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Fix flaky ONNX export test for wav2vec2-style ForPreTraining models (argmax near-tie) #50575

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Merged
ydshieh merged 2 commits into from
Nov 10, 2026
+5 −4
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Fix flaky ONNX export test for wav2vec2-style ForPreTraining models (argmax near-tie) #50575

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1f6e62b
Fix flaky ONNX export test for wav2vec2-style `ForPreTraining` models
ydshieh Nov 10, 2026
60cbcdd
Shorten the `onnx.exactness` reasons, refer to the PR for details
ydshieh Nov 10, 2026
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9 changes: 5 additions & 4 deletions tests/exporters/test_export.py
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Expand Up @@ -234,11 +234,12 @@
# Exported and run as usual, but not compared against eager (see the ``.exactness`` note above).
"onnx.exactness": {
"Wav2Vec2ForPreTraining": (
"`codevector_perplexity` and `projected_quantized_states` come out of a Gumbel-softmax draw "
"inside the forward, so the quantizer picks different codes each run and eager does not agree "
"with itself either."
"The quantizer picks codes with `argmax`; on near-tied logits ORT's rounding can pick another "
"code, and `codevector_perplexity` jumps far over the tolerance. See PR #50575."
),
"UniSpeechForPreTraining": "Same Gumbel-softmax quantizer draw as `Wav2Vec2ForPreTraining`.",
"UniSpeechForPreTraining": "Same `argmax` near-tie as `Wav2Vec2ForPreTraining`.",
"UniSpeechSatForPreTraining": "Same `argmax` near-tie as `Wav2Vec2ForPreTraining`.",
"Wav2Vec2ConformerForPreTraining": "Same `argmax` near-tie as `Wav2Vec2ForPreTraining`.",
Comment on lines +241 to +242

@ydshieh ydshieh Nov 10, 2026

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These last 2 are added in this PR.

"PatchTSTForPretraining": (
"The tiny config sets `random_mask_ratio=0.0`, so nothing is masked and the pretraining loss is "
"`0 / (0 + 1e-10)`: eager reports a clean `0.0` while ORT lands on `NaN`. The reconstruction it "
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