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Reduce Lasso test time #415

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Reduce Lasso test time #415

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8db879d
Reduce Lasso test time
cTatu Aug 10, 2022
44912a7
Update test_lasso.py
cTatu Aug 18, 2022
687e58b
Merge branch 'master' into reduce-lasso-test-time
cTatu Sep 5, 2022
686fc2a
Merge branch 'master' into reduce-lasso-test-time
cTatu Sep 7, 2022
bd8ee55
Merge branch 'master' into reduce-lasso-test-time
cTatu Sep 20, 2022
131cdf5
Merge branch 'master' into reduce-lasso-test-time
cTatu Oct 18, 2022
bced71e
Merge branch 'master' into reduce-lasso-test-time
cTatu Oct 21, 2022
12e7eb6
Merge branch 'master' into reduce-lasso-test-time
cTatu Nov 11, 2022
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37 changes: 10 additions & 27 deletions tests/test_lasso.py
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Original file line number Diff line number Diff line change
Expand Up @@ -43,7 +43,7 @@ def test_save_load(self):

np.random.seed(42)

n_samples, n_features = 50, 100
n_samples, n_features = 10, 20
X = np.random.randn(n_samples, n_features)

# Decreasing coef w. alternated signs for visualization
Expand All @@ -57,43 +57,30 @@ def test_save_load(self):

n_samples = X.shape[0]
X_train, y_train = X[:n_samples // 2], y[:n_samples // 2]
X_test, y_test = X[n_samples // 2:], y[n_samples // 2:]

lasso = Lasso(lmbd=0.1, max_iter=50)
lasso = Lasso(lmbd=0.1, max_iter=1)

lasso.fit(ds.array(X_train, (5, 100)), ds.array(y_train, (5, 1)))
lasso.fit(ds.array(X_train, (5, 20)), ds.array(y_train, (5, 1)))
lasso.save_model("./lasso_model")

lasso2 = Lasso()
lasso2 = Lasso(max_iter=1)
lasso2.load_model("./lasso_model")
y_pred_lasso = lasso2.predict(ds.array(X_test, (25, 100)))
r2_score_lasso = r2_score(y_test, y_pred_lasso.collect())

self.assertAlmostEqual(r2_score_lasso, 0.9481746925431124)

lasso.save_model("./lasso_model", save_format="cbor")

lasso2 = Lasso()
lasso2 = Lasso(max_iter=1)
lasso2.load_model("./lasso_model", load_format="cbor")
y_pred_lasso = lasso2.predict(ds.array(X_test, (25, 100)))
r2_score_lasso = r2_score(y_test, y_pred_lasso.collect())

self.assertAlmostEqual(r2_score_lasso, 0.9481746925431124)

lasso.save_model("./lasso_model", save_format="pickle")

lasso2 = Lasso()
lasso2 = Lasso(max_iter=1)
lasso2.load_model("./lasso_model", load_format="pickle")
y_pred_lasso = lasso2.predict(ds.array(X_test, (25, 100)))
r2_score_lasso = r2_score(y_test, y_pred_lasso.collect())

self.assertAlmostEqual(r2_score_lasso, 0.9481746925431124)

with self.assertRaises(ValueError):
lasso.save_model("./lasso_model", save_format="txt")

with self.assertRaises(ValueError):
lasso2 = Lasso()
lasso2 = Lasso(max_iter=1)
lasso2.load_model("./lasso_model", load_format="txt")

y2 = np.dot(X, coef)
Expand All @@ -102,17 +89,13 @@ def test_save_load(self):
n_samples = X.shape[0]
X_train, y_train = X[:n_samples // 2], y2[:n_samples // 2]

lasso = Lasso(lmbd=0.1, max_iter=50)
lasso = Lasso(lmbd=0.1, max_iter=1)

lasso.fit(ds.array(X_train, (5, 100)), ds.array(y_train, (5, 1)))
lasso.fit(ds.array(X_train, (5, 20)), ds.array(y_train, (5, 1)))
lasso.save_model("./lasso_model", overwrite=False)

lasso2 = Lasso()
lasso2 = Lasso(max_iter=1)
lasso2.load_model("./lasso_model", load_format="pickle")
y_pred_lasso = lasso2.predict(ds.array(X_test, (25, 100)))
r2_score_lasso = r2_score(y_test, y_pred_lasso.collect())

self.assertAlmostEqual(r2_score_lasso, 0.9481746925431124)

cbor2_module = utilmodel.cbor2
utilmodel.cbor2 = None
Expand Down