Comments (2)
- We use 250~500 samples for each conv. layers, and 25,000 samples for each fc. layer. One sample can produce much more constraints in conv. layers than that in fc. layers.
- In the paper, "fine-tune" means update subsequent layers while parameters in the quantized layers remain unchanged. Here, the value of D and B is maintained. However, there is another fine-tuning strategy, i.e. update D via backpropagation with B fixed.
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Thanks a lot!!!
Your replies really clear things up!!!
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Related Issues (20)
- Other Model Architectures HOT 1
- questions about codebook HOT 4
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