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pyproject.toml
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267 lines (244 loc) · 8.29 KB
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[project]
name = "tilelang-paddle"
description = "A tile level programming language to generate high performance code."
readme = "README.md"
requires-python = ">=3.9"
authors = [{ name = "TileLang Contributors" }, { name = "Tile-AI" }]
maintainers = [{ name = "Lei Wang", email = "leiwang1999@outlook.com" }]
license = "MIT"
keywords = ["BLAS", "CUDA", "HIP", "Code Generation", "TVM"]
classifiers = [
"Development Status :: 4 - Beta",
"Environment :: GPU",
"Operating System :: POSIX :: Linux",
"Operating System :: MacOS",
"Programming Language :: C++",
"Programming Language :: Python :: 3",
"Programming Language :: Python :: 3.9",
"Programming Language :: Python :: 3.10",
"Programming Language :: Python :: 3.11",
"Programming Language :: Python :: 3.12",
"Programming Language :: Python :: 3.13",
"Programming Language :: Python :: 3.14",
"Programming Language :: Python :: Implementation :: CPython",
"Intended Audience :: Developers",
"Intended Audience :: Science/Research",
"Topic :: Scientific/Engineering :: Artificial Intelligence",
]
dynamic = ["version"]
dependencies = [
# >=0.1.6 fixes a memory issue: tilelang#1502, but keep
# requirement as wide as possible to be compatible with other libraries
# pip will try to use latest version whenever possible.
"apache-tvm-ffi~=0.1.3,>=0.1.2", # PaddlePaddle need 0.1.3+
# torch-c-dlpack-ext provides prebuilt torch extensions.
# Without it, TVM FFI may require JIT compilation on first import.
# "torch-c-dlpack-ext; python_version < '3.14'", # This is no need in PaddlePaddle
"cloudpickle",
"ml-dtypes",
"numpy>=1.23.5",
"psutil",
# "torch",
# "torch>=2.4; platform_system == 'Darwin'",
# jit-compiling a torch extension needs setuptools
"setuptools; platform_system == 'Darwin'",
"tqdm>=4.62.3",
"typing-extensions>=4.10.0",
"z3-solver>=4.13.0,<4.15.5",
]
[project.optional-dependencies]
# mldtypes should be greater than 0.5.1
# if you want to enable fp4
fp4 = ["ml-dtypes>=0.5.1"]
# if you want to enable layout inference visualization
vis = ["matplotlib"]
# if you want to build with CUDA NVCC support
nvcc = ["nvidia-cuda-nvcc>=13.0.48", "nvidia-cuda-cccl>=13.0.50"]
[build-system]
requires = [
"cython>=3.1.0",
"scikit-build-core",
"z3-solver>=4.13.0,<4.15.5",
# Not for auditwheel, explicitly add patchelf for repairing libz3.so.
# See tvm's CMakeLists.txt for more information.
"patchelf>=0.17.2; platform_system == 'Linux'",
]
build-backend = "scikit_build_core.build"
[tool.scikit-build]
wheel.py-api = "cp38"
cmake.version = ">=3.26.1"
build-dir = "build"
# editable.rebuild = true
# Include backend and git info in version
metadata.version.provider = "version_provider"
metadata.version.provider-path = "."
experimental = true
# build.verbose = true
# logging.level = "DEBUG"
[tool.scikit-build.sdist]
include = [
"./VERSION",
".git_commit.txt",
"./LICENSE",
"THIRDPARTYNOTICES.txt",
"version_provider.py",
"requirements*.txt",
"tilelang/jit/adapter/cython/cython_wrapper.pyx",
"CMakeLists.txt",
"src/**",
"cmake/**",
# The vendored 3rdparty contents in sdist should be same as wheel.
# Need full TVM to build from source.
"3rdparty/tvm",
# CUTLASS
"3rdparty/cutlass/include",
"3rdparty/cutlass/tools",
# Composable Kernel
"3rdparty/composable_kernel/include",
"3rdparty/composable_kernel/library",
"testing/**",
"examples/**",
]
exclude = [".git", ".github", "**/.git", "**/.github", "3rdparty/**", "build"]
[tool.scikit-build.wheel.packages]
tilelang = "tilelang"
"tilelang/src" = "src"
# NOTE: The mapping below places the contents of '3rdparty' inside 'tilelang/3rdparty' in the wheel.
# This is necessary to find TVM shared libraries at runtime.
# The vendored 3rdparty contents in wheel should be same as sdist.
# TVM
"tilelang/3rdparty/tvm/src" = "3rdparty/tvm/src"
"tilelang/3rdparty/tvm/python" = "3rdparty/tvm/python"
"tilelang/3rdparty/tvm/include" = "3rdparty/tvm/include"
"tilelang/3rdparty/tvm/3rdparty/dmlc-core/include" = "3rdparty/tvm/3rdparty/dmlc-core/include"
"tilelang/3rdparty/tvm/version.py" = "3rdparty/tvm/version.py"
# CUTLASS
"tilelang/3rdparty/cutlass/include" = "3rdparty/cutlass/include"
"tilelang/3rdparty/cutlass/tools" = "3rdparty/cutlass/tools"
# Composable Kernel
"tilelang/3rdparty/composable_kernel/include" = "3rdparty/composable_kernel/include"
"tilelang/3rdparty/composable_kernel/library" = "3rdparty/composable_kernel/library"
[tool.codespell]
ignore-words = "docs/spelling_wordlist.txt"
skip = ["build", "3rdparty", "dist", ".venv"]
[tool.ruff]
target-version = "py39"
line-length = 140
output-format = "full"
exclude = ["3rdparty", "examples/deepseek_v32/inference"]
[tool.ruff.format]
quote-style = "double"
indent-style = "space"
skip-magic-trailing-comma = false
line-ending = "auto"
docstring-code-format = false
docstring-code-line-length = "dynamic"
[tool.ruff.lint.per-file-ignores]
# Do not upgrade type hint in testing and examples.
# See https://github.com/tile-ai/tilelang/issues/1079 for more information.
"testing/**.py" = ["UP", "FA"]
"examples/**.py" = ["UP", "FA"]
[tool.ruff.lint]
select = [
# pycodestyle
"E",
"W",
# Pyflakes
"F",
# pyupgrade
"UP",
"FA",
# flake8-bugbear
"B",
# flake8-simplify
"SIM",
# isort
# "I",
]
ignore = [
# Module level import not at top of file
"E402",
# star imports
"F405",
"F403",
# ambiguous name
"E741",
# line too long
"E501",
# if-else-block instead of ternary
"SIM108",
# key in dict.keys()
"SIM118",
# open file w.o. ctx manager
"SIM115",
# memory leaks
"B019",
# zip without explicit strict
"B905",
# No such file or directory
"E902",
]
[tool.pytest.ini_options]
verbosity_assertions = 3
filterwarnings = ["always"]
[tool.cibuildwheel]
archs = ["auto64"]
skip = "*musllinux*"
build-frontend = "build"
environment = { PYTHONDEVMODE = "1", PYTHONUNBUFFERED = "1" }
environment-pass = [
"CUDA_VERSION",
"NO_VERSION_LABEL",
"NO_TOOLCHAIN_VERSION",
"NO_GIT_VERSION",
"COLUMNS",
"CMAKE_GENERATOR",
"CMAKE_BUILD_PARALLEL_LEVEL",
"FORCE_COLOR",
"CLICOLOR_FORCE",
]
before-build = "env -0 | sort -z | tr '\\0' '\\n'"
windows.before-build = "set"
test-command = [
# "python -c 'import tilelang; print(tilelang.__version__)'",
]
[tool.cibuildwheel.linux]
environment.PYTHONDEVMODE = "1"
environment.PYTHONUNBUFFERED = "1"
environment.PATH = "/usr/local/cuda/bin:$PATH"
environment.LD_LIBRARY_PATH = "/usr/local/cuda/lib64:/usr/local/cuda/lib64/stubs:$LD_LIBRARY_PATH"
manylinux-x86_64-image = "manylinux_2_28" # AlmaLinux 8
manylinux-aarch64-image = "manylinux_2_34" # Z3 requires
# Install CUDA runtime and stub driver library
# manylinux_2_28 uses gcc 14, which needs CUDA >=12.8
before-all = """
set -eux
cat /etc/*-release
uname -a
case "$(uname -m)" in
"x86_64")
DEFAULT_CUDA_VERSION="12.8"
dnf config-manager --add-repo https://developer.download.nvidia.cn/compute/cuda/repos/rhel8/x86_64/cuda-rhel8.repo
;;
"aarch64")
DEFAULT_CUDA_VERSION="12.8"
dnf config-manager --add-repo https://developer.download.nvidia.com/compute/cuda/repos/rhel8/sbsa/cuda-rhel8.repo
;;
*)
exit 1
;;
esac
cudaver="$(echo "${CUDA_VERSION:-$DEFAULT_CUDA_VERSION}" | cut -d '.' -f-2)"
v="${cudaver//./-}"
dnf install -y "cuda-minimal-build-${v}" "cuda-driver-devel-${v}" "cuda-nvrtc-devel-${v}"
dnf clean all
"""
# Do not bundle libtvm_ffi.so and libz3.so because they are shipped by the dependency packages.
repair-wheel-command = "auditwheel -v repair --exclude libtvm_ffi.so --exclude libz3.so --exclude libcuda.so.1 --exclude '/usr/local/cuda*' -w {dest_dir} {wheel}"
[tool.cibuildwheel.macos]
repair-wheel-command = "delocate-wheel --verbose --ignore-missing-dependencies --no-sanitize-rpaths --require-archs {delocate_archs} -w {dest_dir} -v {wheel}"
[[tool.cibuildwheel.overrides]]
select = "*linux*x86_64*"
# x86_64 runners in GitHub Actions have limited storage,
# pre-install torch without caching to reduce disk usage during install tilelang.
before-test = ["pip install torch --no-cache-dir"]