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[Model] DiffusionGemma: honor logprob_token_ids on the converging step - #57417
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LucasWilkinson
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LGTM, thanks for the fix!
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The logprobs stashed on a request's converging step went through the top-k path only, so a request's logprob_token_ids were ignored. For a choice over many single-token options that is a real defect: at a 26-way slot only one to eight of the options rank in the top 20, the rest get no value, and the answer changes with the k requested (measured: Swahili at k=10, Greek at k=20 and 32, with most of the mass on tokens that spell the option name). The sampler now keeps the logprob token-id state like the autoregressive sampler does and passes it to compute_topk_scores with a per-row slot mapping, so every requested id gets its exact logprob at every canvas position. Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com> Signed-off-by: Matt Mastracci <matthew@mastracci.com>
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✅ Triggered Buildkite CI #89763 for commit
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2 participants
Purpose
DiffusionGemma ignores
logprob_token_ids. The logprobs it stashes on a request's converging step only go through the top-k path, so a request cannot ask for specifictoken ids.
The diffusion sampler now keeps the same
LogprobTokenIdsStatethe autoregressive sampler does and passes it tocompute_topk_scoreswith a per-row slot mapping, soevery requested id gets its exact logprob at every canvas position. Top-k alone, ids alone, or both all work.
Split out of #57250.
Test plan
Hardware: 1 DGX Spark.
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