sklearn-pickle-model

Dockerfile

FROM python:3.9.1
COPY logistic_regression.py logistic_regression.py 
COPY load_model.py load_model.py 
COPY runner.sh runner.sh
ENTRYPOINT [ "bash", "runner.sh" ]

load_model.py

import pickle

with open("log_reg_iris.pkl","rb") as f:
    model = pickle.load(f)
    print(model)

logistic_regression.py

#https://scikit-learn.org/dev/modules/generated/sklearn.linear_model.LogisticRegression.html
from sklearn.datasets import load_iris
from sklearn.linear_model import LogisticRegression 
import pickle

X, y = load_iris(return_X_y=True)
clf = LogisticRegression(random_state=0).fit(X, y)
clf.predict(X[:2, :])
clf.predict_proba(X[:2, :])
clf.score(X, y)
with open("log_reg_iris.pkl","wb") as f:
    pickle.dump(clf,f)

runner.sh

#!bin/bash
python3 -m venv venv_sklearn_1.0 
source venv_sklearn_1.0/bin/activate
pip install scikit-learn=="1.0" 
python logistic_regression.py
python3 -m venv venv_sklearn_1.1 
source venv_sklearn_1.1/bin/activate
pip install scikit-learn=="1.1"
python load_model.py