code: def forward(self, x1, x2):
      x1 = F.relu(self.fc1a(x1))
      x1 = self.fc1b(x1)
      x2 = x2.type(torch.FloatTensor)
      x2 = F.relu(self.fc2a(x2))
      x2 = self.fc2b(x2)
      # set x2 to FloatTensor
      x = torch.cat((x1, x2), 0)
      return F.log_softmax(x, dim=1)
  
file_path: pytorch-summary/torchsummary/tests/test_models/test_model.py
imports: import torch
  import torch.nn
  import torch.nn.functional
label_desc: Use image node_id 2 for calling the MultipleInputNetDifferentDtypes obj's underlying member method code with example usage: obj.forward(x1, x2) and returns: F