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
wbwtab下的bn_fuse 设置如何参数,都是32bit的bn融合, parser.add_argument("--W", type=int, default=32, help="Wb:2, Wt:3, Wfp:32") parser.add_argument("--A", type=int, default=32, help="Ab:2, Afp:32")
为啥代码还是进入:
针对特征(A)二值的bn融合
融合二值的,这种设置应该是普通融合啊?