Hi I have a prediction of shape [1,1,136,100]  where Class is one and Batch size is 1.
My Label  is of size [1,136,100]
Label = [[[  0,   0,   0,   0,   0,   0,   0,   0,   0,   0,   0,   0,   0,
0,   0,255,…]]]
I am recieving cuda assert error.
Further Trace is given as
self.criterion = nn.CrossEntropyLoss(ignore_index=255)
loss_semantic_seg = self.criterion(mask_pred, labels)
File “/home/danish/miniconda3/envs/open-mmlab/lib/python3.7/site-packages/torch/nn/modules/module.py”, line 532, in call
result = self.forward(*input, **kwargs)
File “/home/danish/miniconda3/envs/open-mmlab/lib/python3.7/site-packages/torch/nn/modules/loss.py”, line 916, in forward
ignore_index=self.ignore_index, reduction=self.reduction)
File “/home/danish/miniconda3/envs/open-mmlab/lib/python3.7/site-packages/torch/nn/functional.py”, line 2021, in cross_entropy
return nll_loss(log_softmax(input, 1), target, weight, None, ignore_index, None, reduction)
File “/home/danish/miniconda3/envs/open-mmlab/lib/python3.7/site-packages/torch/nn/functional.py”, line 1840, in nll_loss
ret = torch._C._nn.nll_loss2d(input, target, weight, _Reduction.get_enum(reduction), ignore_index)