Deep Learning with PyTorch

Creating an ensembling model

We need to create a model that is similar to the architecture diagram show previously. The following code implements this:

class EnsembleModel(nn.Module):        def __init__(self,out_size,training=True):        super().__init__()        self.fc1 = nn.Linear(8192,512)        self.fc2 = nn.Linear(131072,512)        self.fc3 = nn.Linear(82944,512)        self.fc4 = nn.Linear(512,out_size)    def forward(self,inp1,inp2,inp3):        out1 = self.fc1(F.dropout(inp1,training=self.training))        out2 = self.fc2(F.dropout(inp2,training=self.training))        out3 = self.fc3(F.dropout(inp3,training=self.training))        out = out1 + out2 + out3        out = self.fc4(F.dropout(out,training=self.training))        return outem = EnsembleModel(2)if is_cuda:    em = em.cuda()

In the preceding code, we create ...