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### Description 1. move the cache task definition into template 2. In debug mode, the compiler mtime is different in different machine. So, change the CCACHE_COMPILERCHECK to content. ### Motivation and Context 1. Accelerate the CoreML pipeline. Test run: https://dev.azure.com/onnxruntime/onnxruntime/_build/results?buildId=938040&view=logs&j=1ac7588f-a5bd-5ff7-4a8a-a34869d50220 With Cache, the run can be finished in 12 minutes. Without cache, it takes about 1 hour. 3. Make the cache function easy to use and maintain. --------- Co-authored-by: Edward Chen <18449977+edgchen1@users.noreply.github.com> |
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| .. | ||
| github | ||
| __init__.py | ||
| amd_hipify.py | ||
| build.py | ||
| clean_docker_image_cache.py | ||
| coverage.py | ||
| gen_def.py | ||
| get_docker_image.py | ||
| logger.py | ||
| op_registration_utils.py | ||
| op_registration_validator.py | ||
| patch_manylinux.py | ||
| policheck_exclusions.xml | ||
| reduce_op_kernels.py | ||
| replace_urls_in_deps.py | ||
| requirements.txt | ||
| update_tsaoptions.py | ||
| upload_python_package_to_azure_storage.py | ||