Update code doc

ncps/keras/cfc.py

@@ -43,11 +43,11 @@ def __init__(
 
         Examples::
 
-            >>> from ncps.tf import CfC
+            >>> from ncps.keras import CfC
             >>>
             >>> rnn = CfC(50)
             >>> x = keras.random.uniform((2, 10, 20))  # (B,L,C)
-            >>> y = keras.layers.RNN(x)
+            >>> y = rnn(x)
 
         :param units: Number of hidden units
         :param mixed_memory: Whether to augment the RNN by a `memory-cell <https://arxiv.org/abs/2006.04418>`_ to help learn long-term dependencies in the data (default False)

ncps/keras/ltc.py

@@ -43,20 +43,20 @@ def __init__(
             >>> from ncps.keras import LTC
             >>>
             >>> rnn = LTC(50)
-            >>> x = tf.random.uniform((2, 10, 20))  # (B,L,C)
+            >>> x = keras.random.uniform((2, 10, 20))  # (B,L,C)
             >>> y = rnn(x)
 
         .. Note::
             For creating a wired `Neural circuit policy (NCP) <https://publik.tuwien.ac.at/files/publik_292280.pdf>`_ you can pass a `ncps.wirings.NCP` object instead of the number of units
 
         Examples::
 
-            >>> from ncps.tf import LTC
+            >>> from ncps.keras import LTC
             >>> from ncps.wirings import NCP
             >>>
             >>> wiring = NCP(10, 10, 8, 6, 6, 4, 4)
             >>> rnn = LTC(wiring)
-            >>> x = tf.random.uniform((2, 10, 20))  # (B,L,C)
+            >>> x = keras.random.uniform((2, 10, 20))  # (B,L,C)
             >>> y = rnn(x)
 
         :param units: Wiring (ncps.wirings.Wiring instance) or integer representing the number of (fully-connected) hidden units

ncps/keras/ltc_cell.py

@@ -36,12 +36,12 @@ def __init__(
         . Note::
             This is an RNNCell that process single time-steps.
             To get a full RNN that can process sequences,
-            see `ncps.tf.LTC` or wrap the cell with a `keras.layers.RNN <https://www.tensorflow.org/api_docs/python/tf/keras/layers/RNN>`_.
+            see `ncps.keras.LTC` or wrap the cell with a `keras.layers.RNN <https://www.tensorflow.org/api_docs/python/tf/keras/layers/RNN>`_.
 
         Examples::
 
              >>> import ncps
-             >>> from ncps.tf import LTCCell
+             >>> from ncps.keras import LTCCell
              >>>
              >>> wiring = ncps.wirings.Random(16, output_dim=2, sparsity_level=0.5)
              >>> cell = LTCCell(wiring)