This will help during debugging

After talking to Pascal, I decided to leave until in scan_module and not to
export it to theano.until. So I had to fix the tests as well for this.

I needed to do this when debugging, because I wanted to know both of their
values, but there was nothing wrong with the test, and with or without this
change it is the same. I just wanted to stay in a more clear form ( so
people don't get confused by which f1 we talking about)

return_steps has been depricated, and store_steps as well (it actually not
used anymore)

This follows the suggestion of Pascal that flatten just culters the
namespace.

Errors are obvious, first of all the data of the constants don't have to
scalars, and secondly, is not enough for outputs that have no owner to have
same type, but they should have the same index (i.e. correspond to the same
input). As I have all corresponding pairs of inputs in `common` and these
outputs are equal with their inputs, is sufficient to check if them ( as
pair) are part of common

This was in an attempt to fix a stochastic optimization error in DEBUG MODE.

They used to be there, because at one point I was timing the function under
the believe that it takes way to much. Is not the case anymore.

This follows the discussion that I had with Pascal, that tries to simplify
how scan deals with what the user gives it. In that direction I first
depricated some of the possibilities the user had, in order to get better
clarity in the code.

fix following Pascal's suggestion

We don't want scalars to be converted into TensorScalars ( the pushout
optimization will fail if that happens)

Those used to belong to the original implementation of the optimization,
which I changed to fit the new equal_computation function.

It used to be used by the old implementation of equal_computations, but now
is not needed anymore

There is no reason for this, just that I had a lot of problems with this
optimization. It turned out the problem to be caused by
local_useless_subtensor optimization (fix which I will push later).
In my attempts to debug it though, I ended up converting it into a global
optimizer, and I don't want to go through the pain of reverting it and
making sure also that it works.

Basically add information about scan if it stops on a condition or not
(using keyword for or while)

Fix following Pascal suggestion of the __eq__ of scan.

It helps by compiling the inner graph only once, making compilation much
faster

Basically change the code to be aware that the last input can be a
condition, and if so stop when that condition becomes True.

Specifically for initial states, they should always stay variables, and not
be constants !

My optimization pushes in the main graph a lot of computations in terms of
constants, and constant folding maxes out pretty quickly. This is a quick
fix to that. I'm not sure if 50 is not too much, I haven't played with that
value .. maybe 20 or something would suffice. I would also like to increase
this value only for constant folding and not all the others, but I didn't
know how.

theano.until

(note : the implementation of make_thunk is seen by DebugMode as a python
implementation, and it sees no C implementation for that Op. Are there
checks for the C implementation that are not done for the python
implementaion ? )