pytorch/tools
Amy He b2069e7d01 Refactor NnapiCompilation registration into it's own file (#63183)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/63183

Move registration of NnapiCompilation into it's own file, so that `nnapi_bind.cpp` (which contains the implementation of NnapiCompilation) can be moved to `aten_cpu`, while maintaining the selectiveness for registration.

`nnapi_bind.cpp` is moved to `aten_cpu` in https://github.com/pytorch/pytorch/pull/62919. See the PR for more details on why it's needed.

ghstack-source-id: 135900318

Test Plan: Nnapi unit tests: `python test/test_nnapi.py`

Reviewed By: iseeyuan

Differential Revision: D30288708

fbshipit-source-id: 6ed5967fa6bd018075469d18e68f844d413cf265
2021-08-16 15:45:26 -07:00
..
amd_build
autograd Make torch.lu differentiable for wide/tall inputs + jit (#61564) 2021-08-16 11:40:57 -07:00
clang_format_hash
code_analyzer Shard Operators.cpp (#62185) 2021-08-09 16:19:49 -07:00
code_coverage [codemod][lint][caffe2] Extend BLACK coverage 2021-08-13 09:28:10 -07:00
codegen Codegen: Fix operator::name on windows (#62278) 2021-08-10 07:58:09 -07:00
config
coverage_plugins_package
fast_nvcc
gdb
jit
linter Delete .clang-tidy-oss (#62373) 2021-07-29 09:30:18 -07:00
lite_interpreter
lldb [torch deploy] add support for Python C extension modules (#58117) 2021-07-23 19:58:54 -07:00
pyi Implement NumPy-like frombuffer tensor constructor. (#59077) 2021-07-23 13:17:48 -07:00
rules
setup_helpers Respect user-set CMAKE_PREFIX_PATH (#61904) 2021-08-13 13:49:05 -07:00
shared
stats Adds JOB_BASE_NAME to steps of CircleCI mac workflows (#62892) 2021-08-06 11:34:17 -07:00
test Add a script to codemod max_tokens_total pragmas to C/C++ files (#61369) 2021-07-09 13:30:52 -07:00
testing Move all downloading logic out of common_utils.py (#61479) 2021-07-12 11:23:22 -07:00
__init__.py
actions_local_runner.py Update progress and error reporting in clang-tidy (#61672) 2021-07-19 11:19:06 -07:00
build_libtorch.py
build_pytorch_libs.py
build_variables.bzl Refactor NnapiCompilation registration into it's own file (#63183) 2021-08-16 15:45:26 -07:00
download_mnist.py Fix ConnectionError in download_mnist (#61789) 2021-07-16 17:02:13 -07:00
extract_scripts.py
generate_torch_version.py Update version.txt file path (#61177) 2021-07-12 07:30:10 -07:00
generated_dirs.txt
git-pre-commit Fix clang-tidy error in pre-commit script (#61918) 2021-07-20 12:40:56 -07:00
git_add_generated_dirs.sh
git_reset_generated_dirs.sh
nightly.py
pytorch.version
README.md Refactor clang_tidy.py (#61119) 2021-07-06 16:02:11 -07:00
render_junit.py remove unused type: ignore directives (#60006) 2021-06-18 07:23:31 -07:00
vscode_settings.py

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:

  • linter/clang_tidy - Script for running clang-tidy on lines of your script which you changed.
  • extract_scripts.py - Extract scripts from .github/workflows/*.yml into a specified dir, on which linters such as linter/run_shellcheck.sh can be run. Assumes that every run script has shell: bash unless a different shell is explicitly listed on that specific step (so defaults doesn't currently work), but also has some rules for other situations such as actions/github-script. Exits with nonzero status if any of the extracted scripts contain GitHub Actions expressions: ${{<expression> }}
  • 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.)
  • linter/mypy_wrapper.py - Run mypy on a single file using the appropriate subset of our mypy*.ini configs.
  • linter/run_shellcheck.sh - Find *.sh files (recursively) in the directories specified as arguments, and run ShellCheck on all of them.
  • stats/test_history.py - Query S3 to display history of a single test across multiple jobs over time.
  • linter/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.
  • linter/translate_annotations.py - Read Flake8 or clang-tidy warnings (according to a --regex) from a --file, convert to the JSON format accepted by pytorch/add-annotations-github-action, and translate line numbers from HEAD back in time to the given --commit by running git diff-index --unified=0 appropriately.
  • vscode_settings.py - Merge .vscode/settings_recommended.json into your workspace-local .vscode/settings.json, preferring the former in case of conflicts but otherwise preserving the latter as much as possible.

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: