An autoencoder with multiple inputs

8

Multi_AE
puts[idx]))

def forward(self, inputs):
out =
for idx, enc in enumerate(self.encoders):
out.append(enc(in

    z = torch.cat(out, dim=1)
    #z = self.encoder(out)
    #out = self.decoder(z)
    z = torch.split(z, 3, dim=1)
    outs = []
    for idx, dec in enumerate(self.decoders):
        outs.append(dec(out[idx]))
    return outs