fix: use stable seeds in PyTorch notebooks - #644
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Replace process-randomized hash-derived seeds with fixed integer seeds so the PyTorch and Lightning examples initialize their RNGs consistently across Python processes.
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Description
Several PyTorch notebooks here state they behave deterministically, but they don't appear to actually do that. This is because they derive their seeds from
hash("..."). Python randomizes string hashes between interpreter processes, so these notebooks can actually initialize their RNGs differently across runs.This updates:
To make this fix, I had to replace the "self-commenting hashes" - for example,
hash("setting random seeds")- with a named integer seed, so the code has lost a bit of its former character. If y'all want this recovered somehow (perhaps a short comment), just let me know.Why this matters
I found this while researching a prototype Ruff rule for reproducibility problems. I ran a small exploratory search for this pattern, and the same recognizable recipe appeared in at least 24 other repositories. This suggests that the pattern here has propagated beyond W&B's own examples, so correcting this now can help prevent the problem from spreading further.
I've also submitted wandb/docs#3072, which updates the corresponding
wandb/docspage, which contains the same bug.Testing
PYTHONHASHSEED.