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Cortex_M backend: Add conv op #15896
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Currently only support for NHWC memory format. Adds weights-per-tensor quantization as default quantization. Generalizes the CortexMPassManager to work with any pass with exported_program as init arg to support using both XNNPackPasses and ArmPasses. Refactors the QuantizedLinearFusionPass to become a more general CovertToCortexMPass for replacing Aten ops with corresponding Cortex-M ops. Note that this pass and quantized_op_fusion_pass have the same function except that the former uses call() and the latter uses the call_operator() function. This is likely to be refactored in a future patch. Signed-off-by: Adrian Lundell <[email protected]> Change-Id: I7f809550bcc706f5b08bf1597a519b66801489af
🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/15896
Note: Links to docs will display an error until the docs builds have been completed. ✅ You can merge normally! (2 Unrelated Failures)As of commit 5e56eb0 with merge base 3374ff8 ( BROKEN TRUNK - The following jobs failed but were present on the merge base:👉 Rebase onto the `viable/strict` branch to avoid these failures
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Nice, just make sure all Arm tests pass before merge I see some fail but might just be flakey and a retest or rebase might help (I have not checked).
Edit: Seem to have failed in initial setup, re-trigger a test run now.
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Unrelated failures |
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This might have caused some problems |
Currently only support for NHWC memory format.
Adds weights-per-tensor quantization as default quantization.
Generalizes the CortexMPassManager to work with any pass with exported_program as init arg to support using both XNNPackPasses and ArmPasses.
Refactors the QuantizedLinearFusionPass to become a more general CovertToCortexMPass for replacing Aten ops with corresponding Cortex-M ops.
cc @freddan80 @per @zingo @oscarandersson8218 @digantdesai