code: def forward(self, inputs):
      x = inputs
      for i in range(self.num_conv):
          conv = getattr(self, "conv%d" % (i + 1))
          x = conv(x)
      return x
  
imports: import paddle
  import paddle.nn
  import paddle.nn.functional
  from paddleseg.cvlibs import manager
  from paddleseg.models.layers.layer_libs import SyncBatchNorm
  from paddleseg.cvlibs.param_init import kaiming_normal_init
label_desc: Use image node_id 2 for calling the UnetConv2D obj's underlying member method code with example usage: obj.forward(inputs) and returns: x