From 6421dd8d4fc2952a32e54ee9022f07dfa813fad7 Mon Sep 17 00:00:00 2001 From: Jirka Borovec <6035284+Borda@users.noreply.github.com> Date: Wed, 31 Jan 2024 18:09:39 +0100 Subject: [PATCH] precommit: drop Black in favor of Ruff (#19380) --- .pre-commit-config.yaml | 16 +--------------- docs/source-pytorch/extensions/strategy.rst | 2 +- pyproject.toml | 4 ++++ tests/tests_pytorch/utilities/test_compile.py | 10 ++++++---- 4 files changed, 12 insertions(+), 20 deletions(-) diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml index 923e9ef2b9..c48db6c69a 100644 --- a/.pre-commit-config.yaml +++ b/.pre-commit-config.yaml @@ -84,25 +84,11 @@ repos: - flake8-return - repo: https://github.com/astral-sh/ruff-pre-commit - rev: "v0.1.9" + rev: "v0.1.15" hooks: - id: ruff args: ["--fix", "--preview"] - - repo: https://github.com/psf/black - rev: 23.12.1 - hooks: - - id: black - name: Format code - exclude: docs/source-app - - - repo: https://github.com/asottile/blacken-docs - rev: 1.16.0 - hooks: - - id: blacken-docs - args: ["--line-length=120"] - exclude: docs/source-app - - repo: https://github.com/executablebooks/mdformat rev: 0.7.17 hooks: diff --git a/docs/source-pytorch/extensions/strategy.rst b/docs/source-pytorch/extensions/strategy.rst index 409e1b4625..858a6744ee 100644 --- a/docs/source-pytorch/extensions/strategy.rst +++ b/docs/source-pytorch/extensions/strategy.rst @@ -77,7 +77,7 @@ The below table lists all relevant strategies available in Lightning with their - Strategy for multi-process single-device training on one or multiple nodes. :ref:`Learn more. ` * - ddp_spawn - :class:`~lightning.pytorch.strategies.DDPStrategy` - - Same as "ddp" but launches processes using :func:`torch.multiprocessing.spawn` method and joins processes after training finishes. :ref:`Learn more. ` + - Same as "ddp" but launches processes using ``torch.multiprocessing.spawn`` method and joins processes after training finishes. :ref:`Learn more. ` * - deepspeed - :class:`~lightning.pytorch.strategies.DeepSpeedStrategy` - Provides capabilities to run training using the DeepSpeed library, with training optimizations for large billion parameter models. :doc:`Learn more. <../advanced/model_parallel/deepspeed>` diff --git a/pyproject.toml b/pyproject.toml index 1e1e92d771..1ed6dc3866 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -93,6 +93,8 @@ ignore-init-module-imports = true "S113", # todo: Probable use of requests call without timeout "S301", # todo: `pickle` and modules that wrap it can be unsafe when used to deserialize untrusted data, possible security issue "S324", # todo: Probable use of insecure hash functions in `hashlib` + "S403", # todo: `pickle`, `cPickle`, `dill`, and `shelve` modules are possibly insecure + "S404", # todo: `subprocess` module is possibly insecure "S602", # todo: `subprocess` call with `shell=True` identified, security issue "S603", # todo: `subprocess` call: check for execution of untrusted input "S605", # todo: Starting a process with a shell: seems safe, but may be changed in the future; consider rewriting without `shell` @@ -108,6 +110,8 @@ ignore-init-module-imports = true "S311", # todo: Standard pseudo-random generators are not suitable for cryptographic purposes "S108", # todo: Probable insecure usage of temporary file or directory: "/tmp/sys-customizations-sync" "S202", # Uses of `tarfile.extractall()` + "S403", # `pickle`, `cPickle`, `dill`, and `shelve` modules are possibly insecure + "S404", # `subprocess` module is possibly insecure "S602", # todo: `subprocess` call with `shell=True` identified, security issue "S603", # todo: `subprocess` call: check for execution of untrusted input "S605", # todo: Starting a process with a shell: seems safe, but may be changed in the future; consider rewriting without `shell` diff --git a/tests/tests_pytorch/utilities/test_compile.py b/tests/tests_pytorch/utilities/test_compile.py index 7fe03ddf51..c363bbc94c 100644 --- a/tests/tests_pytorch/utilities/test_compile.py +++ b/tests/tests_pytorch/utilities/test_compile.py @@ -16,7 +16,6 @@ from unittest import mock import pytest import torch -from lightning.fabric.utilities.imports import _TORCH_GREATER_EQUAL_2_1 from lightning.pytorch import LightningModule, Trainer from lightning.pytorch.demos.boring_classes import BoringModel from lightning.pytorch.utilities.compile import from_compiled, to_uncompiled @@ -26,7 +25,8 @@ from tests_pytorch.conftest import mock_cuda_count from tests_pytorch.helpers.runif import RunIf -@pytest.mark.skipif(sys.platform == "darwin" and not _TORCH_GREATER_EQUAL_2_1, reason="Fix for MacOS in PyTorch 2.1") +# https://github.com/pytorch/pytorch/issues/95708 +@pytest.mark.skipif(sys.platform == "darwin", reason="fatal error: 'omp.h' file not found") @RunIf(dynamo=True) @mock.patch("lightning.pytorch.trainer.call._call_and_handle_interrupt") def test_trainer_compiled_model(_, tmp_path, monkeypatch, mps_count_0): @@ -112,7 +112,8 @@ def test_compile_uncompile(): assert not has_dynamo(to_uncompiled_model.predict_step) -@pytest.mark.skipif(sys.platform == "darwin" and not _TORCH_GREATER_EQUAL_2_1, reason="Fix for MacOS in PyTorch 2.1") +# https://github.com/pytorch/pytorch/issues/95708 +@pytest.mark.skipif(sys.platform == "darwin", reason="fatal error: 'omp.h' file not found") @RunIf(dynamo=True) def test_trainer_compiled_model_that_logs(tmp_path): class MyModel(BoringModel): @@ -137,7 +138,8 @@ def test_trainer_compiled_model_that_logs(tmp_path): assert set(trainer.callback_metrics) == {"loss"} -@pytest.mark.skipif(sys.platform == "darwin" and not _TORCH_GREATER_EQUAL_2_1, reason="Fix for MacOS in PyTorch 2.1") +# https://github.com/pytorch/pytorch/issues/95708 +@pytest.mark.skipif(sys.platform == "darwin", reason="fatal error: 'omp.h' file not found") @RunIf(dynamo=True) def test_trainer_compiled_model_test(tmp_path): model = BoringModel()