onnxruntime/docs/api/python/sources/auto_examples/plot_profiling.rst.txt
github-actions[bot] 8bde251409
Update Python API docs to commit 9765949 (#10181)
Co-authored-by: natke <natke@users.noreply.github.com>
2022-01-04 09:32:40 -08:00

208 lines
4 KiB
ReStructuredText

.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "auto_examples/plot_profiling.py"
.. LINE NUMBERS ARE GIVEN BELOW.
.. only:: html
.. note::
:class: sphx-glr-download-link-note
Click :ref:`here <sphx_glr_download_auto_examples_plot_profiling.py>`
to download the full example code
.. rst-class:: sphx-glr-example-title
.. _sphx_glr_auto_examples_plot_profiling.py:
.. _l-example-profiling:
Profile the execution of a simple model
=======================================
*ONNX Runtime* can profile the execution of the model.
This example shows how to interpret the results.
.. GENERATED FROM PYTHON SOURCE LINES 14-32
.. code-block:: default
import onnx
import onnxruntime as rt
import numpy
from onnxruntime.datasets import get_example
def change_ir_version(filename, ir_version=6):
"onnxruntime==1.2.0 does not support opset <= 7 and ir_version > 6"
with open(filename, "rb") as f:
model = onnx.load(f)
model.ir_version = 6
if model.opset_import[0].version <= 7:
model.opset_import[0].version = 11
return model
.. GENERATED FROM PYTHON SOURCE LINES 33-34
Let's load a very simple model and compute some prediction.
.. GENERATED FROM PYTHON SOURCE LINES 34-45
.. code-block:: default
example1 = get_example("mul_1.onnx")
onnx_model = change_ir_version(example1)
onnx_model_str = onnx_model.SerializeToString()
sess = rt.InferenceSession(onnx_model_str, providers=rt.get_available_providers())
input_name = sess.get_inputs()[0].name
x = numpy.array([[1.0, 2.0], [3.0, 4.0], [5.0, 6.0]], dtype=numpy.float32)
res = sess.run(None, {input_name: x})
print(res)
.. rst-class:: sphx-glr-script-out
Out:
.. code-block:: none
[array([[ 1., 4.],
[ 9., 16.],
[25., 36.]], dtype=float32)]
.. GENERATED FROM PYTHON SOURCE LINES 46-48
We need to enable to profiling
before running the predictions.
.. GENERATED FROM PYTHON SOURCE LINES 48-60
.. code-block:: default
options = rt.SessionOptions()
options.enable_profiling = True
sess_profile = rt.InferenceSession(onnx_model_str, options, providers=rt.get_available_providers())
input_name = sess.get_inputs()[0].name
x = numpy.array([[1.0, 2.0], [3.0, 4.0], [5.0, 6.0]], dtype=numpy.float32)
sess.run(None, {input_name: x})
prof_file = sess_profile.end_profiling()
print(prof_file)
.. rst-class:: sphx-glr-script-out
Out:
.. code-block:: none
onnxruntime_profile__2022-01-04_17-09-55.json
.. GENERATED FROM PYTHON SOURCE LINES 61-63
The results are stored un a file in JSON format.
Let's see what it contains.
.. GENERATED FROM PYTHON SOURCE LINES 63-71
.. code-block:: default
import json
with open(prof_file, "r") as f:
sess_time = json.load(f)
import pprint
pprint.pprint(sess_time)
.. rst-class:: sphx-glr-script-out
Out:
.. code-block:: none
[{'args': {},
'cat': 'Session',
'dur': 56,
'name': 'model_loading_array',
'ph': 'X',
'pid': 3089,
'tid': 3089,
'ts': 1},
{'args': {},
'cat': 'Session',
'dur': 240,
'name': 'session_initialization',
'ph': 'X',
'pid': 3089,
'tid': 3089,
'ts': 71}]
.. rst-class:: sphx-glr-timing
**Total running time of the script:** ( 0 minutes 0.007 seconds)
.. _sphx_glr_download_auto_examples_plot_profiling.py:
.. only :: html
.. container:: sphx-glr-footer
:class: sphx-glr-footer-example
.. container:: sphx-glr-download sphx-glr-download-python
:download:`Download Python source code: plot_profiling.py <plot_profiling.py>`
.. container:: sphx-glr-download sphx-glr-download-jupyter
:download:`Download Jupyter notebook: plot_profiling.ipynb <plot_profiling.ipynb>`
.. only:: html
.. rst-class:: sphx-glr-signature
`Gallery generated by Sphinx-Gallery <https://sphinx-gallery.github.io>`_