Torch.gather throwing RuntimeError: CUDA error: device-side assert triggered

reward = 3
def custom_loss(outputs,target):
        outputs  = F.softmax(outputs,dim=1)
        outputs, reservation = outputs[:,:-1], outputs[:,-1]
        gain = torch.gather(outputs, dim=1, index=target.unsqueeze(1)).squeeze()
        return loss

I am trying to implement custom loss but it was giving runtime cuda error so i remove lines step by step and tried to run CNN. It works fine. BUT

The moment i enter

gain = torch.gather(outputs, dim=1, index=target.unsqueeze(1)).squeeze()

This line it through

RuntimeError: CUDA error: device-side assert triggered

The stack trace might point to an invalid index and you could rerun the code via:


to see if this is indeed the line of code raising the error.
Also, if you run the code on the CPU you might get a better error message.

1 Like

I am using jupyter notebook so for that i have to
os.environ['CUDA_LAUNCH_BLOCKING'] = '1' # according to this

so now the error is

RuntimeError                              Traceback (most recent call last)
<ipython-input-18-43362cbf6c2c> in <module>
      1 os.environ['CUDA_LAUNCH_BLOCKING'] = '1'
----> 3 history = train_all()
      4 history

<ipython-input-17-3bc06434873b> in train_all(model)
     40             outputs=model(images.float())
     41             loss = custom_loss(outputs,labels)
---> 42             print(loss)
     44             loss.backward()

~/anaconda3/lib/python3.7/site-packages/torch/ in __repr__(self)
    177             return handle_torch_function(Tensor.__repr__, relevant_args, self)
    178         # All strings are unicode in Python 3.
--> 179         return torch._tensor_str._str(self)
    181     def backward(self, gradient=None, retain_graph=None, create_graph=False):

~/anaconda3/lib/python3.7/site-packages/torch/ in _str(self)
    370 def _str(self):
    371     with torch.no_grad():
--> 372         return _str_intern(self)

~/anaconda3/lib/python3.7/site-packages/torch/ in _str_intern(self)
    350                     tensor_str = _tensor_str(self.to_dense(), indent)
    351                 else:
--> 352                     tensor_str = _tensor_str(self, indent)
    354     if self.layout != torch.strided:

~/anaconda3/lib/python3.7/site-packages/torch/ in _tensor_str(self, indent)
    239         return _tensor_str_with_formatter(self, indent, summarize, real_formatter, imag_formatter)
    240     else:
--> 241         formatter = _Formatter(get_summarized_data(self) if summarize else self)
    242         return _tensor_str_with_formatter(self, indent, summarize, formatter)

~/anaconda3/lib/python3.7/site-packages/torch/ in __init__(self, tensor)
     88         else:
---> 89             nonzero_finite_vals = torch.masked_select(tensor_view, torch.isfinite(tensor_view) &
     91             if nonzero_finite_vals.numel() == 0:

RuntimeError: CUDA error: device-side assert triggered

As you said.
I log value of each variable and found that target.unsqueeze(1) is giving value more than valid index.
I then verify output layer of my model was wrong.