The code works for torchtext.datasets.SST.splits(TEXT, LABEL)?

[denAAA]

Running torchtext.SST got the error:

/pytorch/aten/src/THCUNN/ClassNLLCriterion.cu:105: void cunn_ClassNLLCriterion_updateOutput_kernel(Dtype *, Dtype *, Dtype *, long *, Dtype *, int, int, int, int, long) [with Dtype = float, Acctype = float]: block: [0,0,0], thread: [0,0,0] Assertiont >= 0 && t < n_classesfailed. /pytorch/aten/src/THCUNN/ClassNLLCriterion.cu:105: void cunn_ClassNLLCriterion_updateOutput_kernel(Dtype *, Dtype *, Dtype *, long *, Dtype *, int, int, int, int, long) [with Dtype = float, Acctype = float]: block: [0,0,0], thread: [11,0,0] Assertiont >= 0 && t < n_classesfailed. /pytorch/aten/src/THCUNN/ClassNLLCriterion.cu:105: void cunn_ClassNLLCriterion_updateOutput_kernel(Dtype *, Dtype *, Dtype *, long *, Dtype *, int, int, int, int, long) [with Dtype = float, Acctype = float]: block: [0,0,0], thread: [19,0,0] Assertiont >= 0 && t < n_classesfailed. /pytorch/aten/src/THCUNN/ClassNLLCriterion.cu:105: void cunn_ClassNLLCriterion_updateOutput_kernel(Dtype *, Dtype *, Dtype *, long *, Dtype *, int, int, int, int, long) [with Dtype = float, Acctype = float]: block: [0,0,0], thread: [20,0,0] Assertiont >= 0 && t < n_classesfailed. /pytorch/aten/src/THCUNN/ClassNLLCriterion.cu:105: void cunn_ClassNLLCriterion_updateOutput_kernel(Dtype *, Dtype *, Dtype *, long *, Dtype *, int, int, int, int, long) [with Dtype = float, Acctype = float]: block: [0,0,0], thread: [26,0,0] Assertiont >= 0 && t < n_classesfailed. Traceback (most recent call last): File "./main.py", line 91, in <module> train_loss, train_acc = train_model(model, train_iter, epoch) File "./main.py", line 44, in train_model loss.backward() File "....", line 118, in backward torch.autograd.backward(self, gradient, retain_graph, create_graph) File "....", line 93, in backward allow_unreachable=True) # allow_unreachable flag RuntimeError: cuda runtime error (59) : device-side assert triggered at /pytorch/aten/src/THC/generic/THCTensorMath.cu:26

I checked the target values:

tensor([2, 1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 2, 1, 0, 0, 0, 0, 0, 1, 2, 2, 0, 1, 1, 0, 1, 2, 1, 1, 0, 1, 1], device='cuda:0')

there is "2" here that I think makes the problem. Would you please guide me regarding this issue?

[denAAA]

Changing the output size solved the problem.