onnx_profiling_example.py

# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License.

"""
.. _l-example-simple-usage:
Load and predict with ONNX Runtime and a very simple model
==========================================================
This example demonstrates how to load a model and compute
the output for an input vector. It also shows how to
retrieve the definition of its inputs and outputs.
"""

# modified from: https://onnxruntime.ai/docs/api/python/auto_examples/plot_load_and_predict.html#sphx-glr-auto-examples-plot-load-and-predict-py

import numpy
import os

import onnxruntime as rt
from onnxruntime.datasets import get_example

#########################
# Let's load a very simple model.
# The model is available on github `onnx...test_sigmoid <https://github.com/onnx/onnx/blob/main/onnx/backend/test/data/node/test_sigmoid>`_.

example1 = get_example("sigmoid.onnx")
options = rt.SessionOptions()
# enable profiling
options.enable_profiling = True
# enable perf profiling
options.add_session_config_entry("session.profiler.perf_config_file_name", os.path.abspath("perf_config.json"))
sess = rt.InferenceSession(example1, options, providers=rt.get_available_providers())

#########################
# Let's see the input name and shape.

input_name = sess.get_inputs()[0].name
print("input name", input_name)
input_shape = sess.get_inputs()[0].shape
print("input shape", input_shape)
input_type = sess.get_inputs()[0].type
print("input type", input_type)

#########################
# Let's see the output name and shape.

output_name = sess.get_outputs()[0].name
print("output name", output_name)
output_shape = sess.get_outputs()[0].shape
print("output shape", output_shape)
output_type = sess.get_outputs()[0].type
print("output type", output_type)

#########################
# Let's compute its outputs (or predictions if it is a machine learned model).

import numpy.random

x = numpy.random.random((3, 4, 5))
x = x.astype(numpy.float32)
res = sess.run([output_name], {input_name: x})
print(res)