run.py

import numpy as np
import onnx
import onnxruntime
from onnx import numpy_helper
import uproot

model="./model.onnx"

session = onnxruntime.InferenceSession(model, None)
input_name = session.get_inputs()[0].name
output_name = session.get_outputs()[0].name
print(input_name)
print(output_name)

with open("./inputs/branches_21.2.87-1.list.2") as fp:
    branches = [line.strip() for line in fp.readlines()]
print(branches)

m_gluino = 2300
m_lsp = 1200
isGtt = 0

for chunk in uproot.iterate("./inputs/DAOD_TRUTH3.GG_ttn1_2300_5000_1200_nominal.root:ntuple", expressions=branches, library="np", how=tuple):
    step_size = len(chunk[0])
    data = np.stack([*chunk, [isGtt]*step_size, [m_gluino]*step_size, [m_lsp]*step_size]).T
    result = session.run([output_name], {input_name: data.astype('float32')})
    print('result=',result)