We read every piece of feedback, and take your input very seriously.
To see all available qualifiers, see our documentation.
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
使用mnn_offline_quant离线量化,模型是多输入,量化后算子仍然是float32类型。但量化过程没有报错,模型文件大小有所缩减,但是模型推理速度并没有上升。附上量化前和量化后的模型。 量化后.zip 量化前.zip
The text was updated successfully, but these errors were encountered:
多输入的模型可以直接采取权重量化的方式。-MNNConvert --WeightQuantBits这样,具体使用方式参考文档。编译时打开-DMNN_LOW_MEMORY=ON,推理时memory mode使用 low
Sorry, something went wrong.
No branches or pull requests
使用mnn_offline_quant离线量化,模型是多输入,量化后算子仍然是float32类型。但量化过程没有报错,模型文件大小有所缩减,但是模型推理速度并没有上升。附上量化前和量化后的模型。
量化后.zip
量化前.zip
The text was updated successfully, but these errors were encountered: