maybe progress

app.py

@@ -46,12 +46,10 @@ def respond(input):
         trg_mask = torch.autograd.Variable(torch.from_numpy(trg_mask) == 0).to(device)
 
         out = model.out(model.decoder(outputs[:i].unsqueeze(0), e_outputs, src_mask, trg_mask))
-        out = torch.nn.functional.softmax(out, dim=-1).detach()
+        out = torch.nn.functional.softmax(out, dim=-1).squeeze().detach().numpy()
         print(out.shape)
-        print(out[:, -1].data[0])
-        print(out[:, -1].data[0].shape)
-        print(np.sum(out[:, -1].data[0]))
-        ix = np.random.choice(np.arange(len(out[:, -1].data[0])), 1, p=out[:, -1].data[0])
+        print(np.sum(out))
+        ix = np.random.choice(np.arange(len(out)), 1, p=out)
         # val, ix = out[:, -1].data.topk(1)
 
         # outputs[i] = ix[0][0]