try different method

app.py

@@ -46,7 +46,7 @@ def respond(custom_string):
         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().numpy()
+        out = torch.nn.functional.softmax(out, dim=-1).detach()
         ix = np.random.choice(np.arange(out), 1, p=out)
         # val, ix = out[:, -1].data.topk(1)