This adds the missing `update_mapping`s step during cloning, as well as a new
`Feature` cloning step that prevents issues when features are copied to their
clones.

Since it is no longer necessary to clone `Constant`s, and they add extra work
for the merge rewrites, `clone_get_equiv`'s `copy_orphans` option has been
prevented from cloning `Constant`s.  The option is mostly applicable to
constants, but it has been retained for other non-`Constant` cases (just in
case) and backward compatibility.

This method adds the ability to clone a `HasInnerGraph` `Op` and its
inner-`FunctionGraph`.

This new method provides an interface for stateful `Feature`s to be easily
cloned and attached to other `FunctionGraph`s.

All VM implementations now perform variable updates themselves.  This leaves
some now redundant update code in `Function`, but it also removes some from
`Scan.perform`.

In order to use shared updates to pre-allocate the storage for mit-mot input and
output loops, `Scan` would need to remove the corresponding mit-mot outputs from
its inner-`FunctionGraph` before compilation and it would expect the `Function`
compilation pipeline to add them back at the end of the remaining outputs.

Now, `Scan`'s inner-`FunctionGraph`s maintain the same form at every point, and
no special logic is needed to compensate for post-compilation changes in the
order/location of inputs and outputs.

This changes the `update_storage` parameter from a list containing
the input indices that are to be updated with the last N-many outputs
to a tuple of tuples specifying input/output indices.

Now, arbitrary output-to-input update pairings are possible, instead of
forcing graphs and code to compensate for this unnecessary restriction.

This also prevents `SeqOptimizer.apply` from calling `Rewriter.add_requirements`
on each iteration through its list of sub-`Rewriter`s.

A few core `Feature` implementations were using `assert`s and generic
`Exception` instead of `AlreadyThere`, which unnecessarily produces errors
when already-attached `Feature` requirements are added by `Rewriter`s.

These changes allow one to pass an `fgraph` argument to all key functions in the
`Function` compilation pipeline.  The given `FunctionGraph` will be directly
compiled without cloning.  Unlike the previous `FunctionMaker.__init__`, this
one's `fgraph` argument *will* be optimized according to the given `mode` unless
the keyword argument `no_fgraph_prep` is `True`.

- 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(... == ...)`