pyproject.toml

# Package ######################################################################

[build-system]
requires = [
    "numpy",
    "packaging>=24.2",  # required by setuptools>=77 to validate PEP 639 license expressions
    "pyyaml",
    # 1.0 is required for [[tool.dynamic-metadata]], the [tool.scikit-build.env]
    # table, and native CMAKE_BUILD_TYPE env handling used below. CI pins the
    # exact patch we test against in .ci/docker/requirements-ci.txt.
    "scikit-build-core>=1.0",
    # Imported by torchgen at build time (cmake/Codegen.cmake runs
    # `python -m torchgen.gen`, and torchgen/utils.py uses `Self` /
    # `assert_never`). Currently also pulled in transitively through
    # scikit-build-core, but list it explicitly as a direct build-time
    # dep. The CI Docker image ships 4.12.2 on Python <3.14, so do not
    # raise the lower bound without bumping CI.
    "typing-extensions>=4.10.0",
    # Dependency chain: NNPACK -> PeachPy -> six. PeachPy emits NNPACK's hot
    # assembly loops at build time and does `import six`. NNPACK is on by
    # default (USE_NNPACK=ON); isolated PEP 517 builds need six available.
    "six",
]
build-backend = "scikit_build_core.build"

[tool.scikit-build]
# Track the build-system.requires floor (scikit-build-core>=1.0) so the schema
# and defaults are pinned to the version we build against.
minimum-version = "build-system.requires"
build-dir = "build"

[tool.scikit-build.env]
# MAX_JOBS is PyTorch's umbrella parallelism knob (also read by
# linters, cpp_extension JIT, nccl/MKLDNN sub-builds); alias it to the
# variable CMake natively honors for `cmake --build`. setdefault semantics:
# a user-set CMAKE_BUILD_PARALLEL_LEVEL always wins.
CMAKE_BUILD_PARALLEL_LEVEL = { env = "MAX_JOBS" }
# Listing CC/CXX here opts out of scikit-build-core's sysconfig-compiler
# injection (a documented env-table behavior), so CMake detects the compiler
# from PATH -- avoids the conda compiler_compat / stale-venv-gcc probe breaks.
# An ambient CC/CXX is still respected.
CC = { env = "CC" }
CXX = { env = "CXX" }

# cmake.build-type is deliberately not set: it defaults to Release, and
# leaving it unconfigured lets scikit-build-core honor a CMAKE_BUILD_TYPE
# set in the environment (.ci/pytorch/build.sh exports RelWithAssert for
# *-debug CI images). The overrides below map PyTorch's DEBUG and
# REL_WITH_DEB_INFO env vars to the corresponding build types; on
# multi-config generators (Visual Studio) the resolved type is passed as
# --config to cmake --build and cmake --install, ensuring they match.
[[tool.scikit-build.overrides]]
if.env.DEBUG = true
cmake.build-type = "Debug"

[[tool.scikit-build.overrides]]
if.env.REL_WITH_DEB_INFO = true
cmake.build-type = "RelWithDebInfo"

[[tool.scikit-build.overrides]]
# Force the Ninja generator on Windows. scikit-build-core otherwise defaults to
# the Visual Studio (multi-config) generator, under which the oneDNN-XPU
# ExternalProject's -DCMAKE_CXX_COMPILER=icx is ignored (VS picks the compiler by
# toolset), so oneDNN configures with MSVC and fails its -fsycl driver check.
# Generator resolution honors cmake.define.CMAKE_GENERATOR, so this lives
# here as the single source of truth
# (and covers plain non-CI editable builds too) instead of a CI-exported env var.
#
# Under Ninja, CMake does not default to MSVC: with the Intel oneAPI environment
# active (XPU builds) icx is on PATH and gets picked up as the host compiler,
# which miscompiles CPU code (icx passes sleef's __float128 cmake probe but then
# cannot compile sleefqp.c on the Windows target, ENABLEFLOAT128 gets set, the
# build fails). Pin CC/CXX=cl so the host build stays on MSVC while the XPU
# sub-projects keep using icx. env.CC/CXX setdefault semantics respect an
# explicitly set CC/CXX (e.g. clang-cl); platform-system matches sys.platform.
if.platform-system = "win32"
cmake.define.CMAKE_GENERATOR = "Ninja"
env.CC = "cl"
env.CXX = "cl"

# Other than CMAKE_GENERATOR above (win32), cmake.define is intentionally absent
# -- all BUILD_*/USE_* env vars and additional passthrough variables are
# forwarded by cmake/EnvVarForwarding.cmake so there is a single source of truth.

[[tool.dynamic-metadata]]
# Delegates to tools/generate_torch_version.py which resolves the version from
# PYTORCH_BUILD_VERSION (release/nightly), PKG-INFO (sdist), or version.txt.
provider = { path = "tools/metadata", module = "version" }

[[tool.dynamic-metadata]]
# Reads PYTORCH_EXTRA_INSTALL_REQUIREMENTS env var (pipe-separated PEP 508
# strings) to inject CUDA/ROCm/XPU pip package dependencies into the wheel.
provider = { path = "tools/metadata", module = "dependencies" }

[tool.scikit-build.sdist]
# Goal: ship exactly the git-tracked sources, minus repo/CI plumbing. The
# sdist file walk applies gitignore semantics, and several vendored trees
# commit files their own .gitignore matches (XNNPACK gen/ microkernels,
# oneDNN *.cpp via ideep, protobuf *.pb.cc, clog under deps/); PyTorch's own
# .gitignore (gen, *.pb.h) also hits tracked third-party files. The blanket
# includes below restore all of them.
#
# Mechanics governing both lists: an include match beats every exclude
# source (this exclude list, gitignore, built-ins). A !-negation inside
# include is not an exclusion -- it only withdraws include protection, and
# the file still ships unless an exclude source then catches it (built-ins
# catch .git and bytecode; .gitignore catches nccl, which is not a submodule
# but cloned into the tree at build time; the exclude list catches .github).
# That is why **/.github/** appears twice: the negation unprotects it under
# third_party/**, the exclude entry actually drops it -- there and at the
# top level. The exclude list is likewise the only mechanism dropping
# plumbing (.ci, .claude, .spin) that no include pattern covers.
#
# The flatbuffers/ittapi entries drop unneeded language bindings, which
# also contain symlinks (#157814) that sdist.resolve-symlinks="all" would
# otherwise dereference into duplicated content.
include = [
    "third_party/**",
    "aten/src/ATen/native/quantized/cpu/qnnpack/deps/**",
    "!**/.git",
    "!**/__pycache__/**",
    "!**/*.pyc",
    "!third_party/nccl/**",
    # third_party/build/ is an in-tree CMake build dir (gitignored); un-include
    # it so a dirty checkout does not leak build output into the sdist. Anchored
    # like the .gitignore entry, so it does not touch tracked build/ dirs deeper
    # in vendored trees (e.g. cutlass docs, ideep).
    "!third_party/build/**",
    "!**/.github/**",
    "!third_party/flatbuffers/java/**",
    "!third_party/flatbuffers/kotlin/**",
    "!third_party/flatbuffers/docs/source/CONTRIBUTING.md",
    "!third_party/ittapi/rust/**",
]
exclude = [
    "**/.github/**",
    ".ci/**",
    ".claude/**",
    ".spin/**",
    "third_party/flatbuffers/java/**",
    "third_party/flatbuffers/kotlin/**",
    "third_party/flatbuffers/docs/source/CONTRIBUTING.md",
    "third_party/ittapi/rust/**",
]

[tool.scikit-build.install]
# scikit-build-core auto-strips binaries in Release builds. PyTorch needs to
# keep symbols (e.g. for torch.utils.cpp_extension, ABI checks in CI).
strip = false

[tool.scikit-build.wheel]
# CMake install destinations (lib/, include/, share/cmake/) are relative to
# CMAKE_INSTALL_PREFIX. This setting places them under torch/ in the wheel,
# matching the existing layout (e.g., torch/lib/libtorch_cpu.so).
install-dir = "torch"
# Python packages to include in the wheel.
packages = ["torch", "torchgen", "functorch"]
# license-files is declared once under [project] (PEP 639 canonical location);
# scikit-build-core honors it directly. Do NOT also declare it here -- as of
# 0.12 that triggers an AssertionError.

# Mirror the legacy setup.py package_data allowlist as gitignore-style
# exclusions: without it, scikit-build-core's package walk plus the CMake
# install step ship ~2300 extra files (source trees, third-party static
# archives, cmake configs, dev artifacts) that the legacy setup.py omitted.
# This block is intended as a temporary filter; a follow-up will replace
# it with an install-component-based scheme that suppresses third-party
# install rules at source.
exclude = [
    # Static archives never belong in a Python wheel (legacy package_data
    # used a "lib/*.so*"/".dylib*"/".dll"/".lib" allowlist that excluded *.a
    # implicitly). The largest single offender today is libtorch_xpu_ops.a
    # at ~1.1GB.
    "**/*.a",
    # GNUInstallDirs places third-party cmake configs and static libs under
    # lib64/ on x86_64; we don't ship any of them.
    "torch/lib64/**",
    # Bulk C++ source tree -- only the AOTI runtime header is consumed by
    # downstream AOTInductor builds (and is staged explicitly via cmake).
    "torch/csrc/**",
    "!torch/csrc/inductor/aoti_runtime/model.h",
    # Source-only directories the package walk picks up but setup.py excluded.
    # Keep the .py modules nightly ships under torch/nativert/, and the
    # libshm headers consumed at runtime (torch/lib/libshm/{*.h},
    # torch/lib/libshm_windows/libshm.h).
    "torch/nativert/**",
    "!torch/nativert/**/*.py",
    "torch/headeronly/**",
    "torch/lib/libshm/**",
    "!torch/lib/libshm/**/*.h",
    "torch/lib/libshm_windows/**",
    "!torch/lib/libshm_windows/**/*.h",
    # Stray CMakeLists.txt copied in by directory installs.
    "**/CMakeLists.txt",
    # functorch dev artifacts (docs, notebooks, examples, op-analysis tools).
    "functorch/docs/**",
    "functorch/examples/**",
    "functorch/benchmarks/**",
    "functorch/op_analysis/**",
    # torchgen autoheuristic tuning scripts (used to generate heuristics,
    # not consumed at runtime).
    "torchgen/_autoheuristic/**",
    # Third-party cmake configs / docs that subproject installs leak in via
    # GNUInstallDirs share/cmake/ destinations.
    "torch/share/doc/**",
    "torch/share/cmake/fbgemm/**",
    "torch/share/cmake/kineto/**",
    "torch/share/cmake/sleef/**",
    "torch/share/cmake/XNNPACK/**",
    "torch/share/cmake/ittapi/**",
    "torch/share/cmake/dnnl/**",
    "torch/share/cpuinfo/**",
    # Windows analog of the above: third-party import libs and their CMake
    # package configs / pkg-config files leak in via the subproject install()
    # rules (GNUInstallDirs lib/cmake, plus *.lib), the way *.a + share/cmake/*
    # do on Linux. The setuptools wheel ships none of these and downstream
    # find_package(Torch) works: nothing in torch/share/cmake/ (the Torch
    # config tree, shipped identically) consumes them -- MKLDNN/Protobuf resolve
    # via QUIET + bundled-static fallbacks, and dnnl is statically linked into
    # torch_cpu.dll. dnnl.lib alone is ~1.3GB uncompressed. Do NOT broaden to
    # **/*.lib: torch's own c10/torch/torch_cpu/torch_python import libs are
    # required for Windows downstream linking and must stay.
    "torch/lib/dnnl.lib",
    "torch/lib/kineto.lib",
    "torch/lib/libprotobuf.lib",
    "torch/lib/libprotobuf-lite.lib",
    "torch/lib/libprotoc.lib",
    "torch/lib/mimalloc-2.3/mimalloc.lib",
    "torch/lib/cmake/**",
    "torch/cmake/**",
    "torch/lib/pkgconfig/**",
    # File types that are unambiguously build inputs or dev artifacts; none
    # of these appear in nightly wheels today.
    "**/*.bzl",
    "**/*.ipynb",
    "**/*.png",
    "**/*.sh",
    "**/*.proto",
    "**/*.pyi.in",   # codegen templates -> .pyi at build time
    "**/BUCK.oss",   # Bazel build file
    # Docs and editor / dev metadata that scikit-build-core's package walk
    # picks up but legacy setup.py omitted.
    "**/*.md",
    "**/.gitignore",
    "**/*.vim",
    # Lint-tool input only (consumed by tools/linter/adapters/header_only_linter.py),
    # not at runtime.
    "torch/header_only_apis.txt",
    # Example / benchmark sub-trees that look like Python sub-packages but
    # which legacy setup.py shipped 0 files from. Keeping them in lockstep
    # with the legacy wheel surface.
    "torch/ao/pruning/_experimental/data_sparsifier/benchmarks/**",
    "torch/ao/pruning/_experimental/data_sparsifier/lightning/tests/**",
    "torch/ao/quantization/experimental/**",
    "torch/distributed/benchmarks/**",
    "torch/distributed/checkpoint/examples/**",
    "torch/distributed/examples/**",
    "torch/distributed/tensor/examples/**",
    "torch/fx/experimental/shape_inference/**",
    # Only the sparse/ sub-dir is leakage; legacy ships the rest of
    # torch/utils/benchmark/examples/.
    "torch/utils/benchmark/examples/sparse/**",
    "torch/utils/_strobelight/examples/**",
    # Stray license file under torch/fx/experimental/unification/ that
    # legacy did not ship (the canonical vendored-code licenses we do ship
    # live under torch/_vendor/).
    "torch/fx/experimental/unification/LICENSE.txt",
    # torchgen codegen-generator scripts (not consumed at runtime); legacy
    # did not ship these either.
    "torchgen/decompositions/gen_*.py",
    "torchgen/fuse/gen_*.py",
    "torchgen/shape_functions/gen_*.py",
    # Thrift-generated C++ headers under torch/_export/serde/gen-cpp2/ and
    # the ATen Declarations.yaml codegen artefact -- not in legacy wheels.
    "torch/_export/serde/gen-cpp2/**",
    "torch/share/ATen/Declarations.yaml",
    # Convenience headers duplicated at the package root; the canonical
    # copies live at torch/include/torch/*.h. legacy ships only the
    # torch/include/... versions.
    "torch/script.h",
    "torch/library.h",
    "torch/extension.h",
    "torch/custom_class.h",
    "torch/custom_class_detail.h",
    # .py files placed under torch/include/fp16/ by the third_party/FP16
    # source layout (legacy ships only the .h files from that directory);
    # and protobuf .inc files legacy did not ship under torch/include/google/.
    "torch/include/fp16/*.py",
    "torch/include/google/protobuf/*.inc",
    # Browser-side JS files loaded from a CDN URL (torch/cuda/_memory_viz.py
    # references the jsdelivr URL directly) -- the local install copy is
    # never consumed.
    "torch/utils/viz/*.js",
    "torch/distributed/tensor/debug/*.js",
]

[tool.scikit-build.editable]
# Editable installs use redirect mode: Python files come from the source tree,
# CMake-built artifacts from the build tree. Auto-rebuild-on-import is left OFF:
# scikit-build-core's redirect finder otherwise re-runs cmake/ninja on every
# import (~7x, ~25s per `import torch` with no source change, plus build chatter
# on captured stderr). Rebuild explicitly instead; rebuild-on-import can be
# opted into per-install with SKBUILD_EDITABLE_REBUILD=true (or
# -C editable.rebuild=true).
mode = "redirect"
rebuild = false

[dependency-groups]
dev = [
    # This list should be kept in sync with the requirements-build.txt
    # in PyTorch root until the project fully migrates to pyproject.toml
    # after which this can be removed as it is already specified in the
    # [build-system] section
    "scikit-build-core>=1.0",
    "setuptools>=77.0.0,<82",  # 77.0 is the first release with PEP 639 license-files support
    "spin",
    "cmake>=3.27",
    "ninja",
    "numpy",
    "packaging>=24.2",  # required by setuptools>=77 to validate PEP 639 license expressions
    "pyyaml",
    "requests",
    "six",  # dependency chain: NNPACK -> PeachPy -> six
    "typing-extensions>=4.15.0",
    "pip",  # not technically needed, but this makes setup.py invocation work

    # This list should be kept in sync with the requirements.txt in
    # PyTorch root until the project fully migrates to pyproject.toml
    "build[uv]",  # for building sdist and wheel
    "expecttest>=0.3.0",
    "filelock",
    "fsspec>=0.8.5",
    "hypothesis",
    "jinja2",
    "lintrunner ; platform_machine != \"s390x\"",
    "networkx>=2.5.1",
    "optree>=0.13.0",
    "psutil",
    "spin",
    "sympy>=1.13.3",
    "wheel"
]

[project]
name = "torch"
description = "Tensors and Dynamic neural networks in Python with strong GPU acceleration"
readme = "README.md"
requires-python = ">=3.10"
# License info:
#   - The main Pytorch project license is BSD-3-Clause.
#   - The SPDX license expression below reflects installed pytorch packages.
license = "Apache-2.0 AND Apache-2.0 WITH LLVM-exception AND BSD-2-Clause AND BSD-3-Clause AND BSL-1.0 AND MIT"
license-files = [
    "LICENSE",
    "third_party/**/LICENSE",
    "third_party/**/LICENSE.txt",
    "third_party/**/LICENSE.rst",
]
authors = [{ name = "PyTorch Team", email = "packages@pytorch.org" }]
keywords = ["pytorch", "machine learning"]
classifiers = [
    "Development Status :: 5 - Production/Stable",
    "Intended Audience :: Developers",
    "Intended Audience :: Education",
    "Intended Audience :: Science/Research",
    "Topic :: Scientific/Engineering",
    "Topic :: Scientific/Engineering :: Mathematics",
    "Topic :: Scientific/Engineering :: Artificial Intelligence",
    "Topic :: Software Development",
    "Topic :: Software Development :: Libraries",
    "Topic :: Software Development :: Libraries :: Python Modules",
    "Programming Language :: C++",
    "Programming Language :: Python :: 3 :: Only",
    "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 :: 3.15",
]
dynamic = ["version", "dependencies"]

[project.scripts]
torchrun = "torch.distributed.run:main"
torchfrtrace = "torch.distributed.flight_recorder.fr_trace:main"

[project.entry-points."torchrun.logs_specs"]
default = "torch.distributed.elastic.multiprocessing:DefaultLogsSpecs"

[project.entry-points."torch.distributed.backends"]
mpi = "torch.distributed.distributed_c10d:_register_builtin_mpi_backend"
gloo = "torch.distributed.distributed_c10d:_register_builtin_gloo_backend"
nccl = "torch.distributed.distributed_c10d:_register_builtin_nccl_backend"
nccl2 = "torch.distributed.distributed_c10d:_register_builtin_nccl2_backend"
"nccl-lazy" = "torch.distributed.distributed_c10d:_register_builtin_nccl_lazy_backend"
ucc = "torch.distributed.distributed_c10d:_register_builtin_ucc_backend"
xccl = "torch.distributed.distributed_c10d:_register_builtin_xccl_backend"

[project.urls]
Homepage = "https://pytorch.org"
Repository = "https://github.com/pytorch/pytorch"
Documentation = "https://pytorch.org/docs"
"Issue Tracker" = "https://github.com/pytorch/pytorch/issues"
Forum = "https://discuss.pytorch.org"

[project.optional-dependencies]
optree = ["optree>=0.13.0"]
opt-einsum = ["opt-einsum>=3.3"]
pyyaml = ["pyyaml"]

# Linter tools #################################################################

[tool.isort]
src_paths = ["caffe2", "torch", "torchgen", "functorch", "test"]
extra_standard_library = ["typing_extensions"]
skip_gitignore = true
skip_glob = ["third_party/*"]
atomic = true
profile = "black"
indent = 4
line_length = 88
lines_after_imports = 2
multi_line_output = 3
include_trailing_comma = true
combine_as_imports = true

[tool.usort]
preserve_inline_comments = true
collapse_blank_lines_in_category = false

[tool.usort.known]
first_party = ["caffe2", "torch", "torchgen", "functorch", "test"]
standard_library = ["typing_extensions"]

[tool.ruff]
line-length = 88
src = ["caffe2", "torch", "torchgen", "functorch", "test"]
extend-exclude = ["third_party", "test/cpython"]

[tool.ruff.per-file-target-version]
"**/py312_intrinsics.py" = "py312"

[tool.ruff.format]
docstring-code-format = true
quote-style = "double"

[tool.ruff.lint]
# NOTE: Synchronize the ignores with .flake8
external = [
    # lintrunner grep-linter codes (see .lintrunner.toml) suppressed via `# noqa:`.
    "ISINSTANCE_FAKE_TENSOR",
    # Codes from flake8-only plugins that ruff doesn't implement.
    "P201",
    "P204",
    "T484",
    # Codes that are preview-only in ruff, so flake8 is still the enforcer.
    # As ruff promotes these out of preview, move them to flake8's ignore list.
    "B901",
    "B909",
    "E115",
    "E201",
    "E221",
    "E225",
    "E226",
    "E227",
    "E231",
    "E241",
    "E261",
    "E262",
    "E265",
    "E266",
    "E272",
    "E306",
]
ignore = [
    # these ignores are from flake8-bugbear; please fix!
    "B007", "B008", "B017",
    "B018", # Useless expression
    "B023",
    "B028", # No explicit `stacklevel` keyword argument found
    "E402",
    "C408", # C408 ignored because we like the dict keyword argument syntax
    "E501", # E501 is not flexible enough, we're using B950 instead
    "E741",
    "EXE001",
    "F405",
    # these ignores are from ruff NPY; please fix!
    "NPY002",
    # these ignores are from ruff PERF; please fix!
    "PERF203",
    "PERF401",
    # these ignores are from PYI; please fix!
    "PYI024",
    "PYI036",
    "PYI041",
    "PYI056",
    "SIM102", "SIM103", "SIM112", # flake8-simplify code styles
    "SIM105", # these ignores are from flake8-simplify. please fix or ignore with commented reason
    "SIM108", # SIM108 ignored because we prefer if-else-block instead of ternary expression
    "SIM110", # Checks for for loops that can be replaced with a builtin function, like any or all.
    "SIM114", # Combine `if` branches using logical `or` operator
    "SIM116", # Disable Use a dictionary instead of consecutive `if` statements
    "SIM117",
    "SIM300", # Yoda condition detected
    "TC006",
    # TODO: Remove Python-3.10 specific suppressions
    "B905",
]
select = [
    "B",
    "B904", # Re-raised error without specifying the cause via the from keyword
    "C4",
    "G",
    "E",
    "EXE",
    "F",
    "SIM",
    "W",
    # Not included in flake8
    "FURB",
    "LOG",
    "NPY",
    "PERF",
    "PGH004",
    "PIE",
    "PLC0131", # type bivariance
    "PLC0132", # type param mismatch
    "PLC1802", # len({expression}) used as condition without comparison
    "PLC0205", # string as __slots__
    "PLC3002", # unnecessary-direct-lambda-call
    "PLC0414", # Import alias does not rename original package
    "PLE",
    "PLR0133", # constant comparison
    "PLR0206", # property with params
    "PLR1722", # use sys exit
    "PLR1736", # unnecessary list index
    "PLW0127", # Self-assignment of variable
    "PLW0129", # assert on string literal
    "PLW0131", # named expr without context
    "PLW0133", # useless exception statement
    "PLW0245", # super without brackets
    "PLW0406", # import self
    "PLW0711", # binary op exception
    "PLW1501", # bad open mode
    "PLW1507", # shallow copy os.environ
    "PLW1509", # preexec_fn not safe with threads
    "PLW2101", # useless lock statement
    "PLW3301", # nested min max
    "PT006", # TODO: enable more PT rules
    "PT014", # duplicate parameterize case
    "PT022",
    "PT023",
    "PT024",
    "PT025",
    "PT026",
    "PYI",
    "Q003",  # avoidable escaped quote
    "Q004",  # unnecessary escaped quote
    "RSE",
    "RUF007", # pairwise over zip
    "RUF008", # mutable dataclass default
    "RUF013", # ban implicit optional
    "RUF015", # access first ele in constant time
    "RUF016", # type error non-integer index
    "RUF017",
    "RUF018", # no assignment in assert
    "RUF019", # unnecessary-key-check
    "RUF020", # never union
    "RUF024", # from keys mutable
    "RUF026", # default factory kwarg
    "RUF030", # No print statement in assert
    "RUF033", # default values __post_init__ dataclass
    "RUF041", # simplify nested Literal
    "RUF048", # properly parse `__version__`
    "RUF100", # unused noqa
    "RUF200", # validate pyproject.toml
    "S324", # for hashlib FIPS compliance
    "SLOT",
    "TC",
    "TRY002", # ban vanilla raise (todo fix NOQAs)
    "TRY203",
    "TRY401", # verbose-log-message
    "UP",
    "YTT",
    "S101",
]

[tool.ruff.lint.per-file-ignores]
"__init__.py" = [
    "F401",
]
"*.pyi" = [
    "PYI011", # typed-argument-default-in-stub
    "PYI021", # docstring-in-stub
    "PYI053", # string-or-bytes-too-long
]
"functorch/docs/source/tutorials/**" = [
    "F401",
]
"test/export/**" = [
    "PGH004",
]
"test/typing/**" = [
    "PGH004"
]
"test/typing/reveal/**" = [
    "F821",
]
"test/torch_np/numpy_tests/**" = [
    "F821",
    "NPY201",
]
"test/dynamo/test_bytecode_utils.py" = [
    "F821",
]
"test/dynamo/test_debug_utils.py" = [
    "UP037",
]
"test/dynamo/test_misc.py" = [
    "PGH004",
]
"test/jit/**" = [
    "PLR0133", # tests require this for JIT
    "PYI",
    "RUF015",
    "UP", # We don't want to modify the jit test as they test specify syntax
]
"test/test_jit.py" = [
    "PLR0133", # tests require this for JIT
    "PYI",
    "RUF015",
    "UP", # We don't want to modify the jit test as they test specify syntax
]
"test/inductor/s429861_repro.py" = [
    "PGH004",
]
"test/inductor/test_torchinductor.py" = [
    "UP037",
]
# autogenerated #TODO figure out why file level noqa is ignored
"torch/_appdirs.py" = ["PGH004"]
"torch/jit/_shape_functions.py" = ["PGH004"]
"torch/_inductor/fx_passes/serialized_patterns/**" = ["F401", "F501"]
"torch/_inductor/autoheuristic/artifacts/**" = ["F401", "F501"]
"torch/_inductor/codegen/**" = [
    "PGH004"
]
"torchgen/api/types/__init__.py" = [
    "F401",
    "F403",
]
"torch/utils/collect_env.py" = [
    "UP", # collect_env.py needs to work with older versions of Python
]
"torch/_vendor/**" = [
    "UP", # No need to mess with _vendor
]
"tools/linter/**" = [
    "LOG015" # please fix
]

[tool.codespell]
ignore-words = "tools/linter/dictionary.txt"

[tool.spin]
package = 'torch'

[tool.spin.commands]
"Build" = [
  ".spin/cmds.py:develop",
  ".spin/cmds.py:editable",
  ".spin/cmds.py:install",
  ".spin/cmds.py:clean",
  ".spin/cmds.py:lint",
  ".spin/cmds.py:fixlint",
  ".spin/cmds.py:quicklint",
  ".spin/cmds.py:quickfix",
]
"Regenerate" = [
  ".spin/cmds.py:regenerate_version",
  ".spin/cmds.py:regenerate_type_stubs",
  ".spin/cmds.py:regenerate_clangtidy_files",
  ".spin/cmds.py:regenerate_github_workflows",
]
"Documentation" = [
  ".spin/cmds.py:docs",
]
"Type" = [
    ".spin/cmds.py:pyrefly",
]