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android / platform / external / pytorch / 09f1f14569 / . / tools
tree: e3bd6ea1cb4f91c59639cbe304db18e1b3327d52 [path history] [tgz]
  1. amd_build/
  2. autograd/
  3. clang_format_hash/
  4. code_analyzer/
  5. code_coverage/
  6. codegen/
  7. config/
  8. docker/
  9. fast_nvcc/
  10. gdb/
  11. jit/
  12. lite_interpreter/
  13. pyi/
  14. rules/
  15. setup_helpers/
  16. shared/
  17. stats_utils/
  18. test/
  19. __init__.py
  20. build_libtorch.py
  21. build_pytorch_libs.py
  22. build_variables.bzl
  23. clang_format_all.py
  24. clang_format_ci.sh
  25. clang_format_utils.py
  26. clang_tidy.py
  27. download_mnist.py
  28. export_slow_tests.py
  29. flake8_hook.py
  30. generate_torch_version.py
  31. generated_dirs.txt
  32. git-clang-format
  33. git-pre-commit
  34. git_add_generated_dirs.sh
  35. git_reset_generated_dirs.sh
  36. mypy_wrapper.py
  37. nightly.py
  38. print_test_stats.py
  39. pytorch.version
  40. README.md
  41. test_history.py
  42. trailing_newlines.py
  43. update_disabled_tests.sh
tools/README.md

This folder contains a number of scripts which are used as part of the PyTorch build process. This directory also doubles as a Python module hierarchy (thus the __init__.py).

Overview

Modern infrastructure:

  • autograd - Code generation for autograd. This includes definitions of all our derivatives.
  • jit - Code generation for JIT
  • shared - Generic infrastructure that scripts in tools may find useful.
    • module_loader.py - Makes it easier to import arbitrary Python files in a script, without having to add them to the PYTHONPATH first.

Legacy infrastructure (we should kill this):

  • cwrap - Implementation of legacy code generation for THNN/THCUNN. This is used by nnwrap.

Build system pieces:

  • setup_helpers - Helper code for searching for third-party dependencies on the user system.
  • build_pytorch_libs.py - cross-platform script that builds all of the constituent libraries of PyTorch, but not the PyTorch Python extension itself.
  • build_libtorch.py - Script for building libtorch, a standalone C++ library without Python support. This build script is tested in CI.
  • fast_nvcc - Mostly-transparent wrapper over nvcc that parallelizes compilation when used to build CUDA files for multiple architectures at once.
    • fast_nvcc.py - Python script, entrypoint to the fast nvcc wrapper.

Developer tools which you might find useful:

  • clang_tidy.py - Script for running clang-tidy on lines of your script which you changed.
  • git_add_generated_dirs.sh and git_reset_generated_dirs.sh - Use this to force add generated files to your Git index, so that you can conveniently run diffs on them when working on code-generation. (See also generated_dirs.txt which specifies the list of directories with generated files.)
  • mypy_wrapper.py - Run mypy on a single file using the appropriate subset of our mypy*.ini configs.
  • test_history.py - Query S3 to display history of a single test across multiple jobs over time.
  • trailing_newlines.py - Take names of UTF-8 files from stdin, print names of nonempty files whose contents don't end in exactly one trailing newline, exit with status 1 if no output printed or 0 if some filenames were printed.

Important if you want to run on AMD GPU:

  • amd_build - HIPify scripts, for transpiling CUDA into AMD HIP. Right now, PyTorch and Caffe2 share logic for how to do this transpilation, but have separate entry-points for transpiling either PyTorch or Caffe2 code.
    • build_amd.py - Top-level entry point for HIPifying our codebase.

Tools which are only situationally useful: