code: def __init__(self, dim, use_bias=False):
      super(ResnetBlock, self).__init__()
      conv_block = []
      conv_block += [
          nn.Pad2D([1, 1, 1, 1], "reflect"),
          nn.Conv2D(
              dim, dim, kernel_size=3, stride=1, bias_attr=use_bias
          ),
          nn.InstanceNorm2D(dim, weight_attr=False, bias_attr=False),
          nn.ReLU(),
      ]
  
      conv_block += [
          nn.Pad2D([1, 1, 1, 1], "reflect"),
          nn.Conv2D(
              dim, dim, kernel_size=3, stride=1, bias_attr=use_bias
          ),
          nn.InstanceNorm2D(dim, weight_attr=False, bias_attr=False),
      ]
  
      self.conv_block = nn.Sequential(*conv_block)
  
imports: import paddle
  import paddle.nn
  import paddle.nn.functional
label_desc: Use image node_id 1 to create a new ResnetBlock object from inherited base classes: nn with example: obj = ResnetBlock(dim, use_bias)