Qualcomm AI Engine Direct - Enabling Support for Qualcomm Chipsets for Snapdragon 7+ Gen 3 - #22542
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…r Snapdragon 7+ Gen 3
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September 3, 2026 23:56
🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/22542
Note: Links to docs will display an error until the docs builds have been completed. ❌ 4 New FailuresAs of commit 1bec087 with merge base 843f77e ( NEW FAILURES - The following jobs have failed:
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### Summary Fixed a crash on AMD hosts when PyTorch's global backend flags are frozen. `QnnQuantizer.__init__` calls `disable_mkldnn_on_amd()`, which assigns `torch.backends.mkldnn.enabled = False`. PyTorch forbids that assignment once `disable_global_flags()` has been called, which happens whenever `torch.testing._internal.common_utils` is imported — as the Qualcomm test suite does. The result is that constructing a quantizer on an AMD host fails with: ``` RuntimeError: not allowed to set torch.backends.mkldnn flags after disable_global_flags; please use flags() context manager instead ``` The assignment is now guarded, so a frozen-flags environment leaves the existing MKLDNN setting in place instead of raising. Disabling MKLDNN is a workaround for AMD-host crashes, not a correctness requirement, so skipping it when the flag is locked is safe. Note that this is a temporary workaround for an issue introduced in a previous [pr](#22395), not a root-cause fix, I haven't validated that this change has not broken anything else. ### Test plan Ran the tests mentioned in the test plan section of #22542.
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Summary
Adding SoC support for SM7675 (Snapdragon 7+ Gen 3) and SM8635 (Snapdragon 8s Gen 3), both HTP V73.
Scope of Support:
"The SocModel doesn't support FP16"), so FP16 lowering does not produce a delegated graph. Note it also does not degrade gracefully today: models containing ops on the partitioner's non-decompose list (e.g.linear,layer_norm) fail to export rather than falling back to CPU.Note that these changes need the fix added in #22543 for the tests to pass.
Test plan