Replace `torch.tensor()` with `torch.from_numpy()` when processing numpy arrays about transformers HOT 4 OPEN

Thanks for your issue! cc @qubvel in case you have bandwidth :)

from transformers.

Hi @shinyano, thanks for opening the issue!

I'm not sure about replacing torch.tensor() with torch.from_numpy() because I suspect there might be not only np.arrays but for example scalar values. However, we can resolve it by checking if the value is an array.

 def as_tensor(value): 
     if isinstance(value, (list, tuple)) and len(value) > 0: 
         if isinstance(value[0], np.ndarray): 
             value = np.array(value) 
         elif ( 
             isinstance(value[0], (list, tuple)) 
             and len(value[0]) > 0 
             and isinstance(value[0][0], np.ndarray) 
         ): 
             value = np.array(value)
             
     # Modified code 
     if isinstance(value, np.ndarray):
         tensor = torch.from_numpy(value)
     else:
         tensor = torch.tensor(value)
     return tensor

What do you think? Would you like to submit a PR to fix it?

from transformers.

What do you think? Would you like to submit a PR to fix it?

The modification is exactly what I wanted :). And I would be glad to submit the PR.

from transformers.

@shinyano great! ping me for review when it's ready 🤗

from transformers.