forked from kevinlin311tw/Caffe-DeepBinaryCode
-
Notifications
You must be signed in to change notification settings - Fork 0
Expand file tree
/
Copy pathlog.txt
More file actions
1349 lines (1349 loc) · 48.6 KB
/
Copy pathlog.txt
File metadata and controls
1349 lines (1349 loc) · 48.6 KB
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560
561
562
563
564
565
566
567
568
569
570
571
572
573
574
575
576
577
578
579
580
581
582
583
584
585
586
587
588
589
590
591
592
593
594
595
596
597
598
599
600
601
602
603
604
605
606
607
608
609
610
611
612
613
614
615
616
617
618
619
620
621
622
623
624
625
626
627
628
629
630
631
632
633
634
635
636
637
638
639
640
641
642
643
644
645
646
647
648
649
650
651
652
653
654
655
656
657
658
659
660
661
662
663
664
665
666
667
668
669
670
671
672
673
674
675
676
677
678
679
680
681
682
683
684
685
686
687
688
689
690
691
692
693
694
695
696
697
698
699
700
701
702
703
704
705
706
707
708
709
710
711
712
713
714
715
716
717
718
719
720
721
722
723
724
725
726
727
728
729
730
731
732
733
734
735
736
737
738
739
740
741
742
743
744
745
746
747
748
749
750
751
752
753
754
755
756
757
758
759
760
761
762
763
764
765
766
767
768
769
770
771
772
773
774
775
776
777
778
779
780
781
782
783
784
785
786
787
788
789
790
791
792
793
794
795
796
797
798
799
800
801
802
803
804
805
806
807
808
809
810
811
812
813
814
815
816
817
818
819
820
821
822
823
824
825
826
827
828
829
830
831
832
833
834
835
836
837
838
839
840
841
842
843
844
845
846
847
848
849
850
851
852
853
854
855
856
857
858
859
860
861
862
863
864
865
866
867
868
869
870
871
872
873
874
875
876
877
878
879
880
881
882
883
884
885
886
887
888
889
890
891
892
893
894
895
896
897
898
899
900
901
902
903
904
905
906
907
908
909
910
911
912
913
914
915
916
917
918
919
920
921
922
923
924
925
926
927
928
929
930
931
932
933
934
935
936
937
938
939
940
941
942
943
944
945
946
947
948
949
950
951
952
953
954
955
956
957
958
959
960
961
962
963
964
965
966
967
968
969
970
971
972
973
974
975
976
977
978
979
980
981
982
983
984
985
986
987
988
989
990
991
992
993
994
995
996
997
998
999
1000
I0107 22:33:55.702527 14352 caffe.cpp:183] Using GPUs 0
I0107 22:33:56.007503 14352 solver.cpp:54] Initializing solver from parameters:
test_iter: 100
test_interval: 100
base_lr: 0.001
display: 20
max_iter: 50000
lr_policy: "step"
gamma: 0.1
momentum: 0.9
weight_decay: 0.0005
stepsize: 25000
snapshot: 10000
snapshot_prefix: "./examples/SSDH/SSDH48"
device_id: 0
net: "./examples/SSDH/train_val.prototxt"
I0107 22:33:56.007555 14352 solver.cpp:96] Creating training net from net file: ./examples/SSDH/train_val.prototxt
I0107 22:33:56.008244 14352 net.cpp:339] The NetState phase (0) differed from the phase (1) specified by a rule in layer data
I0107 22:33:56.008285 14352 net.cpp:339] The NetState phase (0) differed from the phase (1) specified by a rule in layer accuracy
I0107 22:33:56.008474 14352 net.cpp:50] Initializing net from parameters:
name: "CaffeNet"
state {
phase: TRAIN
}
layer {
name: "data"
type: "Data"
top: "data"
top: "label"
include {
phase: TRAIN
}
transform_param {
mirror: true
crop_size: 227
mean_file: "data/ilsvrc12/imagenet_mean.binaryproto"
}
data_param {
source: "data/cifar10/cifar10_train_leveldb"
batch_size: 32
}
}
layer {
name: "conv1"
type: "Convolution"
bottom: "data"
top: "conv1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 96
kernel_size: 11
stride: 4
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "relu1"
type: "ReLU"
bottom: "conv1"
top: "conv1"
}
layer {
name: "pool1"
type: "Pooling"
bottom: "conv1"
top: "pool1"
pooling_param {
pool: MAX
kernel_size: 3
stride: 2
}
}
layer {
name: "norm1"
type: "LRN"
bottom: "pool1"
top: "norm1"
lrn_param {
local_size: 5
alpha: 0.0001
beta: 0.75
}
}
layer {
name: "conv2"
type: "Convolution"
bottom: "norm1"
top: "conv2"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 256
pad: 2
kernel_size: 5
group: 2
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 1
}
}
}
layer {
name: "relu2"
type: "ReLU"
bottom: "conv2"
top: "conv2"
}
layer {
name: "pool2"
type: "Pooling"
bottom: "conv2"
top: "pool2"
pooling_param {
pool: MAX
kernel_size: 3
stride: 2
}
}
layer {
name: "norm2"
type: "LRN"
bottom: "pool2"
top: "norm2"
lrn_param {
local_size: 5
alpha: 0.0001
beta: 0.75
}
}
layer {
name: "conv3"
type: "Convolution"
bottom: "norm2"
top: "conv3"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 384
pad: 1
kernel_size: 3
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "relu3"
type: "ReLU"
bottom: "conv3"
top: "conv3"
}
layer {
name: "conv4"
type: "Convolution"
bottom: "conv3"
top: "conv4"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 384
pad: 1
kernel_size: 3
group: 2
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 1
}
}
}
layer {
name: "relu4"
type: "ReLU"
bottom: "conv4"
top: "conv4"
}
layer {
name: "conv5"
type: "Convolution"
bottom: "conv4"
top: "conv5"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 256
pad: 1
kernel_size: 3
group: 2
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 1
}
}
}
layer {
name: "relu5"
type: "ReLU"
bottom: "conv5"
top: "conv5"
}
layer {
name: "pool5"
type: "Pooling"
bottom: "conv5"
top: "pool5"
pooling_param {
pool: MAX
kernel_size: 3
stride: 2
}
}
layer {
name: "fc6"
type: "InnerProduct"
bottom: "pool5"
top: "fc6"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
inner_product_param {
num_output: 4096
weight_filler {
type: "gaussian"
std: 0.005
}
bias_filler {
type: "constant"
value: 1
}
}
}
layer {
name: "relu6"
type: "ReLU"
bottom: "fc6"
top: "fc6"
}
layer {
name: "drop6"
type: "Dropout"
bottom: "fc6"
top: "fc6"
dropout_param {
dropout_ratio: 0.5
}
}
layer {
name: "fc7"
type: "InnerProduct"
bottom: "fc6"
top: "fc7"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
inner_product_param {
num_output: 4096
weight_filler {
type: "gaussian"
std: 0.005
}
bias_filler {
type: "constant"
value: 1
}
}
}
layer {
name: "relu7"
type: "ReLU"
bottom: "fc7"
top: "fc7"
}
layer {
name: "drop7"
type: "Dropout"
bottom: "fc7"
top: "fc7"
dropout_param {
dropout_ratio: 0.5
}
}
layer {
name: "latent_layer"
type: "InnerProduct"
bottom: "fc7"
top: "latent_layer"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
inner_product_param {
num_output: 48
weight_filler {
type: "gaussian"
std: 0.005
}
bias_filler {
type: "constant"
value: 1
}
}
}
layer {
name: "encode_neuron"
type: "Sigmoid"
bottom: "latent_layer"
top: "encode_neuron"
}
layer {
name: "loss_beta"
type: "K1_EuclideanLoss"
bottom: "encode_neuron"
bottom: "encode_neuron"
top: "loss: forcing-binary"
loss_weight: 1
}
layer {
name: "loss_gamma"
type: "K2_EuclideanLoss"
bottom: "encode_neuron"
bottom: "encode_neuron"
top: "loss: 50%-fire-rate"
loss_weight: 1
}
layer {
name: "fc8_classification"
type: "InnerProduct"
bottom: "encode_neuron"
top: "fc8_classification"
param {
lr_mult: 10
decay_mult: 1
}
param {
lr_mult: 20
decay_mult: 0
}
inner_product_param {
num_output: 10
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "loss_alpha"
type: "SoftmaxWithLoss"
bottom: "fc8_classification"
bottom: "label"
top: "loss: classfication-error"
loss_weight: 1
}
I0107 22:33:56.008692 14352 layer_factory.hpp:76] Creating layer data
I0107 22:33:56.009207 14352 net.cpp:110] Creating Layer data
I0107 22:33:56.009219 14352 net.cpp:433] data -> data
I0107 22:33:56.009249 14352 net.cpp:433] data -> label
I0107 22:33:56.009265 14352 data_transformer.cpp:23] Loading mean file from: data/ilsvrc12/imagenet_mean.binaryproto
I0107 22:33:56.114115 14364 db_leveldb.cpp:17] Opened leveldb data/cifar10/cifar10_train_leveldb
I0107 22:33:56.115829 14352 data_layer.cpp:44] output data size: 32,3,227,227
I0107 22:33:56.140460 14352 net.cpp:155] Setting up data
I0107 22:33:56.140496 14352 net.cpp:163] Top shape: 32 3 227 227 (4946784)
I0107 22:33:56.140503 14352 net.cpp:163] Top shape: 32 (32)
I0107 22:33:56.140513 14352 layer_factory.hpp:76] Creating layer conv1
I0107 22:33:56.140530 14352 net.cpp:110] Creating Layer conv1
I0107 22:33:56.140537 14352 net.cpp:477] conv1 <- data
I0107 22:33:56.140552 14352 net.cpp:433] conv1 -> conv1
I0107 22:33:56.143748 14352 net.cpp:155] Setting up conv1
I0107 22:33:56.143776 14352 net.cpp:163] Top shape: 32 96 55 55 (9292800)
I0107 22:33:56.143797 14352 layer_factory.hpp:76] Creating layer relu1
I0107 22:33:56.143810 14352 net.cpp:110] Creating Layer relu1
I0107 22:33:56.143815 14352 net.cpp:477] relu1 <- conv1
I0107 22:33:56.143822 14352 net.cpp:419] relu1 -> conv1 (in-place)
I0107 22:33:56.143833 14352 net.cpp:155] Setting up relu1
I0107 22:33:56.143841 14352 net.cpp:163] Top shape: 32 96 55 55 (9292800)
I0107 22:33:56.143846 14352 layer_factory.hpp:76] Creating layer pool1
I0107 22:33:56.143852 14352 net.cpp:110] Creating Layer pool1
I0107 22:33:56.143857 14352 net.cpp:477] pool1 <- conv1
I0107 22:33:56.143882 14352 net.cpp:433] pool1 -> pool1
I0107 22:33:56.143913 14352 net.cpp:155] Setting up pool1
I0107 22:33:56.143920 14352 net.cpp:163] Top shape: 32 96 27 27 (2239488)
I0107 22:33:56.143944 14352 layer_factory.hpp:76] Creating layer norm1
I0107 22:33:56.143952 14352 net.cpp:110] Creating Layer norm1
I0107 22:33:56.143957 14352 net.cpp:477] norm1 <- pool1
I0107 22:33:56.143964 14352 net.cpp:433] norm1 -> norm1
I0107 22:33:56.143975 14352 net.cpp:155] Setting up norm1
I0107 22:33:56.143982 14352 net.cpp:163] Top shape: 32 96 27 27 (2239488)
I0107 22:33:56.143986 14352 layer_factory.hpp:76] Creating layer conv2
I0107 22:33:56.143996 14352 net.cpp:110] Creating Layer conv2
I0107 22:33:56.144001 14352 net.cpp:477] conv2 <- norm1
I0107 22:33:56.144007 14352 net.cpp:433] conv2 -> conv2
I0107 22:33:56.152559 14352 net.cpp:155] Setting up conv2
I0107 22:33:56.152591 14352 net.cpp:163] Top shape: 32 256 27 27 (5971968)
I0107 22:33:56.152607 14352 layer_factory.hpp:76] Creating layer relu2
I0107 22:33:56.152619 14352 net.cpp:110] Creating Layer relu2
I0107 22:33:56.152626 14352 net.cpp:477] relu2 <- conv2
I0107 22:33:56.152633 14352 net.cpp:419] relu2 -> conv2 (in-place)
I0107 22:33:56.152643 14352 net.cpp:155] Setting up relu2
I0107 22:33:56.152648 14352 net.cpp:163] Top shape: 32 256 27 27 (5971968)
I0107 22:33:56.152653 14352 layer_factory.hpp:76] Creating layer pool2
I0107 22:33:56.152660 14352 net.cpp:110] Creating Layer pool2
I0107 22:33:56.152664 14352 net.cpp:477] pool2 <- conv2
I0107 22:33:56.152670 14352 net.cpp:433] pool2 -> pool2
I0107 22:33:56.152681 14352 net.cpp:155] Setting up pool2
I0107 22:33:56.152686 14352 net.cpp:163] Top shape: 32 256 13 13 (1384448)
I0107 22:33:56.152691 14352 layer_factory.hpp:76] Creating layer norm2
I0107 22:33:56.152700 14352 net.cpp:110] Creating Layer norm2
I0107 22:33:56.152704 14352 net.cpp:477] norm2 <- pool2
I0107 22:33:56.152710 14352 net.cpp:433] norm2 -> norm2
I0107 22:33:56.152719 14352 net.cpp:155] Setting up norm2
I0107 22:33:56.152724 14352 net.cpp:163] Top shape: 32 256 13 13 (1384448)
I0107 22:33:56.152729 14352 layer_factory.hpp:76] Creating layer conv3
I0107 22:33:56.152748 14352 net.cpp:110] Creating Layer conv3
I0107 22:33:56.152753 14352 net.cpp:477] conv3 <- norm2
I0107 22:33:56.152760 14352 net.cpp:433] conv3 -> conv3
I0107 22:33:56.175896 14352 net.cpp:155] Setting up conv3
I0107 22:33:56.175925 14352 net.cpp:163] Top shape: 32 384 13 13 (2076672)
I0107 22:33:56.175941 14352 layer_factory.hpp:76] Creating layer relu3
I0107 22:33:56.175952 14352 net.cpp:110] Creating Layer relu3
I0107 22:33:56.175958 14352 net.cpp:477] relu3 <- conv3
I0107 22:33:56.175966 14352 net.cpp:419] relu3 -> conv3 (in-place)
I0107 22:33:56.175976 14352 net.cpp:155] Setting up relu3
I0107 22:33:56.175981 14352 net.cpp:163] Top shape: 32 384 13 13 (2076672)
I0107 22:33:56.175986 14352 layer_factory.hpp:76] Creating layer conv4
I0107 22:33:56.175994 14352 net.cpp:110] Creating Layer conv4
I0107 22:33:56.175999 14352 net.cpp:477] conv4 <- conv3
I0107 22:33:56.176005 14352 net.cpp:433] conv4 -> conv4
I0107 22:33:56.196588 14352 net.cpp:155] Setting up conv4
I0107 22:33:56.196619 14352 net.cpp:163] Top shape: 32 384 13 13 (2076672)
I0107 22:33:56.196632 14352 layer_factory.hpp:76] Creating layer relu4
I0107 22:33:56.196643 14352 net.cpp:110] Creating Layer relu4
I0107 22:33:56.196655 14352 net.cpp:477] relu4 <- conv4
I0107 22:33:56.196667 14352 net.cpp:419] relu4 -> conv4 (in-place)
I0107 22:33:56.196702 14352 net.cpp:155] Setting up relu4
I0107 22:33:56.196713 14352 net.cpp:163] Top shape: 32 384 13 13 (2076672)
I0107 22:33:56.196734 14352 layer_factory.hpp:76] Creating layer conv5
I0107 22:33:56.196749 14352 net.cpp:110] Creating Layer conv5
I0107 22:33:56.196760 14352 net.cpp:477] conv5 <- conv4
I0107 22:33:56.196776 14352 net.cpp:433] conv5 -> conv5
I0107 22:33:56.208353 14352 net.cpp:155] Setting up conv5
I0107 22:33:56.208385 14352 net.cpp:163] Top shape: 32 256 13 13 (1384448)
I0107 22:33:56.208408 14352 layer_factory.hpp:76] Creating layer relu5
I0107 22:33:56.208451 14352 net.cpp:110] Creating Layer relu5
I0107 22:33:56.208458 14352 net.cpp:477] relu5 <- conv5
I0107 22:33:56.208466 14352 net.cpp:419] relu5 -> conv5 (in-place)
I0107 22:33:56.208475 14352 net.cpp:155] Setting up relu5
I0107 22:33:56.208482 14352 net.cpp:163] Top shape: 32 256 13 13 (1384448)
I0107 22:33:56.208487 14352 layer_factory.hpp:76] Creating layer pool5
I0107 22:33:56.208495 14352 net.cpp:110] Creating Layer pool5
I0107 22:33:56.208499 14352 net.cpp:477] pool5 <- conv5
I0107 22:33:56.208505 14352 net.cpp:433] pool5 -> pool5
I0107 22:33:56.208516 14352 net.cpp:155] Setting up pool5
I0107 22:33:56.208523 14352 net.cpp:163] Top shape: 32 256 6 6 (294912)
I0107 22:33:56.208530 14352 layer_factory.hpp:76] Creating layer fc6
I0107 22:33:56.208540 14352 net.cpp:110] Creating Layer fc6
I0107 22:33:56.208545 14352 net.cpp:477] fc6 <- pool5
I0107 22:33:56.208551 14352 net.cpp:433] fc6 -> fc6
I0107 22:33:57.158751 14352 net.cpp:155] Setting up fc6
I0107 22:33:57.158797 14352 net.cpp:163] Top shape: 32 4096 (131072)
I0107 22:33:57.158809 14352 layer_factory.hpp:76] Creating layer relu6
I0107 22:33:57.158820 14352 net.cpp:110] Creating Layer relu6
I0107 22:33:57.158828 14352 net.cpp:477] relu6 <- fc6
I0107 22:33:57.158835 14352 net.cpp:419] relu6 -> fc6 (in-place)
I0107 22:33:57.158849 14352 net.cpp:155] Setting up relu6
I0107 22:33:57.158854 14352 net.cpp:163] Top shape: 32 4096 (131072)
I0107 22:33:57.158859 14352 layer_factory.hpp:76] Creating layer drop6
I0107 22:33:57.158875 14352 net.cpp:110] Creating Layer drop6
I0107 22:33:57.158884 14352 net.cpp:477] drop6 <- fc6
I0107 22:33:57.158890 14352 net.cpp:419] drop6 -> fc6 (in-place)
I0107 22:33:57.158905 14352 net.cpp:155] Setting up drop6
I0107 22:33:57.158912 14352 net.cpp:163] Top shape: 32 4096 (131072)
I0107 22:33:57.158917 14352 layer_factory.hpp:76] Creating layer fc7
I0107 22:33:57.158926 14352 net.cpp:110] Creating Layer fc7
I0107 22:33:57.158931 14352 net.cpp:477] fc7 <- fc6
I0107 22:33:57.158938 14352 net.cpp:433] fc7 -> fc7
I0107 22:33:57.579921 14352 net.cpp:155] Setting up fc7
I0107 22:33:57.579957 14352 net.cpp:163] Top shape: 32 4096 (131072)
I0107 22:33:57.579969 14352 layer_factory.hpp:76] Creating layer relu7
I0107 22:33:57.579980 14352 net.cpp:110] Creating Layer relu7
I0107 22:33:57.579987 14352 net.cpp:477] relu7 <- fc7
I0107 22:33:57.579995 14352 net.cpp:419] relu7 -> fc7 (in-place)
I0107 22:33:57.580005 14352 net.cpp:155] Setting up relu7
I0107 22:33:57.580013 14352 net.cpp:163] Top shape: 32 4096 (131072)
I0107 22:33:57.580018 14352 layer_factory.hpp:76] Creating layer drop7
I0107 22:33:57.580025 14352 net.cpp:110] Creating Layer drop7
I0107 22:33:57.580030 14352 net.cpp:477] drop7 <- fc7
I0107 22:33:57.580036 14352 net.cpp:419] drop7 -> fc7 (in-place)
I0107 22:33:57.580045 14352 net.cpp:155] Setting up drop7
I0107 22:33:57.580052 14352 net.cpp:163] Top shape: 32 4096 (131072)
I0107 22:33:57.580057 14352 layer_factory.hpp:76] Creating layer latent_layer
I0107 22:33:57.580066 14352 net.cpp:110] Creating Layer latent_layer
I0107 22:33:57.580072 14352 net.cpp:477] latent_layer <- fc7
I0107 22:33:57.580080 14352 net.cpp:433] latent_layer -> latent_layer
I0107 22:33:57.585294 14352 net.cpp:155] Setting up latent_layer
I0107 22:33:57.585328 14352 net.cpp:163] Top shape: 32 48 (1536)
I0107 22:33:57.585340 14352 layer_factory.hpp:76] Creating layer encode_neuron
I0107 22:33:57.585351 14352 net.cpp:110] Creating Layer encode_neuron
I0107 22:33:57.585357 14352 net.cpp:477] encode_neuron <- latent_layer
I0107 22:33:57.585366 14352 net.cpp:433] encode_neuron -> encode_neuron
I0107 22:33:57.585377 14352 net.cpp:155] Setting up encode_neuron
I0107 22:33:57.585384 14352 net.cpp:163] Top shape: 32 48 (1536)
I0107 22:33:57.585389 14352 layer_factory.hpp:76] Creating layer encode_neuron_encode_neuron_0_split
I0107 22:33:57.585407 14352 net.cpp:110] Creating Layer encode_neuron_encode_neuron_0_split
I0107 22:33:57.585415 14352 net.cpp:477] encode_neuron_encode_neuron_0_split <- encode_neuron
I0107 22:33:57.585427 14352 net.cpp:433] encode_neuron_encode_neuron_0_split -> encode_neuron_encode_neuron_0_split_0
I0107 22:33:57.585464 14352 net.cpp:433] encode_neuron_encode_neuron_0_split -> encode_neuron_encode_neuron_0_split_1
I0107 22:33:57.585475 14352 net.cpp:433] encode_neuron_encode_neuron_0_split -> encode_neuron_encode_neuron_0_split_2
I0107 22:33:57.585484 14352 net.cpp:433] encode_neuron_encode_neuron_0_split -> encode_neuron_encode_neuron_0_split_3
I0107 22:33:57.585491 14352 net.cpp:433] encode_neuron_encode_neuron_0_split -> encode_neuron_encode_neuron_0_split_4
I0107 22:33:57.585501 14352 net.cpp:155] Setting up encode_neuron_encode_neuron_0_split
I0107 22:33:57.585508 14352 net.cpp:163] Top shape: 32 48 (1536)
I0107 22:33:57.585515 14352 net.cpp:163] Top shape: 32 48 (1536)
I0107 22:33:57.585520 14352 net.cpp:163] Top shape: 32 48 (1536)
I0107 22:33:57.585526 14352 net.cpp:163] Top shape: 32 48 (1536)
I0107 22:33:57.585532 14352 net.cpp:163] Top shape: 32 48 (1536)
I0107 22:33:57.585537 14352 layer_factory.hpp:76] Creating layer loss_beta
I0107 22:33:57.585546 14352 net.cpp:110] Creating Layer loss_beta
I0107 22:33:57.585551 14352 net.cpp:477] loss_beta <- encode_neuron_encode_neuron_0_split_0
I0107 22:33:57.585559 14352 net.cpp:477] loss_beta <- encode_neuron_encode_neuron_0_split_1
I0107 22:33:57.585571 14352 net.cpp:433] loss_beta -> loss: forcing-binary
I0107 22:33:57.585610 14352 net.cpp:155] Setting up loss_beta
I0107 22:33:57.585623 14352 net.cpp:163] Top shape: (1)
I0107 22:33:57.585633 14352 net.cpp:168] with loss weight 1
I0107 22:33:57.585655 14352 layer_factory.hpp:76] Creating layer loss_gamma
I0107 22:33:57.585664 14352 net.cpp:110] Creating Layer loss_gamma
I0107 22:33:57.585669 14352 net.cpp:477] loss_gamma <- encode_neuron_encode_neuron_0_split_2
I0107 22:33:57.585676 14352 net.cpp:477] loss_gamma <- encode_neuron_encode_neuron_0_split_3
I0107 22:33:57.585683 14352 net.cpp:433] loss_gamma -> loss: 50%-fire-rate
I0107 22:33:57.585707 14352 net.cpp:155] Setting up loss_gamma
I0107 22:33:57.585716 14352 net.cpp:163] Top shape: (1)
I0107 22:33:57.585721 14352 net.cpp:168] with loss weight 1
I0107 22:33:57.585728 14352 layer_factory.hpp:76] Creating layer fc8_classification
I0107 22:33:57.585738 14352 net.cpp:110] Creating Layer fc8_classification
I0107 22:33:57.585744 14352 net.cpp:477] fc8_classification <- encode_neuron_encode_neuron_0_split_4
I0107 22:33:57.585752 14352 net.cpp:433] fc8_classification -> fc8_classification
I0107 22:33:57.585810 14352 net.cpp:155] Setting up fc8_classification
I0107 22:33:57.585819 14352 net.cpp:163] Top shape: 32 10 (320)
I0107 22:33:57.585832 14352 layer_factory.hpp:76] Creating layer loss_alpha
I0107 22:33:57.585841 14352 net.cpp:110] Creating Layer loss_alpha
I0107 22:33:57.585846 14352 net.cpp:477] loss_alpha <- fc8_classification
I0107 22:33:57.585853 14352 net.cpp:477] loss_alpha <- label
I0107 22:33:57.585860 14352 net.cpp:433] loss_alpha -> loss: classfication-error
I0107 22:33:57.585871 14352 layer_factory.hpp:76] Creating layer loss_alpha
I0107 22:33:57.585917 14352 net.cpp:155] Setting up loss_alpha
I0107 22:33:57.585927 14352 net.cpp:163] Top shape: (1)
I0107 22:33:57.585932 14352 net.cpp:168] with loss weight 1
I0107 22:33:57.585938 14352 net.cpp:236] loss_alpha needs backward computation.
I0107 22:33:57.585944 14352 net.cpp:236] fc8_classification needs backward computation.
I0107 22:33:57.585950 14352 net.cpp:236] loss_gamma needs backward computation.
I0107 22:33:57.585958 14352 net.cpp:236] loss_beta needs backward computation.
I0107 22:33:57.585966 14352 net.cpp:236] encode_neuron_encode_neuron_0_split needs backward computation.
I0107 22:33:57.585976 14352 net.cpp:236] encode_neuron needs backward computation.
I0107 22:33:57.585984 14352 net.cpp:236] latent_layer needs backward computation.
I0107 22:33:57.585990 14352 net.cpp:236] drop7 needs backward computation.
I0107 22:33:57.585995 14352 net.cpp:236] relu7 needs backward computation.
I0107 22:33:57.586001 14352 net.cpp:236] fc7 needs backward computation.
I0107 22:33:57.586006 14352 net.cpp:236] drop6 needs backward computation.
I0107 22:33:57.586020 14352 net.cpp:236] relu6 needs backward computation.
I0107 22:33:57.586026 14352 net.cpp:236] fc6 needs backward computation.
I0107 22:33:57.586033 14352 net.cpp:236] pool5 needs backward computation.
I0107 22:33:57.586042 14352 net.cpp:236] relu5 needs backward computation.
I0107 22:33:57.586052 14352 net.cpp:236] conv5 needs backward computation.
I0107 22:33:57.586062 14352 net.cpp:236] relu4 needs backward computation.
I0107 22:33:57.586073 14352 net.cpp:236] conv4 needs backward computation.
I0107 22:33:57.586084 14352 net.cpp:236] relu3 needs backward computation.
I0107 22:33:57.586094 14352 net.cpp:236] conv3 needs backward computation.
I0107 22:33:57.586105 14352 net.cpp:236] norm2 needs backward computation.
I0107 22:33:57.586115 14352 net.cpp:236] pool2 needs backward computation.
I0107 22:33:57.586127 14352 net.cpp:236] relu2 needs backward computation.
I0107 22:33:57.586138 14352 net.cpp:236] conv2 needs backward computation.
I0107 22:33:57.586149 14352 net.cpp:236] norm1 needs backward computation.
I0107 22:33:57.586160 14352 net.cpp:236] pool1 needs backward computation.
I0107 22:33:57.586171 14352 net.cpp:236] relu1 needs backward computation.
I0107 22:33:57.586181 14352 net.cpp:236] conv1 needs backward computation.
I0107 22:33:57.586192 14352 net.cpp:240] data does not need backward computation.
I0107 22:33:57.586202 14352 net.cpp:283] This network produces output loss: 50%-fire-rate
I0107 22:33:57.586213 14352 net.cpp:283] This network produces output loss: classfication-error
I0107 22:33:57.586225 14352 net.cpp:283] This network produces output loss: forcing-binary
I0107 22:33:57.586251 14352 net.cpp:297] Network initialization done.
I0107 22:33:57.586258 14352 net.cpp:298] Memory required for data: 219568908
I0107 22:33:57.586906 14352 solver.cpp:186] Creating test net (#0) specified by net file: ./examples/SSDH/train_val.prototxt
I0107 22:33:57.586956 14352 net.cpp:339] The NetState phase (1) differed from the phase (0) specified by a rule in layer data
I0107 22:33:57.587152 14352 net.cpp:50] Initializing net from parameters:
name: "CaffeNet"
state {
phase: TEST
}
layer {
name: "data"
type: "Data"
top: "data"
top: "label"
include {
phase: TEST
}
transform_param {
mirror: true
crop_size: 227
mean_file: "data/ilsvrc12/imagenet_mean.binaryproto"
}
data_param {
source: "data/cifar10/cifar10_val_leveldb"
batch_size: 32
}
}
layer {
name: "conv1"
type: "Convolution"
bottom: "data"
top: "conv1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 96
kernel_size: 11
stride: 4
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "relu1"
type: "ReLU"
bottom: "conv1"
top: "conv1"
}
layer {
name: "pool1"
type: "Pooling"
bottom: "conv1"
top: "pool1"
pooling_param {
pool: MAX
kernel_size: 3
stride: 2
}
}
layer {
name: "norm1"
type: "LRN"
bottom: "pool1"
top: "norm1"
lrn_param {
local_size: 5
alpha: 0.0001
beta: 0.75
}
}
layer {
name: "conv2"
type: "Convolution"
bottom: "norm1"
top: "conv2"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 256
pad: 2
kernel_size: 5
group: 2
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 1
}
}
}
layer {
name: "relu2"
type: "ReLU"
bottom: "conv2"
top: "conv2"
}
layer {
name: "pool2"
type: "Pooling"
bottom: "conv2"
top: "pool2"
pooling_param {
pool: MAX
kernel_size: 3
stride: 2
}
}
layer {
name: "norm2"
type: "LRN"
bottom: "pool2"
top: "norm2"
lrn_param {
local_size: 5
alpha: 0.0001
beta: 0.75
}
}
layer {
name: "conv3"
type: "Convolution"
bottom: "norm2"
top: "conv3"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 384
pad: 1
kernel_size: 3
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "relu3"
type: "ReLU"
bottom: "conv3"
top: "conv3"
}
layer {
name: "conv4"
type: "Convolution"
bottom: "conv3"
top: "conv4"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 384
pad: 1
kernel_size: 3
group: 2
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 1
}
}
}
layer {
name: "relu4"
type: "ReLU"
bottom: "conv4"
top: "conv4"
}
layer {
name: "conv5"
type: "Convolution"
bottom: "conv4"
top: "conv5"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 256
pad: 1
kernel_size: 3
group: 2
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 1
}
}
}
layer {
name: "relu5"
type: "ReLU"
bottom: "conv5"
top: "conv5"
}
layer {
name: "pool5"
type: "Pooling"
bottom: "conv5"
top: "pool5"
pooling_param {
pool: MAX
kernel_size: 3
stride: 2
}
}
layer {
name: "fc6"
type: "InnerProduct"
bottom: "pool5"
top: "fc6"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
inner_product_param {
num_output: 4096
weight_filler {
type: "gaussian"
std: 0.005
}
bias_filler {
type: "constant"
value: 1
}
}
}
layer {
name: "relu6"
type: "ReLU"
bottom: "fc6"
top: "fc6"
}
layer {
name: "drop6"
type: "Dropout"
bottom: "fc6"
top: "fc6"
dropout_param {
dropout_ratio: 0.5
}
}
layer {
name: "fc7"
type: "InnerProduct"
bottom: "fc6"
top: "fc7"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
inner_product_param {
num_output: 4096
weight_filler {
type: "gaussian"
std: 0.005
}
bias_filler {
type: "constant"
value: 1
}
}
}
layer {
name: "relu7"
type: "ReLU"
bottom: "fc7"
top: "fc7"
}
layer {
name: "drop7"
type: "Dropout"
bottom: "fc7"
top: "fc7"
dropout_param {
dropout_ratio: 0.5
}
}
layer {
name: "latent_layer"
type: "InnerProduct"
bottom: "fc7"
top: "latent_layer"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
inner_product_param {
num_output: 48
weight_filler {
type: "gaussian"
std: 0.005
}
bias_filler {