fix: Fix data preprocessing and dragan performance prints (#105)

Author: fabclmnt

examples/regular/cramergan_example.py

@@ -23,7 +23,8 @@
 
 #Before training the GAN do not forget to apply the required data transformations
 #To ease here we've applied a PowerTransformation
-data = transformations(data)
+_, data, _ = transformations(data)
+
 
 #For the purpose of this example we will only synthesize the minority class
 train_data = data.loc[ data['Class']==1 ].copy()

examples/regular/wgan_example.py

@@ -21,7 +21,7 @@
 
 #Before training the GAN do not forget to apply the required data transformations
 #To ease here we've applied a PowerTransformation
-data = transformations(data)
+_, data, _ = transformations(data)
 
 #For the purpose of this example we will only synthesize the minority class
 train_data = data.loc[ data['Class']==1 ].copy()

src/ydata_synthetic/synthesizers/regular/dragan/model.py

@@ -125,10 +125,10 @@ def train(self, data, train_arguments):
                     batch_data = tf.cast(batch_data, dtype=tf.float32)
                     d_loss, g_loss = self.train_step(batch_data)
 
-            print(
-                "Epoch: {} | disc_loss: {} | gen_loss: {}".format(
-                    epoch, d_loss, g_loss
-                ))
+                print(
+                    "Epoch: {} | disc_loss: {} | gen_loss: {}".format(
+                        epoch, d_loss, g_loss
+                    ))
 
             if epoch % train_arguments.sample_interval == 0:
                 # Test here data generation step