sklearn_logistic_regression_to_onnx_conversion_with_skl2onnx.py

1import numpy as np
2from sklearn.datasets import load_iris
3from sklearn.model_selection import train_test_split
4from sklearn.linear_model import LogisticRegression
5from skl2onnx import to_onnx
6
7# 1. Load data and train a model
8iris = load_iris()
9X, y = iris.data, iris.target
10X_train, X_test, y_train, y_test = train_test_split(X, y)
11clr = LogisticRegression()
12clr.fit(X_train, y_train)
13
14# 2. Convert into ONNX format
15onx = to_onnx(clr, X_train[:1].astype(np.float32))
16
17# 3. Save the model
18with open("logreg_iris.onnx", "wb") as f:
19    f.write(onx.SerializeToString())