Correct logic for Node's parents/children association with inputs/outputs in aidge_core/show_graphview.py.

Context

This MR corrects an identified problem within the algorithm allowing to link a Node's parents (or children) nodes to its respective inputs (or outputs) in file aidge_core/show_graphview.py.

In short, only the dimensions of tensors were verified to do the matching, which caused a problem when, for example, multiple Node's inputs (or outputs) had the same dimensions.

Also, it corrects a few errors with the automatic creation of the generated files' paths.

Modified files

• python_binding/graph/pybind_Node.cpp , added the python binding for the method "get_ordered_children()";
• aidge_core/show_graphview.py, corrected logic used to link parents/children to inputs/outputs of a Node and management of paths.

Detailed major modifications

Inside the _create_dict method, employ the aidge_core.Node.outputs() method to retrieve the children of the Node's parents and the associated input index connected to each child. Similarly, use aidge_core.Node.inputs() to retrieve the Node's list of children and outputs.

aidge_core/show_graphview.py

@@ -129,7 +129,7 @@ def _create_dict(ordered_nodes : list[aidge_core.Node], write_trainable_params_e
 
                     if params_file_format=='npz':
                         np.savez_compressed(Path(path_trainable_params, node.name()), **{node.name() : node.get_operator().get_output(0)})
-                        node_dict['tensor_data'] = Path(path_trainable_params, node.name() + '.npz')
+                        node_dict['tensor_data'] = str(Path(path_trainable_params, node.name() + '.npz'))
 
                     elif params_file_format=='json':
                         tensor = np.array(node.get_operator().get_output(0))
@@ -145,7 +145,7 @@ def _create_dict(ordered_nodes : list[aidge_core.Node], write_trainable_params_e
                         with open(Path(path_trainable_params, node.name() + '.json'), 'w') as fp:
                             json.dump(tensor_dict, fp, indent=4)
 
-                        node_dict['tensor_data'] = Path(path_trainable_params, node.name() + '.json')
+                        node_dict['tensor_data'] = str(Path(path_trainable_params, node.name() + '.json'))
 
                     else:
                         raise Exception("File format to write trainable parameters not recognized.")