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Previously, DTensor kept its own copy of the generator state after the first time a random operator was called on a DTensor. This copy would evolve independently from the generator outside of DTensor. After adding support for users to pass a specific generator into random operators (e.g. `uniform_(..., generator=)`), it was determined (in discussion on #159991) to change the semantics so that any random operations performed on DTensor would evolve the state of the publicly visible generators (either the default one or user-passed one). The upsides are (1) it is now possible to call torch.manual_seed() at any point in the program and have a consistent effect on DTensor, (2) DTensor ops have an observable effect on the generator. The downside is that users are now responsible for seeding their generator before using DTensor, ensuring all ranks use the same seed. Fixes #159991 confirmed docs rendered OK <img width="897" height="414" alt="image" src="https://github.com/user-attachments/assets/c082f0f0-5447-47aa-834f-65342eb237cd" /> Pull Request resolved: https://github.com/pytorch/pytorch/pull/160482 Approved by: https://github.com/wanchaol |
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