input all sequence of items to a LSTM (instead of averaging pairs)

models.py

@@ -29,15 +29,13 @@ class MetaLearner(nn.Module):
 
     def forward(self, inputs):
         size = inputs.shape
-        x = inputs.contiguous().view(size[0]*2, size[2], size[3])
-        x = x.transpose(1,0)
+        x = torch.stack([inputs[:,0,0,:],inputs[:,0,1,:],inputs[:,1,1,:]],dim=1)
+        x = x.transpose(0,1)
 
         _,(x,c) = self.rnn(x)
         x = x[-1]
-
         x = x.squeeze(0)
-        x = x.reshape(size[0],2,100)
-        x = torch.mean(x, 1)
+
         return x.view(size[0], 1, 1, self.out_size)