def test_RBM(train_X, train_Y, test_X, test_Y):
# Create and train RBM
rbm = RBM(28 * 28, 500)
rbm.fit(train_X)
rbm.get_filters()
train_X = np.array([rbm.inference(x) for x in train_X])
test_X = np.array([rbm.inference(x) for x in test_X])
logreg = LogisticRegression(max_iter=10)
logreg.fit(train_X, train_Y)
predict_Y = logreg.predict(train_X)
print("Accuracy on training data")
print(accuracy_score(train_Y, predict_Y))
predict_Y = logreg.predict(test_X)
print("Accuracy on test data")
print(accuracy_score(test_Y, predict_Y))
