code: def forward(self, x):
      x = F.relu(self.conv1(x))
      x = F.dropout(x, training=self.training)
      x = self.conv2(x)
      return F.log_softmax(x, dim=1)
  
imports: import dgl.function
  import torch
  import torch.nn.functional
  from torch.nn import Parameter
  from torch_geometric.nn.inits import glorot, zeros
label_desc: Use image node_id 2 for calling the GCNSPMV obj's underlying member method code with example usage: obj.forward(x) and returns: F