* moved sandbox/conv.py to tensor/nnet/conv.py
* created tensor/signal/conv.py which implements generic 2D convolution (i.e.
traditional signal processing definition) + tests
* added tensor/nnet/tests/speed_test_conv.py which contains Fred's speed tests
for ConvOp
* added appropriate documentation to sphinx library docs

-> crossentropy optimization still works when storing labels on the GPU.

gpuelemwise

Get rid of references to the older THEANO_* environment variables in the code comments and inline doc.

Change type of config.unittests.rseed so it accepts the value "random", as THEANO_UNITTEST_SEED did.

* removed numpy as N, tensor as T
* wrapped docstrings to 80cols
* moved getFilterOutShp to staticmethod
* removed some useless code (old convolve2 function)

Reimplemented unittests for conv.

Speed tests will go in separate file (to come)

-side effect, the cuda test are not enabled by default, will be on the build bot.
-also, now the use fct don't have a default value.

fixes to make the behaviour of the cuda shared constructor more strict on accepting only float32 ndarrays