def test_examples(example_dir, artifacts):
example_dir = os.path.join(EXAMPLES_ROOT, example_dir)
readme = os.path.join(example_dir, "README.md")
commands = load_commands_from_readme(readme)
for command in commands:
G_LOGGER.info(command)
assert sp.run(["bash", "-c", command], cwd=example_dir, env={"PYTHONPATH": ROOT_DIR}).returncode == 0
for artifact in artifacts:
artifact_path = os.path.join(example_dir, artifact.name)
assert os.path.exists(artifact_path)
if artifact.infer:
assert infer_model(artifact_path)
os.remove(artifact_path)
def infer_model(path):
model = onnx.load(path)
graph = gs.import_onnx(model)
feed_dict = {}
for tensor in graph.inputs:
feed_dict[tensor.name] = np.random.random_sample(size=tensor.shape).astype(tensor.dtype)
output_names = [out.name for out in graph.outputs]
sess = onnxruntime.InferenceSession(model.SerializeToString())
outputs = sess.run(output_names, feed_dict)
G_LOGGER.info("Inference outputs: {:}".format(outputs))
return outputs
