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Summary: Add the Cross compilation Script for RPi (4 & 5) for Linux host machine #15014
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/15014
Note: Links to docs will display an error until the docs builds have been completed. ❗ 1 Active SEVsThere are 1 currently active SEVs. If your PR is affected, please view them below: ❌ 5 New Failures, 3 Cancelled JobsAs of commit 7120fad with merge base fca0f38 ( NEW FAILURES - The following jobs have failed:
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…pi5) Test Plan: examples/raspberry_pi/rpi_setup.sh pi5 ... [100%] Linking CXX executable llama_main [100%] Built target llama_main [SUCCESS] LLaMA runner built successfully ==== Extracting Bundled Libraries ==== [INFO] Extracting GLIBC libraries from toolchain... [WARNING] Use bundled GLIBC script on RPI device ONLY if you encounter a GLIBC mismatch error when running llama_main. [SUCCESS] Bundled libraries prepared in: /home/sidart/working/executorch/cmake-out/bundled-libs [INFO] On Raspberry Pi, run: sudo ./install_libs.sh ==== Verifying Build Outputs ==== [INFO] Checking required binaries... [SUCCESS] ✓ llama_main (6.1M) [SUCCESS] ✓ libllama_runner.so (4.0M) [SUCCESS] ✓ libextension_module.a (89K) - static library [SUCCESS] All required binaries built successfully! ==== Setup Complete! ==== ✓ ExecuTorch cross-compilation setup completed successfully! 📦 Built binaries: • llama_main: /home/sidart/working/executorch/cmake-out/examples/models/llama/llama_main • libllama_runner.so: /home/sidart/working/executorch/cmake-out/examples/models/llama/runner/libllama_runner.so • libextension_module.a: Statically linked into llama_main ✅ • Bundled libraries: /home/sidart/working/executorch/cmake-out/bundled-libs/ 📋 Next steps: 1. Copy binaries to your Raspberry Pi pi5: scp /home/sidart/working/executorch/cmake-out/examples/models/llama/llama_main pi@<rpi-ip>:~/ scp /home/sidart/working/executorch/cmake-out/examples/models/llama/runner/libllama_runner.so pi@<rpi-ip>:~/ scp -r /home/sidart/working/executorch/cmake-out/bundled-libs/ pi@<rpi-ip>:~/ 2. Copy shared libraries to system location: sudo cp libllama_runner.so /lib/ # Only this one needed! sudo ldconfig 3. Dry run to check for GLIBC or other issues: ./llama_main --help # Ensure there are no GLIBC or other errors before proceeding. 4. If you see GLIBC errors, install bundled libraries: cd ~/bundled-libs && sudo ./install_libs.sh source setup_env.sh # Only do this if you encounter a GLIBC version mismatch or similar error. 5. Download your model and tokenizer: # Refer to the official documentation for exact details. 6. Run ExecuTorch with your model: ./llama_main --model_path ./model.pte --tokenizer_path ./tokenizer.model --seq_len 128 --prompt "What is the meaning of life ?" 🎯 Deployment Summary: 📁 Files to copy: 2 (llama_main + libllama_runner.so) 🏗️ Extension module: Built-in (no separate .so needed) 🔧 Toolchain saved at: /home/sidart/working/executorch/arm-toolchain/arm-gnu-toolchain-14.3.rel1-x86_64-aarch64-none-linux-gnu 🔧 CMake toolchain file: /home/sidart/working/executorch/arm-toolchain-pi5.cmake Happy inferencing! 🚀
Test Plan:
examples/raspberry_pi/rpi_setup.sh pi5
...
[100%] Linking CXX executable llama_main
[100%] Built target llama_main
[SUCCESS] LLaMA runner built successfully
==== Extracting Bundled Libraries ====
[INFO] Extracting GLIBC libraries from toolchain... [WARNING] Use bundled GLIBC script on RPI device ONLY if you encounter a GLIBC mismatch error when running llama_main. [SUCCESS] Bundled libraries prepared in: /home/sidart/working/executorch/cmake-out/bundled-libs [INFO] On Raspberry Pi, run: sudo ./install_libs.sh
==== Verifying Build Outputs ====
[INFO] Checking required binaries...
[SUCCESS] ✓ llama_main (6.1M)
[SUCCESS] ✓ libllama_runner.so (4.0M)
[SUCCESS] ✓ libextension_module.a (89K) - static library [SUCCESS] All required binaries built successfully!
==== Setup Complete! ====
✓ ExecuTorch cross-compilation setup completed successfully!
📦 Built binaries:
• llama_main: /home/sidart/working/executorch/cmake-out/examples/models/llama/llama_main
• libllama_runner.so: /home/sidart/working/executorch/cmake-out/examples/models/llama/runner/libllama_runner.so
• libextension_module.a: Statically linked into llama_main ✅
• Bundled libraries: /home/sidart/working/executorch/cmake-out/bundled-libs/
📋 Next steps:
Copy binaries to your Raspberry Pi pi5: scp /home/sidart/working/executorch/cmake-out/examples/models/llama/llama_main pi@:
/ scp /home/sidart/working/executorch/cmake-out/examples/models/llama/runner/libllama_runner.so pi@:/ scp -r /home/sidart/working/executorch/cmake-out/bundled-libs/ pi@:~/Copy shared libraries to system location: sudo cp libllama_runner.so /lib/ # Only this one needed! sudo ldconfig
Dry run to check for GLIBC or other issues: ./llama_main --help # Ensure there are no GLIBC or other errors before proceeding.
If you see GLIBC errors, install bundled libraries: cd ~/bundled-libs && sudo ./install_libs.sh source setup_env.sh # Only do this if you encounter a GLIBC version mismatch or similar error.
Download your model and tokenizer: # Refer to the official documentation for exact details.
Run ExecuTorch with your model: ./llama_main --model_path ./model.pte --tokenizer_path ./tokenizer.model --seq_len 128 --prompt "What is the meaning of life ?"
🎯 Deployment Summary:
📁 Files to copy: 2 (llama_main + libllama_runner.so)
🏗️ Extension module: Built-in (no separate .so needed)
🔧 Toolchain saved at: /home/sidart/working/executorch/arm-toolchain/arm-gnu-toolchain-14.3.rel1-x86_64-aarch64-none-linux-gnu
🔧 CMake toolchain file: /home/sidart/working/executorch/arm-toolchain-pi5.cmake
Happy inferencing! 🚀
Summary
[PLEASE REMOVE] See CONTRIBUTING.md's Pull Requests for ExecuTorch PR guidelines.
[PLEASE REMOVE] If this PR closes an issue, please add a
Fixes #<issue-id>
line.[PLEASE REMOVE] If this PR introduces a fix or feature that should be the upcoming release notes, please add a "Release notes: " label. For a list of available release notes labels, check out CONTRIBUTING.md's Pull Requests.
Test plan
[PLEASE REMOVE] How did you test this PR? Please write down any manual commands you used and note down tests that you have written if applicable.