666DZY666 / micronet

micronet, a model compression and deploy lib. compression: 1、quantization: quantization-aware-training(QAT), High-Bit(>2b)(DoReFa/Quantization and Training of Neural Networks for Efficient Integer-Arithmetic-Only Inference)、Low-Bit(≤2b)/Ternary and Binary(TWN/BNN/XNOR-Net); post-training-quantization(PTQ), 8-bit(tensorrt); 2、 pruning: normal、regular and group convolutional channel pruning; 3、 group convolution structure; 4、batch-normalization fuse for quantization. deploy: tensorrt, fp32/fp16/int8(ptq-calibration)、op-adapt(upsample)、dynamic_shape
MIT License
2.2k stars 478 forks source link

有量化后和剪枝后的精度对比吗?谢谢 #3

Open betterhalfwzm opened 4 years ago

betterhalfwzm commented 4 years ago

有量化前后和剪枝前后的精度对比吗?

666DZY666 commented 4 years ago

已补充至readme

betterhalfwzm commented 4 years ago

好的,谢谢。量化(8/4/2 bits)这个有对比吗

666DZY666 commented 4 years ago

测试过resnet20,精度方面, W/A: 二值/4bits — 89.16% 4bits/4bits — 91.25% 二值/32bits — 90.64% 其他情况可以自己尝试一下

zhangfeixiang222 commented 3 years ago

实际测试下来,在32bits/32bits(W/A),nin.py中的网络只能达到88%,请问作者有什么可以建议的吗