Small test for ONNX produced by NEMO

onnx_minitest.py

#
# Copyright (C) 2021 University of Bologna
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
# Author: Francesco Conti <f.conti@unibo.it>

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

INVESTIGATE_NODE = '490' # None (for the real output) or set to the node name e.g. '208'
MODEL_NAME = 'model_best.onnx'
DATA_NAME = 'test.npy'

data = np.load(DATA_NAME, allow_pickle=True).item()

if INVESTIGATE_NODE is not None:
    model = onnx.load(MODEL_NAME)
    interm = onnx.helper.ValueInfoProto()
    interm.name = INVESTIGATE_NODE
    model.graph.output.append(interm)
    onnx.save(model, MODEL_NAME+'mod')

if INVESTIGATE_NODE is None:
    sess = rt.InferenceSession(MODEL_NAME)
else:
    sess = rt.InferenceSession(MODEL_NAME+'mod')
input_name = sess.get_inputs()[0].name
output_name = sess.get_outputs()[1 if INVESTIGATE_NODE is not None else 0].name

x = np.expand_dims(data['input'].astype(np.float32), axis=0)
res = sess.run([output_name], {input_name: x})