编译版本，默认配置，android-ndk-r25b，xcode 12.4，ubuntu-18.04，ubuntu-20.04，ubuntu-22.04，vs2015，vs2017，vs2019，vs2022，emscripten-2.0.8
| file | content | arch |
|---|---|---|
| ncnn-full-source.zip | 包含全部 submodule 代码的完整源码 | |
| ncnn-android.zip | android 静态库/动态库 | armeabi-v7a + arm64-v8a + x86 + x86_64 |
| ncnn-android-vulkan.zip | android 静态库/动态库，支持 GPU | armeabi-v7a + arm64-v8a + x86 + x86_64 |
| ncnn-ios.zip | ios 静态库，with and w/o bitcode | armv7 + arm64 + arm64e + i386 + x86_64 |
| ncnn-ios-vulkan.zip | ios 静态库，支持 GPU，with and w/o bitcode | arm64 + arm64e + x86_64 |
| ncnn-macos.zip | macos 静态库 | x86_64 + arm64 |
| ncnn-macos-vulkan.zip | macos 静态库，支持 GPU | x86_64 + arm64 |
| ncnn-ubuntu.zip | ubuntu linux 静态库/动态库，支持 GPU，模型转换工具 | x86_64 |
| ncnn-windows.zip | windows 静态库/动态库，支持 GPU，模型转换工具 | x86 + x64 + arm + arm64 |
| ncnn-webassembly.zip | webassembly 静态库 | wasm32 + simd + threads + simd-threads |
新增loongarch64 lsx向量指令集优化，包括absval/batchnorm/bias/binaryop/cast/clip/concat/convolution1d/convolutiondepthwise/convolution/crop/deconvolutiondepthwise/deconvolution/dequantize/dropout/eltwise/flatten/hardsigmoid/hardswish/innerproduct/interp/mish/packing/padding/pooling/prelu/quantize/relu/requantize/sigmoid/slice/softmax/swish/tanh/unaryop算子(@junchao-loongson)
layernorm x86优化(@LinHeLurking @LRY89757)
batchnorm/elu/prelu/gelu x86优化(@LRY89757)
softmax arm neon优化(@luqiang-guo)
batchnorm/instancenorm riscv vector优化(@thelastlin)
deformableconv2d x86优化(@miemie2013)
elu vulkan优化(@Yoh-Z)
convolution int8 x86 sse2/avx2优化
更新riscv vector segment load/store(@thelastlin)
改善内存池回收机制(@LinHeLurking)
新增获取cpu物理核心数量api，默认线程数设为物理大核心数量
实现控制单层运算特性是否启用的参数
更通用的macos/ios cpu特性探测过程，a15/a16/m2启用bf16和i8mm指令集
统一innerproduct x86 fp32/fp16s内核代码
修复在android省电模式cpu离线导致openmp崩溃的问题
实现glu算子与对应的pnnx转换(@csukuangfj)
新增fold和unfold算子
新增gridsample算子与对应的pnnx转换(@LRY89757)
lstm支持proj_size参数
groupnorm支持1d/2d/4d输入计算
squeeze/expanddims支持4d输入输出
multiheadattention支持kdim vdim参数
修复convolutiondepthwise allocator的错误设置(@w8501)
修正windows arm环境中convolution权重为空的问题
修复onnx2ncnn blob名字超出255长度的问题(@ZhangGe6)
修正expanddims axes参数id错误的问题(@LiuYi-Up)
修正c api allocator无法工作的问题(@qiqikit)
更严格的编译器armv7 fp16功能检查和兼容
修复老版本gcc编译avx512代码的编译错误(@bestpower)
修复windows-arm64编译(@zchrissirhcz)
修复在老版本ndk引用ncnn链接atomic内置函数失败的问题
修复新版本pybind11编译错误(@tpoisonooo)
python模块支持mat.numpy()(@csukuangfj)
更新pybind11和glslang子模块
pyncnn发布python 3.11包和windows arm版本
pnnx支持pytorch 1.13
pnnx现已支持在cpu上加载gpu导出的torchscript
pnnx保存onnx-zero模型文件
pnnx转换时将常量存储在临时文件减少内存占用
pnnx新增命令行参数fp16=0/1控制是否用fp16保存onnx-zero/ncnn模型
pnnx支持大部分数学函数转换，新增nn.Softmax2d/nn.Fold/nn.Unfold/F.fold/F.unfold/bitwise_left_shift/bitwise_right_shift转换
pnnx改善和匹配inplace slice copy操作
融合更多静态的F.convND/F.linear为nn module
合并临接的reshape
合并pad到conv中
改善pnnx F.softmax转换对dtype兼容性(@EdVince)
修正pnnx softmax/normalize/slice负数axis转换错误的问题
修正pnnx slice end下标错误问题
修正pnnx转ncnn保存fp16权重没考虑对齐的问题
pnnx遇到动态size时不再折叠为常量
pnnx自动折叠new_full/full_like
yolov5示例支持yolov5 6.2(@shaoshengsong)
修复编译警告(@tpoisonooo @veahow)
删除无用空行(@MollySophia @Menci)
修正空格对齐(@tonori)
修正拼写错误(@LRY89757 @Zepan @eltociear)
忽略.xmake目录，CMakeSettings.json，Visual Studio CMake文件(@zchrissirhcz)
重构README(@septs)
改善README布局(@magicse)
添加一些示例项目链接(@magicse @shaoshengsong)
faq新增有关禁用fp16设置的内容(@MisakaBit)
更新riscv rvv ci
新增c906 ci
新增loongarch64 lsx ci
迁移部分github action ci到腾讯ci
新增TH1520 cmake toolchain(@luyanaa)
切分大型单元测试加快多进程测试速度
新增Intel Celeron M 420跑分(@MouriNaruto)
新增T-Head TH1520跑分(@YuzukiTsuru)
新增rock5b rk3588跑分(@hwdef)
New Contributors
- @LinHeLurking made their first contribution in #4065
- @septs made their first contribution in #4114
- @w8501 made their first contribution in #4173
- @MollySophia made their first contribution in #4187
- @Menci made their first contribution in #4188
- @magicse made their first contribution in #4193
- @tonori made their first contribution in #4217
- @YuzukiTsuru made their first contribution in #4240
- @ZhangGe6 made their first contribution in #4236
- @MisakaBit made their first contribution in #4248
- @LiuYi-Up made their first contribution in #4259
- @veahow made their first contribution in #4274
- @csukuangfj made their first contribution in #4283
- @Zepan made their first contribution in #4287
- @bestpower made their first contribution in #4294
- @shaoshengsong made their first contribution in #4328
- @junchao-loongson made their first contribution in #4242
- @eltociear made their first contribution in #4358
Full Changelog: 2022072...2022112