This example demonstrates how to use Post-Training Quantization API from Neural Network Compression Framework (NNCF) to quantize and train PyTorch models on the example of Resnet18 quantization aware training, pretrained on Tiny ImageNet-200 dataset.
The example includes the following steps:
At this point it is assumed that you have already installed NNCF. You can find information on installation NNCF here.
To work with the example you should install the corresponding Python package dependencies:
pip install -r requirements.txt
It's pretty simple. The example does not require additional preparation. It will do the preparation itself, such as loading the dataset and model, etc.
python main.py
此处可能存在不合适展示的内容,页面不予展示。您可通过相关编辑功能自查并修改。
如您确认内容无涉及 不当用语 / 纯广告导流 / 暴力 / 低俗色情 / 侵权 / 盗版 / 虚假 / 无价值内容或违法国家有关法律法规的内容,可点击提交进行申诉,我们将尽快为您处理。