Including mixed quant Conv1D op in Jarvis #14865
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/14865
Note: Links to docs will display an error until the docs builds have been completed. ❌ 2 New Failures, 1 PendingAs of commit f27863e with merge base f32e9fc ( NEW FAILURES - The following jobs have failed:
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Summary: # Context With the goal of porting mHML on Executorch, a few operators are missing. The main focus is on improving performance for the operators used by the model. # Summary This diff includes a general and HiFi4 optimized Convolution 1D operator. Specifically, it adds both a standard Convolution 1D implementation and a version optimized for HiFi4 DSPs, ensuring better performance on supported hardware. --- #hthtemplate Reviewed By: skrtskrtfb Differential Revision: D81652570
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Summary: # Context With the goal of porting mHML on Executorch, a few operators are missing. The main focus is on improving performance for the operators used by the model. # Summary This diff includes a general and HiFi4 optimized Convolution 1D operator. Specifically, it adds both a standard Convolution 1D implementation and a version optimized for HiFi4 DSPs, ensuring better performance on supported hardware. --- #hthtemplate Reviewed By: skrtskrtfb Differential Revision: D81652570
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Summary: # Context With the goal of porting mHML on Executorch, a few operators are missing. The main focus is on improving performance for the operators used by the model. # Summary This diff includes a general and HiFi4 optimized Convolution 1D operator. Specifically, it adds both a standard Convolution 1D implementation and a version optimized for HiFi4 DSPs, ensuring better performance on supported hardware. --- #hthtemplate Reviewed By: skrtskrtfb Differential Revision: D81652570
Summary: # Context With the goal of porting mHML on Executorch, a few operators are missing. The main focus is on improving performance for the operators used by the model. # Summary This diff includes a general and HiFi4 optimized Convolution 1D operator. Specifically, it adds both a standard Convolution 1D implementation and a version optimized for HiFi4 DSPs, ensuring better performance on supported hardware. --- #hthtemplate Reviewed By: skrtskrtfb Differential Revision: D81652570
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#hthtemplate
Reviewed By: skrtskrtfb
Differential Revision: D81652570