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
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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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Differential Revision: D81652570 Pull Request resolved: pytorch#14865
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Reviewed By: skrtskrtfb
Differential Revision: D81652570