mirror of
https://github.com/saymrwulf/onnxruntime.git
synced 2026-07-16 18:31:27 +00:00
* initial setup and rename "how to" to "setup" * move API to main nav * move api to main nav * add get starated, rework nav order * rename to install move mds out of install section * update api nav and home page * add install docs and python qs updates * python get started work * remove c and obj c for now * move java, python, and obj-c docs under api folder * move java api html to iframe (ugh) * remove api docs w/o details, move api text getstar * remove api docs wo detail updates get started * remvoe iframes * move eco system to main nav * fix api buttons * added more examples moved intro to ORT * fix links * fix get started titles * fix get started titles * fix more links * fix more links * more link fixes * fix nav remove inferencing and training subnav * fix top nav remove inference and training nav * fix title * fix tutorials nav hierarchy * fix python api button * add tenorflow keras example * fix quickstart toc * add imports fix spacing * fix links * update nav and python get started page * move ort training example, add coming soon for iot * update C# get started * fix spacing on quantization * Add some js get started content * fix formatting * fix typo * removed onnx-pytorch and onnx-tf * updated pip install torch and added links iot page * added pytorch tutorial heirarchy * updated web to docs soon added release blog link * add web link
69 lines
1.6 KiB
Python
69 lines
1.6 KiB
Python
# Copyright (c) Microsoft Corporation. All rights reserved.
|
|
# Licensed under the MIT License.
|
|
|
|
"""
|
|
Draw a pipeline
|
|
===============
|
|
|
|
There is no other way to look into one model stored
|
|
in ONNX format than looking into its node with
|
|
*onnx*. This example demonstrates
|
|
how to draw a model and to retrieve it in *json*
|
|
format.
|
|
|
|
.. contents::
|
|
:local:
|
|
|
|
Retrieve a model in JSON format
|
|
+++++++++++++++++++++++++++++++
|
|
|
|
That's the most simple way.
|
|
"""
|
|
|
|
from onnxruntime.datasets import get_example
|
|
example1 = get_example("mul_1.onnx")
|
|
|
|
import onnx
|
|
model = onnx.load(example1) # model is a ModelProto protobuf message
|
|
|
|
print(model)
|
|
|
|
|
|
#################################
|
|
# Draw a model with ONNX
|
|
# ++++++++++++++++++++++
|
|
# We use `net_drawer.py <https://github.com/onnx/onnx/blob/master/onnx/tools/net_drawer.py>`_
|
|
# included in *onnx* package.
|
|
# We use *onnx* to load the model
|
|
# in a different way than before.
|
|
|
|
|
|
from onnx import ModelProto
|
|
model = ModelProto()
|
|
with open(example1, 'rb') as fid:
|
|
content = fid.read()
|
|
model.ParseFromString(content)
|
|
|
|
###################################
|
|
# We convert it into a graph.
|
|
from onnx.tools.net_drawer import GetPydotGraph, GetOpNodeProducer
|
|
pydot_graph = GetPydotGraph(model.graph, name=model.graph.name, rankdir="LR",
|
|
node_producer=GetOpNodeProducer("docstring"))
|
|
pydot_graph.write_dot("graph.dot")
|
|
|
|
#######################################
|
|
# Then into an image
|
|
import os
|
|
os.system('dot -O -Tpng graph.dot')
|
|
|
|
################################
|
|
# Which we display...
|
|
import matplotlib.pyplot as plt
|
|
image = plt.imread("graph.dot.png")
|
|
plt.imshow(image)
|
|
|
|
|
|
|
|
|
|
|
|
|