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carefree0910carefree0910
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Update _Tests/_UnitTests
1 parent e79f630 commit aa977e9

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4 files changed

+84
-61
lines changed

4 files changed

+84
-61
lines changed

‎_Dist/NeuralNetworks/_Tests/_UnitTests/a_Basic.py

+19-17
Original file line numberDiff line numberDiff line change
@@ -21,22 +21,22 @@
2121
svm = SVM(**copy.deepcopy(base_params))
2222
nn = Basic(**copy.deepcopy(base_params))
2323
linear_svm = LinearSVM(**copy.deepcopy(base_params))
24-
train_set, test_set = DataUtil.gen_noisy_linear(1000, 2, 2, one_hot=False)
24+
train_set, cv_set, test_set = DataUtil.gen_special_linear(1000, 2, 2, 2, one_hot=False)
2525

2626

2727
class TestSVM(unittest.TestCase):
2828
def test_00_train(self):
2929
self.assertIsInstance(
30-
svm.fit(*train_set, *test_set, verbose=0), SVM,
30+
svm.fit(*train_set, *cv_set, verbose=0), SVM,
3131
msg="Train failed"
3232
)
3333

3434
def test_01_predict(self):
3535
self.assertIs(svm.predict(train_set[0]).dtype, np.dtype("float32"), "Predict failed")
36-
self.assertIs(svm.predict_classes(test_set[0]).dtype, np.dtype("int32"), "Predict classes failed")
36+
self.assertIs(svm.predict_classes(cv_set[0]).dtype, np.dtype("int32"), "Predict classes failed")
3737

3838
def test_02_evaluate(self):
39-
self.assertEqual(len(svm.evaluate(*train_set, *test_set)), 3, "Evaluation failed")
39+
self.assertEqual(len(svm.evaluate(*train_set, *cv_set)), 3, "Evaluation failed")
4040

4141
def test_03_save(self):
4242
self.assertIsInstance(svm.save(), SVM, msg="Save failed")
@@ -48,14 +48,14 @@ def test_04_load(self):
4848

4949
def test_05_re_predict(self):
5050
self.assertIs(svm.predict(train_set[0]).dtype, np.dtype("float32"), "Re-Predict failed")
51-
self.assertIs(svm.predict_classes(test_set[0]).dtype, np.dtype("int32"), "Re-Predict classes failed")
51+
self.assertIs(svm.predict_classes(cv_set[0]).dtype, np.dtype("int32"), "Re-Predict classes failed")
5252

5353
def test_06_re_evaluate(self):
54-
self.assertEqual(len(svm.evaluate(*train_set, *test_set)), 3, "Re-Evaluation failed")
54+
self.assertEqual(len(svm.evaluate(*train_set, *cv_set)), 3, "Re-Evaluation failed")
5555

5656
def test_07_re_train(self):
5757
self.assertIsInstance(
58-
svm.fit(*train_set, *test_set, verbose=0), SVM,
58+
svm.fit(*train_set, *cv_set, verbose=0), SVM,
5959
msg="Re-Train failed"
6060
)
6161

@@ -66,16 +66,16 @@ def test_99_clear_cache(self):
6666
class TestBasicNN(unittest.TestCase):
6767
def test_00_train(self):
6868
self.assertIsInstance(
69-
nn.fit(*train_set, *test_set, verbose=0), Basic,
69+
nn.fit(*train_set, *cv_set, verbose=0), Basic,
7070
msg="Train failed"
7171
)
7272

7373
def test_01_predict(self):
7474
self.assertIs(nn.predict(train_set[0]).dtype, np.dtype("float32"), "Predict failed")
75-
self.assertIs(nn.predict_classes(test_set[0]).dtype, np.dtype("int32"), "Predict classes failed")
75+
self.assertIs(nn.predict_classes(cv_set[0]).dtype, np.dtype("int32"), "Predict classes failed")
7676

7777
def test_02_evaluate(self):
78-
self.assertEqual(len(nn.evaluate(*train_set, *test_set)), 3, "Evaluation failed")
78+
self.assertEqual(len(nn.evaluate(*train_set, *cv_set)), 3, "Evaluation failed")
7979

8080
def test_03_save(self):
8181
self.assertIsInstance(nn.save(), Basic, msg="Save failed")
@@ -87,14 +87,14 @@ def test_04_load(self):
8787

8888
def test_05_re_predict(self):
8989
self.assertIs(nn.predict(train_set[0]).dtype, np.dtype("float32"), "Re-Predict failed")
90-
self.assertIs(nn.predict_classes(test_set[0]).dtype, np.dtype("int32"), "Re-Predict classes failed")
90+
self.assertIs(nn.predict_classes(cv_set[0]).dtype, np.dtype("int32"), "Re-Predict classes failed")
9191

9292
def test_06_re_evaluate(self):
93-
self.assertEqual(len(nn.evaluate(*train_set, *test_set)), 3, "Re-Evaluation failed")
93+
self.assertEqual(len(nn.evaluate(*train_set, *cv_set)), 3, "Re-Evaluation failed")
9494

9595
def test_07_re_train(self):
9696
self.assertIsInstance(
97-
nn.fit(*train_set, *test_set, verbose=0), Basic,
97+
nn.fit(*train_set, *cv_set, verbose=0), Basic,
9898
msg="Re-Train failed"
9999
)
100100

@@ -105,16 +105,17 @@ def test_99_clear_cache(self):
105105
class TestLinearSVM(unittest.TestCase):
106106
def test_00_train(self):
107107
self.assertIsInstance(
108-
linear_svm.fit(*train_set, *test_set, verbose=0), LinearSVM,
108+
linear_svm.fit(*train_set, *cv_set, verbose=0), LinearSVM,
109109
msg="Train failed"
110110
)
111111

112112
def test_01_predict(self):
113113
self.assertIs(linear_svm.predict(train_set[0]).dtype, np.dtype("float32"), "Predict failed")
114+
self.assertIs(linear_svm.predict_classes(cv_set[0]).dtype, np.dtype("int32"), "Predict classes failed")
114115
self.assertIs(linear_svm.predict_classes(test_set[0]).dtype, np.dtype("int32"), "Predict classes failed")
115116

116117
def test_02_evaluate(self):
117-
self.assertEqual(len(linear_svm.evaluate(*train_set, *test_set)), 3, "Evaluation failed")
118+
self.assertEqual(len(linear_svm.evaluate(*train_set, *cv_set, *test_set)), 3, "Evaluation failed")
118119

119120
def test_03_save(self):
120121
self.assertIsInstance(linear_svm.save(), LinearSVM, msg="Save failed")
@@ -126,14 +127,15 @@ def test_04_load(self):
126127

127128
def test_05_re_predict(self):
128129
self.assertIs(linear_svm.predict(train_set[0]).dtype, np.dtype("float32"), "Re-Predict failed")
130+
self.assertIs(linear_svm.predict_classes(cv_set[0]).dtype, np.dtype("int32"), "Re-Predict classes failed")
129131
self.assertIs(linear_svm.predict_classes(test_set[0]).dtype, np.dtype("int32"), "Re-Predict classes failed")
130132

131133
def test_06_re_evaluate(self):
132-
self.assertEqual(len(linear_svm.evaluate(*train_set, *test_set)), 3, "Re-Evaluation failed")
134+
self.assertEqual(len(linear_svm.evaluate(*train_set, *cv_set, *test_set)), 3, "Re-Evaluation failed")
133135

134136
def test_07_re_train(self):
135137
self.assertIsInstance(
136-
linear_svm.fit(*train_set, *test_set, verbose=0), LinearSVM,
138+
linear_svm.fit(*train_set, *cv_set, verbose=0), LinearSVM,
137139
msg="Re-Train failed"
138140
)
139141

‎_Dist/NeuralNetworks/_Tests/_UnitTests/b_Advanced.py

+8-6
Original file line numberDiff line numberDiff line change
@@ -15,28 +15,29 @@
1515
base_params = {
1616
"name": "UnitTest",
1717
"data_info": {
18-
"numerical_idx": [True, True, False],
18+
"numerical_idx": [True] * 6 + [False],
1919
"categorical_columns": []
2020
},
2121
"model_param_settings": {"n_epoch": 3, "max_epoch": 5}
2222
}
2323
nn = Advanced(**base_params)
24-
train_set, test_set = DataUtil.gen_noisy_linear(1000, 2, 2, one_hot=False)
24+
train_set, cv_set, test_set = DataUtil.gen_special_linear(1000, 2, 2, 2, one_hot=False)
2525

2626

2727
class TestAdvancedNN(unittest.TestCase):
2828
def test_00_train(self):
2929
self.assertIsInstance(
30-
nn.fit(*train_set, *test_set, verbose=0), Advanced,
30+
nn.fit(*train_set, *cv_set, verbose=0), Advanced,
3131
msg="Train failed"
3232
)
3333

3434
def test_01_predict(self):
3535
self.assertIs(nn.predict(train_set[0]).dtype, np.dtype("float32"), "Predict failed")
36+
self.assertIs(nn.predict_classes(cv_set[0]).dtype, np.dtype("int32"), "Predict classes failed")
3637
self.assertIs(nn.predict_classes(test_set[0]).dtype, np.dtype("int32"), "Predict classes failed")
3738

3839
def test_02_evaluate(self):
39-
self.assertEqual(len(nn.evaluate(*train_set, *test_set)), 3, "Evaluation failed")
40+
self.assertEqual(len(nn.evaluate(*train_set, *cv_set, *test_set)), 3, "Evaluation failed")
4041

4142
def test_03_save(self):
4243
self.assertIsInstance(nn.save(), Advanced, msg="Save failed")
@@ -48,14 +49,15 @@ def test_04_load(self):
4849

4950
def test_05_re_predict(self):
5051
self.assertIs(nn.predict(train_set[0]).dtype, np.dtype("float32"), "Re-Predict failed")
52+
self.assertIs(nn.predict_classes(cv_set[0]).dtype, np.dtype("int32"), "Re-Predict classes failed")
5153
self.assertIs(nn.predict_classes(test_set[0]).dtype, np.dtype("int32"), "Re-Predict classes failed")
5254

5355
def test_06_re_evaluate(self):
54-
self.assertEqual(len(nn.evaluate(*train_set, *test_set)), 3, "Re-Evaluation failed")
56+
self.assertEqual(len(nn.evaluate(*train_set, *cv_set, *test_set)), 3, "Re-Evaluation failed")
5557

5658
def test_07_re_train(self):
5759
self.assertIsInstance(
58-
nn.fit(*train_set, *test_set, verbose=0), Advanced,
60+
nn.fit(*train_set, *cv_set, verbose=0), Advanced,
5961
msg="Re-Train failed"
6062
)
6163

‎_Dist/NeuralNetworks/_Tests/_UnitTests/c_Auto.py

+21-12
Original file line numberDiff line numberDiff line change
@@ -22,7 +22,7 @@
2222
nn = AutoAdvanced(**copy.deepcopy(base_params))
2323
basic_nn = AutoBasic(**copy.deepcopy(base_params))
2424
linear_svm = AutoLinearSVM(**copy.deepcopy(base_params))
25-
train_set, test_set = DataUtil.gen_noisy_linear(1000, 2, 2, one_hot=False)
25+
train_set, cv_set, test_set = DataUtil.gen_special_linear(1000, 2, 2, 2, one_hot=False)
2626

2727
auto_mushroom_params = copy.deepcopy(base_params)
2828
auto_mushroom_params["name"] = "mushroom"
@@ -60,22 +60,25 @@
6060
class TestAutoNN(unittest.TestCase):
6161
def test_00_train_from_numpy(self):
6262
self.assertIsInstance(
63-
nn.fit(*train_set, *test_set, verbose=0), AutoAdvanced,
63+
nn.fit(*train_set, *cv_set, verbose=0), AutoAdvanced,
6464
msg="Train failed"
6565
)
6666
self.assertIsInstance(
67-
basic_nn.fit(*train_set, *test_set, verbose=0), AutoBasic,
67+
basic_nn.fit(*train_set, *cv_set, verbose=0), AutoBasic,
6868
msg="Train failed"
6969
)
7070

7171
def test_01_predict(self):
7272
self.assertIs(nn.predict(train_set[0]).dtype, np.dtype("float32"), "Predict failed")
7373
self.assertIs(basic_nn.predict(train_set[0]).dtype, np.dtype("float32"), "Predict failed")
74+
self.assertIs(nn.predict_classes(cv_set[0]).dtype, np.dtype("int32"), "Predict classes failed")
75+
self.assertIs(basic_nn.predict_classes(cv_set[0]).dtype, np.dtype("int32"), "Predict classes failed")
7476
self.assertIs(nn.predict_classes(test_set[0]).dtype, np.dtype("int32"), "Predict classes failed")
7577
self.assertIs(basic_nn.predict_classes(test_set[0]).dtype, np.dtype("int32"), "Predict classes failed")
7678

7779
def test_02_evaluate(self):
78-
self.assertEqual(len(nn.evaluate(*train_set, *test_set)), 3, "Evaluation failed")
80+
self.assertEqual(len(nn.evaluate(*train_set, *cv_set, *test_set)), 3, "Evaluation failed")
81+
self.assertEqual(len(basic_nn.evaluate(*train_set, *cv_set, *test_set)), 3, "Evaluation failed")
7982

8083
def test_03_save(self):
8184
self.assertIsInstance(nn.save(), AutoAdvanced, msg="Save failed")
@@ -91,20 +94,22 @@ def test_04_load(self):
9194
def test_05_re_predict(self):
9295
self.assertIs(nn.predict(train_set[0]).dtype, np.dtype("float32"), "Re-Predict failed")
9396
self.assertIs(basic_nn.predict(train_set[0]).dtype, np.dtype("float32"), "Re-Predict failed")
97+
self.assertIs(nn.predict_classes(cv_set[0]).dtype, np.dtype("int32"), "Re-Predict classes failed")
98+
self.assertIs(basic_nn.predict_classes(cv_set[0]).dtype, np.dtype("int32"), "Re-Predict classes failed")
9499
self.assertIs(nn.predict_classes(test_set[0]).dtype, np.dtype("int32"), "Re-Predict classes failed")
95100
self.assertIs(basic_nn.predict_classes(test_set[0]).dtype, np.dtype("int32"), "Re-Predict classes failed")
96101

97102
def test_06_re_evaluate(self):
98-
self.assertEqual(len(nn.evaluate(*train_set, *test_set)), 3, "Re-Evaluation failed")
99-
self.assertEqual(len(basic_nn.evaluate(*train_set, *test_set)), 3, "Re-Evaluation failed")
103+
self.assertEqual(len(nn.evaluate(*train_set, *cv_set, *test_set)), 3, "Re-Evaluation failed")
104+
self.assertEqual(len(basic_nn.evaluate(*train_set, *cv_set, *test_set)), 3, "Re-Evaluation failed")
100105

101106
def test_07_re_train(self):
102107
self.assertIsInstance(
103-
nn.fit(*train_set, *test_set, verbose=0), AutoAdvanced,
108+
nn.fit(*train_set, *cv_set, verbose=0), AutoAdvanced,
104109
msg="Re-Train failed"
105110
)
106111
self.assertIsInstance(
107-
basic_nn.fit(*train_set, *test_set, verbose=0), AutoBasic,
112+
basic_nn.fit(*train_set, *cv_set, verbose=0), AutoBasic,
108113
msg="Re-Train failed"
109114
)
110115

@@ -353,15 +358,17 @@ def test_99_clear_cache(self):
353358
class TestAutoLinearSVM(unittest.TestCase):
354359
def test_00_train_from_numpy(self):
355360
self.assertIsInstance(
356-
linear_svm.fit(*train_set, *test_set, verbose=0), AutoLinearSVM,
361+
linear_svm.fit(*train_set, *cv_set, verbose=0), AutoLinearSVM,
357362
msg="Train failed"
358363
)
359364

360365
def test_01_predict(self):
361366
self.assertIs(linear_svm.predict(train_set[0]).dtype, np.dtype("float32"), "Predict failed")
367+
self.assertIs(linear_svm.predict(cv_set[0]).dtype, np.dtype("float32"), "Predict failed")
368+
self.assertIs(linear_svm.predict(test_set[0]).dtype, np.dtype("float32"), "Predict failed")
362369

363370
def test_02_evaluate(self):
364-
self.assertEqual(len(linear_svm.evaluate(*train_set, *test_set)), 3, "Evaluation failed")
371+
self.assertEqual(len(linear_svm.evaluate(*train_set, *cv_set, *test_set)), 3, "Evaluation failed")
365372

366373
def test_03_save(self):
367374
self.assertIsInstance(linear_svm.save(), AutoLinearSVM, msg="Save failed")
@@ -373,13 +380,15 @@ def test_04_load(self):
373380

374381
def test_05_re_predict(self):
375382
self.assertIs(linear_svm.predict(train_set[0]).dtype, np.dtype("float32"), "Re-Predict failed")
383+
self.assertIs(linear_svm.predict(cv_set[0]).dtype, np.dtype("float32"), "Re-Predict failed")
384+
self.assertIs(linear_svm.predict(test_set[0]).dtype, np.dtype("float32"), "Re-Predict failed")
376385

377386
def test_06_re_evaluate(self):
378-
self.assertEqual(len(linear_svm.evaluate(*train_set, *test_set)), 3, "Re-Evaluation failed")
387+
self.assertEqual(len(linear_svm.evaluate(*train_set, *cv_set, *test_set)), 3, "Re-Evaluation failed")
379388

380389
def test_07_re_train(self):
381390
self.assertIsInstance(
382-
linear_svm.fit(*train_set, *test_set, verbose=0), AutoLinearSVM,
391+
linear_svm.fit(*train_set, *cv_set, verbose=0), AutoLinearSVM,
383392
msg="Re-Train failed"
384393
)
385394

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