[Refactor] Skip patchelf if not installed #477
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…architectures * Updated the TMA barrier validation in `inject_tma_barrier.cc` to check for non-empty `barrier_id_to_range_` before raising an error for missing `create_list_of_mbarrier`. * Refactored architecture checks in `phase.py` to utilize a new constant `SUPPORTED_TMA_ARCHS`, allowing for easier updates and improved readability in the target architecture validation logic.
…hase.py * Added logging configuration to setup.py, replacing print statements with logger for better traceability. * Updated download and extraction functions to use logger for status messages. * Refactored TMA architecture checks in phase.py to utilize the new `have_tma` function for improved clarity and maintainability. * Introduced support for additional compute capabilities in nvcc.py, including TMA support checks.
…t GPU compute capability range
…pute_version * Updated the `have_tma` function in nvcc.py to take a `target` parameter, improving clarity and usability. * Adjusted calls to `have_tma` in phase.py to pass the target directly, enhancing maintainability and consistency in TMA support checks.
lucifer1004
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May 16, 2025
* [Refactor] Enhance TMA barrier validation and support for additional architectures * Updated the TMA barrier validation in `inject_tma_barrier.cc` to check for non-empty `barrier_id_to_range_` before raising an error for missing `create_list_of_mbarrier`. * Refactored architecture checks in `phase.py` to utilize a new constant `SUPPORTED_TMA_ARCHS`, allowing for easier updates and improved readability in the target architecture validation logic. * Enhance logging in setup.py and refactor TMA architecture checks in phase.py * Added logging configuration to setup.py, replacing print statements with logger for better traceability. * Updated download and extraction functions to use logger for status messages. * Refactored TMA architecture checks in phase.py to utilize the new `have_tma` function for improved clarity and maintainability. * Introduced support for additional compute capabilities in nvcc.py, including TMA support checks. * Update documentation for get_target_compute_version to reflect correct GPU compute capability range * Refactor have_tma function to accept tvm.target.Target instead of compute_version * Updated the `have_tma` function in nvcc.py to take a `target` parameter, improving clarity and usability. * Adjusted calls to `have_tma` in phase.py to pass the target directly, enhancing maintainability and consistency in TMA support checks.
LeiWang1999
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Jul 18, 2025
* [Refactor] Enhance TMA barrier validation and support for additional architectures * Updated the TMA barrier validation in `inject_tma_barrier.cc` to check for non-empty `barrier_id_to_range_` before raising an error for missing `create_list_of_mbarrier`. * Refactored architecture checks in `phase.py` to utilize a new constant `SUPPORTED_TMA_ARCHS`, allowing for easier updates and improved readability in the target architecture validation logic. * Enhance logging in setup.py and refactor TMA architecture checks in phase.py * Added logging configuration to setup.py, replacing print statements with logger for better traceability. * Updated download and extraction functions to use logger for status messages. * Refactored TMA architecture checks in phase.py to utilize the new `have_tma` function for improved clarity and maintainability. * Introduced support for additional compute capabilities in nvcc.py, including TMA support checks. * Update documentation for get_target_compute_version to reflect correct GPU compute capability range * Refactor have_tma function to accept tvm.target.Target instead of compute_version * Updated the `have_tma` function in nvcc.py to take a `target` parameter, improving clarity and usability. * Adjusted calls to `have_tma` in phase.py to pass the target directly, enhancing maintainability and consistency in TMA support checks.
LeiWang1999
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Jul 20, 2025
* [Refactor] Enhance TMA barrier validation and support for additional architectures * Updated the TMA barrier validation in `inject_tma_barrier.cc` to check for non-empty `barrier_id_to_range_` before raising an error for missing `create_list_of_mbarrier`. * Refactored architecture checks in `phase.py` to utilize a new constant `SUPPORTED_TMA_ARCHS`, allowing for easier updates and improved readability in the target architecture validation logic. * Enhance logging in setup.py and refactor TMA architecture checks in phase.py * Added logging configuration to setup.py, replacing print statements with logger for better traceability. * Updated download and extraction functions to use logger for status messages. * Refactored TMA architecture checks in phase.py to utilize the new `have_tma` function for improved clarity and maintainability. * Introduced support for additional compute capabilities in nvcc.py, including TMA support checks. * Update documentation for get_target_compute_version to reflect correct GPU compute capability range * Refactor have_tma function to accept tvm.target.Target instead of compute_version * Updated the `have_tma` function in nvcc.py to take a `target` parameter, improving clarity and usability. * Adjusted calls to `have_tma` in phase.py to pass the target directly, enhancing maintainability and consistency in TMA support checks.
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This pull request introduces logging enhancements to replace
printstatements with a standardized logging approach, improves GPU architecture handling, and refactors TMA (Tensor Memory Accelerator) support logic. These changes enhance maintainability, debugging, and extendability of the codebase.Logging enhancements:
setup.pyfor consistent logging across the script. Replaced allprintstatements with appropriateloggercalls, such aslogger.infoandlogger.warning. This includes updates in functions likedownload_and_extract_llvm,is_git_repo,patch_libs, and various methods in custom commands. [1] [2] [3] [4] [5] [6] [7] [8] [9] [10]