class_docstr: Implement of BernNet
code: def forward(self, graph, feature):
      feature = self.feat_dropout_1(feature)
      feature = F.relu(self.linear_1(feature))
  
      feature = self.feat_dropout_1(feature)
      feature = self.linear_2(feature)
  
      if self.dprate > 0.0:
          feature = self.feat_dropout_2(feature)
      feature = self.prop(graph, feature)
  
      return feature
  
imports: import pgl
  import paddle.nn
  import paddle.nn.functional
  from propagation import BernProp
label_desc: Use image node_id 2 for calling the BernNet obj's underlying member method code with example usage: obj.forward(graph, feature) and returns: feature