From f4475a52c1939e75488642bcf29f9a80bc527dd3 Mon Sep 17 00:00:00 2001 From: Pavel Zwerschke Date: Wed, 25 Oct 2023 15:11:09 +0200 Subject: [PATCH 1/3] Add ruff-format and support for python 3.12 --- .github/release.yml | 14 +- .github/workflows/ci.yml | 7 +- .gitignore | 2 - .pre-commit-config.yaml | 10 +- benchmark.py | 8 +- examples/pickle_lgbm.py | 4 +- examples/pickle_sklearn.py | 4 +- examples/utils.py | 4 +- pixi.lock | 13077 ++++++++++++++++++++++++++++ pyproject.toml | 20 +- slim_trees/__init__.py | 8 +- slim_trees/compression_utils.py | 8 +- slim_trees/lgbm_booster.py | 16 +- slim_trees/pickling.py | 12 +- tests/test_lgbm_compression.py | 4 +- tests/test_sklearn_compression.py | 20 +- tests/util.py | 15 +- 17 files changed, 13128 insertions(+), 105 deletions(-) create mode 100644 pixi.lock diff --git a/.github/release.yml b/.github/release.yml index c9c7b02..aaad370 100644 --- a/.github/release.yml +++ b/.github/release.yml @@ -2,20 +2,22 @@ changelog: exclude: labels: - ignore for release - - ci categories: - - title: New features + - title: ✨ New features labels: - enhancement - - title: Bug fixes + - title: 🐛 Bug fixes labels: - bug - - title: Documentation + - title: 📝 Documentation labels: - documentation - - title: Dependencies + - title: ⬆️ Dependencies labels: - dependencies - - title: Other changes + - title: 🚀 CI + labels: + - ci + - title: 🤷🏻 Other changes labels: - '*' diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml index 20db915..ba64945 100644 --- a/.github/workflows/ci.yml +++ b/.github/workflows/ci.yml @@ -33,6 +33,7 @@ jobs: - { PYTHON_VERSION: '3.9', SKLEARN_VERSION: '', LGBM_VERSION: '' } - { PYTHON_VERSION: '3.10', SKLEARN_VERSION: '', LGBM_VERSION: '' } - { PYTHON_VERSION: '3.11', SKLEARN_VERSION: '', LGBM_VERSION: '' } + - { PYTHON_VERSION: '3.12', SKLEARN_VERSION: '', LGBM_VERSION: '' } steps: - uses: actions/checkout@v4 - name: Set up conda env @@ -56,13 +57,11 @@ jobs: ${{ matrix.SKLEARN_VERSION }}${{ matrix.LGBM_VERSION }} linux-unittests-pixi: - name: "Unit tests Pixi - Python ${{ matrix.PYTHON_VERSION }}" + name: Unit tests Pixi timeout-minutes: 15 runs-on: ubuntu-latest strategy: fail-fast: false - matrix: - PYTHON_VERSION: ['3.11'] steps: - uses: actions/checkout@v4 - uses: prefix-dev/setup-pixi@v0.3.0 @@ -73,7 +72,7 @@ jobs: uses: pavelzw/pytest-action@v2 with: custom-pytest: pixi run test - report-title: "Unit tests Linux Pixi - Python ${{ matrix.PYTHON_VERSION }}" + report-title: Unit tests Linux Pixi pre-commit: # todo switch to pre-commit.ci name: "Pre-commit checks" diff --git a/.gitignore b/.gitignore index 7689c83..a1fbdb4 100644 --- a/.gitignore +++ b/.gitignore @@ -121,5 +121,3 @@ mlruns # pixi .pixi -# this is a library so we don't include pixi.lock -pixi.lock diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml index 5dab678..a2f4d4d 100644 --- a/.pre-commit-config.yaml +++ b/.pre-commit-config.yaml @@ -7,16 +7,10 @@ repos: - id: trailing-whitespace - id: check-toml - repo: https://github.com/quantco/pre-commit-mirrors-ruff - rev: 0.0.291 + rev: 0.1.2 hooks: - id: ruff-conda - - repo: https://github.com/quantco/pre-commit-mirrors-black - rev: 23.9.1 - hooks: - - id: black-conda - args: - - --safe - - --target-version=py38 + - id: ruff-format-conda - repo: https://github.com/quantco/pre-commit-mirrors-mypy rev: 1.5.1 hooks: diff --git a/benchmark.py b/benchmark.py index 8aed120..0264db3 100644 --- a/benchmark.py +++ b/benchmark.py @@ -66,16 +66,12 @@ def train_sklearn_rf_1g() -> RandomForestRegressor: def train_sklearn_gb_2m() -> GradientBoostingRegressor: return load_model( "sklearn_gb_2m", - lambda: GradientBoostingRegressor( - n_estimators=2000, random_state=42, verbose=True - ), + lambda: GradientBoostingRegressor(n_estimators=2000, random_state=42, verbose=True), ) def train_lgbm_gbdt_2m() -> lgb.LGBMRegressor: - return load_model( - "lgbm_gbdt_2m", lambda: lgb.LGBMRegressor(n_estimators=1000, random_state=42) - ) + return load_model("lgbm_gbdt_2m", lambda: lgb.LGBMRegressor(n_estimators=1000, random_state=42)) def train_lgbm_gbdt_5m() -> lgb.LGBMRegressor: diff --git a/examples/pickle_lgbm.py b/examples/pickle_lgbm.py index b6cc375..37cea6b 100644 --- a/examples/pickle_lgbm.py +++ b/examples/pickle_lgbm.py @@ -44,7 +44,5 @@ def dump_model_string(booster: Booster, path: Union[str, pathlib.Path]): dump_model_string(model.booster_, "examples/out/model_uncompressed.model") dump_model_string(model_compressed.booster_, "examples/out/model_compressed.model") - evaluate_prediction_difference( - model, model_compressed, generate_dataset(n_samples=10000)[0] - ) + evaluate_prediction_difference(model, model_compressed, generate_dataset(n_samples=10000)[0]) evaluate_compression_performance(model, dump) diff --git a/examples/pickle_sklearn.py b/examples/pickle_sklearn.py index 91a8f85..29e4c06 100644 --- a/examples/pickle_sklearn.py +++ b/examples/pickle_sklearn.py @@ -28,7 +28,5 @@ def train_model() -> RandomForestRegressor: dump_sklearn_compressed(model, path, "no") model_compressed = load_compressed(path, "no") - evaluate_prediction_difference( - model, model_compressed, generate_dataset(n_samples=10000)[0] - ) + evaluate_prediction_difference(model, model_compressed, generate_dataset(n_samples=10000)[0]) evaluate_compression_performance(model, dump) diff --git a/examples/utils.py b/examples/utils.py index 645190e..b5becf6 100644 --- a/examples/utils.py +++ b/examples/utils.py @@ -58,9 +58,7 @@ def generate_dataset_train_test( return train_test_split(X, y, test_size=0.2, random_state=42) -def evaluate_compression_performance( - 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\.eggs - | \.git - | \.venv - | build - | dist -)/ -''' - [tool.ruff] line-length = 100 target-version = "py38" @@ -84,8 +73,15 @@ select = [ ignore = [ # variable in function should be lowercase "N806", + # may cause conflicts with ruff formatter + "E501", + "W191", ] +[tool.ruff.format] +quote-style = "double" +indent-style = "space" + [tool.mypy] python_version = "3.8" ignore_missing_imports = true diff --git a/slim_trees/__init__.py b/slim_trees/__init__.py index b71f4f4..8dec32d 100644 --- a/slim_trees/__init__.py +++ b/slim_trees/__init__.py @@ -60,9 +60,7 @@ def dump_sklearn_compressed( dump_compressed(model, path, compression, dump) -def dumps_sklearn_compressed( - model: Any, compression: Optional[Union[str, dict]] = None -) -> bytes: +def dumps_sklearn_compressed(model: Any, compression: Optional[Union[str, dict]] = None) -> bytes: """ Pickles a model and returns the saved object as bytes. @@ -97,9 +95,7 @@ def dump_lgbm_compressed( dump_compressed(model, path, compression, dump) -def dumps_lgbm_compressed( - model: Any, compression: Optional[Union[str, dict]] = None -) -> bytes: +def dumps_lgbm_compressed(model: Any, compression: Optional[Union[str, dict]] = None) -> bytes: """ Pickles a model and returns the saved object as bytes. diff --git a/slim_trees/compression_utils.py b/slim_trees/compression_utils.py index 8499760..cfd9901 100644 --- a/slim_trees/compression_utils.py +++ b/slim_trees/compression_utils.py @@ -15,9 +15,7 @@ def _is_in_neighborhood_of_int(arr, iinfo, eps=1e-12): side of the next int. """ return ( - (np.minimum(np.abs(arr % 1 - 1), arr % 1) < eps) - & (arr >= iinfo.min) - & (arr <= iinfo.max) + (np.minimum(np.abs(arr % 1 - 1), arr % 1) < eps) & (arr >= iinfo.min) & (arr <= iinfo.max) ) @@ -50,9 +48,7 @@ def compress_half_int_float_array(a, compression_dtype="int8"): def decompress_half_int_float_array(state): n_thresholds = len(state["a2_compressible"]) + len(state["a_incompressible"]) - is_compressible = np.unpackbits( - state["is_compressible"], count=n_thresholds - ).astype("bool") + is_compressible = np.unpackbits(state["is_compressible"], count=n_thresholds).astype("bool") a = np.zeros(len(is_compressible), dtype="float64") a[is_compressible] = state["a2_compressible"] / 2.0 a[~is_compressible] = state["a_incompressible"] diff --git a/slim_trees/lgbm_booster.py b/slim_trees/lgbm_booster.py index 33001a2..1ab208d 100644 --- a/slim_trees/lgbm_booster.py +++ b/slim_trees/lgbm_booster.py @@ -73,18 +73,14 @@ def _compress_booster_state(state: dict): """ assert isinstance(state, dict) compressed_state = {k: v for k, v in state.items() if k != _handle_key_name} - compressed_state["compressed_handle"] = _compress_booster_handle( - state[_handle_key_name] - ) + compressed_state["compressed_handle"] = _compress_booster_handle(state[_handle_key_name]) return compressed_state def _decompress_booster_state(compressed_state: dict): assert isinstance(compressed_state, dict) state = {k: v for k, v in compressed_state.items() if k != "compressed_handle"} - state[_handle_key_name] = _decompress_booster_handle( - compressed_state["compressed_handle"] - ) + state[_handle_key_name] = _decompress_booster_handle(compressed_state["compressed_handle"]) return state @@ -238,9 +234,7 @@ def _decompress_booster_handle(compressed_state: Tuple[str, List[dict], str]) -> tree_str += "\nsplit_gain=" + ("0 " * num_nodes)[:-1] threshold = decompress_half_int_float_array(tree["threshold"]) tree_str += "\nthreshold=" + " ".join([str(x) for x in threshold]) - tree_str += "\ndecision_type=" + " ".join( - [str(x) for x in tree["decision_type"]] - ) + tree_str += "\ndecision_type=" + " ".join([str(x) for x in tree["decision_type"]]) tree_str += "\nleft_child=" + " ".join([str(x) for x in tree["left_child"]]) tree_str += "\nright_child=" + " ".join([str(x) for x in tree["right_child"]]) tree_str += "\nleaf_value=" + " ".join([str(x) for x in tree["leaf_value"]]) @@ -252,9 +246,7 @@ def _decompress_booster_handle(compressed_state: Tuple[str, List[dict], str]) -> tree_str += f"\nis_linear={tree['is_linear']}" if is_linear: tree_str += "\nleaf_const=" + " ".join(str(x) for x in tree["leaf_const"]) - tree_str += "\nnum_features=" + " ".join( - str(x) for x in tree["num_features"] - ) + tree_str += "\nnum_features=" + " ".join(str(x) for x in tree["num_features"]) tree_str += "\nleaf_features=" + " ".join( "" if f == -1 else str(int(f)) for f in tree["leaf_features"] ) diff --git a/slim_trees/pickling.py b/slim_trees/pickling.py index f3af990..26e063b 100644 --- a/slim_trees/pickling.py +++ b/slim_trees/pickling.py @@ -57,9 +57,7 @@ def _unpack_compression_args( if isinstance(compression, str): return compression, _get_default_kwargs(compression) elif isinstance(compression, dict): - return compression["method"], { - k: compression[k] for k in compression if k != "method" - } + return compression["method"], {k: compression[k] for k in compression if k != "method"} raise ValueError("compression must be either a string or a dict") if path is not None: # try to find out the compression using the file extension @@ -90,9 +88,7 @@ def dump_compressed( dump_function = pickle.dump compression_method, kwargs = _unpack_compression_args(compression, path) - with _get_compression_library(compression_method).open( - path, mode="wb", **kwargs - ) as file: + with _get_compression_library(compression_method).open(path, mode="wb", **kwargs) as file: dump_function(obj, file) @@ -140,9 +136,7 @@ def load_compressed( when required module or function names have been refactored. """ compression_method, kwargs = _unpack_compression_args(compression, path) - with _get_compression_library(compression_method).open( - path, mode="rb", **kwargs - ) as file: + with _get_compression_library(compression_method).open(path, mode="rb", **kwargs) as file: return unpickler_class(file).load() diff --git a/tests/test_lgbm_compression.py b/tests/test_lgbm_compression.py index eaaf5ec..2b98bae 100644 --- a/tests/test_lgbm_compression.py +++ b/tests/test_lgbm_compression.py @@ -26,9 +26,7 @@ def lgbm_regressor_linear(rng): return LGBMRegressor(random_state=rng, linear_trees=True) -@pytest.mark.parametrize( - "lgbm_regressor", [lgbm_regressor, lgbm_regressor_linear], indirect=True -) +@pytest.mark.parametrize("lgbm_regressor", [lgbm_regressor, lgbm_regressor_linear], indirect=True) def test_compressed_predictions(diabetes_toy_df, lgbm_regressor, tmp_path): X, y = diabetes_toy_df lgbm_regressor.fit(X, y) diff --git a/tests/test_sklearn_compression.py b/tests/test_sklearn_compression.py index a2fcd2b..e9d2d28 100644 --- a/tests/test_sklearn_compression.py +++ b/tests/test_sklearn_compression.py @@ -45,9 +45,7 @@ def test_compressed_predictions(diabetes_toy_df, random_forest_regressor, tmp_pa np.testing.assert_allclose(prediction_no_reduction, prediction_reduction) -def test_compressed_internal_structure( - diabetes_toy_df, decision_tree_regressor, tmp_path -): +def test_compressed_internal_structure(diabetes_toy_df, decision_tree_regressor, tmp_path): X, y = diabetes_toy_df decision_tree_regressor.fit(X, y) @@ -64,13 +62,9 @@ def test_compressed_internal_structure( np.testing.assert_array_equal( tree_dtype_reduction.children_right, tree_no_reduction.children_right ) - np.testing.assert_array_equal( - tree_dtype_reduction.feature, tree_no_reduction.feature - ) + np.testing.assert_array_equal(tree_dtype_reduction.feature, tree_no_reduction.feature) # threshold compression should be lossless (even for float compression) - np.testing.assert_array_equal( - tree_dtype_reduction.threshold, tree_no_reduction.threshold - ) + np.testing.assert_array_equal(tree_dtype_reduction.threshold, tree_no_reduction.threshold) is_leaf = tree_dtype_reduction.children_left == -1 np.testing.assert_allclose( tree_dtype_reduction.value[is_leaf], tree_no_reduction.value[is_leaf] @@ -100,9 +94,7 @@ def test_compression_size(diabetes_toy_df, random_forest_regressor, tmp_path): @pytest.mark.parametrize("compression_method", ["no", "lzma", "gzip", "bz2"]) -def test_dump_times( - diabetes_toy_df, random_forest_regressor, tmp_path, compression_method -): +def test_dump_times(diabetes_toy_df, random_forest_regressor, tmp_path, compression_method): X, y = diabetes_toy_df random_forest_regressor.fit(X, y) factor = 4 if compression_method == "no" else 1.5 @@ -114,9 +106,7 @@ def test_dump_times( @pytest.mark.parametrize("compression_method", ["no", "lzma", "gzip", "bz2"]) -def test_load_times( - diabetes_toy_df, random_forest_regressor, tmp_path, compression_method -): +def test_load_times(diabetes_toy_df, random_forest_regressor, tmp_path, compression_method): X, y = diabetes_toy_df random_forest_regressor.fit(X, y) diff --git a/tests/util.py b/tests/util.py index 4274c67..3ab20a3 100644 --- a/tests/util.py +++ b/tests/util.py @@ -30,9 +30,7 @@ def get_load_times(model, dump_lib_compressed, tmp_path, method): load_time_compressed = timeit.timeit( lambda: load_compressed(model_path_compressed, method), number=5 ) - load_time_uncompressed = timeit.timeit( - lambda: load_compressed(model_path, method), number=5 - ) + load_time_uncompressed = timeit.timeit(lambda: load_compressed(model_path, method), number=5) return load_time_compressed, load_time_uncompressed @@ -42,10 +40,13 @@ def assert_version_pickle(pickle_function, element): def assert_version_unpickle(pickle_function, element): - _unpickle_function, ( - reconstructor, - args, - (version, compressed_state), + ( + _unpickle_function, + ( + reconstructor, + args, + (version, compressed_state), + ), ) = pickle_function(element) with warnings.catch_warnings(): warnings.simplefilter("error") From ae8b24a571f38f9c97dd1403ff790bb74b106724 Mon Sep 17 00:00:00 2001 From: Pavel Zwerschke Date: Wed, 25 Oct 2023 15:34:50 +0200 Subject: [PATCH 2/3] Use line length 88 --- benchmark.py | 8 ++++++-- examples/pickle_lgbm.py | 4 +++- examples/pickle_sklearn.py | 4 +++- examples/utils.py | 4 +++- pyproject.toml | 2 +- slim_trees/__init__.py | 8 ++++++-- slim_trees/compression_utils.py | 8 ++++++-- slim_trees/lgbm_booster.py | 16 ++++++++++++---- slim_trees/pickling.py | 12 +++++++++--- tests/test_lgbm_compression.py | 4 +++- tests/test_sklearn_compression.py | 20 +++++++++++++++----- tests/util.py | 4 +++- 12 files changed, 70 insertions(+), 24 deletions(-) diff --git a/benchmark.py b/benchmark.py index 0264db3..8aed120 100644 --- a/benchmark.py +++ b/benchmark.py @@ -66,12 +66,16 @@ def train_sklearn_rf_1g() -> RandomForestRegressor: def train_sklearn_gb_2m() -> GradientBoostingRegressor: return load_model( "sklearn_gb_2m", - lambda: GradientBoostingRegressor(n_estimators=2000, random_state=42, verbose=True), + lambda: GradientBoostingRegressor( + n_estimators=2000, random_state=42, verbose=True + ), ) def train_lgbm_gbdt_2m() -> lgb.LGBMRegressor: - return load_model("lgbm_gbdt_2m", lambda: lgb.LGBMRegressor(n_estimators=1000, random_state=42)) + return load_model( + "lgbm_gbdt_2m", lambda: lgb.LGBMRegressor(n_estimators=1000, random_state=42) + ) def train_lgbm_gbdt_5m() -> lgb.LGBMRegressor: diff --git a/examples/pickle_lgbm.py b/examples/pickle_lgbm.py index 37cea6b..b6cc375 100644 --- a/examples/pickle_lgbm.py +++ b/examples/pickle_lgbm.py @@ -44,5 +44,7 @@ def dump_model_string(booster: Booster, path: Union[str, pathlib.Path]): dump_model_string(model.booster_, "examples/out/model_uncompressed.model") dump_model_string(model_compressed.booster_, "examples/out/model_compressed.model") - evaluate_prediction_difference(model, model_compressed, generate_dataset(n_samples=10000)[0]) + evaluate_prediction_difference( + model, model_compressed, generate_dataset(n_samples=10000)[0] + ) evaluate_compression_performance(model, dump) diff --git a/examples/pickle_sklearn.py b/examples/pickle_sklearn.py index 29e4c06..91a8f85 100644 --- a/examples/pickle_sklearn.py +++ b/examples/pickle_sklearn.py @@ -28,5 +28,7 @@ def train_model() -> RandomForestRegressor: dump_sklearn_compressed(model, path, "no") model_compressed = load_compressed(path, "no") - evaluate_prediction_difference(model, model_compressed, generate_dataset(n_samples=10000)[0]) + evaluate_prediction_difference( + model, model_compressed, generate_dataset(n_samples=10000)[0] + ) evaluate_compression_performance(model, dump) diff --git a/examples/utils.py b/examples/utils.py index b5becf6..645190e 100644 --- a/examples/utils.py +++ b/examples/utils.py @@ -58,7 +58,9 @@ def generate_dataset_train_test( return train_test_split(X, y, test_size=0.2, random_state=42) -def evaluate_compression_performance(model: Any, dump: Callable, print_performance: bool = True): +def evaluate_compression_performance( + model: Any, dump: Callable, print_performance: bool = True +): compressions = ["no", "lzma", "bz2", "gzip"] performance = [] for compression, dump_function in product(compressions, [None, dump]): diff --git a/pyproject.toml b/pyproject.toml index 86b96bc..4b415b0 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -41,7 +41,7 @@ include = [ ] [tool.ruff] -line-length = 100 +line-length = 88 target-version = "py38" select = [ diff --git a/slim_trees/__init__.py b/slim_trees/__init__.py index 8dec32d..b71f4f4 100644 --- a/slim_trees/__init__.py +++ b/slim_trees/__init__.py @@ -60,7 +60,9 @@ def dump_sklearn_compressed( dump_compressed(model, path, compression, dump) -def dumps_sklearn_compressed(model: Any, compression: Optional[Union[str, dict]] = None) -> bytes: +def dumps_sklearn_compressed( + model: Any, compression: Optional[Union[str, dict]] = None +) -> bytes: """ Pickles a model and returns the saved object as bytes. @@ -95,7 +97,9 @@ def dump_lgbm_compressed( dump_compressed(model, path, compression, dump) -def dumps_lgbm_compressed(model: Any, compression: Optional[Union[str, dict]] = None) -> bytes: +def dumps_lgbm_compressed( + model: Any, compression: Optional[Union[str, dict]] = None +) -> bytes: """ Pickles a model and returns the saved object as bytes. diff --git a/slim_trees/compression_utils.py b/slim_trees/compression_utils.py index cfd9901..8499760 100644 --- a/slim_trees/compression_utils.py +++ b/slim_trees/compression_utils.py @@ -15,7 +15,9 @@ def _is_in_neighborhood_of_int(arr, iinfo, eps=1e-12): side of the next int. """ return ( - (np.minimum(np.abs(arr % 1 - 1), arr % 1) < eps) & (arr >= iinfo.min) & (arr <= iinfo.max) + (np.minimum(np.abs(arr % 1 - 1), arr % 1) < eps) + & (arr >= iinfo.min) + & (arr <= iinfo.max) ) @@ -48,7 +50,9 @@ def compress_half_int_float_array(a, compression_dtype="int8"): def decompress_half_int_float_array(state): n_thresholds = len(state["a2_compressible"]) + len(state["a_incompressible"]) - is_compressible = np.unpackbits(state["is_compressible"], count=n_thresholds).astype("bool") + is_compressible = np.unpackbits( + state["is_compressible"], count=n_thresholds + ).astype("bool") a = np.zeros(len(is_compressible), dtype="float64") a[is_compressible] = state["a2_compressible"] / 2.0 a[~is_compressible] = state["a_incompressible"] diff --git a/slim_trees/lgbm_booster.py b/slim_trees/lgbm_booster.py index 1ab208d..33001a2 100644 --- a/slim_trees/lgbm_booster.py +++ b/slim_trees/lgbm_booster.py @@ -73,14 +73,18 @@ def _compress_booster_state(state: dict): """ assert isinstance(state, dict) compressed_state = {k: v for k, v in state.items() if k != _handle_key_name} - compressed_state["compressed_handle"] = _compress_booster_handle(state[_handle_key_name]) + compressed_state["compressed_handle"] = _compress_booster_handle( + state[_handle_key_name] + ) return compressed_state def _decompress_booster_state(compressed_state: dict): assert isinstance(compressed_state, dict) state = {k: v for k, v in compressed_state.items() if k != "compressed_handle"} - state[_handle_key_name] = _decompress_booster_handle(compressed_state["compressed_handle"]) + state[_handle_key_name] = _decompress_booster_handle( + compressed_state["compressed_handle"] + ) return state @@ -234,7 +238,9 @@ def _decompress_booster_handle(compressed_state: Tuple[str, List[dict], str]) -> tree_str += "\nsplit_gain=" + ("0 " * num_nodes)[:-1] threshold = decompress_half_int_float_array(tree["threshold"]) tree_str += "\nthreshold=" + " ".join([str(x) for x in threshold]) - tree_str += "\ndecision_type=" + " ".join([str(x) for x in tree["decision_type"]]) + tree_str += "\ndecision_type=" + " ".join( + [str(x) for x in tree["decision_type"]] + ) tree_str += "\nleft_child=" + " ".join([str(x) for x in tree["left_child"]]) tree_str += "\nright_child=" + " ".join([str(x) for x in tree["right_child"]]) tree_str += "\nleaf_value=" + " ".join([str(x) for x in tree["leaf_value"]]) @@ -246,7 +252,9 @@ def _decompress_booster_handle(compressed_state: Tuple[str, List[dict], str]) -> tree_str += f"\nis_linear={tree['is_linear']}" if is_linear: tree_str += "\nleaf_const=" + " ".join(str(x) for x in tree["leaf_const"]) - tree_str += "\nnum_features=" + " ".join(str(x) for x in tree["num_features"]) + tree_str += "\nnum_features=" + " ".join( + str(x) for x in tree["num_features"] + ) tree_str += "\nleaf_features=" + " ".join( "" if f == -1 else str(int(f)) for f in tree["leaf_features"] ) diff --git a/slim_trees/pickling.py b/slim_trees/pickling.py index 26e063b..f3af990 100644 --- a/slim_trees/pickling.py +++ b/slim_trees/pickling.py @@ -57,7 +57,9 @@ def _unpack_compression_args( if isinstance(compression, str): return compression, _get_default_kwargs(compression) elif isinstance(compression, dict): - return compression["method"], {k: compression[k] for k in compression if k != "method"} + return compression["method"], { + k: compression[k] for k in compression if k != "method" + } raise ValueError("compression must be either a string or a dict") if path is not None: # try to find out the compression using the file extension @@ -88,7 +90,9 @@ def dump_compressed( dump_function = pickle.dump compression_method, kwargs = _unpack_compression_args(compression, path) - with _get_compression_library(compression_method).open(path, mode="wb", **kwargs) as file: + with _get_compression_library(compression_method).open( + path, mode="wb", **kwargs + ) as file: dump_function(obj, file) @@ -136,7 +140,9 @@ def load_compressed( when required module or function names have been refactored. """ compression_method, kwargs = _unpack_compression_args(compression, path) - with _get_compression_library(compression_method).open(path, mode="rb", **kwargs) as file: + with _get_compression_library(compression_method).open( + path, mode="rb", **kwargs + ) as file: return unpickler_class(file).load() diff --git a/tests/test_lgbm_compression.py b/tests/test_lgbm_compression.py index 2b98bae..eaaf5ec 100644 --- a/tests/test_lgbm_compression.py +++ b/tests/test_lgbm_compression.py @@ -26,7 +26,9 @@ def lgbm_regressor_linear(rng): return LGBMRegressor(random_state=rng, linear_trees=True) -@pytest.mark.parametrize("lgbm_regressor", [lgbm_regressor, lgbm_regressor_linear], indirect=True) +@pytest.mark.parametrize( + "lgbm_regressor", [lgbm_regressor, lgbm_regressor_linear], indirect=True +) def test_compressed_predictions(diabetes_toy_df, lgbm_regressor, tmp_path): X, y = diabetes_toy_df lgbm_regressor.fit(X, y) diff --git a/tests/test_sklearn_compression.py b/tests/test_sklearn_compression.py index e9d2d28..a2fcd2b 100644 --- a/tests/test_sklearn_compression.py +++ b/tests/test_sklearn_compression.py @@ -45,7 +45,9 @@ def test_compressed_predictions(diabetes_toy_df, random_forest_regressor, tmp_pa np.testing.assert_allclose(prediction_no_reduction, prediction_reduction) -def test_compressed_internal_structure(diabetes_toy_df, decision_tree_regressor, tmp_path): +def test_compressed_internal_structure( + diabetes_toy_df, decision_tree_regressor, tmp_path +): X, y = diabetes_toy_df decision_tree_regressor.fit(X, y) @@ -62,9 +64,13 @@ def test_compressed_internal_structure(diabetes_toy_df, decision_tree_regressor, np.testing.assert_array_equal( tree_dtype_reduction.children_right, tree_no_reduction.children_right ) - np.testing.assert_array_equal(tree_dtype_reduction.feature, tree_no_reduction.feature) + np.testing.assert_array_equal( + tree_dtype_reduction.feature, tree_no_reduction.feature + ) # threshold compression should be lossless (even for float compression) - np.testing.assert_array_equal(tree_dtype_reduction.threshold, tree_no_reduction.threshold) + np.testing.assert_array_equal( + tree_dtype_reduction.threshold, tree_no_reduction.threshold + ) is_leaf = tree_dtype_reduction.children_left == -1 np.testing.assert_allclose( tree_dtype_reduction.value[is_leaf], tree_no_reduction.value[is_leaf] @@ -94,7 +100,9 @@ def test_compression_size(diabetes_toy_df, random_forest_regressor, tmp_path): @pytest.mark.parametrize("compression_method", ["no", "lzma", "gzip", "bz2"]) -def test_dump_times(diabetes_toy_df, random_forest_regressor, tmp_path, compression_method): +def test_dump_times( + diabetes_toy_df, random_forest_regressor, tmp_path, compression_method +): X, y = diabetes_toy_df random_forest_regressor.fit(X, y) factor = 4 if compression_method == "no" else 1.5 @@ -106,7 +114,9 @@ def test_dump_times(diabetes_toy_df, random_forest_regressor, tmp_path, compress @pytest.mark.parametrize("compression_method", ["no", "lzma", "gzip", "bz2"]) -def test_load_times(diabetes_toy_df, random_forest_regressor, tmp_path, compression_method): +def test_load_times( + diabetes_toy_df, random_forest_regressor, tmp_path, compression_method +): X, y = diabetes_toy_df random_forest_regressor.fit(X, y) diff --git a/tests/util.py b/tests/util.py index 3ab20a3..58b6ad6 100644 --- a/tests/util.py +++ b/tests/util.py @@ -30,7 +30,9 @@ def get_load_times(model, dump_lib_compressed, tmp_path, method): load_time_compressed = timeit.timeit( lambda: load_compressed(model_path_compressed, method), number=5 ) - load_time_uncompressed = timeit.timeit(lambda: load_compressed(model_path, method), number=5) + load_time_uncompressed = timeit.timeit( + lambda: load_compressed(model_path, method), number=5 + ) return load_time_compressed, load_time_uncompressed From bfafef4a83525ab47c09220f6b9b08742286c82d Mon Sep 17 00:00:00 2001 From: Pavel Zwerschke Date: Thu, 26 Oct 2023 11:46:47 +0200 Subject: [PATCH 3/3] bump version --- pixi.toml | 2 +- pyproject.toml | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/pixi.toml b/pixi.toml index aea5e2d..f67521e 100644 --- a/pixi.toml +++ b/pixi.toml @@ -1,6 +1,6 @@ [project] # TODO: move to pyproject.toml once pixi supports it name = "slim-trees" -version = "0.2.4" +version = "0.2.5" description = "A python package for efficient pickling of ML models." authors = ["Pavel Zwerschke "] channels = ["conda-forge"] diff --git a/pyproject.toml b/pyproject.toml index 4f432ad..26d9fe8 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -5,7 +5,7 @@ build-backend = "hatchling.build" [project] name = "slim-trees" description = "A python package for efficient pickling of ML models." -version = "0.2.4" +version = "0.2.5" readme = "README.md" license = "MIT" requires-python = ">=3.8"