Hello,

I’m trying to multiply two tensors to mask out certain values.

```
a = torch.tensor([[1,2],[3,4]])
b = torch.tensor([[1,0],[0,1]])
c = a*b
```

Where c should return tensor([[1, 0],[0, 4]]). This works perfectly in my python notebook.

However, in my train loop, I’m multiplying X_pos * y which outputs the X_pos tensor rather than the multiplication of the two tensors.

```
for batch in dataloader:
X, y = batch[0][:], batch[1][:]
X_pos = X[:,1,:]
Mask_X = X[:,2,:]
X,y = X[:,0,:],y[:,0,:]
sequence_length = y.size(1)
tgt_mask = model.get_tgt_mask(sequence_length).to(self.device)
print(X_pos.size(),X_pos)
print(y.size(),y)
print(X_pos*y)
pred = model(X, X_pos*y,mask=Mask_X, tgt_mask=tgt_mask)
pred = pred.permute(1,2,0)
loss = loss_fn(pred, y.type(torch.LongTensor).to(self.device))
opt.zero_grad()
loss.backward()
opt.step()
total_loss += loss.detach().item()
```

I was not able to reproduce this behaviour.