On Wed, Sep 13, 2023 at 8:38 AM Antoine Pitrou <anto...@python.org> wrote:
> > Le 13/09/2023 à 02:37, Rok Mihevc a écrit : > > > > * **ragged_dimensions** = indices of ragged dimensions whose sizes may > > differ. Dimensions where all elements have the same size are called > > uniform dimensions. Indices are a subset of all possible dimension > > indices ([0, 1, .., N-1]). > > Ragged dimensions list can be left out. In that case all dimensions > > are assumed ragged. > > It's a bit confusing that an empty list means "no ragged dimensions" but > a missing entry means "all dimensions are ragged". This seems > error-prone to me. > > Also, to be clear, "ragged_dimensions" is only useful for data validation? > > I am also quite confused by how to interpret / use ragged dimensions. Given that this is a "variable" shaped tensor, I personally find specifying the exceptional case -- the "uniform" dimensions -- to be much more clear. I would propose instead: **uniform_dimenions** = Indices of dimensions whose sizes are guaranteed to remain constant. Indices are a subset of all possible dimension indices ([0, 1, .., N-1]). The uniform dimensions must still be represented in the `shape` field, and must always be the same value for all tensors in the array -- this allows code to interpret the tensor correctly without accounting for uniform dimensions while still permitting optional optimizations that take advantage of the uniformity. Uniform_dimensions can be left out, in which case it is assumed that all dimensions might be variable.
