )
  
      padding, out_padding = get_padding(x1.size(), x3.size(), 4)
      x3 = F.conv_transpose2d(
          x3,
          self.deconv_weight2,
          stride=4,
          padding=padding,
          output_padding=out_padding,
      )
      return x1 + x2 + x3
  
imports: import torch.nn.functional
  from .utils import *
  from .backbone import *
label_desc: Use image node_id 2 for calling the Refine_block3_1 obj's underlying member method code with example usage: obj.forward() and returns: unknown