Approach is based on the approach of THC's pointwiseApply{1,2,3} family of kernels,
but doesn't have any dependencies on that code.
Adjacent contiguous dimensions of input tensors are compressed to reduce the complexity of indexing math.
For the completely contiguous case, the indexing logic simplifies to just the linear index.
In simple tests, this code matched or beat the equivalent from THC.
- To test whether or not a multiline string matches some expected
value, you can use assertExpected. This tests that the string
matches the content stored at a file based on the name of the
test (and an optional subname parameter you can pass if you
what to assertExpected multiple times.)
- Suppose you make a change that modifies the output in a big way.
Instead of manually going through and updating each test, you instead
run python test/test_jit.py --accept. This updates all of the expected
outputs. You can now review them one-by-one and make sure your
changes make sense.
We can add more features later (e.g., munging the output to make it
more stable, more sanity checking) but this is just to get us started
testing. One thing to watch out for is that accept tests on intermediate
representation can be a bit wobbly: it is *extremely* important that
people be able to read the IR. It may be worth introducing niceties
to the printer in order to ensure this is the case.
Signed-off-by: Edward Z. Yang <ezyang@fb.com>
