pytorch

7dd795cb - Prevent ref cycle creation in inner hook (#82776)

Prevent ref cycle creation in inner hook (#82776) Towards fixing https://github.com/pytorch/pytorch/issues/82482 This PR fixes two things: ## 1) memory leak The .detach() call prevents a true memory leak in some cases where the user function is using multiple ops in a row that save their inputs. The following chain of objects keep each other alive - the `storage` object - a recomputed Tensor y - y's grad_fn FooBackward (in c++) - FooBackward's SavedVariables (in c++) - SavedVariable Hook - the `inner_pack` function - captures `storage` Since part of this cycle is in c++, the python gc is not able to break it. Should THPCppFunction_traverse actually visit it's SavedVariables which in turn should visit their hooks? I think the answer is yes but I haven't dived into which python object is traversing what as if there is non-unique ownership of the c++ object, it makes the traversal a lot trickier. @ezyang do you think we should dive into this more? In this case, this can be easily solved anyways by storing `y.detach()` in the `storage` object as we don't care about the temporary backward graph that gets created during the second forward call. ## 2) Lifetime of the recomputed buffers The new storage system is now such that the lifetime of the recomputed buffer is directly linked to the SavedVariable c++ object. Meaning that this buffer will get deleted IIF the SavedVariable is cleared. This means that we now get the exact same behavior as the version without the saved variable hook where Tensors are saved directly on the SavedVariable object. This is great as this solves all the cases where the non-checkpoint version used to work but the checkpoint version does not (even double access or retain_graph=True). The one drawback of this approach though is that the buffer do NOT get cleared when the user passes in `retain_graph=True`! The next backward won't even re-run the forward as it already has all the buffers available. Is this a problem that you think we would need to find a solution for @rohan-varma or it is niche enough that we don't care for now? Pull Request resolved: https://github.com/pytorch/pytorch/pull/82776 Approved by: https://github.com/ezyang, https://github.com/rohan-varma