ONNX benchmarks#
The following benchmarks compare runtime or backend with ONNX.
Benchmark for ONNX#
The following benchmarks measure the prediction time between scikit-learn, onnxruntime and mlprodict for different models related to one-off predictions and batch predictions.
- Benchmark (ONNX) for common datasets (classification)
- Benchmark (ONNX) for common datasets (regression)
- Benchmark (ONNX) for common datasets (regression) with k-NN
- Benchmark (ONNX) for ensemble models
- Benchmark (ONNX) for LogisticRegression
- Benchmark (ONNX) for DecisionTreeClassifier
- Benchmark (ONNX) for DecisionTreeRegressor
- Benchmark (ONNX) for GradientBoostingRegressor
- Benchmark (ONNX) for GaussianProcessRegressor
- Benchmark (ONNX) for HistBoostingGradientRegressor
- Benchmark (ONNX) for KNeighborsClassifier
- Benchmark (ONNX) for RandomForestClassifier
- Benchmark (ONNX) for MLPClassifier
Benchmark specific operators (Add, Scaler, …)#
The following benchmarks look into simplified models to help understand how runtime behave for specific operators.