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* test(version-compat): keep GRPO fake-run logits finite on CPU The GRPO fake-run test samples completions from a tiny untrained model on CPU. Such a model can emit non-finite logits, so torch.multinomial inside generate() intermittently raises "probability tensor contains either inf, nan or element < 0" -- a nondeterministic sampling failure, not a regression (the Trainer already fixes the seed, but CPU reduction order is not bit-reproducible). Add a forward hook that sanitizes the LM head logits to a finite bounded range before sampling, so the fake run reliably exercises the whole train loop; the test checks the loop runs, not the numerics. * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * test(version-compat): drop redundant nan_to_num bounds (clamp handles them) * test(version-compat): scope GRPO finite-logits guard to the GRPO test Only test_grpo_trains_on_cpu autoregressively samples completions, so it is the only canary that can hit the non-finite-logits torch.multinomial crash. Move the _guard_finite_logits hook out of the shared _load_plain() and into test_grpo_trains_on_cpu so the SFT and DPO canaries keep asserting against the model's true, unclamped logits. --------- Co-authored-by: Daniel Han <unslothai@gmail.com> Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> |
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| .. | ||
| __init__.py | ||
| _fetch.py | ||
| test_bitsandbytes_pinned_symbols.py | ||
| test_peft_pinned_symbols.py | ||
| test_sentence_transformers_pinned_symbols.py | ||
| test_transformers_pinned_symbols.py | ||
| test_trl_fake_train_cpu.py | ||
| test_trl_grpo_fake_run.py | ||
| test_trl_grpo_pinned_symbols.py | ||
| test_unsloth_zoo_save_merged_pinned_symbols.py | ||