Hi Fred, I tried it out, but for me, it doesnt find conv() in package cuda_ndarray gpuval = cuda_ndarray.conv(img, kern, mode, subsample). So, made the changes in the test_conv_cuda_ndarray _test_dummy().

I see that the cpu version is computed using py_conv(), which in turn calls scipy.signal.convolve2d. How can the result 'gpuval' now be the same as scipy.signal.convolve2d instead of the scipy.signal.correlate?

Also, this still passes tests for all image, kernel, channel and batch sizes: https://github.com/stencilman/Theano-1/blob/fb66035292ef070b86466bf61c9c42b8faaa0a1c/theano/sandbox/cuda/tests/test_conv_gemm.py

[CRASH] remove assert in opt and remove print

[CRASH] fix tutorial example related to lazy evaluation.

[FIX] Fix the init/deinit of the cublas handle

[ENH] Make the gpu back-end use the new numpy c interface

[CRASH, ENH] fix crash cublas and extra debug info for shared var.

If we re-init a new cublas context, destroy the old one. Better error me...

Linalg

fix crash of profiling atexit when it clashes with pycuda atexit handler

Crash fix in IncSubtensor.grad

Add tutorial test about it.

Used traceback module to set name of theano.function to file_name:line_number.