Added test with pycuda as example.

This probably didn't happen due to the order of optimization. But as
they are in a dictionnary we can't be sure it won't change with

set_subtensor.

This was the cause of the 3 failing test in scan. I also revised the entire
optimization, writing a bit more comments/

variables and some other cosmetic changes.

* * *
More informative error message

ensure they don't belong to a different env.

Also update the documentation.

The scope is to make the computational graph more readable, and to move
constants in the inner graph, allowing constant folding in the inner graph
to do its job (performance).

obtain some outputs/or other node.

In order for scan to identify which of the inner outputs is the stopping
condition I use this dummy class to wrap my condition in it.

Look for conditions that the user might provide ( if scan is to terminate on
a condition ). This feature will be later used the conditional terminating
scan.

One thing that I've tried is to avoid importing cuda.