mirror of https://github.com/kendryte/nncase.git
* Add accuracy test. * Move if_quant/w_quaint into remark. * enlarge qsize for CI server and reset postprocess result for nncase. * Add '\n' for each item in remark. |
||
---|---|---|
.github | ||
benchmark | ||
cmake | ||
csharp | ||
docs | ||
examples | ||
modules | ||
python | ||
src | ||
targets | ||
tests | ||
third_party | ||
toolchains | ||
tools | ||
.clang-format | ||
.editorconfig | ||
.gitattributes | ||
.gitignore | ||
.gitmodules | ||
.pep8 | ||
CMakeLists.txt | ||
Directory.Packages.props | ||
LICENSE | ||
NuGet.Config | ||
README.md | ||
conanfile.py | ||
nncase.sln | ||
pyproject.toml | ||
requirements.test.txt | ||
setup.py |
README.md

nncase
is a neural network compiler for AI accelerators.
nncase
是一个为 AI 加速器设计的神经网络编译器。
技术交流 QQ 群:790699378
Telegram: nncase community
Install from binaries
从二进制安装
Download prebuilt binaries from Release.
下载预编译的二进制文件 Release。
Build from source
从源码编译
Supported operators
支持的算子
K210/K510
K230
Resources
资源
K210
Architecture
架构

Features
- Supports multiple inputs and outputs and multi-branch structure
- Static memory allocation, no heap memory acquired
- Operators fusion and optimizations
- Support float and quantized uint8 inference
- Support post quantization from float model with calibration dataset
- Flat model with zero copy loading
功能
- 支持多输入输出网络,支持多分支结构
- 静态内存分配,不需要堆内存
- 算子合并和优化
- 支持 float 和量化 uint8 推理
- 支持训练后量化,使用浮点模型和量化校准集
- 平坦模型,支持零拷贝加载