TNN: developed by Tencent Youtu Lab and Guangying Lab, a uniform deep learning inference framework for mobile、desktop and server. TNN is distinguished by several outstanding features, including its cross-platform capability, high performance, model compression and code pruning. Based on ncnn and Rapidnet, TNN further strengthens the support and performance optimization for mobile devices, and also draws on the advantages of good extensibility and high performance from existed open source efforts. TNN has been deployed in multiple Apps from Tencent, such as Mobile QQ, Weishi, Pitu, etc. Contributions are welcome to work in collaborative with us and make TNN a better framework.
1. 环境（environment）
RunTime DEVICE: ARM/OPENCL/METAL
2. Github版本
commit(optional):
3. 编译方式(compile method) CMake完整编译参数(full cmake arguments)
4. 编译日志(build log)
5. 详细描述bug 情况 (Describe the bug) 在Concat的时候 维度对不上 但是onnx阶段是正常的 6. 运行日志（runtime log）
7. 截图（Screenshots）
具体说明一下： 这个Concat是将一个普通conv输出的向量和一个经过上采样的向量进行Concat 但是会发现经过普通卷积输出的coonv的一个维度为为135 经过上采样的是136 这个两个的shape对不上 导致错误 我怀疑是不是conv出现了问题