pytorch/pytorch

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• Generated by apply-lint bot, see ${GH_RUN_URL}"
• SECONDS + 60 * 60 ))
• auditwheel repair --plat ${PLATFORM} --exclude libtriton.so ${RUNNER_TEMP}/artifacts/*.whl -w ${RUNNER_TEMP}/artifact...
• bash ${RUNNER_TEMP}/linter_script
• bash .ci/pytorch/binary_linux_test.sh
• convert $(SPHINXPROJ).docset/icon@2x.png -resize 16x16 $(SPHINXPROJ).docset/icon.png
• doc2dash --name $(SPHINXPROJ) --icon $(SOURCEDIR)/_static/img/pytorch-logo-flame.png --enable-js --online-redirect-ur...
• done < $SCAN
• elif [[ ${REF_TYPE} == tag
• inspect the test artifacts for details."
• lintrunner
• lintrunner --all-files
• lintrunner --apply-patches
• lintrunner -a --take $LINTERS -m origin/${BASE_BRANCH} 2>/dev/null
• lintrunner init
• lintrunner init --take $LINTERS
• node test/profiler/test_memory_viz.js
• python .ci/libtorch/smoke_test_extract_libtorch.py --output-dir ${GITHUB_WORKSPACE}/libtorch_output
• python .ci/pytorch/smoke_test/smoke_test.py --package torchonly
• python .github/scripts/trymerge.py --check-mergeability ${PR_NUM}
• python test/bench_mps_ops.py
• quote_names < $SCAN
• scan_escaping > $SCAN
• sha256sum requirements.txt pyproject.toml .lintrunner.toml > .lintbin/.lintrunner.sha256
• trap rm -f "$SCAN" "${UTIL_ERR:-}" EXIT
• type == number)) as $e (.
• type == number)) as $f ($acc
• while [ $SECONDS -lt $END_WAIT ]

full scan as JSON

• Device-agnostic acceleration codeAvoid hardcoding specific device types like 'cuda' in AI code. Instead, use device-agnostic approaches such as device type variables or a...

  pytorch/pytorch AI Python ml-systems 2025-07-07

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• Optimize numerical precisionWhen implementing AI operations that involve matrix multiplication or neural network components, explicitly support modern numerical prec...

  pytorch/pytorch AI C++ ml-systems 2025-07-08

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• Graceful API evolutionWhen modifying, deprecating, or replacing APIs, ensure a smooth transition experience for developers by following these practices: 1. **A...

  pytorch/pytorch API Python ml-systems 2025-05-15

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• Handle errors specificallyAlways be explicit and specific when handling errors rather than using catch-all approaches or implicit conventions. This improves code r...

  pytorch/pytorch Error Handling Python ml-systems 2025-07-08

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• Prevent null pollutionDesign your code to minimize the unexpected introduction of None values into data structures and APIs. Use immutable parameter types when...

  pytorch/pytorch Null Handling Python ml-systems 2025-07-08

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• Use higher-level iterationsWhen working with multiple sequences that need to be combined, prefer higher-level iteration abstractions over nested loops. This improve...

  pytorch/pytorch Algorithms Python ml-systems 2025-07-08

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• Choose appropriate exceptionsSelect the proper exception type based on the error scenario to provide clearer error handling and better debugging experience: 1. Use Va...

  pytorch/pytorch Error Handling C++ ml-systems 2025-07-08

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• Normalize configuration parametersAlways normalize configuration inputs (especially environment variables) by removing whitespace and applying consistent case transformati...

  pytorch/pytorch Configurations Python ml-systems 2025-07-08

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• Design for compatibilityWhen evolving APIs, prioritize backward compatibility to minimize disruption for existing users. Add new functionality using default argu...

  pytorch/pytorch API C++ ml-systems 2025-07-07

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• Optimize memory usageLimit memory consumption in performance-critical paths by conditionally creating large data structures or deferring allocation until need...

  pytorch/pytorch Performance Optimization C++ ml-systems 2025-07-02

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• Eliminate redundant operationsAvoid unnecessary operations that can impact performance. This includes:\n\ \n1. Redundant data transformations:\n - Load data directly...

  pytorch/pytorch Performance Optimization Python ml-systems 2025-07-01

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• Check CUDA availability firstAlways verify CUDA availability before performing CUDA-specific operations to prevent runtime errors when code runs on systems without CU...

  pytorch/pytorch Pytorch Python ml-systems 2025-07-08

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• Parameterize similar test casesInstead of duplicating test code or using nested loops, use test parameterization to handle multiple test cases efficiently. This improve...

  pytorch/pytorch Testing Python ml-systems 2025-07-08

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• Prefer HINTS in CMakeWhen configuring library searches in CMake, use `HINTS` instead of `PATHS` when you want to prioritize specific locations before falling ...

  pytorch/pytorch Configurations Txt ml-systems 2025-07-07

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• Purpose-revealing identifier namesChoose identifier names that clearly reveal their purpose and behavior. Names should be specific, descriptive, and self-explanatory: - **...

  pytorch/pytorch Naming Conventions Python ml-systems 2025-07-07

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• Reduce code duplicationEliminate repeated code patterns by using appropriate abstraction techniques. This improves readability, reduces maintenance burden, and ...

  pytorch/pytorch Code Style C++ ml-systems 2025-07-07

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• Thread context managementAlways explicitly set required thread context and state rather than assuming inheritance from parent threads or other concurrent processe...

  pytorch/pytorch Concurrency Python ml-systems 2025-07-05

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• Structure for readabilityStructure code to maximize readability by reducing unnecessary complexity. Use early returns to minimize nesting levels, move invariant c...

  pytorch/pytorch Code Style Python ml-systems 2025-07-04

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• Consistent code organizationFollow consistent code organization patterns: 1. Place static definitions in .cpp files rather than headers to prevent duplicate definiti...

  pytorch/pytorch Code Style Other ml-systems 2025-07-02

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• Modular configuration designConfiguration systems should be designed with modularity and clarity in mind. When creating configuration classes or mechanisms: 1. **Sep...

  pytorch/pytorch Configurations Other ml-systems 2025-06-30

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• Document configuration decisionsAlways document configuration decisions in package metadata files like `pyproject.toml` with clear comments, especially when: 1. Using de...

  pytorch/pytorch Configurations Toml ml-systems 2025-06-26

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• Reusable workflow designDesign CI/CD workflows with reusability and clear naming conventions from the start. Use meaningful prefixes that reflect the conceptual ...

  pytorch/pytorch CI/CD Yaml ml-systems 2025-06-05

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• Preserve API compatibilityWhen modifying existing APIs, always prioritize backward compatibility to avoid breaking client code. Before changing API signatures, fun...

  pytorch/pytorch API Other ml-systems 2025-07-08

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• Hardware acceleration considerationsWhen implementing hardware-accelerated operations for AI models, ensure support for the latest architectures while considering determinis...

  pytorch/pytorch AI Other ml-systems 2025-07-04

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• Actionable error messagesWhen writing error messages in PyTorch code, include not only what went wrong but also clear guidance on how to fix the issue. This helps...

  pytorch/pytorch Pytorch C++ ml-systems 2025-07-03

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• Descriptive unambiguous namesAlways use descriptive variable names that clearly indicate their purpose without requiring readers to check call sites or implementation...

  pytorch/pytorch Naming Conventions C++ ml-systems 2025-07-03

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• Centralize configuration detectionAlways use centralized configuration detection mechanisms (like CMake finder modules) instead of hardcoding paths or environment variable...

  pytorch/pytorch Configurations Shell ml-systems 2025-07-02

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• Choose data structures wiselyWhen designing algorithms, select data structures that accommodate all possible scenarios, not just the common case. For static analysis ...

  pytorch/pytorch Algorithms Other ml-systems 2025-07-02

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• Reuse existing algorithmsBefore implementing common algorithms or utilities, check if the codebase already contains an appropriate implementation. Reusing existin...

  pytorch/pytorch Algorithms C++ ml-systems 2025-06-24

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• Optimize container operationsMinimize CPU overhead in container operations by using efficient data structure patterns: 1. **Use static containers** for fixed lookup t...

  pytorch/pytorch Performance Optimization Other ml-systems 2025-06-04

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• Type-appropriate null representationAlways use type-appropriate mechanisms to represent the absence of a value. For objects, use default constructors rather than nullptr. Fo...

  pytorch/pytorch Null Handling C++ ml-systems 2025-06-03

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• Choose appropriate pointer typesSelect the right pointer type based on ownership semantics to prevent null reference issues and memory leaks. Follow these guidelines: 1....

  pytorch/pytorch Null Handling Other ml-systems 2025-05-28

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