Documentation mentions that it is possible to pass per class probabilities as a target.

The target that this criterion expects should contain either:
…
Probabilities for each class;
…
Target: … If containing class probabilities, same shape as the input.

which also comes with example:
>>> # Example of target with class probabilities
>>> input = torch.randn(3, 5, requires_grad=True)
>>> target = torch.randn(3, 5).softmax(dim=1)
>>> output = loss(input, target)
>>> output.backward()

Example fails with
  File "../torch/nn/functional.py", line 2824, in cross_entropy
    return torch._C._nn.cross_entropy_loss(input, target, weight, _Reduction.get_enum(reduction), ignore_index)
RuntimeError: 1D target tensor expected, multi-target not supported

Am I missing something?