class_docstr: ResidualConvUnit, pre-activate residual unit.
  Args:
      in_channels (int): number of channels in the input feature map.
      act_layer (nn.Module): activation layer.
      norm_layer (nn.Module): norm layer.
      stride (int): stride of the first block. Default: 1
      dilation (int): dilation rate for convs layers. Default: 1.
code: def forward(self, inputs):
      inputs_ = inputs.clone()
      x = self.conv1(inputs)
      x = self.conv2(x)
      return x + inputs_
  
imports: import copy
  from functools import partial
  import math
  import warnings
  import torch
  import torch.nn
  from .ops import resize
label_desc: Use image node_id 2 for calling the PreActResidualConvUnit obj's underlying member method code with example usage: obj.forward(inputs) and returns: unknown