- Use newer, NumPy-recommended `numpy.random` functions (e.g. replace `rand`
  `random`, `randn` with `standard_normal`, etc.)
- Seed some unseeded/inconsistently seeded tests
- Minor `pytest` usage updates (e.g. use parameterizations, `pytest.raises`, and
  `pytest.warns`)
- Use `np.array_equal` instead of `np.all(... == ...)`

This removes an inconsistency between Numpy and Aesara broadcasting rules, where a variable dimension with unknown shape was always assumed to be non-broadcastable (i.e., different than 1)

This adds `SharedVariable` construction tracking that allows one to determine
which variables were created within a specific scope (e.g. within a Python
function).  With this ability, we're able to determine which shared variable
update should and shouldn't be performed within the iterations of a `Scan` node.