Convert onehot encoded output to target

[arya47 (Aryaman)]

Currently i have my targets one hot encoded st their values are:

tensor([[1, 0],
        [0, 1],
        [0, 1],
        [0, 1],
        [0, 1],
        [0, 1],
        [1, 0],
        [0, 1],
        [1, 0],
        [1, 0]])

for a batch size 10,
how do i convert these to required format for CrossEntropy before training?

Thanks

[arya47 (Aryaman)]

solved

PyTocrh way for one-hot-encoding multiclass target variable

You could use this code snippet to transform your class indices into a one-hot encoded target: target = torch.randint(0, 10, (10,)) one_hot = torch.nn.functional.one_hot(target)