Arm backend: Keep DeepSeek FP8 on xlarge path - #21612
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bdemirb merged 2 commits intoAug 7, 2026
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Keep the DeepSeek-R1-Distill-Qwen-1.5B FP8 layer tests on the existing generic xlarge TOSA and VKML model suites. This drops the dedicated DeepSeek job wiring added in the previous patchset and follows the existing Arm backend model for memory-heavy coverage: smaller cases stay in the normal shard and heavy cases run through the serialized xlarge path. That keeps the FP8 coverage in CI without introducing DeepSeek-specific test entrypoints or workflow jobs. Authored with Codex. Signed-off-by: Baris Demir <baris.demir@arm.com> Change-Id: I2337d551a1b3c6c2d23b09d697c7713de6d9a5c0
🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/21612
Note: Links to docs will display an error until the docs builds have been completed. ❗ 1 Active SEVsThere are 1 currently active SEVs. If your PR is affected, please view them below: ❌ 7 New Failures, 1 Unrelated FailureAs of commit 1750c29 with merge base 8702327 ( NEW FAILURES - The following jobs have failed:
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…R1_Distill_Qwen_1.5B_reland
zingo
approved these changes
Aug 6, 2026
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Keep the DeepSeek-R1-Distill-Qwen-1.5B FP8 layer tests on the existing generic xlarge TOSA and VKML model suites.
This drops the dedicated DeepSeek job wiring added in the previous patchset and follows the existing Arm backend model for memory-heavy coverage: smaller cases stay in the normal shard and heavy cases run through the serialised xlarge path.
That keeps the FP8 coverage in CI without introducing DeepSeek-specific test entrypoints or workflow jobs.
cc @digantdesai @freddan80 @per @zingo @oscarandersson8218 @mansnils @Sebastian-Larsson @robell @rascani