remove test + update other test

tests/integration/synthesizer/test_tvae.py

@@ -11,42 +11,10 @@
 
 import numpy as np
 import pandas as pd
-from sklearn import datasets
 
 from ctgan.synthesizers.tvae import TVAE
 
 
-def test_tvae(tmpdir, capsys):
-    """Test the TVAE load/save methods."""
-    # Setup
-    iris = datasets.load_iris()
-    data = pd.DataFrame(iris.data, columns=iris.feature_names)
-    data['class'] = pd.Series(iris.target).map(iris.target_names.__getitem__)
-    tvae = TVAE(epochs=10, verbose=True)
-
-    # Run
-    tvae.fit(data, ['class'])
-    captured_out = capsys.readouterr().err
-
-    path = str(tmpdir / 'test_tvae.pkl')
-    tvae.save(path)
-    tvae = TVAE.load(path)
-
-    sampled = tvae.sample(100)
-
-    # Assert
-    assert sampled.shape == (100, 5)
-    assert isinstance(sampled, pd.DataFrame)
-    assert set(sampled.columns) == set(data.columns)
-    assert set(sampled.dtypes) == set(data.dtypes)
-    loss_values = tvae.loss_values
-    assert len(loss_values) == 10
-    assert set(loss_values.columns) == {'Epoch', 'Batch', 'Loss'}
-    assert all(loss_values['Batch'] == 0)
-    last_loss_val = loss_values['Loss'].iloc[-1]
-    assert f'Loss: {round(last_loss_val, 3):.3f}: 100%' in captured_out
-
-
 def test_drop_last_false():
     """Test the TVAE predicts the correct values."""
     data = pd.DataFrame({
@@ -122,17 +90,18 @@ def test_fixed_random_seed():
     np.testing.assert_array_equal(sampled_0_1, sampled_1_1)
 
 
-def test_tvae_save(tmpdir):
+def test_tvae_save(tmpdir, capsys):
     """Test that the ``TVAE`` model can be saved and loaded."""
     # Setup
     data = pd.DataFrame({
         'continuous': np.random.random(100),
         'discrete': np.random.choice(['a', 'b', 'c'], 100)
     })
-    discrete_columns = [1]
+    discrete_columns = ['discrete']
 
-    tvae = TVAE(epochs=1)
-    tvae.fit(data.to_numpy(), discrete_columns)
+    tvae = TVAE(epochs=10, verbose=True)
+    tvae.fit(data, discrete_columns)
+    captured_out = capsys.readouterr().err
     tvae.set_random_state(0)
 
     tvae.sample(100)
@@ -143,4 +112,16 @@ def test_tvae_save(tmpdir):
 
     # Load
     loaded_instance = TVAE.load(str(model_path))
-    loaded_instance.sample(100)
+    sampled = loaded_instance.sample(100)
+
+    # Assert
+    assert sampled.shape == (100, 2)
+    assert isinstance(sampled, pd.DataFrame)
+    assert set(sampled.columns) == set(data.columns)
+    assert set(sampled.dtypes) == set(data.dtypes)
+    loss_values = tvae.loss_values
+    assert len(loss_values) == 10
+    assert set(loss_values.columns) == {'Epoch', 'Batch', 'Loss'}
+    assert all(loss_values['Batch'] == 0)
+    last_loss_val = loss_values['Loss'].iloc[-1]
+    assert f'Loss: {round(last_loss_val, 3):.3f}: 100%' in captured_out