How can I find the operation in the code which is using aten::ne op in backward that doesn’t support sparse tensors? Is there any method for debugging the backward?
I have an untrackable exception when I’m trying to backpropogate gradients:
RuntimeError: Could not run 'aten::ne.Tensor' with arguments from the 'SparseCUDATensorId' backend. 'aten::ne.Tensor' is only available for these backends: [CUDATensorId, QuantizedCPUTensorId, CPUTensorId, VariableTensorId].
Maybe there is a list of python torch ops that have aten:ne in the backward c++ implementation?
Unfortunately, I can’t generate a simple code snippet for testing, because the issue is not about the support of sparse tensor in aten::ne but about the python op that contains the usage of it. Still, the code that I’m trying to work with is the pytorch implementation of nerf: yenchenlin/nerf-pytorch 1. I’m just inserting sparse nn.Embedding in module list on the line here/line#83 1.