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
666DZY666
commented
4 years ago
你好，看到你的readme介绍，你实现了规整剪枝、正常剪枝和分组卷积结构剪枝，我理解规整和正常剪枝是实现了slimming论文里的剪枝方法是吗，那分组卷积剪枝具体实现的是Rethinking the Value of Network Pruning论文里提到的哪个方法呢？