Hi,
I have a problem when I want to obtain a loss value.
Firstly, for example, I design my own DataLoader including 3 inputs (Each input has 4 one-hot vector) and 3 outputs (Each output has a vector with size = 33), The problem is a multiclass classification (just one class must be activated!):
class MyDataset(Dataset):
def init(self):
self.X = Variable(torch.Tensor([
[[0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0],[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0],[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1], [0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0]],
[[1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0],[0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0],[0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0], [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0]],
[[1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0],[0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0],[0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0], [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0]]
]))
self.Y = Variable(torch.Tensor([[1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0], [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0], [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0]]))
self.len = 3
def __getitem__(self, index):
    return self.X[index], self.Y[index]

def __len__(self):
    return self.len

and in the forward() method of the Model class, the return line is a 33-dimensional vector :
Z = torch.nn.functional.softmax(self.linear_final(Z), dim=1)
and with the following criterion:
loss = criterion(y_hat, labels.long())
where,
criterion = torch.nn.CrossEntropyLoss()
Then, it launches the following error:
RuntimeError: multi-target not supported at /opt/conda/conda-bld/pytorch-cpu_1556653093101/work/aten/src/THNN/generic/ClassNLLCriterion.c:20
Does anyone knows the problem?
When I print the y_hat and the labels, I get the following result (batch_size=2):
tensor([[0.0126, 0.0251, 0.0233, 0.0266, 0.0150, 0.0274, 0.0565, 0.0332, 0.0490,
0.0282, 0.0231, 0.0313, 0.0362, 0.0102, 0.0111, 0.0923, 0.0161, 0.0842,
0.0192, 0.0235, 0.0163, 0.0274, 0.0200, 0.0190, 0.0223, 0.0361, 0.0098,
0.0532, 0.0126, 0.0279, 0.0771, 0.0254, 0.0085],
[0.0276, 0.0481, 0.0292, 0.0282, 0.0292, 0.0101, 0.0470, 0.0183, 0.0195,
0.0154, 0.0347, 0.0329, 0.0257, 0.0327, 0.0100, 0.0998, 0.0284, 0.0368,
0.0137, 0.0426, 0.0376, 0.0172, 0.0099, 0.0166, 0.0305, 0.0196, 0.0275,
0.0179, 0.0287, 0.0394, 0.0295, 0.0697, 0.0259]],
grad_fn=)
tensor([[0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0.],
[1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.]])
Thank you very much in advance.