code: def __init__(self, nf=64, gc=32, bias=True):
      super(ResidualDenseBlock_5C, self).__init__()
      # gc: growth channel, i.e. intermediate channels
      self.conv1 = nn.Conv2D(nf, gc, 3, 1, 1, bias_attr=bias)
      self.conv2 = nn.Conv2D(nf + gc, gc, 3, 1, 1, bias_attr=bias)
      self.conv3 = nn.Conv2D(nf + 2 * gc, gc, 3, 1, 1, bias_attr=bias)
      self.conv4 = nn.Conv2D(nf + 3 * gc, gc, 3, 1, 1, bias_attr=bias)
      self.conv5 = nn.Conv2D(nf + 4 * gc, nf, 3, 1, 1, bias_attr=bias)
      self.lrelu = nn.LeakyReLU(negative_slope=0.2)
  
imports: import functools
  import paddle
  import paddle.nn
  import paddle.nn.functional
label_desc: Use image node_id 1 to create a new ResidualDenseBlock_5C object from inherited base classes: nn with example: obj = ResidualDenseBlock_5C(nf, gc, bias)