## Appendix A Fine-Grained Pruning Algorithm  
```
1 Begin
2/*Initialization*/
3\(Mask=1\)
4\(W=zavier\)initialisation()
5\(t=0,t_{0}\)(first\(pruning\)iteration),step
6
7/*Pretraining*/
8\(While\)(\(t<t_{0}\))
9\(W_{t}=W_{t-1}-\mu\
abla\)
10\(t=t+1\)
11
12/*Pruning*/
13\(S_{t}=S+(S_{0}-S)\)\(\left(1-\frac{t-t_{0}}{t\_0-t_{\text{m}}}\right)\)
14\(W_{s}=sort(W)\)
15\(threshold=W_{s}[S_{t}\times lenght(W_{s})]\)
16 if\(|W|<threshold\)
17\(Mask=0\)
18\(W=W.Mask\)
19
20/*Retraining*/
21\(W_{t}=W_{t-1}-\mu\
abla\)
22\(W=W.Mask\)
23\(t=t+1\)
24 if\((t\equiv step)\)thenGoto Pruning
25





## Appendix B Filter-level Pruning
```
1 Begin
2/*Initialization*/
3\(Mask=1\)
4\(W\)=zavier initialisation()
5\(t=0,t_{0}(first pruning iteration),step\)
6
7/*Pretraining*/
8 While(\(t<t_{0}\))
9\(W_{t}=W_{t-1}-\mu\triangledown\)
10\(t=t+1\)
11
12/*Pruning*/
13\(S_{t}=S+(S_{0}-S)\left(1-\frac{t-t_{0}}{t_{0}-t_{m}}\right)\)
14\(FilterSum=\sum_{filters}|W|\)
15\(F_{g}=sort(FilterSum)\)
16\(threshold=F_{g}[S_{t}\times lenght(F_{g})]\)
17\(if\sum_{filters}|W|<threshold\)
18\(Mask=0\)
19\(\prime\)Retraining*/
20\(W_{t}=W_{t-1}-\mu\triangledown\)
21\(W=W.Mask\)
22\(t=t+1\)
23\(if(t\equiv step)\)thenGoto Pruning
24 End
```

**Algorithm A2: Filter-level Pruning**

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