Sparse fake tensor support (#82172)
Add support for sparse fake tensors.
- The testing strategy is to run a fake tensor cross ref test on `test_sparse.py`. This is necessary because OpInfo sparse coverage is completely nonexistent. We could have tried to turn on cross ref testing globally for all files, but that would be very time consuming and the tests I'm interested in are mostly in this file. There are some exclusions in testing for things that don't work.
- I make fake tensor converter raise a UnsupportedFakeTensorException if the meta converter fails to do a conversion (which can happen in a relatively large number of situations).
- I relax fake tensor invariants so that you can make a fake tensor from a meta tensor. This is useful because in the cross ref test sometimes we operate on meta tensors.
- Fake tensor wrapping is improved to handle the case when a function doesn't return any tensors
- Meta converter is taught how to convert sparse tensors to meta
There's still a little more cleanup that needs to be done, but this is good for review.
Signed-off-by: Edward Z. Yang <[email protected]>
Pull Request resolved: https://github.com/pytorch/pytorch/pull/82172
Approved by: https://github.com/eellison
diff --git a/test/test_proxy_tensor.py b/test/test_proxy_tensor.py
index a4503b1..ab33104 100644
--- a/test/test_proxy_tensor.py
+++ b/test/test_proxy_tensor.py
@@ -556,8 +556,8 @@
# ???
xfail('nn.functional.ctc_loss'),
- # Sparse tensors are not supported with faketensors for now
- xfail('to_sparse'),
+ # proxy tensor doesn't support sparse correctly right now
+ skip('to_sparse'),
# segfaults
skip('block_diag'),
}
