def _decision_function(self, X):
        check_is_fitted(self, ["t_", "coef_", "intercept_"], all_or_any=all)

        X = check_array(X, accept_sparse='csr')

        scores = safe_sparse_dot(X, self.coef_.T,
                                 dense_output=True) + self.intercept_
        return scores.ravel()
Installs wrk on the VM.
dataset/ETHPy150Open scikit-learn/scikit-learn/sklearn/linear_model/stochastic_gradient.py/BaseSGDRegressor._decision_function--crossover with--dataset/ETHPy150Open GoogleCloudPlatform/PerfKitBenchmarker/perfkitbenchmarker/linux_packages/wrk.py/YumInstall