In [1]:

from sklearn_benchmarks.reporting.utils import ReportingInfo
from pathlib import Path
import pandas as pd
from sklearn_benchmarks.utils import default_run_dir
from sklearn_benchmarks.config import DEFAULT_NOTEBOOKS
pd.set_option('display.max_colwidth', None)
pd.set_option('display.max_columns', None)
pd.set_option('display.max_rows', None)

sklearn_benchmarks reporting¶

In [2]:

run_dir = default_run_dir()
notebooks = DEFAULT_NOTEBOOKS
static = False

In [3]:

# Parameters
static = True
notebooks = [
    "scikit_learn_intelex_vs_scikit_learn",
    "onnx_vs_scikit_learn",
    "gradient_boosting",
]
run_dir = "./results/local/20220316T125727/"

In [4]:

run_dir = Path(run_dir)

In [5]:

reporting_info = ReportingInfo(run_dir=run_dir, notebooks=notebooks, static=static)
reporting_info.display()

Last run: Wednesday 16 March, 2022 at 12:57:28.

Notebooks¶

scikit-learn-intelex (Intel® oneAPI) vs. scikit-learn benchmarks

ONNX Runtime (Microsoft) vs. scikit-learn benchmarks

Gradient boosting: randomized HPO benchmarks

Benchmark environment information¶

System¶


python	3.8.12 \| packaged by conda-forge \| (default, Jan 30 2022, 23:42:07) [GCC 9.4.0]
executable	/usr/share/miniconda/envs/sklbench/bin/python
machine	Linux-5.11.0-1028-azure-x86_64-with-glibc2.10

Dependencies¶


pip	22.0.4
setuptools	60.9.3
sklearn	1.0.2
numpy	1.22.3
scipy	1.8.0
Cython	None
pandas	1.4.1
matplotlib	3.5.1
joblib	1.1.0
threadpoolctl	3.1.0

Threadpool¶

	user_api	internal_api	prefix	filepath	version	threading_layer	architecture	num_threads
0	blas	openblas	libopenblas	/usr/share/miniconda/envs/sklbench/lib/libopenblasp-r0.3.18.so	0.3.18	pthreads	SkylakeX	2
1	openmp	openmp	libgomp	/usr/share/miniconda/envs/sklbench/lib/libgomp.so.1.0.0	None	NaN	NaN	2

Cpu_count¶


cpu_count	2
physical_cpu_count	2

Time report¶

Total time elapsed: 1h 42m 1s

Hyperparameters match benchmarks¶

	time elapsed
estimator
sklearnex_PCA	3s
sklearnex_Ridge	8s
sklearnex_KMeans_short	10s
sklearn_PCA	14s
sklearn_KMeans_short	17s
sklearn_Ridge	18s
sklearnex_KNeighborsClassifier_brute_force	28s
sklearnex_LinearRegression	29s
sklearn_TSNE	35s
sklearnex_LogisticRegression	35s
sklearnex_TSNE	37s
sklearn_LogisticRegression	1m 10s
sklearn_LinearRegression	1m 20s
sklearnex_KMeans_tall	1m 24s
sklearnex_KNeighborsClassifier_kd_tree	1m 33s
sklearn_KMeans_tall	1m 48s
sklearn_HistGradientBoostingClassifier_best	4m 34s
sklearn_KNeighborsClassifier_kd_tree	5m 57s
sklearn_KNeighborsClassifier_brute_force	17m 19s

Hyperparameters optimization benchmarks¶

	time elapsed
estimator
xgboost	11m 4s
lightgbm	11m 38s
catboost_lossguide	12m 12s
sklearn_HistGradientBoostingClassifier	12m 28s
catboost_symmetric	15m 40s