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[Backend Tester] Add SNR validation #12924

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merged 5 commits into from
Jul 29, 2025

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@GregoryComer GregoryComer commented Jul 28, 2025

Add SNR validation for model outputs. This is a generally more robust than tight element-wise tolerances, as it takes the entire tensor into account. I'm relaxing atol to handle outliers and reduce noise.

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🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/12924

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[ghstack-poisoned]
GregoryComer added a commit that referenced this pull request Jul 29, 2025
ghstack-source-id: c8c9103
ghstack-comment-id: 3129418402
Pull-Request: #12924
@GregoryComer GregoryComer marked this pull request as ready for review July 29, 2025 05:58
@GregoryComer GregoryComer requested a review from cccclai as a code owner July 29, 2025 05:58
@GregoryComer GregoryComer requested a review from digantdesai July 29, 2025 05:58
rtol=rtol,
equal_nan=True,
)
and computed_snr >= snr
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Suggested change
and computed_snr >= snr
and (computed_snr >= snr
or math.isnan(computed_snr))

[ghstack-poisoned]
GregoryComer added a commit that referenced this pull request Jul 29, 2025
ghstack-source-id: 8f34ea9
ghstack-comment-id: 3129418402
Pull-Request: #12924
[ghstack-poisoned]
GregoryComer added a commit that referenced this pull request Jul 29, 2025
ghstack-source-id: 8f34ea9
ghstack-comment-id: 3129418402
Pull-Request: #12924
[ghstack-poisoned]
GregoryComer added a commit that referenced this pull request Jul 29, 2025
ghstack-source-id: 8f34ea9
ghstack-comment-id: 3129418402
Pull-Request: #12924
@GregoryComer GregoryComer merged commit 15504dc into gh/GregoryComer/103/head Jul 29, 2025
98 of 115 checks passed
@GregoryComer GregoryComer deleted the gh/GregoryComer/104/head branch July 29, 2025 17:43
@GregoryComer GregoryComer restored the gh/GregoryComer/104/head branch July 29, 2025 21:37
@GregoryComer GregoryComer deleted the gh/GregoryComer/104/head branch July 29, 2025 21:37
GregoryComer added a commit to GregoryComer/executorch that referenced this pull request Jul 31, 2025
Add SNR validation for model outputs. This is a generally more robust
than tight element-wise tolerances, as it takes the entire tensor into
account. I'm relaxing atol to handle outliers and reduce noise.
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3 participants