[tutorials] Migrate the SOFIE GNN tutorials to PyTorch and ONNX

The SOFIE GNN tutorials defined their model with DeepMind graph_nets and
dm-sonnet, whose last releases date from 2020 and which cannot be
installed together with current Python and TensorFlow versions anymore.

Define the same model with plain PyTorch instead: an
Encode-Process-Decode graph network with the identical architecture
(graph-network blocks following Battaglia et al., arXiv:1806.01261,
with 4-layer ReLU MLP update functions, LayerNorm in the core network
and summation aggregation).  The components are exported to ONNX with
the torch.export-based exporter and the inference code is generated
with the SOFIE ONNX parser, so the GNN-specific SOFIE classes and the
graph_nets parser are no longer involved.

The graph-network block maps onto standard ONNX operators: Gemm+Relu,
Concat, Gather of the sender/receiver node features,
ScatterElements(reduction=add) for the edge aggregation (the equivalent
of unsorted_segment_sum), ReduceSum and LayerNormalization.

- TMVA_SOFIE_GNN.py validates the generated inference against PyTorch
  (agreement at float32 precision) and compares the execution times.
- TMVA_SOFIE_GNN_Parser.py exports the model with dynamic node and edge
  counts, generates the inference code and writes variable-sized input
  graphs plus PyTorch reference results to a ROOT file.
- TMVA_SOFIE_GNN_Application.C evaluates the generated code in C++ on
  that file, like before, now with the ONNX-generated session interface.

The tutorials are now gated on the torch and onnx Python modules
instead of sonnet and graph_nets.

🤖 Done with the help of AI

Author: guitargeek

tutorials/CMakeLists.txt

@@ -357,8 +357,6 @@ else()
   #these depends on external packages
   ROOT_FIND_PYTHON_MODULE(torch)
   ROOT_FIND_PYTHON_MODULE(keras)
-  ROOT_FIND_PYTHON_MODULE(sonnet)
-  ROOT_FIND_PYTHON_MODULE(graph_nets)
   ROOT_FIND_PYTHON_MODULE(onnx)
 
 
@@ -380,7 +378,8 @@ else()
   endif()
   #veto this tutorial since it is added directly
   list(APPEND tmva_veto machine_learning/TMVA_SOFIE_GNN_Parser.py)
-  if (NOT ROOT_SONNET_FOUND OR NOT ROOT_GRAPH_NETS_FOUND)
+  # The GNN tutorials define their model with PyTorch and export it to ONNX
+  if (NOT ROOT_TORCH_FOUND OR NOT ROOT_ONNX_FOUND)
     list(APPEND tmva_veto machine_learning/TMVA_SOFIE_GNN.py)
     list(APPEND tmva_veto machine_learning/TMVA_SOFIE_GNN_Application.C)
   endif()
@@ -683,7 +682,7 @@ if(geom)
                 FAILREGEX "Error in" "error:" "warning: Failed to call" LABELS tutorial ENVIRONMENT ${TUTORIAL_ENV})
 endif()
 # define Python GNN parsing tutorial needed to run before
-if (ROOT_SONNET_FOUND AND ROOT_GRAPH_NETS_FOUND)
+if (ROOT_TORCH_FOUND AND ROOT_ONNX_FOUND)
   ROOT_ADD_TEST(tutorial-machine_learning-TMVA_SOFIE_GNN_Parser COMMAND ${Python3_EXECUTABLE}
   ${CMAKE_CURRENT_SOURCE_DIR}/machine_learning/TMVA_SOFIE_GNN_Parser.py
   PASSRC 0 FAILREGEX "Error in" ": error:" LABELS tutorial ENVIRONMENT ${TUTORIAL_ENV})