Reading the documentation https://pytorch.org/cppdocs/notes/tensor_basics.html 196 it looks like accessor() takes a template value which specifies the dimensionality. Is this value allowed to be different than the source tensor? For example if I want to access a tensor as a logical 1-d array, but the source tensor is a possibly noncontiguous (coming from a slice operation) n-d tensor, am I allowed to do my_tensor.accessor<float, 1>()?