pytorch

bb779078 - Make aot_autograd explicitly error when double backward (#92348)

Make aot_autograd explicitly error when double backward (#92348) Mitigates https://github.com/pytorch/pytorch/issues/91469 Changes: - ~once_differentiable can now be parametrized to print a custom error message~ - instead of once_differentiable, we do the backward inside another custom Function, which makes sure the graph is connected, but also makes sure to error on double backward - we now explicitly error when doing double backward with torch.compile + aot_autograd instead of being silently incorrect. ~The niceness of the error message can vary depending on whether your grad_outputs are passed, or whether you are doing `.grad()` or `.backward()`.~ Unchanged: - doing backward inside compiled function is still allowed. It currently causes a graph break and is equivalent to doing backward outside the compiled function. It might be nice to disallow this explicitly as well, but that can be done in a follow up. Pull Request resolved: https://github.com/pytorch/pytorch/pull/92348 Approved by: https://github.com/albanD