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2f9166ef89
This PR: - changes generate_vmap_rule to either be True or False. Previously it could be True, False, or not set. This simplifies the implementation a bit. - changes the vmap staticmethod to always be on the autograd.Function rather than sometimes defined. This is how the other staticmethod (forward, backward, jvp) are implemented and allows us to document it. There are 4 possible states for the autograd.Function w.r.t. to the above: - generate_vmap_rule is True, vmap staticmethod overriden. This raises an error when used with vmap. - generate_vmap_rule is False, vmap staticmethod overriden. This is valid. - generate_vmap_rule is True, vmap staticmethod not overriden. This is valid. - generate_vmap_rule is False, vmap staticmethod not overriden. This raises an error when used with vmap. Future: - setup_context needs the same treatment, but that's a bit tricker to implement. Test Plan: - new unittest - existing tests Pull Request resolved: https://github.com/pytorch/pytorch/pull/91787 Approved by: https://github.com/soulitzer |
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| .. | ||
| amp_examples.rst | ||
| autograd.rst | ||
| broadcasting.rst | ||
| cpu_threading_runtimes.svg | ||
| cpu_threading_torchscript_inference.rst | ||
| cpu_threading_torchscript_inference.svg | ||
| cuda.rst | ||
| ddp.rst | ||
| extending.func.rst | ||
| extending.rst | ||
| faq.rst | ||
| gradcheck.rst | ||
| hip.rst | ||
| large_scale_deployments.rst | ||
| modules.rst | ||
| mps.rst | ||
| multiprocessing.rst | ||
| numerical_accuracy.rst | ||
| randomness.rst | ||
| serialization.rst | ||
| windows.rst | ||
