fix(cgan): y_train when None

neuralnetlib/models.py

@@ -2644,10 +2644,16 @@ def fit(
                     callback.on_epoch_begin(epoch, epoch_logs)
 
                 start_time = time.time()
-                x_train_shuffled, y_train_shuffled = shuffle(
-                    x_train, y_train,
-                    random_state=random_state if random_state is not None else self.random_state
-                )
+                if y_train:
+                    x_train_shuffled, y_train_shuffled = shuffle(
+                        x_train, y_train,
+                        random_state=random_state if random_state is not None else self.random_state
+                    )
+                else:
+                    x_train_shuffled = shuffle(
+                        x_train,
+                        random_state=random_state if random_state is not None else self.random_state
+                    )
                 d_error = 0
                 g_error = 0
 
@@ -2662,7 +2668,10 @@ def fit(
                     for j in range(0, x_train.shape[0], batch_size):
                         batch_index = j // batch_size
                         x_batch = x_train_shuffled[j:j + batch_size]
-                        y_batch = y_train_shuffled[j:j + batch_size] if y_train is not None else None
+                        if y_train:
+                            y_batch = y_train_shuffled[j:j + batch_size]
+                        else:
+                            y_batch = None
 
                         batch_logs = {
                             'batch': batch_index,