def _display_intermediate_steps(model_onnx, inputs):
import onnxruntime
print("[_display_intermediate_steps] BEGIN")
if isinstance(model_onnx, str):
import onnx
model_onnx = onnx.load(model_onnx)
for name, node in enumerate_model_initializers(model_onnx, add_node=True):
print("INIT: {} - {}".format(name, _guess_type(node)))
for out, node in enumerate_model_node_outputs(model_onnx, add_node=True):
print('-')
print("OUTPUT: {} from {}".format(out, node.name))
step = select_model_inputs_outputs(model_onnx, out)
try:
step_sess = onnxruntime.InferenceSession(step.SerializeToString())
except Exception as e:
raise RuntimeError("Unable to load ONNX model with onnxruntime. "
"Last added node is:\n{}".format(node)) from e
for o in step_sess.get_inputs():
print("IN :", o)
for o in step_sess.get_outputs():
print("OUT: ", o)
if inputs:
res = step_sess.run(inputs)
print(res)
print("[_display_intermediate_steps] END")
def _display_intermediate_steps(model_onnx, inputs, disable_optimisation):
import onnxruntime
print("[_display_intermediate_steps] BEGIN")
if isinstance(model_onnx, str):
import onnx
model_onnx = onnx.load(model_onnx)
for name, node in enumerate_model_initializers(model_onnx, add_node=True):
print("INIT: {} - {}".format(name, _guess_type(node)))
for out, node in enumerate_model_node_outputs(model_onnx, add_node=True):
print('-')
print("OUTPUT: {} from {}".format(out, node.name))
step = select_model_inputs_outputs(model_onnx, out)
if (disable_optimisation
and hasattr(onnxruntime, 'GraphOptimizationLevel')):
opts = onnxruntime.SessionOptions()
opts.graph_optimization_level = (
onnxruntime.GraphOptimizationLevel.ORT_DISABLE_ALL)
else:
opts = None
try:
step_sess = onnxruntime.InferenceSession(step.SerializeToString(),
sess_options=opts)
except Exception as e:
raise RuntimeError("Unable to load ONNX model with onnxruntime. "
"Last added node is:\n{}".format(node)) from e
for o in step_sess.get_inputs():
print("IN :", o)
for o in step_sess.get_outputs():
print("OUT: ", o)
if inputs:
res = step_sess.run(inputs)
print(res)
print("[_display_intermediate_steps] END")