Joel Schlosser 5dabe2d464 Fix NJT backward tests (#143072) ... This PR fixes some issues with NJT backward / compile backward tests: 1. `requires_grad` was not being propagated appropriately during `SampleInput` generation, so a LOT of backward cases were untested before (sad times). This PR utilizes a helper function `_clone()` to clone() / detach() NJTs for SampleInputs while preserving `requires_grad` status. Note: the clone() / detach() stuff is for autograd; can't have two SampleInputs as part of the same autograd graph. 2. Per-sample skips weren't -fully- working; the op logic would still be invoked even with a skip. I found this out thanks to `split_with_sizes`, which segfaults during backwards because it tries to use an NST-specific formula. As annoying as it is, I tried a ton of things but ultimately had to split the `subtest_ctx` into that + a `skip_xfail_ctx` to run the subtests within. * Updated all uses of per-sample skips / xfails: 4 in `test_nestedtensor.py` and 1 in `test_vmap.py` 3. Added the appropriate skips / xfails to get everything passing. There are a shitton of bugs to fix! Pull Request resolved: https://github.com/pytorch/pytorch/pull/143072 Approved by: https://github.com/cpuhrsch, https://github.com/soulitzer		2024-12-12 18:06:23 +00:00
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definitions	Fix NJT backward tests (#143072)	2024-12-12 18:06:23 +00:00
__init__.py
core.py	Fix NJT backward tests (#143072)	2024-12-12 18:06:23 +00:00
refs.py	[BE][Easy][19/19] enforce style for empty lines in import segments in torch/[o-z]*/ (#129771)	2024-08-01 17:07:14 +00:00
utils.py	Remove unused Python variables in torch/[b-z]* (#136963)	2024-10-19 16:45:22 +00:00