xref: /OK3568_Linux_fs/external/rknn-toolkit2/examples/caffe/mobilenet_v2/mobilenet_v2.prototxt (revision 4882a59341e53eb6f0b4789bf948001014eff981) 
1name: "MOBILENET_V2"
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 {
13    shape {
14      dim: 1
15      dim: 3
16      dim: 224
17      dim: 224
18    }
19  }
20}
21layer {
22  name: "conv1"
23  type: "Convolution"
24  bottom: "data"
25  top: "conv1"
26  param {
27    lr_mult: 1
28    decay_mult: 1
29  }
30  convolution_param {
31    num_output: 32
32    bias_term: false
33    pad: 1
34    kernel_size: 3
35    stride: 2
36    weight_filler {
37      type: "msra"
38    }
39  }
40}
41layer {
42  name: "conv1/bn"
43  type: "BatchNorm"
44  bottom: "conv1"
45  top: "conv1/bn"
46  param {
47    lr_mult: 0
48    decay_mult: 0
49  }
50  param {
51    lr_mult: 0
52    decay_mult: 0
53  }
54  param {
55    lr_mult: 0
56    decay_mult: 0
57  }
58  batch_norm_param {
59    use_global_stats: true
60    eps: 1e-5
61  }
62}
63layer {
64  name: "conv1/scale"
65  type: "Scale"
66  bottom: "conv1/bn"
67  top: "conv1/bn"
68  param {
69    lr_mult: 1
70    decay_mult: 0
71  }
72  param {
73    lr_mult: 1
74    decay_mult: 0
75  }
76  scale_param {
77    bias_term: true
78  }
79}
80layer {
81  name: "relu1"
82  type: "ReLU"
83  bottom: "conv1/bn"
84  top: "conv1/bn"
85}
86layer {
87  name: "conv2_1/expand"
88  type: "Convolution"
89  bottom: "conv1/bn"
90  top: "conv2_1/expand"
91  param {
92    lr_mult: 1
93    decay_mult: 1
94  }
95  convolution_param {
96    num_output: 32
97    bias_term: false
98    kernel_size: 1
99    weight_filler {
100      type: "msra"
101    }
102  }
103}
104layer {
105  name: "conv2_1/expand/bn"
106  type: "BatchNorm"
107  bottom: "conv2_1/expand"
108  top: "conv2_1/expand/bn"
109  param {
110    lr_mult: 0
111    decay_mult: 0
112  }
113  param {
114    lr_mult: 0
115    decay_mult: 0
116  }
117  param {
118    lr_mult: 0
119    decay_mult: 0
120  }
121  batch_norm_param {
122    use_global_stats: true
123    eps: 1e-5
124  }
125}
126layer {
127  name: "conv2_1/expand/scale"
128  type: "Scale"
129  bottom: "conv2_1/expand/bn"
130  top: "conv2_1/expand/bn"
131  param {
132    lr_mult: 1
133    decay_mult: 0
134  }
135  param {
136    lr_mult: 1
137    decay_mult: 0
138  }
139  scale_param {
140    bias_term: true
141  }
142}
143layer {
144  name: "relu2_1/expand"
145  type: "ReLU"
146  bottom: "conv2_1/expand/bn"
147  top: "conv2_1/expand/bn"
148}
149layer {
150  name: "conv2_1/dwise"
151  type: "Convolution"
152  bottom: "conv2_1/expand/bn"
153  top: "conv2_1/dwise"
154  param {
155    lr_mult: 1
156    decay_mult: 1
157  }
158  convolution_param {
159    num_output: 32
160    bias_term: false
161    pad: 1
162    kernel_size: 3
163    group: 32
164    weight_filler {
165      type: "msra"
166    }
167    engine: CAFFE
168  }
169}
170layer {
171  name: "conv2_1/dwise/bn"
172  type: "BatchNorm"
173  bottom: "conv2_1/dwise"
174  top: "conv2_1/dwise/bn"
175  param {
176    lr_mult: 0
177    decay_mult: 0
178  }
179  param {
180    lr_mult: 0
181    decay_mult: 0
182  }
183  param {
184    lr_mult: 0
185    decay_mult: 0
186  }
187  batch_norm_param {
188    use_global_stats: true
189    eps: 1e-5
190  }
191}
192layer {
193  name: "conv2_1/dwise/scale"
194  type: "Scale"
195  bottom: "conv2_1/dwise/bn"
196  top: "conv2_1/dwise/bn"
197  param {
198    lr_mult: 1
199    decay_mult: 0
200  }
201  param {
202    lr_mult: 1
203    decay_mult: 0
204  }
205  scale_param {
206    bias_term: true
207  }
208}
209layer {
210  name: "relu2_1/dwise"
211  type: "ReLU"
212  bottom: "conv2_1/dwise/bn"
213  top: "conv2_1/dwise/bn"
214}
215layer {
216  name: "conv2_1/linear"
217  type: "Convolution"
218  bottom: "conv2_1/dwise/bn"
219  top: "conv2_1/linear"
220  param {
221    lr_mult: 1
222    decay_mult: 1
223  }
224  convolution_param {
225    num_output: 16
226    bias_term: false
227    kernel_size: 1
228    weight_filler {
229      type: "msra"
230    }
231  }
232}
233layer {
234  name: "conv2_1/linear/bn"
235  type: "BatchNorm"
236  bottom: "conv2_1/linear"
237  top: "conv2_1/linear/bn"
238  param {
239    lr_mult: 0
240    decay_mult: 0
241  }
242  param {
243    lr_mult: 0
244    decay_mult: 0
245  }
246  param {
247    lr_mult: 0
248    decay_mult: 0
249  }
250  batch_norm_param {
251    use_global_stats: true
252    eps: 1e-5
253  }
254}
255layer {
256  name: "conv2_1/linear/scale"
257  type: "Scale"
258  bottom: "conv2_1/linear/bn"
259  top: "conv2_1/linear/bn"
260  param {
261    lr_mult: 1
262    decay_mult: 0
263  }
264  param {
265    lr_mult: 1
266    decay_mult: 0
267  }
268  scale_param {
269    bias_term: true
270  }
271}
272layer {
273  name: "conv2_2/expand"
274  type: "Convolution"
275  bottom: "conv2_1/linear/bn"
276  top: "conv2_2/expand"
277  param {
278    lr_mult: 1
279    decay_mult: 1
280  }
281  convolution_param {
282    num_output: 96
283    bias_term: false
284    kernel_size: 1
285    weight_filler {
286      type: "msra"
287    }
288  }
289}
290layer {
291  name: "conv2_2/expand/bn"
292  type: "BatchNorm"
293  bottom: "conv2_2/expand"
294  top: "conv2_2/expand/bn"
295  param {
296    lr_mult: 0
297    decay_mult: 0
298  }
299  param {
300    lr_mult: 0
301    decay_mult: 0
302  }
303  param {
304    lr_mult: 0
305    decay_mult: 0
306  }
307  batch_norm_param {
308    use_global_stats: true
309    eps: 1e-5
310  }
311}
312layer {
313  name: "conv2_2/expand/scale"
314  type: "Scale"
315  bottom: "conv2_2/expand/bn"
316  top: "conv2_2/expand/bn"
317  param {
318    lr_mult: 1
319    decay_mult: 0
320  }
321  param {
322    lr_mult: 1
323    decay_mult: 0
324  }
325  scale_param {
326    bias_term: true
327  }
328}
329layer {
330  name: "relu2_2/expand"
331  type: "ReLU"
332  bottom: "conv2_2/expand/bn"
333  top: "conv2_2/expand/bn"
334}
335layer {
336  name: "conv2_2/dwise"
337  type: "Convolution"
338  bottom: "conv2_2/expand/bn"
339  top: "conv2_2/dwise"
340  param {
341    lr_mult: 1
342    decay_mult: 1
343  }
344  convolution_param {
345    num_output: 96
346    bias_term: false
347    pad: 1
348    kernel_size: 3
349    group: 96
350    stride: 2
351    weight_filler {
352      type: "msra"
353    }
354    engine: CAFFE
355  }
356}
357layer {
358  name: "conv2_2/dwise/bn"
359  type: "BatchNorm"
360  bottom: "conv2_2/dwise"
361  top: "conv2_2/dwise/bn"
362  param {
363    lr_mult: 0
364    decay_mult: 0
365  }
366  param {
367    lr_mult: 0
368    decay_mult: 0
369  }
370  param {
371    lr_mult: 0
372    decay_mult: 0
373  }
374  batch_norm_param {
375    use_global_stats: true
376    eps: 1e-5
377  }
378}
379layer {
380  name: "conv2_2/dwise/scale"
381  type: "Scale"
382  bottom: "conv2_2/dwise/bn"
383  top: "conv2_2/dwise/bn"
384  param {
385    lr_mult: 1
386    decay_mult: 0
387  }
388  param {
389    lr_mult: 1
390    decay_mult: 0
391  }
392  scale_param {
393    bias_term: true
394  }
395}
396layer {
397  name: "relu2_2/dwise"
398  type: "ReLU"
399  bottom: "conv2_2/dwise/bn"
400  top: "conv2_2/dwise/bn"
401}
402layer {
403  name: "conv2_2/linear"
404  type: "Convolution"
405  bottom: "conv2_2/dwise/bn"
406  top: "conv2_2/linear"
407  param {
408    lr_mult: 1
409    decay_mult: 1
410  }
411  convolution_param {
412    num_output: 24
413    bias_term: false
414    kernel_size: 1
415    weight_filler {
416      type: "msra"
417    }
418  }
419}
420layer {
421  name: "conv2_2/linear/bn"
422  type: "BatchNorm"
423  bottom: "conv2_2/linear"
424  top: "conv2_2/linear/bn"
425  param {
426    lr_mult: 0
427    decay_mult: 0
428  }
429  param {
430    lr_mult: 0
431    decay_mult: 0
432  }
433  param {
434    lr_mult: 0
435    decay_mult: 0
436  }
437  batch_norm_param {
438    use_global_stats: true
439    eps: 1e-5
440  }
441}
442layer {
443  name: "conv2_2/linear/scale"
444  type: "Scale"
445  bottom: "conv2_2/linear/bn"
446  top: "conv2_2/linear/bn"
447  param {
448    lr_mult: 1
449    decay_mult: 0
450  }
451  param {
452    lr_mult: 1
453    decay_mult: 0
454  }
455  scale_param {
456    bias_term: true
457  }
458}
459layer {
460  name: "conv3_1/expand"
461  type: "Convolution"
462  bottom: "conv2_2/linear/bn"
463  top: "conv3_1/expand"
464  param {
465    lr_mult: 1
466    decay_mult: 1
467  }
468  convolution_param {
469    num_output: 144
470    bias_term: false
471    kernel_size: 1
472    weight_filler {
473      type: "msra"
474    }
475  }
476}
477layer {
478  name: "conv3_1/expand/bn"
479  type: "BatchNorm"
480  bottom: "conv3_1/expand"
481  top: "conv3_1/expand/bn"
482  param {
483    lr_mult: 0
484    decay_mult: 0
485  }
486  param {
487    lr_mult: 0
488    decay_mult: 0
489  }
490  param {
491    lr_mult: 0
492    decay_mult: 0
493  }
494  batch_norm_param {
495    use_global_stats: true
496    eps: 1e-5
497  }
498}
499layer {
500  name: "conv3_1/expand/scale"
501  type: "Scale"
502  bottom: "conv3_1/expand/bn"
503  top: "conv3_1/expand/bn"
504  param {
505    lr_mult: 1
506    decay_mult: 0
507  }
508  param {
509    lr_mult: 1
510    decay_mult: 0
511  }
512  scale_param {
513    bias_term: true
514  }
515}
516layer {
517  name: "relu3_1/expand"
518  type: "ReLU"
519  bottom: "conv3_1/expand/bn"
520  top: "conv3_1/expand/bn"
521}
522layer {
523  name: "conv3_1/dwise"
524  type: "Convolution"
525  bottom: "conv3_1/expand/bn"
526  top: "conv3_1/dwise"
527  param {
528    lr_mult: 1
529    decay_mult: 1
530  }
531  convolution_param {
532    num_output: 144
533    bias_term: false
534    pad: 1
535    kernel_size: 3
536    group: 144
537    weight_filler {
538      type: "msra"
539    }
540    engine: CAFFE
541  }
542}
543layer {
544  name: "conv3_1/dwise/bn"
545  type: "BatchNorm"
546  bottom: "conv3_1/dwise"
547  top: "conv3_1/dwise/bn"
548  param {
549    lr_mult: 0
550    decay_mult: 0
551  }
552  param {
553    lr_mult: 0
554    decay_mult: 0
555  }
556  param {
557    lr_mult: 0
558    decay_mult: 0
559  }
560  batch_norm_param {
561    use_global_stats: true
562    eps: 1e-5
563  }
564}
565layer {
566  name: "conv3_1/dwise/scale"
567  type: "Scale"
568  bottom: "conv3_1/dwise/bn"
569  top: "conv3_1/dwise/bn"
570  param {
571    lr_mult: 1
572    decay_mult: 0
573  }
574  param {
575    lr_mult: 1
576    decay_mult: 0
577  }
578  scale_param {
579    bias_term: true
580  }
581}
582layer {
583  name: "relu3_1/dwise"
584  type: "ReLU"
585  bottom: "conv3_1/dwise/bn"
586  top: "conv3_1/dwise/bn"
587}
588layer {
589  name: "conv3_1/linear"
590  type: "Convolution"
591  bottom: "conv3_1/dwise/bn"
592  top: "conv3_1/linear"
593  param {
594    lr_mult: 1
595    decay_mult: 1
596  }
597  convolution_param {
598    num_output: 24
599    bias_term: false
600    kernel_size: 1
601    weight_filler {
602      type: "msra"
603    }
604  }
605}
606layer {
607  name: "conv3_1/linear/bn"
608  type: "BatchNorm"
609  bottom: "conv3_1/linear"
610  top: "conv3_1/linear/bn"
611  param {
612    lr_mult: 0
613    decay_mult: 0
614  }
615  param {
616    lr_mult: 0
617    decay_mult: 0
618  }
619  param {
620    lr_mult: 0
621    decay_mult: 0
622  }
623  batch_norm_param {
624    use_global_stats: true
625    eps: 1e-5
626  }
627}
628layer {
629  name: "conv3_1/linear/scale"
630  type: "Scale"
631  bottom: "conv3_1/linear/bn"
632  top: "conv3_1/linear/bn"
633  param {
634    lr_mult: 1
635    decay_mult: 0
636  }
637  param {
638    lr_mult: 1
639    decay_mult: 0
640  }
641  scale_param {
642    bias_term: true
643  }
644}
645layer {
646  name: "block_3_1"
647  type: "Eltwise"
648  bottom: "conv2_2/linear/bn"
649  bottom: "conv3_1/linear/bn"
650  top: "block_3_1"
651}
652layer {
653  name: "conv3_2/expand"
654  type: "Convolution"
655  bottom: "block_3_1"
656  top: "conv3_2/expand"
657  param {
658    lr_mult: 1
659    decay_mult: 1
660  }
661  convolution_param {
662    num_output: 144
663    bias_term: false
664    kernel_size: 1
665    weight_filler {
666      type: "msra"
667    }
668  }
669}
670layer {
671  name: "conv3_2/expand/bn"
672  type: "BatchNorm"
673  bottom: "conv3_2/expand"
674  top: "conv3_2/expand/bn"
675  param {
676    lr_mult: 0
677    decay_mult: 0
678  }
679  param {
680    lr_mult: 0
681    decay_mult: 0
682  }
683  param {
684    lr_mult: 0
685    decay_mult: 0
686  }
687  batch_norm_param {
688    use_global_stats: true
689    eps: 1e-5
690  }
691}
692layer {
693  name: "conv3_2/expand/scale"
694  type: "Scale"
695  bottom: "conv3_2/expand/bn"
696  top: "conv3_2/expand/bn"
697  param {
698    lr_mult: 1
699    decay_mult: 0
700  }
701  param {
702    lr_mult: 1
703    decay_mult: 0
704  }
705  scale_param {
706    bias_term: true
707  }
708}
709layer {
710  name: "relu3_2/expand"
711  type: "ReLU"
712  bottom: "conv3_2/expand/bn"
713  top: "conv3_2/expand/bn"
714}
715layer {
716  name: "conv3_2/dwise"
717  type: "Convolution"
718  bottom: "conv3_2/expand/bn"
719  top: "conv3_2/dwise"
720  param {
721    lr_mult: 1
722    decay_mult: 1
723  }
724  convolution_param {
725    num_output: 144
726    bias_term: false
727    pad: 1
728    kernel_size: 3
729    group: 144
730    stride: 2
731    weight_filler {
732      type: "msra"
733    }
734    engine: CAFFE
735  }
736}
737layer {
738  name: "conv3_2/dwise/bn"
739  type: "BatchNorm"
740  bottom: "conv3_2/dwise"
741  top: "conv3_2/dwise/bn"
742  param {
743    lr_mult: 0
744    decay_mult: 0
745  }
746  param {
747    lr_mult: 0
748    decay_mult: 0
749  }
750  param {
751    lr_mult: 0
752    decay_mult: 0
753  }
754  batch_norm_param {
755    use_global_stats: true
756    eps: 1e-5
757  }
758}
759layer {
760  name: "conv3_2/dwise/scale"
761  type: "Scale"
762  bottom: "conv3_2/dwise/bn"
763  top: "conv3_2/dwise/bn"
764  param {
765    lr_mult: 1
766    decay_mult: 0
767  }
768  param {
769    lr_mult: 1
770    decay_mult: 0
771  }
772  scale_param {
773    bias_term: true
774  }
775}
776layer {
777  name: "relu3_2/dwise"
778  type: "ReLU"
779  bottom: "conv3_2/dwise/bn"
780  top: "conv3_2/dwise/bn"
781}
782layer {
783  name: "conv3_2/linear"
784  type: "Convolution"
785  bottom: "conv3_2/dwise/bn"
786  top: "conv3_2/linear"
787  param {
788    lr_mult: 1
789    decay_mult: 1
790  }
791  convolution_param {
792    num_output: 32
793    bias_term: false
794    kernel_size: 1
795    weight_filler {
796      type: "msra"
797    }
798  }
799}
800layer {
801  name: "conv3_2/linear/bn"
802  type: "BatchNorm"
803  bottom: "conv3_2/linear"
804  top: "conv3_2/linear/bn"
805  param {
806    lr_mult: 0
807    decay_mult: 0
808  }
809  param {
810    lr_mult: 0
811    decay_mult: 0
812  }
813  param {
814    lr_mult: 0
815    decay_mult: 0
816  }
817  batch_norm_param {
818    use_global_stats: true
819    eps: 1e-5
820  }
821}
822layer {
823  name: "conv3_2/linear/scale"
824  type: "Scale"
825  bottom: "conv3_2/linear/bn"
826  top: "conv3_2/linear/bn"
827  param {
828    lr_mult: 1
829    decay_mult: 0
830  }
831  param {
832    lr_mult: 1
833    decay_mult: 0
834  }
835  scale_param {
836    bias_term: true
837  }
838}
839layer {
840  name: "conv4_1/expand"
841  type: "Convolution"
842  bottom: "conv3_2/linear/bn"
843  top: "conv4_1/expand"
844  param {
845    lr_mult: 1
846    decay_mult: 1
847  }
848  convolution_param {
849    num_output: 192
850    bias_term: false
851    kernel_size: 1
852    weight_filler {
853      type: "msra"
854    }
855  }
856}
857layer {
858  name: "conv4_1/expand/bn"
859  type: "BatchNorm"
860  bottom: "conv4_1/expand"
861  top: "conv4_1/expand/bn"
862  param {
863    lr_mult: 0
864    decay_mult: 0
865  }
866  param {
867    lr_mult: 0
868    decay_mult: 0
869  }
870  param {
871    lr_mult: 0
872    decay_mult: 0
873  }
874  batch_norm_param {
875    use_global_stats: true
876    eps: 1e-5
877  }
878}
879layer {
880  name: "conv4_1/expand/scale"
881  type: "Scale"
882  bottom: "conv4_1/expand/bn"
883  top: "conv4_1/expand/bn"
884  param {
885    lr_mult: 1
886    decay_mult: 0
887  }
888  param {
889    lr_mult: 1
890    decay_mult: 0
891  }
892  scale_param {
893    bias_term: true
894  }
895}
896layer {
897  name: "relu4_1/expand"
898  type: "ReLU"
899  bottom: "conv4_1/expand/bn"
900  top: "conv4_1/expand/bn"
901}
902layer {
903  name: "conv4_1/dwise"
904  type: "Convolution"
905  bottom: "conv4_1/expand/bn"
906  top: "conv4_1/dwise"
907  param {
908    lr_mult: 1
909    decay_mult: 1
910  }
911  convolution_param {
912    num_output: 192
913    bias_term: false
914    pad: 1
915    kernel_size: 3
916    group: 192
917    weight_filler {
918      type: "msra"
919    }
920    engine: CAFFE
921  }
922}
923layer {
924  name: "conv4_1/dwise/bn"
925  type: "BatchNorm"
926  bottom: "conv4_1/dwise"
927  top: "conv4_1/dwise/bn"
928  param {
929    lr_mult: 0
930    decay_mult: 0
931  }
932  param {
933    lr_mult: 0
934    decay_mult: 0
935  }
936  param {
937    lr_mult: 0
938    decay_mult: 0
939  }
940  batch_norm_param {
941    use_global_stats: true
942    eps: 1e-5
943  }
944}
945layer {
946  name: "conv4_1/dwise/scale"
947  type: "Scale"
948  bottom: "conv4_1/dwise/bn"
949  top: "conv4_1/dwise/bn"
950  param {
951    lr_mult: 1
952    decay_mult: 0
953  }
954  param {
955    lr_mult: 1
956    decay_mult: 0
957  }
958  scale_param {
959    bias_term: true
960  }
961}
962layer {
963  name: "relu4_1/dwise"
964  type: "ReLU"
965  bottom: "conv4_1/dwise/bn"
966  top: "conv4_1/dwise/bn"
967}
968layer {
969  name: "conv4_1/linear"
970  type: "Convolution"
971  bottom: "conv4_1/dwise/bn"
972  top: "conv4_1/linear"
973  param {
974    lr_mult: 1
975    decay_mult: 1
976  }
977  convolution_param {
978    num_output: 32
979    bias_term: false
980    kernel_size: 1
981    weight_filler {
982      type: "msra"
983    }
984  }
985}
986layer {
987  name: "conv4_1/linear/bn"
988  type: "BatchNorm"
989  bottom: "conv4_1/linear"
990  top: "conv4_1/linear/bn"
991  param {
992    lr_mult: 0
993    decay_mult: 0
994  }
995  param {
996    lr_mult: 0
997    decay_mult: 0
998  }
999  param {
1000    lr_mult: 0
1001    decay_mult: 0
1002  }
1003  batch_norm_param {
1004    use_global_stats: true
1005    eps: 1e-5
1006  }
1007}
1008layer {
1009  name: "conv4_1/linear/scale"
1010  type: "Scale"
1011  bottom: "conv4_1/linear/bn"
1012  top: "conv4_1/linear/bn"
1013  param {
1014    lr_mult: 1
1015    decay_mult: 0
1016  }
1017  param {
1018    lr_mult: 1
1019    decay_mult: 0
1020  }
1021  scale_param {
1022    bias_term: true
1023  }
1024}
1025layer {
1026  name: "block_4_1"
1027  type: "Eltwise"
1028  bottom: "conv3_2/linear/bn"
1029  bottom: "conv4_1/linear/bn"
1030  top: "block_4_1"
1031}
1032layer {
1033  name: "conv4_2/expand"
1034  type: "Convolution"
1035  bottom: "block_4_1"
1036  top: "conv4_2/expand"
1037  param {
1038    lr_mult: 1
1039    decay_mult: 1
1040  }
1041  convolution_param {
1042    num_output: 192
1043    bias_term: false
1044    kernel_size: 1
1045    weight_filler {
1046      type: "msra"
1047    }
1048  }
1049}
1050layer {
1051  name: "conv4_2/expand/bn"
1052  type: "BatchNorm"
1053  bottom: "conv4_2/expand"
1054  top: "conv4_2/expand/bn"
1055  param {
1056    lr_mult: 0
1057    decay_mult: 0
1058  }
1059  param {
1060    lr_mult: 0
1061    decay_mult: 0
1062  }
1063  param {
1064    lr_mult: 0
1065    decay_mult: 0
1066  }
1067  batch_norm_param {
1068    use_global_stats: true
1069    eps: 1e-5
1070  }
1071}
1072layer {
1073  name: "conv4_2/expand/scale"
1074  type: "Scale"
1075  bottom: "conv4_2/expand/bn"
1076  top: "conv4_2/expand/bn"
1077  param {
1078    lr_mult: 1
1079    decay_mult: 0
1080  }
1081  param {
1082    lr_mult: 1
1083    decay_mult: 0
1084  }
1085  scale_param {
1086    bias_term: true
1087  }
1088}
1089layer {
1090  name: "relu4_2/expand"
1091  type: "ReLU"
1092  bottom: "conv4_2/expand/bn"
1093  top: "conv4_2/expand/bn"
1094}
1095layer {
1096  name: "conv4_2/dwise"
1097  type: "Convolution"
1098  bottom: "conv4_2/expand/bn"
1099  top: "conv4_2/dwise"
1100  param {
1101    lr_mult: 1
1102    decay_mult: 1
1103  }
1104  convolution_param {
1105    num_output: 192
1106    bias_term: false
1107    pad: 1
1108    kernel_size: 3
1109    group: 192
1110    weight_filler {
1111      type: "msra"
1112    }
1113    engine: CAFFE
1114  }
1115}
1116layer {
1117  name: "conv4_2/dwise/bn"
1118  type: "BatchNorm"
1119  bottom: "conv4_2/dwise"
1120  top: "conv4_2/dwise/bn"
1121  param {
1122    lr_mult: 0
1123    decay_mult: 0
1124  }
1125  param {
1126    lr_mult: 0
1127    decay_mult: 0
1128  }
1129  param {
1130    lr_mult: 0
1131    decay_mult: 0
1132  }
1133  batch_norm_param {
1134    use_global_stats: true
1135    eps: 1e-5
1136  }
1137}
1138layer {
1139  name: "conv4_2/dwise/scale"
1140  type: "Scale"
1141  bottom: "conv4_2/dwise/bn"
1142  top: "conv4_2/dwise/bn"
1143  param {
1144    lr_mult: 1
1145    decay_mult: 0
1146  }
1147  param {
1148    lr_mult: 1
1149    decay_mult: 0
1150  }
1151  scale_param {
1152    bias_term: true
1153  }
1154}
1155layer {
1156  name: "relu4_2/dwise"
1157  type: "ReLU"
1158  bottom: "conv4_2/dwise/bn"
1159  top: "conv4_2/dwise/bn"
1160}
1161layer {
1162  name: "conv4_2/linear"
1163  type: "Convolution"
1164  bottom: "conv4_2/dwise/bn"
1165  top: "conv4_2/linear"
1166  param {
1167    lr_mult: 1
1168    decay_mult: 1
1169  }
1170  convolution_param {
1171    num_output: 32
1172    bias_term: false
1173    kernel_size: 1
1174    weight_filler {
1175      type: "msra"
1176    }
1177  }
1178}
1179layer {
1180  name: "conv4_2/linear/bn"
1181  type: "BatchNorm"
1182  bottom: "conv4_2/linear"
1183  top: "conv4_2/linear/bn"
1184  param {
1185    lr_mult: 0
1186    decay_mult: 0
1187  }
1188  param {
1189    lr_mult: 0
1190    decay_mult: 0
1191  }
1192  param {
1193    lr_mult: 0
1194    decay_mult: 0
1195  }
1196  batch_norm_param {
1197    use_global_stats: true
1198    eps: 1e-5
1199  }
1200}
1201layer {
1202  name: "conv4_2/linear/scale"
1203  type: "Scale"
1204  bottom: "conv4_2/linear/bn"
1205  top: "conv4_2/linear/bn"
1206  param {
1207    lr_mult: 1
1208    decay_mult: 0
1209  }
1210  param {
1211    lr_mult: 1
1212    decay_mult: 0
1213  }
1214  scale_param {
1215    bias_term: true
1216  }
1217}
1218layer {
1219  name: "block_4_2"
1220  type: "Eltwise"
1221  bottom: "block_4_1"
1222  bottom: "conv4_2/linear/bn"
1223  top: "block_4_2"
1224}
1225layer {
1226  name: "conv4_3/expand"
1227  type: "Convolution"
1228  bottom: "block_4_2"
1229  top: "conv4_3/expand"
1230  param {
1231    lr_mult: 1
1232    decay_mult: 1
1233  }
1234  convolution_param {
1235    num_output: 192
1236    bias_term: false
1237    kernel_size: 1
1238    weight_filler {
1239      type: "msra"
1240    }
1241  }
1242}
1243layer {
1244  name: "conv4_3/expand/bn"
1245  type: "BatchNorm"
1246  bottom: "conv4_3/expand"
1247  top: "conv4_3/expand/bn"
1248  param {
1249    lr_mult: 0
1250    decay_mult: 0
1251  }
1252  param {
1253    lr_mult: 0
1254    decay_mult: 0
1255  }
1256  param {
1257    lr_mult: 0
1258    decay_mult: 0
1259  }
1260  batch_norm_param {
1261    use_global_stats: true
1262    eps: 1e-5
1263  }
1264}
1265layer {
1266  name: "conv4_3/expand/scale"
1267  type: "Scale"
1268  bottom: "conv4_3/expand/bn"
1269  top: "conv4_3/expand/bn"
1270  param {
1271    lr_mult: 1
1272    decay_mult: 0
1273  }
1274  param {
1275    lr_mult: 1
1276    decay_mult: 0
1277  }
1278  scale_param {
1279    bias_term: true
1280  }
1281}
1282layer {
1283  name: "relu4_3/expand"
1284  type: "ReLU"
1285  bottom: "conv4_3/expand/bn"
1286  top: "conv4_3/expand/bn"
1287}
1288layer {
1289  name: "conv4_3/dwise"
1290  type: "Convolution"
1291  bottom: "conv4_3/expand/bn"
1292  top: "conv4_3/dwise"
1293  param {
1294    lr_mult: 1
1295    decay_mult: 1
1296  }
1297  convolution_param {
1298    num_output: 192
1299    bias_term: false
1300    pad: 1
1301    kernel_size: 3
1302    group: 192
1303    weight_filler {
1304      type: "msra"
1305    }
1306    engine: CAFFE
1307  }
1308}
1309layer {
1310  name: "conv4_3/dwise/bn"
1311  type: "BatchNorm"
1312  bottom: "conv4_3/dwise"
1313  top: "conv4_3/dwise/bn"
1314  param {
1315    lr_mult: 0
1316    decay_mult: 0
1317  }
1318  param {
1319    lr_mult: 0
1320    decay_mult: 0
1321  }
1322  param {
1323    lr_mult: 0
1324    decay_mult: 0
1325  }
1326  batch_norm_param {
1327    use_global_stats: true
1328    eps: 1e-5
1329  }
1330}
1331layer {
1332  name: "conv4_3/dwise/scale"
1333  type: "Scale"
1334  bottom: "conv4_3/dwise/bn"
1335  top: "conv4_3/dwise/bn"
1336  param {
1337    lr_mult: 1
1338    decay_mult: 0
1339  }
1340  param {
1341    lr_mult: 1
1342    decay_mult: 0
1343  }
1344  scale_param {
1345    bias_term: true
1346  }
1347}
1348layer {
1349  name: "relu4_3/dwise"
1350  type: "ReLU"
1351  bottom: "conv4_3/dwise/bn"
1352  top: "conv4_3/dwise/bn"
1353}
1354layer {
1355  name: "conv4_3/linear"
1356  type: "Convolution"
1357  bottom: "conv4_3/dwise/bn"
1358  top: "conv4_3/linear"
1359  param {
1360    lr_mult: 1
1361    decay_mult: 1
1362  }
1363  convolution_param {
1364    num_output: 64
1365    bias_term: false
1366    kernel_size: 1
1367    weight_filler {
1368      type: "msra"
1369    }
1370  }
1371}
1372layer {
1373  name: "conv4_3/linear/bn"
1374  type: "BatchNorm"
1375  bottom: "conv4_3/linear"
1376  top: "conv4_3/linear/bn"
1377  param {
1378    lr_mult: 0
1379    decay_mult: 0
1380  }
1381  param {
1382    lr_mult: 0
1383    decay_mult: 0
1384  }
1385  param {
1386    lr_mult: 0
1387    decay_mult: 0
1388  }
1389  batch_norm_param {
1390    use_global_stats: true
1391    eps: 1e-5
1392  }
1393}
1394layer {
1395  name: "conv4_3/linear/scale"
1396  type: "Scale"
1397  bottom: "conv4_3/linear/bn"
1398  top: "conv4_3/linear/bn"
1399  param {
1400    lr_mult: 1
1401    decay_mult: 0
1402  }
1403  param {
1404    lr_mult: 1
1405    decay_mult: 0
1406  }
1407  scale_param {
1408    bias_term: true
1409  }
1410}
1411layer {
1412  name: "conv4_4/expand"
1413  type: "Convolution"
1414  bottom: "conv4_3/linear/bn"
1415  top: "conv4_4/expand"
1416  param {
1417    lr_mult: 1
1418    decay_mult: 1
1419  }
1420  convolution_param {
1421    num_output: 384
1422    bias_term: false
1423    kernel_size: 1
1424    weight_filler {
1425      type: "msra"
1426    }
1427  }
1428}
1429layer {
1430  name: "conv4_4/expand/bn"
1431  type: "BatchNorm"
1432  bottom: "conv4_4/expand"
1433  top: "conv4_4/expand/bn"
1434  param {
1435    lr_mult: 0
1436    decay_mult: 0
1437  }
1438  param {
1439    lr_mult: 0
1440    decay_mult: 0
1441  }
1442  param {
1443    lr_mult: 0
1444    decay_mult: 0
1445  }
1446  batch_norm_param {
1447    use_global_stats: true
1448    eps: 1e-5
1449  }
1450}
1451layer {
1452  name: "conv4_4/expand/scale"
1453  type: "Scale"
1454  bottom: "conv4_4/expand/bn"
1455  top: "conv4_4/expand/bn"
1456  param {
1457    lr_mult: 1
1458    decay_mult: 0
1459  }
1460  param {
1461    lr_mult: 1
1462    decay_mult: 0
1463  }
1464  scale_param {
1465    bias_term: true
1466  }
1467}
1468layer {
1469  name: "relu4_4/expand"
1470  type: "ReLU"
1471  bottom: "conv4_4/expand/bn"
1472  top: "conv4_4/expand/bn"
1473}
1474layer {
1475  name: "conv4_4/dwise"
1476  type: "Convolution"
1477  bottom: "conv4_4/expand/bn"
1478  top: "conv4_4/dwise"
1479  param {
1480    lr_mult: 1
1481    decay_mult: 1
1482  }
1483  convolution_param {
1484    num_output: 384
1485    bias_term: false
1486    pad: 1
1487    kernel_size: 3
1488    group: 384
1489    weight_filler {
1490      type: "msra"
1491    }
1492    engine: CAFFE
1493  }
1494}
1495layer {
1496  name: "conv4_4/dwise/bn"
1497  type: "BatchNorm"
1498  bottom: "conv4_4/dwise"
1499  top: "conv4_4/dwise/bn"
1500  param {
1501    lr_mult: 0
1502    decay_mult: 0
1503  }
1504  param {
1505    lr_mult: 0
1506    decay_mult: 0
1507  }
1508  param {
1509    lr_mult: 0
1510    decay_mult: 0
1511  }
1512  batch_norm_param {
1513    use_global_stats: true
1514    eps: 1e-5
1515  }
1516}
1517layer {
1518  name: "conv4_4/dwise/scale"
1519  type: "Scale"
1520  bottom: "conv4_4/dwise/bn"
1521  top: "conv4_4/dwise/bn"
1522  param {
1523    lr_mult: 1
1524    decay_mult: 0
1525  }
1526  param {
1527    lr_mult: 1
1528    decay_mult: 0
1529  }
1530  scale_param {
1531    bias_term: true
1532  }
1533}
1534layer {
1535  name: "relu4_4/dwise"
1536  type: "ReLU"
1537  bottom: "conv4_4/dwise/bn"
1538  top: "conv4_4/dwise/bn"
1539}
1540layer {
1541  name: "conv4_4/linear"
1542  type: "Convolution"
1543  bottom: "conv4_4/dwise/bn"
1544  top: "conv4_4/linear"
1545  param {
1546    lr_mult: 1
1547    decay_mult: 1
1548  }
1549  convolution_param {
1550    num_output: 64
1551    bias_term: false
1552    kernel_size: 1
1553    weight_filler {
1554      type: "msra"
1555    }
1556  }
1557}
1558layer {
1559  name: "conv4_4/linear/bn"
1560  type: "BatchNorm"
1561  bottom: "conv4_4/linear"
1562  top: "conv4_4/linear/bn"
1563  param {
1564    lr_mult: 0
1565    decay_mult: 0
1566  }
1567  param {
1568    lr_mult: 0
1569    decay_mult: 0
1570  }
1571  param {
1572    lr_mult: 0
1573    decay_mult: 0
1574  }
1575  batch_norm_param {
1576    use_global_stats: true
1577    eps: 1e-5
1578  }
1579}
1580layer {
1581  name: "conv4_4/linear/scale"
1582  type: "Scale"
1583  bottom: "conv4_4/linear/bn"
1584  top: "conv4_4/linear/bn"
1585  param {
1586    lr_mult: 1
1587    decay_mult: 0
1588  }
1589  param {
1590    lr_mult: 1
1591    decay_mult: 0
1592  }
1593  scale_param {
1594    bias_term: true
1595  }
1596}
1597layer {
1598  name: "block_4_4"
1599  type: "Eltwise"
1600  bottom: "conv4_3/linear/bn"
1601  bottom: "conv4_4/linear/bn"
1602  top: "block_4_4"
1603}
1604layer {
1605  name: "conv4_5/expand"
1606  type: "Convolution"
1607  bottom: "block_4_4"
1608  top: "conv4_5/expand"
1609  param {
1610    lr_mult: 1
1611    decay_mult: 1
1612  }
1613  convolution_param {
1614    num_output: 384
1615    bias_term: false
1616    kernel_size: 1
1617    weight_filler {
1618      type: "msra"
1619    }
1620  }
1621}
1622layer {
1623  name: "conv4_5/expand/bn"
1624  type: "BatchNorm"
1625  bottom: "conv4_5/expand"
1626  top: "conv4_5/expand/bn"
1627  param {
1628    lr_mult: 0
1629    decay_mult: 0
1630  }
1631  param {
1632    lr_mult: 0
1633    decay_mult: 0
1634  }
1635  param {
1636    lr_mult: 0
1637    decay_mult: 0
1638  }
1639  batch_norm_param {
1640    use_global_stats: true
1641    eps: 1e-5
1642  }
1643}
1644layer {
1645  name: "conv4_5/expand/scale"
1646  type: "Scale"
1647  bottom: "conv4_5/expand/bn"
1648  top: "conv4_5/expand/bn"
1649  param {
1650    lr_mult: 1
1651    decay_mult: 0
1652  }
1653  param {
1654    lr_mult: 1
1655    decay_mult: 0
1656  }
1657  scale_param {
1658    bias_term: true
1659  }
1660}
1661layer {
1662  name: "relu4_5/expand"
1663  type: "ReLU"
1664  bottom: "conv4_5/expand/bn"
1665  top: "conv4_5/expand/bn"
1666}
1667layer {
1668  name: "conv4_5/dwise"
1669  type: "Convolution"
1670  bottom: "conv4_5/expand/bn"
1671  top: "conv4_5/dwise"
1672  param {
1673    lr_mult: 1
1674    decay_mult: 1
1675  }
1676  convolution_param {
1677    num_output: 384
1678    bias_term: false
1679    pad: 1
1680    kernel_size: 3
1681    group: 384
1682    weight_filler {
1683      type: "msra"
1684    }
1685    engine: CAFFE
1686  }
1687}
1688layer {
1689  name: "conv4_5/dwise/bn"
1690  type: "BatchNorm"
1691  bottom: "conv4_5/dwise"
1692  top: "conv4_5/dwise/bn"
1693  param {
1694    lr_mult: 0
1695    decay_mult: 0
1696  }
1697  param {
1698    lr_mult: 0
1699    decay_mult: 0
1700  }
1701  param {
1702    lr_mult: 0
1703    decay_mult: 0
1704  }
1705  batch_norm_param {
1706    use_global_stats: true
1707    eps: 1e-5
1708  }
1709}
1710layer {
1711  name: "conv4_5/dwise/scale"
1712  type: "Scale"
1713  bottom: "conv4_5/dwise/bn"
1714  top: "conv4_5/dwise/bn"
1715  param {
1716    lr_mult: 1
1717    decay_mult: 0
1718  }
1719  param {
1720    lr_mult: 1
1721    decay_mult: 0
1722  }
1723  scale_param {
1724    bias_term: true
1725  }
1726}
1727layer {
1728  name: "relu4_5/dwise"
1729  type: "ReLU"
1730  bottom: "conv4_5/dwise/bn"
1731  top: "conv4_5/dwise/bn"
1732}
1733layer {
1734  name: "conv4_5/linear"
1735  type: "Convolution"
1736  bottom: "conv4_5/dwise/bn"
1737  top: "conv4_5/linear"
1738  param {
1739    lr_mult: 1
1740    decay_mult: 1
1741  }
1742  convolution_param {
1743    num_output: 64
1744    bias_term: false
1745    kernel_size: 1
1746    weight_filler {
1747      type: "msra"
1748    }
1749  }
1750}
1751layer {
1752  name: "conv4_5/linear/bn"
1753  type: "BatchNorm"
1754  bottom: "conv4_5/linear"
1755  top: "conv4_5/linear/bn"
1756  param {
1757    lr_mult: 0
1758    decay_mult: 0
1759  }
1760  param {
1761    lr_mult: 0
1762    decay_mult: 0
1763  }
1764  param {
1765    lr_mult: 0
1766    decay_mult: 0
1767  }
1768  batch_norm_param {
1769    use_global_stats: true
1770    eps: 1e-5
1771  }
1772}
1773layer {
1774  name: "conv4_5/linear/scale"
1775  type: "Scale"
1776  bottom: "conv4_5/linear/bn"
1777  top: "conv4_5/linear/bn"
1778  param {
1779    lr_mult: 1
1780    decay_mult: 0
1781  }
1782  param {
1783    lr_mult: 1
1784    decay_mult: 0
1785  }
1786  scale_param {
1787    bias_term: true
1788  }
1789}
1790layer {
1791  name: "block_4_5"
1792  type: "Eltwise"
1793  bottom: "block_4_4"
1794  bottom: "conv4_5/linear/bn"
1795  top: "block_4_5"
1796}
1797layer {
1798  name: "conv4_6/expand"
1799  type: "Convolution"
1800  bottom: "block_4_5"
1801  top: "conv4_6/expand"
1802  param {
1803    lr_mult: 1
1804    decay_mult: 1
1805  }
1806  convolution_param {
1807    num_output: 384
1808    bias_term: false
1809    kernel_size: 1
1810    weight_filler {
1811      type: "msra"
1812    }
1813  }
1814}
1815layer {
1816  name: "conv4_6/expand/bn"
1817  type: "BatchNorm"
1818  bottom: "conv4_6/expand"
1819  top: "conv4_6/expand/bn"
1820  param {
1821    lr_mult: 0
1822    decay_mult: 0
1823  }
1824  param {
1825    lr_mult: 0
1826    decay_mult: 0
1827  }
1828  param {
1829    lr_mult: 0
1830    decay_mult: 0
1831  }
1832  batch_norm_param {
1833    use_global_stats: true
1834    eps: 1e-5
1835  }
1836}
1837layer {
1838  name: "conv4_6/expand/scale"
1839  type: "Scale"
1840  bottom: "conv4_6/expand/bn"
1841  top: "conv4_6/expand/bn"
1842  param {
1843    lr_mult: 1
1844    decay_mult: 0
1845  }
1846  param {
1847    lr_mult: 1
1848    decay_mult: 0
1849  }
1850  scale_param {
1851    bias_term: true
1852  }
1853}
1854layer {
1855  name: "relu4_6/expand"
1856  type: "ReLU"
1857  bottom: "conv4_6/expand/bn"
1858  top: "conv4_6/expand/bn"
1859}
1860layer {
1861  name: "conv4_6/dwise"
1862  type: "Convolution"
1863  bottom: "conv4_6/expand/bn"
1864  top: "conv4_6/dwise"
1865  param {
1866    lr_mult: 1
1867    decay_mult: 1
1868  }
1869  convolution_param {
1870    num_output: 384
1871    bias_term: false
1872    pad: 1
1873    kernel_size: 3
1874    group: 384
1875    weight_filler {
1876      type: "msra"
1877    }
1878    engine: CAFFE
1879  }
1880}
1881layer {
1882  name: "conv4_6/dwise/bn"
1883  type: "BatchNorm"
1884  bottom: "conv4_6/dwise"
1885  top: "conv4_6/dwise/bn"
1886  param {
1887    lr_mult: 0
1888    decay_mult: 0
1889  }
1890  param {
1891    lr_mult: 0
1892    decay_mult: 0
1893  }
1894  param {
1895    lr_mult: 0
1896    decay_mult: 0
1897  }
1898  batch_norm_param {
1899    use_global_stats: true
1900    eps: 1e-5
1901  }
1902}
1903layer {
1904  name: "conv4_6/dwise/scale"
1905  type: "Scale"
1906  bottom: "conv4_6/dwise/bn"
1907  top: "conv4_6/dwise/bn"
1908  param {
1909    lr_mult: 1
1910    decay_mult: 0
1911  }
1912  param {
1913    lr_mult: 1
1914    decay_mult: 0
1915  }
1916  scale_param {
1917    bias_term: true
1918  }
1919}
1920layer {
1921  name: "relu4_6/dwise"
1922  type: "ReLU"
1923  bottom: "conv4_6/dwise/bn"
1924  top: "conv4_6/dwise/bn"
1925}
1926layer {
1927  name: "conv4_6/linear"
1928  type: "Convolution"
1929  bottom: "conv4_6/dwise/bn"
1930  top: "conv4_6/linear"
1931  param {
1932    lr_mult: 1
1933    decay_mult: 1
1934  }
1935  convolution_param {
1936    num_output: 64
1937    bias_term: false
1938    kernel_size: 1
1939    weight_filler {
1940      type: "msra"
1941    }
1942  }
1943}
1944layer {
1945  name: "conv4_6/linear/bn"
1946  type: "BatchNorm"
1947  bottom: "conv4_6/linear"
1948  top: "conv4_6/linear/bn"
1949  param {
1950    lr_mult: 0
1951    decay_mult: 0
1952  }
1953  param {
1954    lr_mult: 0
1955    decay_mult: 0
1956  }
1957  param {
1958    lr_mult: 0
1959    decay_mult: 0
1960  }
1961  batch_norm_param {
1962    use_global_stats: true
1963    eps: 1e-5
1964  }
1965}
1966layer {
1967  name: "conv4_6/linear/scale"
1968  type: "Scale"
1969  bottom: "conv4_6/linear/bn"
1970  top: "conv4_6/linear/bn"
1971  param {
1972    lr_mult: 1
1973    decay_mult: 0
1974  }
1975  param {
1976    lr_mult: 1
1977    decay_mult: 0
1978  }
1979  scale_param {
1980    bias_term: true
1981  }
1982}
1983layer {
1984  name: "block_4_6"
1985  type: "Eltwise"
1986  bottom: "block_4_5"
1987  bottom: "conv4_6/linear/bn"
1988  top: "block_4_6"
1989}
1990layer {
1991  name: "conv4_7/expand"
1992  type: "Convolution"
1993  bottom: "block_4_6"
1994  top: "conv4_7/expand"
1995  param {
1996    lr_mult: 1
1997    decay_mult: 1
1998  }
1999  convolution_param {
2000    num_output: 384
2001    bias_term: false
2002    kernel_size: 1
2003    weight_filler {
2004      type: "msra"
2005    }
2006  }
2007}
2008layer {
2009  name: "conv4_7/expand/bn"
2010  type: "BatchNorm"
2011  bottom: "conv4_7/expand"
2012  top: "conv4_7/expand/bn"
2013  param {
2014    lr_mult: 0
2015    decay_mult: 0
2016  }
2017  param {
2018    lr_mult: 0
2019    decay_mult: 0
2020  }
2021  param {
2022    lr_mult: 0
2023    decay_mult: 0
2024  }
2025  batch_norm_param {
2026    use_global_stats: true
2027    eps: 1e-5
2028  }
2029}
2030layer {
2031  name: "conv4_7/expand/scale"
2032  type: "Scale"
2033  bottom: "conv4_7/expand/bn"
2034  top: "conv4_7/expand/bn"
2035  param {
2036    lr_mult: 1
2037    decay_mult: 0
2038  }
2039  param {
2040    lr_mult: 1
2041    decay_mult: 0
2042  }
2043  scale_param {
2044    bias_term: true
2045  }
2046}
2047layer {
2048  name: "relu4_7/expand"
2049  type: "ReLU"
2050  bottom: "conv4_7/expand/bn"
2051  top: "conv4_7/expand/bn"
2052}
2053layer {
2054  name: "conv4_7/dwise"
2055  type: "Convolution"
2056  bottom: "conv4_7/expand/bn"
2057  top: "conv4_7/dwise"
2058  param {
2059    lr_mult: 1
2060    decay_mult: 1
2061  }
2062  convolution_param {
2063    num_output: 384
2064    bias_term: false
2065    pad: 1
2066    kernel_size: 3
2067    group: 384
2068    stride: 2
2069    weight_filler {
2070      type: "msra"
2071    }
2072    engine: CAFFE
2073  }
2074}
2075layer {
2076  name: "conv4_7/dwise/bn"
2077  type: "BatchNorm"
2078  bottom: "conv4_7/dwise"
2079  top: "conv4_7/dwise/bn"
2080  param {
2081    lr_mult: 0
2082    decay_mult: 0
2083  }
2084  param {
2085    lr_mult: 0
2086    decay_mult: 0
2087  }
2088  param {
2089    lr_mult: 0
2090    decay_mult: 0
2091  }
2092  batch_norm_param {
2093    use_global_stats: true
2094    eps: 1e-5
2095  }
2096}
2097layer {
2098  name: "conv4_7/dwise/scale"
2099  type: "Scale"
2100  bottom: "conv4_7/dwise/bn"
2101  top: "conv4_7/dwise/bn"
2102  param {
2103    lr_mult: 1
2104    decay_mult: 0
2105  }
2106  param {
2107    lr_mult: 1
2108    decay_mult: 0
2109  }
2110  scale_param {
2111    bias_term: true
2112  }
2113}
2114layer {
2115  name: "relu4_7/dwise"
2116  type: "ReLU"
2117  bottom: "conv4_7/dwise/bn"
2118  top: "conv4_7/dwise/bn"
2119}
2120layer {
2121  name: "conv4_7/linear"
2122  type: "Convolution"
2123  bottom: "conv4_7/dwise/bn"
2124  top: "conv4_7/linear"
2125  param {
2126    lr_mult: 1
2127    decay_mult: 1
2128  }
2129  convolution_param {
2130    num_output: 96
2131    bias_term: false
2132    kernel_size: 1
2133    weight_filler {
2134      type: "msra"
2135    }
2136  }
2137}
2138layer {
2139  name: "conv4_7/linear/bn"
2140  type: "BatchNorm"
2141  bottom: "conv4_7/linear"
2142  top: "conv4_7/linear/bn"
2143  param {
2144    lr_mult: 0
2145    decay_mult: 0
2146  }
2147  param {
2148    lr_mult: 0
2149    decay_mult: 0
2150  }
2151  param {
2152    lr_mult: 0
2153    decay_mult: 0
2154  }
2155  batch_norm_param {
2156    use_global_stats: true
2157    eps: 1e-5
2158  }
2159}
2160layer {
2161  name: "conv4_7/linear/scale"
2162  type: "Scale"
2163  bottom: "conv4_7/linear/bn"
2164  top: "conv4_7/linear/bn"
2165  param {
2166    lr_mult: 1
2167    decay_mult: 0
2168  }
2169  param {
2170    lr_mult: 1
2171    decay_mult: 0
2172  }
2173  scale_param {
2174    bias_term: true
2175  }
2176}
2177layer {
2178  name: "conv5_1/expand"
2179  type: "Convolution"
2180  bottom: "conv4_7/linear/bn"
2181  top: "conv5_1/expand"
2182  param {
2183    lr_mult: 1
2184    decay_mult: 1
2185  }
2186  convolution_param {
2187    num_output: 576
2188    bias_term: false
2189    kernel_size: 1
2190    weight_filler {
2191      type: "msra"
2192    }
2193  }
2194}
2195layer {
2196  name: "conv5_1/expand/bn"
2197  type: "BatchNorm"
2198  bottom: "conv5_1/expand"
2199  top: "conv5_1/expand/bn"
2200  param {
2201    lr_mult: 0
2202    decay_mult: 0
2203  }
2204  param {
2205    lr_mult: 0
2206    decay_mult: 0
2207  }
2208  param {
2209    lr_mult: 0
2210    decay_mult: 0
2211  }
2212  batch_norm_param {
2213    use_global_stats: true
2214    eps: 1e-5
2215  }
2216}
2217layer {
2218  name: "conv5_1/expand/scale"
2219  type: "Scale"
2220  bottom: "conv5_1/expand/bn"
2221  top: "conv5_1/expand/bn"
2222  param {
2223    lr_mult: 1
2224    decay_mult: 0
2225  }
2226  param {
2227    lr_mult: 1
2228    decay_mult: 0
2229  }
2230  scale_param {
2231    bias_term: true
2232  }
2233}
2234layer {
2235  name: "relu5_1/expand"
2236  type: "ReLU"
2237  bottom: "conv5_1/expand/bn"
2238  top: "conv5_1/expand/bn"
2239}
2240layer {
2241  name: "conv5_1/dwise"
2242  type: "Convolution"
2243  bottom: "conv5_1/expand/bn"
2244  top: "conv5_1/dwise"
2245  param {
2246    lr_mult: 1
2247    decay_mult: 1
2248  }
2249  convolution_param {
2250    num_output: 576
2251    bias_term: false
2252    pad: 1
2253    kernel_size: 3
2254    group: 576
2255    weight_filler {
2256      type: "msra"
2257    }
2258    engine: CAFFE
2259  }
2260}
2261layer {
2262  name: "conv5_1/dwise/bn"
2263  type: "BatchNorm"
2264  bottom: "conv5_1/dwise"
2265  top: "conv5_1/dwise/bn"
2266  param {
2267    lr_mult: 0
2268    decay_mult: 0
2269  }
2270  param {
2271    lr_mult: 0
2272    decay_mult: 0
2273  }
2274  param {
2275    lr_mult: 0
2276    decay_mult: 0
2277  }
2278  batch_norm_param {
2279    use_global_stats: true
2280    eps: 1e-5
2281  }
2282}
2283layer {
2284  name: "conv5_1/dwise/scale"
2285  type: "Scale"
2286  bottom: "conv5_1/dwise/bn"
2287  top: "conv5_1/dwise/bn"
2288  param {
2289    lr_mult: 1
2290    decay_mult: 0
2291  }
2292  param {
2293    lr_mult: 1
2294    decay_mult: 0
2295  }
2296  scale_param {
2297    bias_term: true
2298  }
2299}
2300layer {
2301  name: "relu5_1/dwise"
2302  type: "ReLU"
2303  bottom: "conv5_1/dwise/bn"
2304  top: "conv5_1/dwise/bn"
2305}
2306layer {
2307  name: "conv5_1/linear"
2308  type: "Convolution"
2309  bottom: "conv5_1/dwise/bn"
2310  top: "conv5_1/linear"
2311  param {
2312    lr_mult: 1
2313    decay_mult: 1
2314  }
2315  convolution_param {
2316    num_output: 96
2317    bias_term: false
2318    kernel_size: 1
2319    weight_filler {
2320      type: "msra"
2321    }
2322  }
2323}
2324layer {
2325  name: "conv5_1/linear/bn"
2326  type: "BatchNorm"
2327  bottom: "conv5_1/linear"
2328  top: "conv5_1/linear/bn"
2329  param {
2330    lr_mult: 0
2331    decay_mult: 0
2332  }
2333  param {
2334    lr_mult: 0
2335    decay_mult: 0
2336  }
2337  param {
2338    lr_mult: 0
2339    decay_mult: 0
2340  }
2341  batch_norm_param {
2342    use_global_stats: true
2343    eps: 1e-5
2344  }
2345}
2346layer {
2347  name: "conv5_1/linear/scale"
2348  type: "Scale"
2349  bottom: "conv5_1/linear/bn"
2350  top: "conv5_1/linear/bn"
2351  param {
2352    lr_mult: 1
2353    decay_mult: 0
2354  }
2355  param {
2356    lr_mult: 1
2357    decay_mult: 0
2358  }
2359  scale_param {
2360    bias_term: true
2361  }
2362}
2363layer {
2364  name: "block_5_1"
2365  type: "Eltwise"
2366  bottom: "conv4_7/linear/bn"
2367  bottom: "conv5_1/linear/bn"
2368  top: "block_5_1"
2369}
2370layer {
2371  name: "conv5_2/expand"
2372  type: "Convolution"
2373  bottom: "block_5_1"
2374  top: "conv5_2/expand"
2375  param {
2376    lr_mult: 1
2377    decay_mult: 1
2378  }
2379  convolution_param {
2380    num_output: 576
2381    bias_term: false
2382    kernel_size: 1
2383    weight_filler {
2384      type: "msra"
2385    }
2386  }
2387}
2388layer {
2389  name: "conv5_2/expand/bn"
2390  type: "BatchNorm"
2391  bottom: "conv5_2/expand"
2392  top: "conv5_2/expand/bn"
2393  param {
2394    lr_mult: 0
2395    decay_mult: 0
2396  }
2397  param {
2398    lr_mult: 0
2399    decay_mult: 0
2400  }
2401  param {
2402    lr_mult: 0
2403    decay_mult: 0
2404  }
2405  batch_norm_param {
2406    use_global_stats: true
2407    eps: 1e-5
2408  }
2409}
2410layer {
2411  name: "conv5_2/expand/scale"
2412  type: "Scale"
2413  bottom: "conv5_2/expand/bn"
2414  top: "conv5_2/expand/bn"
2415  param {
2416    lr_mult: 1
2417    decay_mult: 0
2418  }
2419  param {
2420    lr_mult: 1
2421    decay_mult: 0
2422  }
2423  scale_param {
2424    bias_term: true
2425  }
2426}
2427layer {
2428  name: "relu5_2/expand"
2429  type: "ReLU"
2430  bottom: "conv5_2/expand/bn"
2431  top: "conv5_2/expand/bn"
2432}
2433layer {
2434  name: "conv5_2/dwise"
2435  type: "Convolution"
2436  bottom: "conv5_2/expand/bn"
2437  top: "conv5_2/dwise"
2438  param {
2439    lr_mult: 1
2440    decay_mult: 1
2441  }
2442  convolution_param {
2443    num_output: 576
2444    bias_term: false
2445    pad: 1
2446    kernel_size: 3
2447    group: 576
2448    weight_filler {
2449      type: "msra"
2450    }
2451    engine: CAFFE
2452  }
2453}
2454layer {
2455  name: "conv5_2/dwise/bn"
2456  type: "BatchNorm"
2457  bottom: "conv5_2/dwise"
2458  top: "conv5_2/dwise/bn"
2459  param {
2460    lr_mult: 0
2461    decay_mult: 0
2462  }
2463  param {
2464    lr_mult: 0
2465    decay_mult: 0
2466  }
2467  param {
2468    lr_mult: 0
2469    decay_mult: 0
2470  }
2471  batch_norm_param {
2472    use_global_stats: true
2473    eps: 1e-5
2474  }
2475}
2476layer {
2477  name: "conv5_2/dwise/scale"
2478  type: "Scale"
2479  bottom: "conv5_2/dwise/bn"
2480  top: "conv5_2/dwise/bn"
2481  param {
2482    lr_mult: 1
2483    decay_mult: 0
2484  }
2485  param {
2486    lr_mult: 1
2487    decay_mult: 0
2488  }
2489  scale_param {
2490    bias_term: true
2491  }
2492}
2493layer {
2494  name: "relu5_2/dwise"
2495  type: "ReLU"
2496  bottom: "conv5_2/dwise/bn"
2497  top: "conv5_2/dwise/bn"
2498}
2499layer {
2500  name: "conv5_2/linear"
2501  type: "Convolution"
2502  bottom: "conv5_2/dwise/bn"
2503  top: "conv5_2/linear"
2504  param {
2505    lr_mult: 1
2506    decay_mult: 1
2507  }
2508  convolution_param {
2509    num_output: 96
2510    bias_term: false
2511    kernel_size: 1
2512    weight_filler {
2513      type: "msra"
2514    }
2515  }
2516}
2517layer {
2518  name: "conv5_2/linear/bn"
2519  type: "BatchNorm"
2520  bottom: "conv5_2/linear"
2521  top: "conv5_2/linear/bn"
2522  param {
2523    lr_mult: 0
2524    decay_mult: 0
2525  }
2526  param {
2527    lr_mult: 0
2528    decay_mult: 0
2529  }
2530  param {
2531    lr_mult: 0
2532    decay_mult: 0
2533  }
2534  batch_norm_param {
2535    use_global_stats: true
2536    eps: 1e-5
2537  }
2538}
2539layer {
2540  name: "conv5_2/linear/scale"
2541  type: "Scale"
2542  bottom: "conv5_2/linear/bn"
2543  top: "conv5_2/linear/bn"
2544  param {
2545    lr_mult: 1
2546    decay_mult: 0
2547  }
2548  param {
2549    lr_mult: 1
2550    decay_mult: 0
2551  }
2552  scale_param {
2553    bias_term: true
2554  }
2555}
2556layer {
2557  name: "block_5_2"
2558  type: "Eltwise"
2559  bottom: "block_5_1"
2560  bottom: "conv5_2/linear/bn"
2561  top: "block_5_2"
2562}
2563layer {
2564  name: "conv5_3/expand"
2565  type: "Convolution"
2566  bottom: "block_5_2"
2567  top: "conv5_3/expand"
2568  param {
2569    lr_mult: 1
2570    decay_mult: 1
2571  }
2572  convolution_param {
2573    num_output: 576
2574    bias_term: false
2575    kernel_size: 1
2576    weight_filler {
2577      type: "msra"
2578    }
2579  }
2580}
2581layer {
2582  name: "conv5_3/expand/bn"
2583  type: "BatchNorm"
2584  bottom: "conv5_3/expand"
2585  top: "conv5_3/expand/bn"
2586  param {
2587    lr_mult: 0
2588    decay_mult: 0
2589  }
2590  param {
2591    lr_mult: 0
2592    decay_mult: 0
2593  }
2594  param {
2595    lr_mult: 0
2596    decay_mult: 0
2597  }
2598  batch_norm_param {
2599    use_global_stats: true
2600    eps: 1e-5
2601  }
2602}
2603layer {
2604  name: "conv5_3/expand/scale"
2605  type: "Scale"
2606  bottom: "conv5_3/expand/bn"
2607  top: "conv5_3/expand/bn"
2608  param {
2609    lr_mult: 1
2610    decay_mult: 0
2611  }
2612  param {
2613    lr_mult: 1
2614    decay_mult: 0
2615  }
2616  scale_param {
2617    bias_term: true
2618  }
2619}
2620layer {
2621  name: "relu5_3/expand"
2622  type: "ReLU"
2623  bottom: "conv5_3/expand/bn"
2624  top: "conv5_3/expand/bn"
2625}
2626layer {
2627  name: "conv5_3/dwise"
2628  type: "Convolution"
2629  bottom: "conv5_3/expand/bn"
2630  top: "conv5_3/dwise"
2631  param {
2632    lr_mult: 1
2633    decay_mult: 1
2634  }
2635  convolution_param {
2636    num_output: 576
2637    bias_term: false
2638    pad: 1
2639    kernel_size: 3
2640    group: 576
2641    stride: 2
2642    weight_filler {
2643      type: "msra"
2644    }
2645    engine: CAFFE
2646  }
2647}
2648layer {
2649  name: "conv5_3/dwise/bn"
2650  type: "BatchNorm"
2651  bottom: "conv5_3/dwise"
2652  top: "conv5_3/dwise/bn"
2653  param {
2654    lr_mult: 0
2655    decay_mult: 0
2656  }
2657  param {
2658    lr_mult: 0
2659    decay_mult: 0
2660  }
2661  param {
2662    lr_mult: 0
2663    decay_mult: 0
2664  }
2665  batch_norm_param {
2666    use_global_stats: true
2667    eps: 1e-5
2668  }
2669}
2670layer {
2671  name: "conv5_3/dwise/scale"
2672  type: "Scale"
2673  bottom: "conv5_3/dwise/bn"
2674  top: "conv5_3/dwise/bn"
2675  param {
2676    lr_mult: 1
2677    decay_mult: 0
2678  }
2679  param {
2680    lr_mult: 1
2681    decay_mult: 0
2682  }
2683  scale_param {
2684    bias_term: true
2685  }
2686}
2687layer {
2688  name: "relu5_3/dwise"
2689  type: "ReLU"
2690  bottom: "conv5_3/dwise/bn"
2691  top: "conv5_3/dwise/bn"
2692}
2693layer {
2694  name: "conv5_3/linear"
2695  type: "Convolution"
2696  bottom: "conv5_3/dwise/bn"
2697  top: "conv5_3/linear"
2698  param {
2699    lr_mult: 1
2700    decay_mult: 1
2701  }
2702  convolution_param {
2703    num_output: 160
2704    bias_term: false
2705    kernel_size: 1
2706    weight_filler {
2707      type: "msra"
2708    }
2709  }
2710}
2711layer {
2712  name: "conv5_3/linear/bn"
2713  type: "BatchNorm"
2714  bottom: "conv5_3/linear"
2715  top: "conv5_3/linear/bn"
2716  param {
2717    lr_mult: 0
2718    decay_mult: 0
2719  }
2720  param {
2721    lr_mult: 0
2722    decay_mult: 0
2723  }
2724  param {
2725    lr_mult: 0
2726    decay_mult: 0
2727  }
2728  batch_norm_param {
2729    use_global_stats: true
2730    eps: 1e-5
2731  }
2732}
2733layer {
2734  name: "conv5_3/linear/scale"
2735  type: "Scale"
2736  bottom: "conv5_3/linear/bn"
2737  top: "conv5_3/linear/bn"
2738  param {
2739    lr_mult: 1
2740    decay_mult: 0
2741  }
2742  param {
2743    lr_mult: 1
2744    decay_mult: 0
2745  }
2746  scale_param {
2747    bias_term: true
2748  }
2749}
2750layer {
2751  name: "conv6_1/expand"
2752  type: "Convolution"
2753  bottom: "conv5_3/linear/bn"
2754  top: "conv6_1/expand"
2755  param {
2756    lr_mult: 1
2757    decay_mult: 1
2758  }
2759  convolution_param {
2760    num_output: 960
2761    bias_term: false
2762    kernel_size: 1
2763    weight_filler {
2764      type: "msra"
2765    }
2766  }
2767}
2768layer {
2769  name: "conv6_1/expand/bn"
2770  type: "BatchNorm"
2771  bottom: "conv6_1/expand"
2772  top: "conv6_1/expand/bn"
2773  param {
2774    lr_mult: 0
2775    decay_mult: 0
2776  }
2777  param {
2778    lr_mult: 0
2779    decay_mult: 0
2780  }
2781  param {
2782    lr_mult: 0
2783    decay_mult: 0
2784  }
2785  batch_norm_param {
2786    use_global_stats: true
2787    eps: 1e-5
2788  }
2789}
2790layer {
2791  name: "conv6_1/expand/scale"
2792  type: "Scale"
2793  bottom: "conv6_1/expand/bn"
2794  top: "conv6_1/expand/bn"
2795  param {
2796    lr_mult: 1
2797    decay_mult: 0
2798  }
2799  param {
2800    lr_mult: 1
2801    decay_mult: 0
2802  }
2803  scale_param {
2804    bias_term: true
2805  }
2806}
2807layer {
2808  name: "relu6_1/expand"
2809  type: "ReLU"
2810  bottom: "conv6_1/expand/bn"
2811  top: "conv6_1/expand/bn"
2812}
2813layer {
2814  name: "conv6_1/dwise"
2815  type: "Convolution"
2816  bottom: "conv6_1/expand/bn"
2817  top: "conv6_1/dwise"
2818  param {
2819    lr_mult: 1
2820    decay_mult: 1
2821  }
2822  convolution_param {
2823    num_output: 960
2824    bias_term: false
2825    pad: 1
2826    kernel_size: 3
2827    group: 960
2828    weight_filler {
2829      type: "msra"
2830    }
2831    engine: CAFFE
2832  }
2833}
2834layer {
2835  name: "conv6_1/dwise/bn"
2836  type: "BatchNorm"
2837  bottom: "conv6_1/dwise"
2838  top: "conv6_1/dwise/bn"
2839  param {
2840    lr_mult: 0
2841    decay_mult: 0
2842  }
2843  param {
2844    lr_mult: 0
2845    decay_mult: 0
2846  }
2847  param {
2848    lr_mult: 0
2849    decay_mult: 0
2850  }
2851  batch_norm_param {
2852    use_global_stats: true
2853    eps: 1e-5
2854  }
2855}
2856layer {
2857  name: "conv6_1/dwise/scale"
2858  type: "Scale"
2859  bottom: "conv6_1/dwise/bn"
2860  top: "conv6_1/dwise/bn"
2861  param {
2862    lr_mult: 1
2863    decay_mult: 0
2864  }
2865  param {
2866    lr_mult: 1
2867    decay_mult: 0
2868  }
2869  scale_param {
2870    bias_term: true
2871  }
2872}
2873layer {
2874  name: "relu6_1/dwise"
2875  type: "ReLU"
2876  bottom: "conv6_1/dwise/bn"
2877  top: "conv6_1/dwise/bn"
2878}
2879layer {
2880  name: "conv6_1/linear"
2881  type: "Convolution"
2882  bottom: "conv6_1/dwise/bn"
2883  top: "conv6_1/linear"
2884  param {
2885    lr_mult: 1
2886    decay_mult: 1
2887  }
2888  convolution_param {
2889    num_output: 160
2890    bias_term: false
2891    kernel_size: 1
2892    weight_filler {
2893      type: "msra"
2894    }
2895  }
2896}
2897layer {
2898  name: "conv6_1/linear/bn"
2899  type: "BatchNorm"
2900  bottom: "conv6_1/linear"
2901  top: "conv6_1/linear/bn"
2902  param {
2903    lr_mult: 0
2904    decay_mult: 0
2905  }
2906  param {
2907    lr_mult: 0
2908    decay_mult: 0
2909  }
2910  param {
2911    lr_mult: 0
2912    decay_mult: 0
2913  }
2914  batch_norm_param {
2915    use_global_stats: true
2916    eps: 1e-5
2917  }
2918}
2919layer {
2920  name: "conv6_1/linear/scale"
2921  type: "Scale"
2922  bottom: "conv6_1/linear/bn"
2923  top: "conv6_1/linear/bn"
2924  param {
2925    lr_mult: 1
2926    decay_mult: 0
2927  }
2928  param {
2929    lr_mult: 1
2930    decay_mult: 0
2931  }
2932  scale_param {
2933    bias_term: true
2934  }
2935}
2936layer {
2937  name: "block_6_1"
2938  type: "Eltwise"
2939  bottom: "conv5_3/linear/bn"
2940  bottom: "conv6_1/linear/bn"
2941  top: "block_6_1"
2942}
2943layer {
2944  name: "conv6_2/expand"
2945  type: "Convolution"
2946  bottom: "block_6_1"
2947  top: "conv6_2/expand"
2948  param {
2949    lr_mult: 1
2950    decay_mult: 1
2951  }
2952  convolution_param {
2953    num_output: 960
2954    bias_term: false
2955    kernel_size: 1
2956    weight_filler {
2957      type: "msra"
2958    }
2959  }
2960}
2961layer {
2962  name: "conv6_2/expand/bn"
2963  type: "BatchNorm"
2964  bottom: "conv6_2/expand"
2965  top: "conv6_2/expand/bn"
2966  param {
2967    lr_mult: 0
2968    decay_mult: 0
2969  }
2970  param {
2971    lr_mult: 0
2972    decay_mult: 0
2973  }
2974  param {
2975    lr_mult: 0
2976    decay_mult: 0
2977  }
2978  batch_norm_param {
2979    use_global_stats: true
2980    eps: 1e-5
2981  }
2982}
2983layer {
2984  name: "conv6_2/expand/scale"
2985  type: "Scale"
2986  bottom: "conv6_2/expand/bn"
2987  top: "conv6_2/expand/bn"
2988  param {
2989    lr_mult: 1
2990    decay_mult: 0
2991  }
2992  param {
2993    lr_mult: 1
2994    decay_mult: 0
2995  }
2996  scale_param {
2997    bias_term: true
2998  }
2999}
3000layer {
3001  name: "relu6_2/expand"
3002  type: "ReLU"
3003  bottom: "conv6_2/expand/bn"
3004  top: "conv6_2/expand/bn"
3005}
3006layer {
3007  name: "conv6_2/dwise"
3008  type: "Convolution"
3009  bottom: "conv6_2/expand/bn"
3010  top: "conv6_2/dwise"
3011  param {
3012    lr_mult: 1
3013    decay_mult: 1
3014  }
3015  convolution_param {
3016    num_output: 960
3017    bias_term: false
3018    pad: 1
3019    kernel_size: 3
3020    group: 960
3021    weight_filler {
3022      type: "msra"
3023    }
3024    engine: CAFFE
3025  }
3026}
3027layer {
3028  name: "conv6_2/dwise/bn"
3029  type: "BatchNorm"
3030  bottom: "conv6_2/dwise"
3031  top: "conv6_2/dwise/bn"
3032  param {
3033    lr_mult: 0
3034    decay_mult: 0
3035  }
3036  param {
3037    lr_mult: 0
3038    decay_mult: 0
3039  }
3040  param {
3041    lr_mult: 0
3042    decay_mult: 0
3043  }
3044  batch_norm_param {
3045    use_global_stats: true
3046    eps: 1e-5
3047  }
3048}
3049layer {
3050  name: "conv6_2/dwise/scale"
3051  type: "Scale"
3052  bottom: "conv6_2/dwise/bn"
3053  top: "conv6_2/dwise/bn"
3054  param {
3055    lr_mult: 1
3056    decay_mult: 0
3057  }
3058  param {
3059    lr_mult: 1
3060    decay_mult: 0
3061  }
3062  scale_param {
3063    bias_term: true
3064  }
3065}
3066layer {
3067  name: "relu6_2/dwise"
3068  type: "ReLU"
3069  bottom: "conv6_2/dwise/bn"
3070  top: "conv6_2/dwise/bn"
3071}
3072layer {
3073  name: "conv6_2/linear"
3074  type: "Convolution"
3075  bottom: "conv6_2/dwise/bn"
3076  top: "conv6_2/linear"
3077  param {
3078    lr_mult: 1
3079    decay_mult: 1
3080  }
3081  convolution_param {
3082    num_output: 160
3083    bias_term: false
3084    kernel_size: 1
3085    weight_filler {
3086      type: "msra"
3087    }
3088  }
3089}
3090layer {
3091  name: "conv6_2/linear/bn"
3092  type: "BatchNorm"
3093  bottom: "conv6_2/linear"
3094  top: "conv6_2/linear/bn"
3095  param {
3096    lr_mult: 0
3097    decay_mult: 0
3098  }
3099  param {
3100    lr_mult: 0
3101    decay_mult: 0
3102  }
3103  param {
3104    lr_mult: 0
3105    decay_mult: 0
3106  }
3107  batch_norm_param {
3108    use_global_stats: true
3109    eps: 1e-5
3110  }
3111}
3112layer {
3113  name: "conv6_2/linear/scale"
3114  type: "Scale"
3115  bottom: "conv6_2/linear/bn"
3116  top: "conv6_2/linear/bn"
3117  param {
3118    lr_mult: 1
3119    decay_mult: 0
3120  }
3121  param {
3122    lr_mult: 1
3123    decay_mult: 0
3124  }
3125  scale_param {
3126    bias_term: true
3127  }
3128}
3129layer {
3130  name: "block_6_2"
3131  type: "Eltwise"
3132  bottom: "block_6_1"
3133  bottom: "conv6_2/linear/bn"
3134  top: "block_6_2"
3135}
3136layer {
3137  name: "conv6_3/expand"
3138  type: "Convolution"
3139  bottom: "block_6_2"
3140  top: "conv6_3/expand"
3141  param {
3142    lr_mult: 1
3143    decay_mult: 1
3144  }
3145  convolution_param {
3146    num_output: 960
3147    bias_term: false
3148    kernel_size: 1
3149    weight_filler {
3150      type: "msra"
3151    }
3152  }
3153}
3154layer {
3155  name: "conv6_3/expand/bn"
3156  type: "BatchNorm"
3157  bottom: "conv6_3/expand"
3158  top: "conv6_3/expand/bn"
3159  param {
3160    lr_mult: 0
3161    decay_mult: 0
3162  }
3163  param {
3164    lr_mult: 0
3165    decay_mult: 0
3166  }
3167  param {
3168    lr_mult: 0
3169    decay_mult: 0
3170  }
3171  batch_norm_param {
3172    use_global_stats: true
3173    eps: 1e-5
3174  }
3175}
3176layer {
3177  name: "conv6_3/expand/scale"
3178  type: "Scale"
3179  bottom: "conv6_3/expand/bn"
3180  top: "conv6_3/expand/bn"
3181  param {
3182    lr_mult: 1
3183    decay_mult: 0
3184  }
3185  param {
3186    lr_mult: 1
3187    decay_mult: 0
3188  }
3189  scale_param {
3190    bias_term: true
3191  }
3192}
3193layer {
3194  name: "relu6_3/expand"
3195  type: "ReLU"
3196  bottom: "conv6_3/expand/bn"
3197  top: "conv6_3/expand/bn"
3198}
3199layer {
3200  name: "conv6_3/dwise"
3201  type: "Convolution"
3202  bottom: "conv6_3/expand/bn"
3203  top: "conv6_3/dwise"
3204  param {
3205    lr_mult: 1
3206    decay_mult: 1
3207  }
3208  convolution_param {
3209    num_output: 960
3210    bias_term: false
3211    pad: 1
3212    kernel_size: 3
3213    group: 960
3214    weight_filler {
3215      type: "msra"
3216    }
3217    engine: CAFFE
3218  }
3219}
3220layer {
3221  name: "conv6_3/dwise/bn"
3222  type: "BatchNorm"
3223  bottom: "conv6_3/dwise"
3224  top: "conv6_3/dwise/bn"
3225  param {
3226    lr_mult: 0
3227    decay_mult: 0
3228  }
3229  param {
3230    lr_mult: 0
3231    decay_mult: 0
3232  }
3233  param {
3234    lr_mult: 0
3235    decay_mult: 0
3236  }
3237  batch_norm_param {
3238    use_global_stats: true
3239    eps: 1e-5
3240  }
3241}
3242layer {
3243  name: "conv6_3/dwise/scale"
3244  type: "Scale"
3245  bottom: "conv6_3/dwise/bn"
3246  top: "conv6_3/dwise/bn"
3247  param {
3248    lr_mult: 1
3249    decay_mult: 0
3250  }
3251  param {
3252    lr_mult: 1
3253    decay_mult: 0
3254  }
3255  scale_param {
3256    bias_term: true
3257  }
3258}
3259layer {
3260  name: "relu6_3/dwise"
3261  type: "ReLU"
3262  bottom: "conv6_3/dwise/bn"
3263  top: "conv6_3/dwise/bn"
3264}
3265layer {
3266  name: "conv6_3/linear"
3267  type: "Convolution"
3268  bottom: "conv6_3/dwise/bn"
3269  top: "conv6_3/linear"
3270  param {
3271    lr_mult: 1
3272    decay_mult: 1
3273  }
3274  convolution_param {
3275    num_output: 320
3276    bias_term: false
3277    kernel_size: 1
3278    weight_filler {
3279      type: "msra"
3280    }
3281  }
3282}
3283layer {
3284  name: "conv6_3/linear/bn"
3285  type: "BatchNorm"
3286  bottom: "conv6_3/linear"
3287  top: "conv6_3/linear/bn"
3288  param {
3289    lr_mult: 0
3290    decay_mult: 0
3291  }
3292  param {
3293    lr_mult: 0
3294    decay_mult: 0
3295  }
3296  param {
3297    lr_mult: 0
3298    decay_mult: 0
3299  }
3300  batch_norm_param {
3301    use_global_stats: true
3302    eps: 1e-5
3303  }
3304}
3305layer {
3306  name: "conv6_3/linear/scale"
3307  type: "Scale"
3308  bottom: "conv6_3/linear/bn"
3309  top: "conv6_3/linear/bn"
3310  param {
3311    lr_mult: 1
3312    decay_mult: 0
3313  }
3314  param {
3315    lr_mult: 1
3316    decay_mult: 0
3317  }
3318  scale_param {
3319    bias_term: true
3320  }
3321}
3322layer {
3323  name: "conv6_4"
3324  type: "Convolution"
3325  bottom: "conv6_3/linear/bn"
3326  top: "conv6_4"
3327  param {
3328    lr_mult: 1
3329    decay_mult: 1
3330  }
3331  convolution_param {
3332    num_output: 1280
3333    bias_term: false
3334    kernel_size: 1
3335    weight_filler {
3336      type: "msra"
3337    }
3338  }
3339}
3340layer {
3341  name: "conv6_4/bn"
3342  type: "BatchNorm"
3343  bottom: "conv6_4"
3344  top: "conv6_4/bn"
3345  param {
3346    lr_mult: 0
3347    decay_mult: 0
3348  }
3349  param {
3350    lr_mult: 0
3351    decay_mult: 0
3352  }
3353  param {
3354    lr_mult: 0
3355    decay_mult: 0
3356  }
3357  batch_norm_param {
3358    use_global_stats: true
3359    eps: 1e-5
3360  }
3361}
3362layer {
3363  name: "conv6_4/scale"
3364  type: "Scale"
3365  bottom: "conv6_4/bn"
3366  top: "conv6_4/bn"
3367  param {
3368    lr_mult: 1
3369    decay_mult: 0
3370  }
3371  param {
3372    lr_mult: 1
3373    decay_mult: 0
3374  }
3375  scale_param {
3376    bias_term: true
3377  }
3378}
3379layer {
3380  name: "relu6_4"
3381  type: "ReLU"
3382  bottom: "conv6_4/bn"
3383  top: "conv6_4/bn"
3384}
3385layer {
3386  name: "pool6"
3387  type: "Pooling"
3388  bottom: "conv6_4/bn"
3389  top: "pool6"
3390  pooling_param {
3391    pool: AVE
3392    global_pooling: true
3393  }
3394}
3395layer {
3396  name: "fc7"
3397  type: "Convolution"
3398  bottom: "pool6"
3399  top: "fc7"
3400  param {
3401    lr_mult: 1
3402    decay_mult: 1
3403  }
3404  param {
3405    lr_mult: 2
3406    decay_mult: 0
3407  }
3408  convolution_param {
3409    num_output: 1000
3410    kernel_size: 1
3411    weight_filler {
3412      type: "msra"
3413    }
3414    bias_filler {
3415      type: "constant"
3416      value: 0
3417    }
3418  }
3419}
3420layer {
3421  name: "prob"
3422  type: "Softmax"
3423  bottom: "fc7"
3424  top: "prob"
3425}
3426