I am new about torch text. I was using this repo https://github.com/prakashpandey9/Text-Classification-Pytorch 6 for text classification (IMDB). It perfectly worked for IMDB, but when I changed train_data, test_data = datasets.IMDB.splits(TEXT, LABEL) to train_data, valid_data, test_data = datasets.SST.splits(TEXT, LABEL), it got this 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] Assertion  t >= 0 && t < n_classes failed. /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] Assertion t >= 0 && t < n_classes failed. /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] Assertion t >= 0 && t < n_classes failed. /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] Assertion t >= 0 && t < n_classes failed. /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] Assertion t >= 0 && t < n_classes  failed. 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 size of prediction and targets, they are
torch.Size([32, 2])
torch.Size([32])

and the target values are
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')
this means the target has more than two classes? something like positive, negative, natural responses?  how can I solve this error?