code: def forward(self, high_feature, *low_features):
      features = [self.up(high_feature)]
      for feature in low_features:
          features.append(feature)
      cat_features = paddle.concat(features, axis=1)
      out = self.conv(cat_features)
  
      return out
  
file_path: PaddleSeg/paddleseg/models/unet_plusplus.py
imports: import paddle
  import paddle.nn
  from paddleseg.cvlibs import manager
  from paddleseg.utils import load_entire_model
  from paddleseg.cvlibs.param_init import kaiming_normal_init
  from paddleseg.models.layers.layer_libs import SyncBatchNorm
label_desc: Use image node_id 2 for calling the UpSampling obj's underlying member method code with example usage: obj.forward(high_feature) and returns: out