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

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关于反卷积和BN层融合的疑惑

xiaoluomi opened this issue · comments

您好,我看了您的代码,在考虑计算加速的时候,目前代码还没有考虑反卷积和BN层融合的量化训练对吗?

commented

convtrans_bn_fuse还没有,有兴趣可以加加