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dabnn
mirror of https://github.com/JDAI-CV/dabnn
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dabnn/third_party
daquexian 7460af8369 Eliminate dropout by custom onnx optimizer 4 years ago
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benchmark @ f0901417c8 init 5 years ago
eigen/Eigen Move eigen to third_party and include them as system headers 4 years ago
flatbuffers @ 9e7e8cbe9f Move flatbuffers to submodule 4 years ago
glog @ de82428e52 init 5 years ago
googletest @ 3f5b5b8f84 Update googletest since my android fix is merged 5 years ago
onnx @ 9f70c11891 Eliminate dropout by custom onnx optimizer 4 years ago
protobuf @ 6973c3a504 onnx2bnn python package 5 years ago
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我们推出了 dabnn，一个用 ARM 汇编重写了卷积，高度优化的二值网络 inference 框架。实验显示 dabnn 相对于现有的二值网络和浮点网络 inference 框架均能带来极大的加速。在运行单个二值卷积时，我们的速度是 BMXNet （除 dabnn 外唯一一个二值网络 inference 框架） 的 800%~2400%，在运行二值化的 ResNet-18 时，我们的速度是 BMXNet 的约 700%。

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