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https://github.com/saymrwulf/onnxruntime.git
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c7c8757a1c
Use ruff as the code formatter in place of black and isort since it is much faster, and as projects like PyTorch and ONNX have adopted ruff format as well. This PR include only auto-fixed changes in formatting.
69 lines
1.9 KiB
Python
69 lines
1.9 KiB
Python
# Copyright (c) Microsoft Corporation. All rights reserved.
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# Licensed under the MIT License.
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"""
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.. _l-example-profiling:
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Profile the execution of a simple model
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=======================================
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*ONNX Runtime* can profile the execution of the model.
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This example shows how to interpret the results.
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"""
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import numpy
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import onnx
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import onnxruntime as rt
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from onnxruntime.datasets import get_example
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def change_ir_version(filename, ir_version=6):
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"onnxruntime==1.2.0 does not support opset <= 7 and ir_version > 6"
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with open(filename, "rb") as f:
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model = onnx.load(f)
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model.ir_version = 6
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if model.opset_import[0].version <= 7:
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model.opset_import[0].version = 11
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return model
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#########################
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# Let's load a very simple model and compute some prediction.
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example1 = get_example("mul_1.onnx")
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onnx_model = change_ir_version(example1)
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onnx_model_str = onnx_model.SerializeToString()
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sess = rt.InferenceSession(onnx_model_str, providers=rt.get_available_providers())
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input_name = sess.get_inputs()[0].name
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x = numpy.array([[1.0, 2.0], [3.0, 4.0], [5.0, 6.0]], dtype=numpy.float32)
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res = sess.run(None, {input_name: x})
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print(res)
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#########################
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# We need to enable to profiling
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# before running the predictions.
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options = rt.SessionOptions()
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options.enable_profiling = True
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sess_profile = rt.InferenceSession(onnx_model_str, options, providers=rt.get_available_providers())
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input_name = sess.get_inputs()[0].name
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x = numpy.array([[1.0, 2.0], [3.0, 4.0], [5.0, 6.0]], dtype=numpy.float32)
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sess.run(None, {input_name: x})
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prof_file = sess_profile.end_profiling()
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print(prof_file)
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###########################
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# The results are stored un a file in JSON format.
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# Let's see what it contains.
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import json # noqa: E402
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with open(prof_file) as f:
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sess_time = json.load(f)
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import pprint # noqa: E402
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pprint.pprint(sess_time)
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