Fixed docstrings

Signed-off-by: Jim Martens <github@2martens.de>

src/twomartens/masterthesis/aae/train.py

@@ -41,6 +41,7 @@ def train_mnist(folding_id: int, inlier_classes: Sequence[int], total_classes: i
                 folds: int = 5):
     """
     Train AAE for mnist data set.
+    
     :param folding_id: id of fold used for test data
     :param inlier_classes: list of class ids that are considered inliers
     :param total_classes: total number of classes
@@ -76,6 +77,7 @@ def train_mnist(folding_id: int, inlier_classes: Sequence[int], total_classes: i
     def list_of_pairs_to_numpy(list_of_pairs: Sequence[Tuple[int, np.ndarray]]) -> Tuple[np.ndarray, np.ndarray]:
         """
         Converts a list of pairs to a numpy array.
+        
         :param list_of_pairs: list of pairs
         :return: numpy array
         """
@@ -129,6 +131,7 @@ def train_mnist(folding_id: int, inlier_classes: Sequence[int], total_classes: i
         def shuffle(train_data: np.ndarray) -> None:
             """
             Shuffles the given training data inplace.
+            
             :param train_data: numpy array of training data
             """
             np.take(train_data, np.random.permutation(train_data.shape[0]), axis=0, out=train_data)
@@ -388,6 +391,7 @@ def get_z_variable(batch_size: int, zsize: int) -> tf.Variable:
 def extract_batch(data: np.ndarray, it: int, batch_size: int) -> tf.Variable:
     """
     Extracts a batch from data.
+    
     :param data: numpy array of data
     :param it: current iteration in epoch (or batch number)
     :param batch_size: size of batch