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update doc for pr #3488(quantization speedup tool) #3512
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J-shang
approved these changes
Apr 6, 2021
| which increases the difficulty of deploying deep neural network model. Quantization is a | ||
| fundamental technology which is widely used to reduce memory footprint and speed up inference | ||
| process. Many frameworks begin to support quantization, but few of them support mixed precision | ||
| quantiation. Frameworks like `HAQ: Hardware-Aware Automated Quantization with Mixed Precision <https://arxiv.org/pdf/1811.08886.pdf>`__\, only support simulated mixed precision quantization which will |
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quantiation -> quantization?
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Thanks, have fixed.
QuanluZhang
reviewed
Apr 7, 2021
| For complete examples please refer to :githublink:`the code <examples/model_compress/quantization/mixed_precision_speedup_mnist.py>`. | ||
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| For more parameters about the class 'TensorRTModelSpeedUp', you can refer to :githublink:`the code <nni/compression/pytorch/speedup/quantization_speedup/integrated_tensorrt.py>`. |
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better to refer to API doc instead of source code
QuanluZhang
approved these changes
Apr 9, 2021
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