Discovery on adding support for name scopes to computations

[yanndupis]

Original clickup ticke: https://app.clickup.com/t/dx2y33

For graph visualization (and debugging) we would like to have support for name scoping. These should have no effort at runtime but simply add a bit of superficial meta-structure to computations that can be very useful in certain situations. See for instance https://www.tensorflow.org/api_docs/python/tf/name_scope.

An alternative to name scopes would be to have layered graphs, where hints are added to the computation to allow upper layers to function as an interpretation of lower layers, including interpretations for higher level tensors based on lower level tensors. The tricky part here seems to be that of what to do when we optimize a graph by either merging or pruning nodes. This means we will have to deal with composite higher level nodes (eg add+add+add) and partial higher level edges (with some component values not being computed).

Another related concept is that of sub-graphs and/or sub-computations, although these have an effort at runtime. We should also figure out how relevant name scopes are given we have support for sb-graphs and sub-computations.