Code for sparse was stolen from Yann Dauphin.

Make mlp_test test a more sensible case.

Previous test was testing settings where we removed either the
"local_track_shape_i" or "local_shape_to_shape_i" optimizations.
These are unlikely settings, what we test now is the complete
removal of the "ShapeOpt" optimization.

Fixed grad of grad of scan

Fixed tests with script run_tests_in_batch.py

Note sure it makes the file anymore readable, but at least I've tried.

Otherwise the numberic differentiation gradient quickly becomes numerically
unstable.

the index goes from 0 to n_mit_mot-1 for mit_mot sequnces.

The main bug was gradients where represented as shared variables.
Now we represent them as sit_sot sequences to which only the last step
is used (hence the savemem optimization does the memory clean up). The
advantage is that gradients with respect to sitsot are well defined.

When collecting shapes from the outputs of the inner function, we should
keep track that mit_mot arguments have multiple outputs for one argument.

The error was raised if either the dtype didn't match or ndim didn't match.
However the error message did not display the ndims.

Added missing __init__.py so that tests can be imported by nose.

All tests are now passing under Windows with Python 2.4.

Fixed max/argmax gradient tests in float32

fix how we compute the number of elements in the compile dir.

Work around bug in numpy 1.6 with ufunc.reduce

fix for fails in the buildbot

The tolerance needs to be increased because the numbers in the computations
are too small.

Fixes for Windows and Python 2.4

Fixed import error in a sparse test

Minor stuff (PEP8 and typos mostly)

The rephrasing is to avoid using 'type' for class name, given that
'type' has a special meaning in Theano.