1name: "MOBILENET"
2#  transform_param {
3#    scale: 0.017
4#    mirror: false
5#    crop_size: 224
6#    mean_value: [103.94,116.78,123.68]
7#  }
8layer {
9  name: "data"
10  type: "Input"
11  top: "data"
12  input_param: { shape: { dim: 1 dim: 3 dim: 224 dim: 224 } }
13}
14#input: "data"
15#input_dim: 1
16#input_dim: 3
17#input_dim: 224
18#input_dim: 224
19layer {
20  name: "conv1"
21  type: "Convolution"
22  bottom: "data"
23  top: "conv1"
24  param {
25    lr_mult: 1
26    decay_mult: 1
27  }
28  convolution_param {
29    num_output: 32
30    bias_term: false
31    pad: 1
32    kernel_size: 3
33    stride: 2
34    weight_filler {
35      type: "msra"
36    }
37  }
38}
39layer {
40  name: "conv1/bn"
41  type: "BatchNorm"
42  bottom: "conv1"
43  top: "conv1"
44  param {
45    lr_mult: 0
46    decay_mult: 0
47  }
48  param {
49    lr_mult: 0
50    decay_mult: 0
51  }
52  param {
53    lr_mult: 0
54    decay_mult: 0
55  }
56  batch_norm_param {
57    use_global_stats: true
58    eps: 1e-5
59  }
60}
61layer {
62  name: "conv1/scale"
63  type: "Scale"
64  bottom: "conv1"
65  top: "conv1"
66  param {
67    lr_mult: 1
68    decay_mult: 0
69  }
70  param {
71    lr_mult: 1
72    decay_mult: 0
73  }
74  scale_param {
75    filler {
76      value: 1
77    }
78    bias_term: true
79    bias_filler {
80      value: 0
81    }
82  }
83}
84layer {
85  name: "relu1"
86  type: "ReLU"
87  bottom: "conv1"
88  top: "conv1"
89}
90layer {
91  name: "conv2_1/dw"
92  type: "Convolution"
93  bottom: "conv1"
94  top: "conv2_1/dw"
95  param {
96    lr_mult: 1
97    decay_mult: 1
98  }
99  convolution_param {
100    num_output: 32
101    bias_term: false
102    pad: 1
103    kernel_size: 3
104    group: 32
105    engine: CAFFE
106    stride: 1
107    weight_filler {
108      type: "msra"
109    }
110  }
111}
112layer {
113  name: "conv2_1/dw/bn"
114  type: "BatchNorm"
115  bottom: "conv2_1/dw"
116  top: "conv2_1/dw"
117  param {
118    lr_mult: 0
119    decay_mult: 0
120  }
121  param {
122    lr_mult: 0
123    decay_mult: 0
124  }
125  param {
126    lr_mult: 0
127    decay_mult: 0
128  }
129  batch_norm_param {
130    use_global_stats: true
131    eps: 1e-5
132  }
133}
134layer {
135  name: "conv2_1/dw/scale"
136  type: "Scale"
137  bottom: "conv2_1/dw"
138  top: "conv2_1/dw"
139  param {
140    lr_mult: 1
141    decay_mult: 0
142  }
143  param {
144    lr_mult: 1
145    decay_mult: 0
146  }
147  scale_param {
148    filler {
149      value: 1
150    }
151    bias_term: true
152    bias_filler {
153      value: 0
154    }
155  }
156}
157layer {
158  name: "relu2_1/dw"
159  type: "ReLU"
160  bottom: "conv2_1/dw"
161  top: "conv2_1/dw"
162}
163layer {
164  name: "conv2_1/sep"
165  type: "Convolution"
166  bottom: "conv2_1/dw"
167  top: "conv2_1/sep"
168  param {
169    lr_mult: 1
170    decay_mult: 1
171  }
172  convolution_param {
173    num_output: 64
174    bias_term: false
175    pad: 0
176    kernel_size: 1
177    stride: 1
178    weight_filler {
179      type: "msra"
180    }
181  }
182}
183layer {
184  name: "conv2_1/sep/bn"
185  type: "BatchNorm"
186  bottom: "conv2_1/sep"
187  top: "conv2_1/sep"
188  param {
189    lr_mult: 0
190    decay_mult: 0
191  }
192  param {
193    lr_mult: 0
194    decay_mult: 0
195  }
196  param {
197    lr_mult: 0
198    decay_mult: 0
199  }
200  batch_norm_param {
201    use_global_stats: true
202    eps: 1e-5
203  }
204}
205layer {
206  name: "conv2_1/sep/scale"
207  type: "Scale"
208  bottom: "conv2_1/sep"
209  top: "conv2_1/sep"
210  param {
211    lr_mult: 1
212    decay_mult: 0
213  }
214  param {
215    lr_mult: 1
216    decay_mult: 0
217  }
218  scale_param {
219    filler {
220      value: 1
221    }
222    bias_term: true
223    bias_filler {
224      value: 0
225    }
226  }
227}
228layer {
229  name: "relu2_1/sep"
230  type: "ReLU"
231  bottom: "conv2_1/sep"
232  top: "conv2_1/sep"
233}
234layer {
235  name: "conv2_2/dw"
236  type: "Convolution"
237  bottom: "conv2_1/sep"
238  top: "conv2_2/dw"
239  param {
240    lr_mult: 1
241    decay_mult: 1
242  }
243  convolution_param {
244    num_output: 64
245    bias_term: false
246    pad: 1
247    kernel_size: 3
248    group: 64
249    engine: CAFFE
250    stride: 2
251    weight_filler {
252      type: "msra"
253    }
254  }
255}
256layer {
257  name: "conv2_2/dw/bn"
258  type: "BatchNorm"
259  bottom: "conv2_2/dw"
260  top: "conv2_2/dw"
261  param {
262    lr_mult: 0
263    decay_mult: 0
264  }
265  param {
266    lr_mult: 0
267    decay_mult: 0
268  }
269  param {
270    lr_mult: 0
271    decay_mult: 0
272  }
273  batch_norm_param {
274    use_global_stats: true
275    eps: 1e-5
276  }
277}
278layer {
279  name: "conv2_2/dw/scale"
280  type: "Scale"
281  bottom: "conv2_2/dw"
282  top: "conv2_2/dw"
283  param {
284    lr_mult: 1
285    decay_mult: 0
286  }
287  param {
288    lr_mult: 1
289    decay_mult: 0
290  }
291  scale_param {
292    filler {
293      value: 1
294    }
295    bias_term: true
296    bias_filler {
297      value: 0
298    }
299  }
300}
301layer {
302  name: "relu2_2/dw"
303  type: "ReLU"
304  bottom: "conv2_2/dw"
305  top: "conv2_2/dw"
306}
307layer {
308  name: "conv2_2/sep"
309  type: "Convolution"
310  bottom: "conv2_2/dw"
311  top: "conv2_2/sep"
312  param {
313    lr_mult: 1
314    decay_mult: 1
315  }
316  convolution_param {
317    num_output: 128
318    bias_term: false
319    pad: 0
320    kernel_size: 1
321    stride: 1
322    weight_filler {
323      type: "msra"
324    }
325  }
326}
327layer {
328  name: "conv2_2/sep/bn"
329  type: "BatchNorm"
330  bottom: "conv2_2/sep"
331  top: "conv2_2/sep"
332  param {
333    lr_mult: 0
334    decay_mult: 0
335  }
336  param {
337    lr_mult: 0
338    decay_mult: 0
339  }
340  param {
341    lr_mult: 0
342    decay_mult: 0
343  }
344  batch_norm_param {
345    use_global_stats: true
346    eps: 1e-5
347  }
348}
349layer {
350  name: "conv2_2/sep/scale"
351  type: "Scale"
352  bottom: "conv2_2/sep"
353  top: "conv2_2/sep"
354  param {
355    lr_mult: 1
356    decay_mult: 0
357  }
358  param {
359    lr_mult: 1
360    decay_mult: 0
361  }
362  scale_param {
363    filler {
364      value: 1
365    }
366    bias_term: true
367    bias_filler {
368      value: 0
369    }
370  }
371}
372layer {
373  name: "relu2_2/sep"
374  type: "ReLU"
375  bottom: "conv2_2/sep"
376  top: "conv2_2/sep"
377}
378layer {
379  name: "conv3_1/dw"
380  type: "Convolution"
381  bottom: "conv2_2/sep"
382  top: "conv3_1/dw"
383  param {
384    lr_mult: 1
385    decay_mult: 1
386  }
387  convolution_param {
388    num_output: 128
389    bias_term: false
390    pad: 1
391    kernel_size: 3
392    group: 128
393    engine: CAFFE
394    stride: 1
395    weight_filler {
396      type: "msra"
397    }
398  }
399}
400layer {
401  name: "conv3_1/dw/bn"
402  type: "BatchNorm"
403  bottom: "conv3_1/dw"
404  top: "conv3_1/dw"
405  param {
406    lr_mult: 0
407    decay_mult: 0
408  }
409  param {
410    lr_mult: 0
411    decay_mult: 0
412  }
413  param {
414    lr_mult: 0
415    decay_mult: 0
416  }
417  batch_norm_param {
418    use_global_stats: true
419    eps: 1e-5
420  }
421}
422layer {
423  name: "conv3_1/dw/scale"
424  type: "Scale"
425  bottom: "conv3_1/dw"
426  top: "conv3_1/dw"
427  param {
428    lr_mult: 1
429    decay_mult: 0
430  }
431  param {
432    lr_mult: 1
433    decay_mult: 0
434  }
435  scale_param {
436    filler {
437      value: 1
438    }
439    bias_term: true
440    bias_filler {
441      value: 0
442    }
443  }
444}
445layer {
446  name: "relu3_1/dw"
447  type: "ReLU"
448  bottom: "conv3_1/dw"
449  top: "conv3_1/dw"
450}
451layer {
452  name: "conv3_1/sep"
453  type: "Convolution"
454  bottom: "conv3_1/dw"
455  top: "conv3_1/sep"
456  param {
457    lr_mult: 1
458    decay_mult: 1
459  }
460  convolution_param {
461    num_output: 128
462    bias_term: false
463    pad: 0
464    kernel_size: 1
465    stride: 1
466    weight_filler {
467      type: "msra"
468    }
469  }
470}
471layer {
472  name: "conv3_1/sep/bn"
473  type: "BatchNorm"
474  bottom: "conv3_1/sep"
475  top: "conv3_1/sep"
476  param {
477    lr_mult: 0
478    decay_mult: 0
479  }
480  param {
481    lr_mult: 0
482    decay_mult: 0
483  }
484  param {
485    lr_mult: 0
486    decay_mult: 0
487  }
488  batch_norm_param {
489    use_global_stats: true
490    eps: 1e-5
491  }
492}
493layer {
494  name: "conv3_1/sep/scale"
495  type: "Scale"
496  bottom: "conv3_1/sep"
497  top: "conv3_1/sep"
498  param {
499    lr_mult: 1
500    decay_mult: 0
501  }
502  param {
503    lr_mult: 1
504    decay_mult: 0
505  }
506  scale_param {
507    filler {
508      value: 1
509    }
510    bias_term: true
511    bias_filler {
512      value: 0
513    }
514  }
515}
516layer {
517  name: "relu3_1/sep"
518  type: "ReLU"
519  bottom: "conv3_1/sep"
520  top: "conv3_1/sep"
521}
522layer {
523  name: "conv3_2/dw"
524  type: "Convolution"
525  bottom: "conv3_1/sep"
526  top: "conv3_2/dw"
527  param {
528    lr_mult: 1
529    decay_mult: 1
530  }
531  convolution_param {
532    num_output: 128
533    bias_term: false
534    pad: 1
535    kernel_size: 3
536    group: 128
537    engine: CAFFE
538    stride: 2
539    weight_filler {
540      type: "msra"
541    }
542  }
543}
544layer {
545  name: "conv3_2/dw/bn"
546  type: "BatchNorm"
547  bottom: "conv3_2/dw"
548  top: "conv3_2/dw"
549  param {
550    lr_mult: 0
551    decay_mult: 0
552  }
553  param {
554    lr_mult: 0
555    decay_mult: 0
556  }
557  param {
558    lr_mult: 0
559    decay_mult: 0
560  }
561  batch_norm_param {
562    use_global_stats: true
563    eps: 1e-5
564  }
565}
566layer {
567  name: "conv3_2/dw/scale"
568  type: "Scale"
569  bottom: "conv3_2/dw"
570  top: "conv3_2/dw"
571  param {
572    lr_mult: 1
573    decay_mult: 0
574  }
575  param {
576    lr_mult: 1
577    decay_mult: 0
578  }
579  scale_param {
580    filler {
581      value: 1
582    }
583    bias_term: true
584    bias_filler {
585      value: 0
586    }
587  }
588}
589layer {
590  name: "relu3_2/dw"
591  type: "ReLU"
592  bottom: "conv3_2/dw"
593  top: "conv3_2/dw"
594}
595layer {
596  name: "conv3_2/sep"
597  type: "Convolution"
598  bottom: "conv3_2/dw"
599  top: "conv3_2/sep"
600  param {
601    lr_mult: 1
602    decay_mult: 1
603  }
604  convolution_param {
605    num_output: 256
606    bias_term: false
607    pad: 0
608    kernel_size: 1
609    stride: 1
610    weight_filler {
611      type: "msra"
612    }
613  }
614}
615layer {
616  name: "conv3_2/sep/bn"
617  type: "BatchNorm"
618  bottom: "conv3_2/sep"
619  top: "conv3_2/sep"
620  param {
621    lr_mult: 0
622    decay_mult: 0
623  }
624  param {
625    lr_mult: 0
626    decay_mult: 0
627  }
628  param {
629    lr_mult: 0
630    decay_mult: 0
631  }
632  batch_norm_param {
633    use_global_stats: true
634    eps: 1e-5
635  }
636}
637layer {
638  name: "conv3_2/sep/scale"
639  type: "Scale"
640  bottom: "conv3_2/sep"
641  top: "conv3_2/sep"
642  param {
643    lr_mult: 1
644    decay_mult: 0
645  }
646  param {
647    lr_mult: 1
648    decay_mult: 0
649  }
650  scale_param {
651    filler {
652      value: 1
653    }
654    bias_term: true
655    bias_filler {
656      value: 0
657    }
658  }
659}
660layer {
661  name: "relu3_2/sep"
662  type: "ReLU"
663  bottom: "conv3_2/sep"
664  top: "conv3_2/sep"
665}
666layer {
667  name: "conv4_1/dw"
668  type: "Convolution"
669  bottom: "conv3_2/sep"
670  top: "conv4_1/dw"
671  param {
672    lr_mult: 1
673    decay_mult: 1
674  }
675  convolution_param {
676    num_output: 256
677    bias_term: false
678    pad: 1
679    kernel_size: 3
680    group: 256
681    engine: CAFFE
682    stride: 1
683    weight_filler {
684      type: "msra"
685    }
686  }
687}
688layer {
689  name: "conv4_1/dw/bn"
690  type: "BatchNorm"
691  bottom: "conv4_1/dw"
692  top: "conv4_1/dw"
693  param {
694    lr_mult: 0
695    decay_mult: 0
696  }
697  param {
698    lr_mult: 0
699    decay_mult: 0
700  }
701  param {
702    lr_mult: 0
703    decay_mult: 0
704  }
705  batch_norm_param {
706    use_global_stats: true
707    eps: 1e-5
708  }
709}
710layer {
711  name: "conv4_1/dw/scale"
712  type: "Scale"
713  bottom: "conv4_1/dw"
714  top: "conv4_1/dw"
715  param {
716    lr_mult: 1
717    decay_mult: 0
718  }
719  param {
720    lr_mult: 1
721    decay_mult: 0
722  }
723  scale_param {
724    filler {
725      value: 1
726    }
727    bias_term: true
728    bias_filler {
729      value: 0
730    }
731  }
732}
733layer {
734  name: "relu4_1/dw"
735  type: "ReLU"
736  bottom: "conv4_1/dw"
737  top: "conv4_1/dw"
738}
739layer {
740  name: "conv4_1/sep"
741  type: "Convolution"
742  bottom: "conv4_1/dw"
743  top: "conv4_1/sep"
744  param {
745    lr_mult: 1
746    decay_mult: 1
747  }
748  convolution_param {
749    num_output: 256
750    bias_term: false
751    pad: 0
752    kernel_size: 1
753    stride: 1
754    weight_filler {
755      type: "msra"
756    }
757  }
758}
759layer {
760  name: "conv4_1/sep/bn"
761  type: "BatchNorm"
762  bottom: "conv4_1/sep"
763  top: "conv4_1/sep"
764  param {
765    lr_mult: 0
766    decay_mult: 0
767  }
768  param {
769    lr_mult: 0
770    decay_mult: 0
771  }
772  param {
773    lr_mult: 0
774    decay_mult: 0
775  }
776  batch_norm_param {
777    use_global_stats: true
778    eps: 1e-5
779  }
780}
781layer {
782  name: "conv4_1/sep/scale"
783  type: "Scale"
784  bottom: "conv4_1/sep"
785  top: "conv4_1/sep"
786  param {
787    lr_mult: 1
788    decay_mult: 0
789  }
790  param {
791    lr_mult: 1
792    decay_mult: 0
793  }
794  scale_param {
795    filler {
796      value: 1
797    }
798    bias_term: true
799    bias_filler {
800      value: 0
801    }
802  }
803}
804layer {
805  name: "relu4_1/sep"
806  type: "ReLU"
807  bottom: "conv4_1/sep"
808  top: "conv4_1/sep"
809}
810layer {
811  name: "conv4_2/dw"
812  type: "Convolution"
813  bottom: "conv4_1/sep"
814  top: "conv4_2/dw"
815  param {
816    lr_mult: 1
817    decay_mult: 1
818  }
819  convolution_param {
820    num_output: 256
821    bias_term: false
822    pad: 1
823    kernel_size: 3
824    group: 256
825    engine: CAFFE
826    stride: 2
827    weight_filler {
828      type: "msra"
829    }
830  }
831}
832layer {
833  name: "conv4_2/dw/bn"
834  type: "BatchNorm"
835  bottom: "conv4_2/dw"
836  top: "conv4_2/dw"
837  param {
838    lr_mult: 0
839    decay_mult: 0
840  }
841  param {
842    lr_mult: 0
843    decay_mult: 0
844  }
845  param {
846    lr_mult: 0
847    decay_mult: 0
848  }
849  batch_norm_param {
850    use_global_stats: true
851    eps: 1e-5
852  }
853}
854layer {
855  name: "conv4_2/dw/scale"
856  type: "Scale"
857  bottom: "conv4_2/dw"
858  top: "conv4_2/dw"
859  param {
860    lr_mult: 1
861    decay_mult: 0
862  }
863  param {
864    lr_mult: 1
865    decay_mult: 0
866  }
867  scale_param {
868    filler {
869      value: 1
870    }
871    bias_term: true
872    bias_filler {
873      value: 0
874    }
875  }
876}
877layer {
878  name: "relu4_2/dw"
879  type: "ReLU"
880  bottom: "conv4_2/dw"
881  top: "conv4_2/dw"
882}
883layer {
884  name: "conv4_2/sep"
885  type: "Convolution"
886  bottom: "conv4_2/dw"
887  top: "conv4_2/sep"
888  param {
889    lr_mult: 1
890    decay_mult: 1
891  }
892  convolution_param {
893    num_output: 512
894    bias_term: false
895    pad: 0
896    kernel_size: 1
897    stride: 1
898    weight_filler {
899      type: "msra"
900    }
901  }
902}
903layer {
904  name: "conv4_2/sep/bn"
905  type: "BatchNorm"
906  bottom: "conv4_2/sep"
907  top: "conv4_2/sep"
908  param {
909    lr_mult: 0
910    decay_mult: 0
911  }
912  param {
913    lr_mult: 0
914    decay_mult: 0
915  }
916  param {
917    lr_mult: 0
918    decay_mult: 0
919  }
920  batch_norm_param {
921    use_global_stats: true
922    eps: 1e-5
923  }
924}
925layer {
926  name: "conv4_2/sep/scale"
927  type: "Scale"
928  bottom: "conv4_2/sep"
929  top: "conv4_2/sep"
930  param {
931    lr_mult: 1
932    decay_mult: 0
933  }
934  param {
935    lr_mult: 1
936    decay_mult: 0
937  }
938  scale_param {
939    filler {
940      value: 1
941    }
942    bias_term: true
943    bias_filler {
944      value: 0
945    }
946  }
947}
948layer {
949  name: "relu4_2/sep"
950  type: "ReLU"
951  bottom: "conv4_2/sep"
952  top: "conv4_2/sep"
953}
954layer {
955  name: "conv5_1/dw"
956  type: "Convolution"
957  bottom: "conv4_2/sep"
958  top: "conv5_1/dw"
959  param {
960    lr_mult: 1
961    decay_mult: 1
962  }
963  convolution_param {
964    num_output: 512
965    bias_term: false
966    pad: 1
967    kernel_size: 3
968    group: 512
969    engine: CAFFE
970    stride: 1
971    weight_filler {
972      type: "msra"
973    }
974  }
975}
976layer {
977  name: "conv5_1/dw/bn"
978  type: "BatchNorm"
979  bottom: "conv5_1/dw"
980  top: "conv5_1/dw"
981  param {
982    lr_mult: 0
983    decay_mult: 0
984  }
985  param {
986    lr_mult: 0
987    decay_mult: 0
988  }
989  param {
990    lr_mult: 0
991    decay_mult: 0
992  }
993  batch_norm_param {
994    use_global_stats: true
995    eps: 1e-5
996  }
997}
998layer {
999  name: "conv5_1/dw/scale"
1000  type: "Scale"
1001  bottom: "conv5_1/dw"
1002  top: "conv5_1/dw"
1003  param {
1004    lr_mult: 1
1005    decay_mult: 0
1006  }
1007  param {
1008    lr_mult: 1
1009    decay_mult: 0
1010  }
1011  scale_param {
1012    filler {
1013      value: 1
1014    }
1015    bias_term: true
1016    bias_filler {
1017      value: 0
1018    }
1019  }
1020}
1021layer {
1022  name: "relu5_1/dw"
1023  type: "ReLU"
1024  bottom: "conv5_1/dw"
1025  top: "conv5_1/dw"
1026}
1027layer {
1028  name: "conv5_1/sep"
1029  type: "Convolution"
1030  bottom: "conv5_1/dw"
1031  top: "conv5_1/sep"
1032  param {
1033    lr_mult: 1
1034    decay_mult: 1
1035  }
1036  convolution_param {
1037    num_output: 512
1038    bias_term: false
1039    pad: 0
1040    kernel_size: 1
1041    stride: 1
1042    weight_filler {
1043      type: "msra"
1044    }
1045  }
1046}
1047layer {
1048  name: "conv5_1/sep/bn"
1049  type: "BatchNorm"
1050  bottom: "conv5_1/sep"
1051  top: "conv5_1/sep"
1052  param {
1053    lr_mult: 0
1054    decay_mult: 0
1055  }
1056  param {
1057    lr_mult: 0
1058    decay_mult: 0
1059  }
1060  param {
1061    lr_mult: 0
1062    decay_mult: 0
1063  }
1064  batch_norm_param {
1065    use_global_stats: true
1066    eps: 1e-5
1067  }
1068}
1069layer {
1070  name: "conv5_1/sep/scale"
1071  type: "Scale"
1072  bottom: "conv5_1/sep"
1073  top: "conv5_1/sep"
1074  param {
1075    lr_mult: 1
1076    decay_mult: 0
1077  }
1078  param {
1079    lr_mult: 1
1080    decay_mult: 0
1081  }
1082  scale_param {
1083    filler {
1084      value: 1
1085    }
1086    bias_term: true
1087    bias_filler {
1088      value: 0
1089    }
1090  }
1091}
1092layer {
1093  name: "relu5_1/sep"
1094  type: "ReLU"
1095  bottom: "conv5_1/sep"
1096  top: "conv5_1/sep"
1097}
1098layer {
1099  name: "conv5_2/dw"
1100  type: "Convolution"
1101  bottom: "conv5_1/sep"
1102  top: "conv5_2/dw"
1103  param {
1104    lr_mult: 1
1105    decay_mult: 1
1106  }
1107  convolution_param {
1108    num_output: 512
1109    bias_term: false
1110    pad: 1
1111    kernel_size: 3
1112    group: 512
1113    engine: CAFFE
1114    stride: 1
1115    weight_filler {
1116      type: "msra"
1117    }
1118  }
1119}
1120layer {
1121  name: "conv5_2/dw/bn"
1122  type: "BatchNorm"
1123  bottom: "conv5_2/dw"
1124  top: "conv5_2/dw"
1125  param {
1126    lr_mult: 0
1127    decay_mult: 0
1128  }
1129  param {
1130    lr_mult: 0
1131    decay_mult: 0
1132  }
1133  param {
1134    lr_mult: 0
1135    decay_mult: 0
1136  }
1137  batch_norm_param {
1138    use_global_stats: true
1139    eps: 1e-5
1140  }
1141}
1142layer {
1143  name: "conv5_2/dw/scale"
1144  type: "Scale"
1145  bottom: "conv5_2/dw"
1146  top: "conv5_2/dw"
1147  param {
1148    lr_mult: 1
1149    decay_mult: 0
1150  }
1151  param {
1152    lr_mult: 1
1153    decay_mult: 0
1154  }
1155  scale_param {
1156    filler {
1157      value: 1
1158    }
1159    bias_term: true
1160    bias_filler {
1161      value: 0
1162    }
1163  }
1164}
1165layer {
1166  name: "relu5_2/dw"
1167  type: "ReLU"
1168  bottom: "conv5_2/dw"
1169  top: "conv5_2/dw"
1170}
1171layer {
1172  name: "conv5_2/sep"
1173  type: "Convolution"
1174  bottom: "conv5_2/dw"
1175  top: "conv5_2/sep"
1176  param {
1177    lr_mult: 1
1178    decay_mult: 1
1179  }
1180  convolution_param {
1181    num_output: 512
1182    bias_term: false
1183    pad: 0
1184    kernel_size: 1
1185    stride: 1
1186    weight_filler {
1187      type: "msra"
1188    }
1189  }
1190}
1191layer {
1192  name: "conv5_2/sep/bn"
1193  type: "BatchNorm"
1194  bottom: "conv5_2/sep"
1195  top: "conv5_2/sep"
1196  param {
1197    lr_mult: 0
1198    decay_mult: 0
1199  }
1200  param {
1201    lr_mult: 0
1202    decay_mult: 0
1203  }
1204  param {
1205    lr_mult: 0
1206    decay_mult: 0
1207  }
1208  batch_norm_param {
1209    use_global_stats: true
1210    eps: 1e-5
1211  }
1212}
1213layer {
1214  name: "conv5_2/sep/scale"
1215  type: "Scale"
1216  bottom: "conv5_2/sep"
1217  top: "conv5_2/sep"
1218  param {
1219    lr_mult: 1
1220    decay_mult: 0
1221  }
1222  param {
1223    lr_mult: 1
1224    decay_mult: 0
1225  }
1226  scale_param {
1227    filler {
1228      value: 1
1229    }
1230    bias_term: true
1231    bias_filler {
1232      value: 0
1233    }
1234  }
1235}
1236layer {
1237  name: "relu5_2/sep"
1238  type: "ReLU"
1239  bottom: "conv5_2/sep"
1240  top: "conv5_2/sep"
1241}
1242layer {
1243  name: "conv5_3/dw"
1244  type: "Convolution"
1245  bottom: "conv5_2/sep"
1246  top: "conv5_3/dw"
1247  param {
1248    lr_mult: 1
1249    decay_mult: 1
1250  }
1251  convolution_param {
1252    num_output: 512
1253    bias_term: false
1254    pad: 1
1255    kernel_size: 3
1256    group: 512
1257    engine: CAFFE
1258    stride: 1
1259    weight_filler {
1260      type: "msra"
1261    }
1262  }
1263}
1264layer {
1265  name: "conv5_3/dw/bn"
1266  type: "BatchNorm"
1267  bottom: "conv5_3/dw"
1268  top: "conv5_3/dw"
1269  param {
1270    lr_mult: 0
1271    decay_mult: 0
1272  }
1273  param {
1274    lr_mult: 0
1275    decay_mult: 0
1276  }
1277  param {
1278    lr_mult: 0
1279    decay_mult: 0
1280  }
1281  batch_norm_param {
1282    use_global_stats: true
1283    eps: 1e-5
1284  }
1285}
1286layer {
1287  name: "conv5_3/dw/scale"
1288  type: "Scale"
1289  bottom: "conv5_3/dw"
1290  top: "conv5_3/dw"
1291  param {
1292    lr_mult: 1
1293    decay_mult: 0
1294  }
1295  param {
1296    lr_mult: 1
1297    decay_mult: 0
1298  }
1299  scale_param {
1300    filler {
1301      value: 1
1302    }
1303    bias_term: true
1304    bias_filler {
1305      value: 0
1306    }
1307  }
1308}
1309layer {
1310  name: "relu5_3/dw"
1311  type: "ReLU"
1312  bottom: "conv5_3/dw"
1313  top: "conv5_3/dw"
1314}
1315layer {
1316  name: "conv5_3/sep"
1317  type: "Convolution"
1318  bottom: "conv5_3/dw"
1319  top: "conv5_3/sep"
1320  param {
1321    lr_mult: 1
1322    decay_mult: 1
1323  }
1324  convolution_param {
1325    num_output: 512
1326    bias_term: false
1327    pad: 0
1328    kernel_size: 1
1329    stride: 1
1330    weight_filler {
1331      type: "msra"
1332    }
1333  }
1334}
1335layer {
1336  name: "conv5_3/sep/bn"
1337  type: "BatchNorm"
1338  bottom: "conv5_3/sep"
1339  top: "conv5_3/sep"
1340  param {
1341    lr_mult: 0
1342    decay_mult: 0
1343  }
1344  param {
1345    lr_mult: 0
1346    decay_mult: 0
1347  }
1348  param {
1349    lr_mult: 0
1350    decay_mult: 0
1351  }
1352  batch_norm_param {
1353    use_global_stats: true
1354    eps: 1e-5
1355  }
1356}
1357layer {
1358  name: "conv5_3/sep/scale"
1359  type: "Scale"
1360  bottom: "conv5_3/sep"
1361  top: "conv5_3/sep"
1362  param {
1363    lr_mult: 1
1364    decay_mult: 0
1365  }
1366  param {
1367    lr_mult: 1
1368    decay_mult: 0
1369  }
1370  scale_param {
1371    filler {
1372      value: 1
1373    }
1374    bias_term: true
1375    bias_filler {
1376      value: 0
1377    }
1378  }
1379}
1380layer {
1381  name: "relu5_3/sep"
1382  type: "ReLU"
1383  bottom: "conv5_3/sep"
1384  top: "conv5_3/sep"
1385}
1386layer {
1387  name: "conv5_4/dw"
1388  type: "Convolution"
1389  bottom: "conv5_3/sep"
1390  top: "conv5_4/dw"
1391  param {
1392    lr_mult: 1
1393    decay_mult: 1
1394  }
1395  convolution_param {
1396    num_output: 512
1397    bias_term: false
1398    pad: 1
1399    kernel_size: 3
1400    group: 512
1401    engine: CAFFE
1402    stride: 1
1403    weight_filler {
1404      type: "msra"
1405    }
1406  }
1407}
1408layer {
1409  name: "conv5_4/dw/bn"
1410  type: "BatchNorm"
1411  bottom: "conv5_4/dw"
1412  top: "conv5_4/dw"
1413  param {
1414    lr_mult: 0
1415    decay_mult: 0
1416  }
1417  param {
1418    lr_mult: 0
1419    decay_mult: 0
1420  }
1421  param {
1422    lr_mult: 0
1423    decay_mult: 0
1424  }
1425  batch_norm_param {
1426    use_global_stats: true
1427    eps: 1e-5
1428  }
1429}
1430layer {
1431  name: "conv5_4/dw/scale"
1432  type: "Scale"
1433  bottom: "conv5_4/dw"
1434  top: "conv5_4/dw"
1435  param {
1436    lr_mult: 1
1437    decay_mult: 0
1438  }
1439  param {
1440    lr_mult: 1
1441    decay_mult: 0
1442  }
1443  scale_param {
1444    filler {
1445      value: 1
1446    }
1447    bias_term: true
1448    bias_filler {
1449      value: 0
1450    }
1451  }
1452}
1453layer {
1454  name: "relu5_4/dw"
1455  type: "ReLU"
1456  bottom: "conv5_4/dw"
1457  top: "conv5_4/dw"
1458}
1459layer {
1460  name: "conv5_4/sep"
1461  type: "Convolution"
1462  bottom: "conv5_4/dw"
1463  top: "conv5_4/sep"
1464  param {
1465    lr_mult: 1
1466    decay_mult: 1
1467  }
1468  convolution_param {
1469    num_output: 512
1470    bias_term: false
1471    pad: 0
1472    kernel_size: 1
1473    stride: 1
1474    weight_filler {
1475      type: "msra"
1476    }
1477  }
1478}
1479layer {
1480  name: "conv5_4/sep/bn"
1481  type: "BatchNorm"
1482  bottom: "conv5_4/sep"
1483  top: "conv5_4/sep"
1484  param {
1485    lr_mult: 0
1486    decay_mult: 0
1487  }
1488  param {
1489    lr_mult: 0
1490    decay_mult: 0
1491  }
1492  param {
1493    lr_mult: 0
1494    decay_mult: 0
1495  }
1496  batch_norm_param {
1497    use_global_stats: true
1498    eps: 1e-5
1499  }
1500}
1501layer {
1502  name: "conv5_4/sep/scale"
1503  type: "Scale"
1504  bottom: "conv5_4/sep"
1505  top: "conv5_4/sep"
1506  param {
1507    lr_mult: 1
1508    decay_mult: 0
1509  }
1510  param {
1511    lr_mult: 1
1512    decay_mult: 0
1513  }
1514  scale_param {
1515    filler {
1516      value: 1
1517    }
1518    bias_term: true
1519    bias_filler {
1520      value: 0
1521    }
1522  }
1523}
1524layer {
1525  name: "relu5_4/sep"
1526  type: "ReLU"
1527  bottom: "conv5_4/sep"
1528  top: "conv5_4/sep"
1529}
1530layer {
1531  name: "conv5_5/dw"
1532  type: "Convolution"
1533  bottom: "conv5_4/sep"
1534  top: "conv5_5/dw"
1535  param {
1536    lr_mult: 1
1537    decay_mult: 1
1538  }
1539  convolution_param {
1540    num_output: 512
1541    bias_term: false
1542    pad: 1
1543    kernel_size: 3
1544    group: 512
1545    engine: CAFFE
1546    stride: 1
1547    weight_filler {
1548      type: "msra"
1549    }
1550  }
1551}
1552layer {
1553  name: "conv5_5/dw/bn"
1554  type: "BatchNorm"
1555  bottom: "conv5_5/dw"
1556  top: "conv5_5/dw"
1557  param {
1558    lr_mult: 0
1559    decay_mult: 0
1560  }
1561  param {
1562    lr_mult: 0
1563    decay_mult: 0
1564  }
1565  param {
1566    lr_mult: 0
1567    decay_mult: 0
1568  }
1569  batch_norm_param {
1570    use_global_stats: true
1571    eps: 1e-5
1572  }
1573}
1574layer {
1575  name: "conv5_5/dw/scale"
1576  type: "Scale"
1577  bottom: "conv5_5/dw"
1578  top: "conv5_5/dw"
1579  param {
1580    lr_mult: 1
1581    decay_mult: 0
1582  }
1583  param {
1584    lr_mult: 1
1585    decay_mult: 0
1586  }
1587  scale_param {
1588    filler {
1589      value: 1
1590    }
1591    bias_term: true
1592    bias_filler {
1593      value: 0
1594    }
1595  }
1596}
1597layer {
1598  name: "relu5_5/dw"
1599  type: "ReLU"
1600  bottom: "conv5_5/dw"
1601  top: "conv5_5/dw"
1602}
1603layer {
1604  name: "conv5_5/sep"
1605  type: "Convolution"
1606  bottom: "conv5_5/dw"
1607  top: "conv5_5/sep"
1608  param {
1609    lr_mult: 1
1610    decay_mult: 1
1611  }
1612  convolution_param {
1613    num_output: 512
1614    bias_term: false
1615    pad: 0
1616    kernel_size: 1
1617    stride: 1
1618    weight_filler {
1619      type: "msra"
1620    }
1621  }
1622}
1623layer {
1624  name: "conv5_5/sep/bn"
1625  type: "BatchNorm"
1626  bottom: "conv5_5/sep"
1627  top: "conv5_5/sep"
1628  param {
1629    lr_mult: 0
1630    decay_mult: 0
1631  }
1632  param {
1633    lr_mult: 0
1634    decay_mult: 0
1635  }
1636  param {
1637    lr_mult: 0
1638    decay_mult: 0
1639  }
1640  batch_norm_param {
1641    use_global_stats: true
1642    eps: 1e-5
1643  }
1644}
1645layer {
1646  name: "conv5_5/sep/scale"
1647  type: "Scale"
1648  bottom: "conv5_5/sep"
1649  top: "conv5_5/sep"
1650  param {
1651    lr_mult: 1
1652    decay_mult: 0
1653  }
1654  param {
1655    lr_mult: 1
1656    decay_mult: 0
1657  }
1658  scale_param {
1659    filler {
1660      value: 1
1661    }
1662    bias_term: true
1663    bias_filler {
1664      value: 0
1665    }
1666  }
1667}
1668layer {
1669  name: "relu5_5/sep"
1670  type: "ReLU"
1671  bottom: "conv5_5/sep"
1672  top: "conv5_5/sep"
1673}
1674layer {
1675  name: "conv5_6/dw"
1676  type: "Convolution"
1677  bottom: "conv5_5/sep"
1678  top: "conv5_6/dw"
1679  param {
1680    lr_mult: 1
1681    decay_mult: 1
1682  }
1683  convolution_param {
1684    num_output: 512
1685    bias_term: false
1686    pad: 1
1687    kernel_size: 3
1688    group: 512
1689    engine: CAFFE
1690    stride: 2
1691    weight_filler {
1692      type: "msra"
1693    }
1694  }
1695}
1696layer {
1697  name: "conv5_6/dw/bn"
1698  type: "BatchNorm"
1699  bottom: "conv5_6/dw"
1700  top: "conv5_6/dw"
1701  param {
1702    lr_mult: 0
1703    decay_mult: 0
1704  }
1705  param {
1706    lr_mult: 0
1707    decay_mult: 0
1708  }
1709  param {
1710    lr_mult: 0
1711    decay_mult: 0
1712  }
1713  batch_norm_param {
1714    use_global_stats: true
1715    eps: 1e-5
1716  }
1717}
1718layer {
1719  name: "conv5_6/dw/scale"
1720  type: "Scale"
1721  bottom: "conv5_6/dw"
1722  top: "conv5_6/dw"
1723  param {
1724    lr_mult: 1
1725    decay_mult: 0
1726  }
1727  param {
1728    lr_mult: 1
1729    decay_mult: 0
1730  }
1731  scale_param {
1732    filler {
1733      value: 1
1734    }
1735    bias_term: true
1736    bias_filler {
1737      value: 0
1738    }
1739  }
1740}
1741layer {
1742  name: "relu5_6/dw"
1743  type: "ReLU"
1744  bottom: "conv5_6/dw"
1745  top: "conv5_6/dw"
1746}
1747layer {
1748  name: "conv5_6/sep"
1749  type: "Convolution"
1750  bottom: "conv5_6/dw"
1751  top: "conv5_6/sep"
1752  param {
1753    lr_mult: 1
1754    decay_mult: 1
1755  }
1756  convolution_param {
1757    num_output: 1024
1758    bias_term: false
1759    pad: 0
1760    kernel_size: 1
1761    stride: 1
1762    weight_filler {
1763      type: "msra"
1764    }
1765  }
1766}
1767layer {
1768  name: "conv5_6/sep/bn"
1769  type: "BatchNorm"
1770  bottom: "conv5_6/sep"
1771  top: "conv5_6/sep"
1772  param {
1773    lr_mult: 0
1774    decay_mult: 0
1775  }
1776  param {
1777    lr_mult: 0
1778    decay_mult: 0
1779  }
1780  param {
1781    lr_mult: 0
1782    decay_mult: 0
1783  }
1784  batch_norm_param {
1785    use_global_stats: true
1786    eps: 1e-5
1787  }
1788}
1789layer {
1790  name: "conv5_6/sep/scale"
1791  type: "Scale"
1792  bottom: "conv5_6/sep"
1793  top: "conv5_6/sep"
1794  param {
1795    lr_mult: 1
1796    decay_mult: 0
1797  }
1798  param {
1799    lr_mult: 1
1800    decay_mult: 0
1801  }
1802  scale_param {
1803    filler {
1804      value: 1
1805    }
1806    bias_term: true
1807    bias_filler {
1808      value: 0
1809    }
1810  }
1811}
1812layer {
1813  name: "relu5_6/sep"
1814  type: "ReLU"
1815  bottom: "conv5_6/sep"
1816  top: "conv5_6/sep"
1817}
1818layer {
1819  name: "conv6/dw"
1820  type: "Convolution"
1821  bottom: "conv5_6/sep"
1822  top: "conv6/dw"
1823  param {
1824    lr_mult: 1
1825    decay_mult: 1
1826  }
1827  convolution_param {
1828    num_output: 1024
1829    bias_term: false
1830    pad: 1
1831    kernel_size: 3
1832    group: 1024
1833    engine: CAFFE
1834    stride: 1
1835    weight_filler {
1836      type: "msra"
1837    }
1838  }
1839}
1840layer {
1841  name: "conv6/dw/bn"
1842  type: "BatchNorm"
1843  bottom: "conv6/dw"
1844  top: "conv6/dw"
1845  param {
1846    lr_mult: 0
1847    decay_mult: 0
1848  }
1849  param {
1850    lr_mult: 0
1851    decay_mult: 0
1852  }
1853  param {
1854    lr_mult: 0
1855    decay_mult: 0
1856  }
1857  batch_norm_param {
1858    use_global_stats: true
1859    eps: 1e-5
1860  }
1861}
1862layer {
1863  name: "conv6/dw/scale"
1864  type: "Scale"
1865  bottom: "conv6/dw"
1866  top: "conv6/dw"
1867  param {
1868    lr_mult: 1
1869    decay_mult: 0
1870  }
1871  param {
1872    lr_mult: 1
1873    decay_mult: 0
1874  }
1875  scale_param {
1876    filler {
1877      value: 1
1878    }
1879    bias_term: true
1880    bias_filler {
1881      value: 0
1882    }
1883  }
1884}
1885layer {
1886  name: "relu6/dw"
1887  type: "ReLU"
1888  bottom: "conv6/dw"
1889  top: "conv6/dw"
1890}
1891layer {
1892  name: "conv6/sep"
1893  type: "Convolution"
1894  bottom: "conv6/dw"
1895  top: "conv6/sep"
1896  param {
1897    lr_mult: 1
1898    decay_mult: 1
1899  }
1900  convolution_param {
1901    num_output: 1024
1902    bias_term: false
1903    pad: 0
1904    kernel_size: 1
1905    stride: 1
1906    weight_filler {
1907      type: "msra"
1908    }
1909  }
1910}
1911layer {
1912  name: "conv6/sep/bn"
1913  type: "BatchNorm"
1914  bottom: "conv6/sep"
1915  top: "conv6/sep"
1916  param {
1917    lr_mult: 0
1918    decay_mult: 0
1919  }
1920  param {
1921    lr_mult: 0
1922    decay_mult: 0
1923  }
1924  param {
1925    lr_mult: 0
1926    decay_mult: 0
1927  }
1928  batch_norm_param {
1929    use_global_stats: true
1930    eps: 1e-5
1931  }
1932}
1933layer {
1934  name: "conv6/sep/scale"
1935  type: "Scale"
1936  bottom: "conv6/sep"
1937  top: "conv6/sep"
1938  param {
1939    lr_mult: 1
1940    decay_mult: 0
1941  }
1942  param {
1943    lr_mult: 1
1944    decay_mult: 0
1945  }
1946  scale_param {
1947    filler {
1948      value: 1
1949    }
1950    bias_term: true
1951    bias_filler {
1952      value: 0
1953    }
1954  }
1955}
1956layer {
1957  name: "relu6/sep"
1958  type: "ReLU"
1959  bottom: "conv6/sep"
1960  top: "conv6/sep"
1961}
1962layer {
1963  name: "pool6"
1964  type: "Pooling"
1965  bottom: "conv6/sep"
1966  top: "pool6"
1967  pooling_param {
1968    pool: AVE
1969    global_pooling: true
1970  }
1971}
1972layer {
1973  name: "fc7"
1974  type: "Convolution"
1975  bottom: "pool6"
1976  top: "fc7"
1977  param {
1978    lr_mult: 1
1979    decay_mult: 1
1980  }
1981  param {
1982    lr_mult: 2
1983    decay_mult: 0
1984  }
1985  convolution_param {
1986    num_output: 1000
1987    kernel_size: 1
1988    weight_filler {
1989      type: "msra"
1990    }
1991    bias_filler {
1992      type: "constant"
1993      value: 0
1994    }
1995  }
1996}
1997layer {
1998  name: "prob"
1999  type: "Softmax"
2000  bottom: "fc7"
2001  top: "prob"
2002}
2003