TMVA_SOFIE_PyTorch_HiggsModel.py File Reference

Functions

 TMVA_SOFIE_PyTorch_HiggsModel.CreateModel (nlayers=4, nunits=64)    TMVA_SOFIE_PyTorch_HiggsModel.ExportModel (model, modelName)    TMVA_SOFIE_PyTorch_HiggsModel.GenerateCode (modelFile="model.onnx")    TMVA_SOFIE_PyTorch_HiggsModel.PrepareData ()    TMVA_SOFIE_PyTorch_HiggsModel.TrainModel (model, x, y, epochs=5, batch_size=50)     str TMVA_SOFIE_PyTorch_HiggsModel.modelHeaderFile = modelName + ".hxx"    TMVA_SOFIE_PyTorch_HiggsModel.modelName = GenerateCode(modelFile)  Step 2 : Parse model and generate inference code with SOFIE.
   TMVA_SOFIE_PyTorch_HiggsModel.session = sofie.Session()    TMVA_SOFIE_PyTorch_HiggsModel.sofie = getattr(ROOT, "TMVA_SOFIE_" + modelName)  Step 3 : Compile the generated C++ model code.
   TMVA_SOFIE_PyTorch_HiggsModel.x_check = x_test[:10]    TMVA_SOFIE_PyTorch_HiggsModel.x_test  Step 1 : Create and train the model, export it to ONNX.
   TMVA_SOFIE_PyTorch_HiggsModel.x_train  Step 1 : Create and train the model, export it to ONNX.
   TMVA_SOFIE_PyTorch_HiggsModel.y = session.infer(x_check[i])    TMVA_SOFIE_PyTorch_HiggsModel.y_test  Step 1 : Create and train the model, export it to ONNX.
   TMVA_SOFIE_PyTorch_HiggsModel.y_train  Step 1 : Create and train the model, export it to ONNX.
   TMVA_SOFIE_PyTorch_HiggsModel.ytorch = model(torch.from_numpy(x_check)).numpy()  

Detailed Description

This macro trains a simple deep neural network on the Higgs dataset with PyTorch, exports the model to ONNX and runs the SOFIE parser on it to generate and compile C++ inference code.

The trained model is saved as HiggsModel.onnx and is used as input by other SOFIE tutorials (e.g. TMVA_SOFIE_RDataFrame.C), so this macro needs to be run before them.

size of data 10000
Sequential(
  (0): Linear(in_features=7, out_features=64, bias=True)
  (1): ReLU()
  (2): Linear(in_features=64, out_features=64, bias=True)
  (3): ReLU()
  (4): Linear(in_features=64, out_features=1, bias=True)
  (5): Sigmoid()
)
Epoch 1/5 - average loss: 0.6755
Epoch 2/5 - average loss: 0.6561
Epoch 3/5 - average loss: 0.6461
Epoch 4/5 - average loss: 0.6386
Epoch 5/5 - average loss: 0.6333
calling torch.onnx.export with parameters {'input_names': ['input'], 'output_names': ['output'], 'external_data': False, 'dynamo': True}
[torch.onnx] Obtain model graph for `Sequential([...]` with `torch.export.export(..., strict=False)`...
[torch.onnx] Obtain model graph for `Sequential([...]` with `torch.export.export(..., strict=False)`... ✅
[torch.onnx] Run decompositions...
[torch.onnx] Run decompositions... ✅
[torch.onnx] Translate the graph into ONNX...
[torch.onnx] Translate the graph into ONNX... ✅
[torch.onnx] Optimize the ONNX graph...
[torch.onnx] Optimize the ONNX graph... ✅
model exported to ONNX as HiggsModel.onnx
input to model is  [1.3551283  1.0198661  0.98278755 0.5504138  1.2055093  0.91609305
 0.93084896] 
    -> output using SOFIE =  0.3763280510902405  using PyTorch =  0.37632805
input to model is  [1.0965776 0.9103265 1.9756684 1.3508093 1.3468878 1.4005579 1.1609015] 
    -> output using SOFIE =  0.5212275385856628  using PyTorch =  0.5212275
input to model is  [0.846992  0.9408182 0.98906   1.6148995 1.038698  1.2381754 1.0323234] 
    -> output using SOFIE =  0.6604689359664917  using PyTorch =  0.66046894
input to model is  [1.897264   1.234499   0.98704207 0.708829   0.7279103  0.9053675
 0.76521254] 
    -> output using SOFIE =  0.5919074416160583  using PyTorch =  0.59190744
input to model is  [0.791873   0.9792347  0.9924756  0.9159218  1.1000326  0.94064647
 0.79085195] 
    -> output using SOFIE =  0.6196779012680054  using PyTorch =  0.6196779
input to model is  [0.9692043  0.6372814  0.9850732  0.9201175  0.72131383 0.8001433
 0.7160924 ] 
    -> output using SOFIE =  0.5712547898292542  using PyTorch =  0.57125473
input to model is  [1.5037444 1.1279533 0.9814414 1.5327642 0.7886151 1.1838427 1.0383142] 
    -> output using SOFIE =  0.5804571509361267  using PyTorch =  0.58045715
input to model is  [1.2042431  1.0750061  1.5724212  1.1590953  1.367509   1.1043229
 0.99204683] 
    -> output using SOFIE =  0.48698461055755615  using PyTorch =  0.4869846
input to model is  [1.012179   0.76250947 0.9957243  0.48331824 0.4295301  0.55478483
 0.7100585 ] 
    -> output using SOFIE =  0.35637032985687256  using PyTorch =  0.35637033
input to model is  [0.8616951  1.1908345  0.99018383 1.2523934  1.1448306  1.0246366
 0.9923519 ] 
    -> output using SOFIE =  0.6398386359214783  using PyTorch =  0.63983864
OK

Definition in file TMVA_SOFIE_PyTorch_HiggsModel.py.