update for keras 3.0

kgcnn/literature/AttentiveFP/_make.py

@@ -73,6 +73,17 @@ def make_model(inputs: list = None,
     r"""Make `AttentiveFP <https://doi.org/10.1021/acs.jmedchem.9b00959>`_ graph network via functional API.
     Default parameters can be found in :obj:`kgcnn.literature.AttentiveFP.model_default`.
 
+    Model inputs:
+    Model uses the list template of inputs and standard output template.
+    The supported inputs are  :obj:`[nodes, edges, edge_indices, ...]`
+    with '...' indicating mask or id tensors following the template below:
+    %s
+
+    Model outputs:
+    The standard output template:
+    %s
+
+
     Args:
         inputs (list): List of dictionaries unpacked in :obj:`tf.keras.layers.Input`. Order must match model definition.
         cast_disjoint_kwargs (dict): Dictionary of arguments for :obj:`CastBatchedIndicesToDisjoint` .
@@ -141,3 +152,6 @@ def set_scale(*args, **kwargs):
         setattr(model, "set_scale", set_scale)
 
     return model
+
+
+make_model.__doc__ = make_model.__doc__ % (template_cast_list_input.__doc__, template_cast_output.__doc__)

kgcnn/models/casting.py

@@ -9,6 +9,8 @@
 
 def template_cast_output(model_outputs,
                          output_embedding, output_tensor_type, input_tensor_type, cast_disjoint_kwargs):
+    """TODO"""
+
     out, batch_id_node, batch_id_edge, node_id, edge_id, count_nodes, count_edges = model_outputs
 
     # Output embedding choice
@@ -55,7 +57,7 @@ def template_cast_list_input(model_inputs,
                              has_graph_state: Union[int, bool] = False,
                              has_crystal_input: Union[int, bool] = False,
                              return_sub_id: bool = True):
-
+    """TODO"""
     standard_inputs = [x for x in model_inputs]
 
     batched_nodes = []