Update Pico2 docs with CMSIS-NN INT8 support and latency instrumentation#18898
Update Pico2 docs with CMSIS-NN INT8 support and latency instrumentation#18898psiddh merged 3 commits intopytorch:mainfrom
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Add documentation for the new --cmsis build flag, INT8 quantized model export via export_mlp_mnist_cmsis.py, and updated serial output showing per-inference latency timing and memory usage diagnostics. Co-authored-by: Claude <noreply@anthropic.com>
🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/18898
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Pull request overview
Updates the Pico2 MNIST documentation to describe the new CMSIS-NN INT8 workflow and the expanded runtime diagnostics printed over serial.
Changes:
- Document FP32 vs INT8 (CMSIS-NN accelerated) model export paths and firmware build commands.
- Add
--cmsisflag usage and include a build script options table. - Update example serial output to include per-inference timing, a latency summary, and post-load memory usage.
Reviewed changes
Copilot reviewed 2 out of 2 changed files in this pull request and generated 2 comments.
| File | Description |
|---|---|
| examples/raspberry_pi/pico2/README.md | Adds FP32/INT8 build+export instructions, script flags table, and updated sample serial output/diagnostics. |
| docs/source/pico2_tutorial.md | Mirrors the README updates in the Sphinx tutorial, including the CMSIS-NN INT8 workflow and updated runtime output examples. |
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Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
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Pull request overview
Copilot reviewed 2 out of 2 changed files in this pull request and generated 6 comments.
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- Memory pools are 200KB (204800 bytes), not 131072/4096 - Memory usage prints before inference loop, not after - Remove duplicate memory block from after latency summary - Fix PREDICTED line to include 🎯 prefix matching main.cpp Co-authored-by: Claude <noreply@anthropic.com>
Add documentation for the new --cmsis build flag, INT8 quantized model export via export_mlp_mnist_cmsis.py, and updated serial output showing per-inference latency timing and memory usage diagnostics.