Make blas functions work with all stride patterns

Fix dtype in sparse test.

Mixed changes

Test nvidia driver

This allow to make sure the test for the driver was executed.

raise an exception if the test fail. This is because some nvidia driver version don't correctly handle our reduction code.

Both BLAS and Numpy were trying to be too clever, BLAS by wanting a
pointer to the beginning of the memory chunk (even if it will start from
the end, and Numpy by providing a pointer to the first element, that is
at the end of the memory buffer.

PyArray_GETCONTINUOUS considers 0-sized arrays as contiguous,
even if they have negative strides on the 0-length dimension for
instance, which confuses BLAS.

And it seems a good idea, since several are failing...

Do not repeat a variable in a function's inputs

Simplified code for In.borrow and Param.borrow

That's the reason why DebugMode was complaining.

Broadcast input of sparse_from_dense so ndim=2

Fix dtype of input value in test_diag

Since csc_matrix's default dtype is floatX, the numpy value needs
to have a compatible dtype.

Do not constant-fold Alloc if it is the output

Since mutable=True is incompatible with borrow=False, it is better to
raise an exception to make sure it's being noticed.

make_node used to crash, now it works.
A test detects the problem.

This makes things easier for shape inference and gradient operations.
Also fix broadcasting pattern of the gradient.

This commit simplifies the code so that In.borrow and Param.borrow can
only be True or False (not None). It also makes the corresponding code
for these two objects more similar.

There should be no functional change, it just makes the code easier to
understand.

Finished DOC/TEST/REVIEW sparse Diag Op

Fix test_diag_grad to work with verify_grad