resnet152
Find this model in the ResNetV2 model summary
resnet152 Model Summary Plots
resnet152 Model Selected Details
layer_type
N
M
Q
alpha
D
alpha-hat
log_SN
% Rand
num_traps
num_fingers
rank_loss
layer_id
1
CONV2D
64
3
21.33
2.02
0.08
2.87
1.42
87.67
94
0
0
7
CONV2D
64
64
1.00
1.44
0.16
0.92
0.64
78.35
5
0
2
9
CONV2D
64
64
1.00
2.01
0.05
1.48
0.73
74.36
26
0
46
11
CONV2D
256
64
4.00
3.10
0.06
3.21
1.03
69.63
4
0
5
15
CONV2D
256
64
4.00
2.20
0.20
3.18
1.44
78.79
6
8
0
18
CONV2D
256
64
4.00
2.62
0.14
1.71
0.65
79.73
1
1
1
20
CONV2D
64
64
1.00
1.86
0.09
1.00
0.54
79.46
20
1
9
22
CONV2D
256
64
4.00
1.91
0.19
1.07
0.56
86.59
3
3
0
26
CONV2D
256
64
4.00
2.46
0.15
1.24
0.51
83.75
0
2
0
28
CONV2D
64
64
1.00
1.77
0.10
0.53
0.30
82.82
12
0
5
30
CONV2D
256
64
4.00
4.61
0.15
2.03
0.44
87.58
1
1
0
35
CONV2D
256
128
2.00
2.38
0.12
1.70
0.72
83.34
0
0
0
37
CONV2D
128
128
1.00
2.99
0.09
0.66
0.22
85.35
15
0
7
39
CONV2D
512
128
4.00
3.26
0.12
1.71
0.52
83.78
0
0
0
43
CONV2D
512
256
2.00
1.90
0.07
2.11
1.11
67.04
6
0
0
46
CONV2D
512
128
4.00
2.15
0.10
1.46
0.68
67.44
1
0
0
48
CONV2D
128
128
1.00
1.85
0.05
0.99
0.53
66.46
30
0
9
50
CONV2D
512
128
4.00
1.55
0.15
0.92
0.59
75.19
1
4
0
54
CONV2D
512
128
4.00
2.09
0.13
1.02
0.49
77.66
1
1
0
56
CONV2D
128
128
1.00
2.28
0.07
0.48
0.21
77.62
25
0
7
58
CONV2D
512
128
4.00
2.15
0.16
1.04
0.48
80.30
0
4
0
62
CONV2D
512
128
4.00
3.14
0.10
1.40
0.45
79.27
0
0
0
64
CONV2D
128
128
1.00
1.89
0.07
0.66
0.35
77.58
18
0
5
66
CONV2D
512
128
4.00
1.89
0.13
0.95
0.50
80.03
1
1
0
70
CONV2D
512
128
4.00
1.59
0.12
0.90
0.57
72.55
0
3
0
72
CONV2D
128
128
1.00
1.99
0.05
0.63
0.32
74.77
18
0
5
74
CONV2D
512
128
4.00
1.54
0.15
0.59
0.38
76.95
1
2
0
78
CONV2D
512
128
4.00
2.67
0.12
0.93
0.35
80.07
0
0
1
80
CONV2D
128
128
1.00
2.09
0.08
0.15
0.07
82.03
15
0
12
82
CONV2D
512
128
4.00
3.10
0.10
1.13
0.36
81.06
0
0
0
86
CONV2D
512
128
4.00
2.57
0.10
1.56
0.61
76.41
0
0
0
88
CONV2D
128
128
1.00
2.13
0.05
0.54
0.25
77.74
20
0
8
90
CONV2D
512
128
4.00
3.53
0.12
1.26
0.36
80.92
1
0
0
94
CONV2D
512
128
4.00
2.38
0.13
1.07
0.45
82.34
0
2
0
96
CONV2D
128
128
1.00
2.85
0.07
0.52
0.18
86.11
17
0
7
98
CONV2D
512
128
4.00
3.29
0.07
1.70
0.52
81.14
1
0
0
103
CONV2D
512
256
2.00
2.94
0.10
2.44
0.83
80.92
0
0
0
105
CONV2D
256
256
1.00
4.17
0.08
0.04
0.01
91.21
39
0
9
107
CONV2D
1024
256
4.00
3.88
0.12
2.46
0.63
82.92
0
1
0
111
CONV2D
1024
512
2.00
2.59
0.06
2.40
0.93
74.34
6
0
0
114
CONV2D
1024
256
4.00
1.57
0.10
0.75
0.48
69.05
1
0
0
116
CONV2D
256
256
1.00
2.03
0.07
0.33
0.16
75.55
30
0
14
118
CONV2D
1024
256
4.00
2.90
0.11
1.80
0.62
76.82
4
1
0
122
CONV2D
1024
256
4.00
1.55
0.11
0.41
0.26
72.38
1
0
0
124
CONV2D
256
256
1.00
2.13
0.05
0.49
0.23
71.80
26
0
15
126
CONV2D
1024
256
4.00
2.02
0.11
1.01
0.50
76.96
0
1
0
130
CONV2D
1024
256
4.00
1.62
0.10
0.41
0.25
73.05
2
1
0
132
CONV2D
256
256
1.00
2.05
0.08
0.15
0.07
75.34
20
1
16
134
CONV2D
1024
256
4.00
1.66
0.11
0.68
0.41
76.40
2
1
0
138
CONV2D
1024
256
4.00
1.68
0.06
0.76
0.45
66.50
0
0
0
140
CONV2D
256
256
1.00
2.03
0.05
0.51
0.25
73.66
29
0
16
142
CONV2D
1024
256
4.00
1.69
0.11
0.79
0.46
71.56
1
0
0
146
CONV2D
1024
256
4.00
1.64
0.11
0.61
0.38
76.51
2
0
0
148
CONV2D
256
256
1.00
2.23
0.07
-0.08
-0.04
79.64
26
0
14
150
CONV2D
1024
256
4.00
2.01
0.11
0.63
0.31
80.09
0
1
0
154
CONV2D
1024
256
4.00
2.80
0.10
1.04
0.37
76.72
1
0
0
156
CONV2D
256
256
1.00
2.13
0.06
0.31
0.14
77.65
19
0
16
158
CONV2D
1024
256
4.00
1.94
0.12
0.89
0.46
77.72
1
1
0
162
CONV2D
1024
256
4.00
1.80
0.10
0.64
0.36
75.39
1
1
0
164
CONV2D
256
256
1.00
1.94
0.08
-0.04
-0.02
77.48
10
0
14
166
CONV2D
1024
256
4.00
2.15
0.09
0.69
0.32
75.56
1
0
0
170
CONV2D
1024
256
4.00
1.76
0.11
0.49
0.28
77.65
2
0
0
172
CONV2D
256
256
1.00
2.08
0.07
-0.06
-0.03
78.67
20
0
12
174
CONV2D
1024
256
4.00
2.22
0.09
1.06
0.48
75.47
1
0
0
178
CONV2D
1024
256
4.00
2.34
0.10
0.92
0.39
78.93
0
0
0
180
CONV2D
256
256
1.00
3.28
0.05
0.36
0.11
82.69
32
0
11
182
CONV2D
1024
256
4.00
3.34
0.07
1.79
0.54
78.47
0
0
0
186
CONV2D
1024
256
4.00
1.74
0.10
0.76
0.44
76.76
3
0
0
188
CONV2D
256
256
1.00
1.99
0.08
0.23
0.11
79.20
23
0
12
190
CONV2D
1024
256
4.00
1.95
0.11
0.88
0.45
77.32
0
2
0
194
CONV2D
1024
256
4.00
2.80
0.09
1.14
0.41
77.40
0
0
0
196
CONV2D
256
256
1.00
2.10
0.05
0.32
0.15
77.97
14
0
15
198
CONV2D
1024
256
4.00
1.74
0.12
0.48
0.28
78.28
1
1
0
202
CONV2D
1024
256
4.00
2.60
0.10
0.69
0.26
82.25
1
0
0
204
CONV2D
256
256
1.00
2.48
0.05
-0.14
-0.06
80.13
15
0
15
206
CONV2D
1024
256
4.00
2.21
0.08
0.74
0.33
77.60
1
0
0
210
CONV2D
1024
256
4.00
4.00
0.12
1.46
0.37
84.09
0
1
0
212
CONV2D
256
256
1.00
2.67
0.04
-0.04
-0.01
85.63
33
0
13
214
CONV2D
1024
256
4.00
2.61
0.12
1.15
0.44
84.08
2
1
0
218
CONV2D
1024
256
4.00
1.92
0.11
0.79
0.41
79.99
0
1
0
220
CONV2D
256
256
1.00
2.20
0.05
0.53
0.24
78.80
20
0
14
222
CONV2D
1024
256
4.00
3.55
0.11
1.54
0.43
78.55
1
1
0
226
CONV2D
1024
256
4.00
1.97
0.09
0.65
0.33
78.01
0
0
0
228
CONV2D
256
256
1.00
1.98
0.07
-0.16
-0.08
76.28
10
0
15
230
CONV2D
1024
256
4.00
1.91
0.10
0.77
0.40
75.86
1
1
0
234
CONV2D
1024
256
4.00
2.21
0.10
0.64
0.29
81.71
0
1
0
236
CONV2D
256
256
1.00
2.34
0.05
0.16
0.07
80.10
23
0
17
238
CONV2D
1024
256
4.00
2.07
0.11
0.79
0.38
80.64
1
1
0
242
CONV2D
1024
256
4.00
2.41
0.08
0.92
0.38
81.94
0
0
0
244
CONV2D
256
256
1.00
3.45
0.03
-0.20
-0.06
88.93
36
0
11
246
CONV2D
1024
256
4.00
4.38
0.09
0.88
0.20
85.62
0
0
0
250
CONV2D
1024
256
4.00
4.14
0.10
1.27
0.31
83.76
0
0
0
252
CONV2D
256
256
1.00
3.20
0.06
-0.82
-0.26
88.04
26
0
10
254
CONV2D
1024
256
4.00
4.05
0.09
0.71
0.18
85.77
1
0
0
258
CONV2D
1024
256
4.00
2.87
0.10
0.91
0.32
82.81
0
0
0
260
CONV2D
256
256
1.00
2.84
0.06
-0.28
-0.10
85.69
24
0
12
262
CONV2D
1024
256
4.00
2.93
0.13
1.08
0.37
86.01
1
1
0
266
CONV2D
1024
256
4.00
3.49
0.06
1.14
0.33
85.30
0
0
0
268
CONV2D
256
256
1.00
2.62
0.03
0.08
0.03
82.83
14
0
11
270
CONV2D
1024
256
4.00
3.06
0.05
1.30
0.43
82.67
1
0
0
274
CONV2D
1024
256
4.00
2.08
0.08
1.26
0.61
79.15
0
0
0
276
CONV2D
256
256
1.00
3.17
0.05
0.14
0.04
86.68
31
0
8
278
CONV2D
1024
256
4.00
3.45
0.08
1.39
0.40
83.58
0
0
0
282
CONV2D
1024
256
4.00
2.40
0.13
0.80
0.33
86.11
0
4
0
284
CONV2D
256
256
1.00
2.94
0.03
-0.12
-0.04
87.32
25
0
12
286
CONV2D
1024
256
4.00
3.59
0.14
1.71
0.47
88.92
1
2
0
290
CONV2D
1024
256
4.00
2.97
0.11
0.68
0.23
87.33
0
0
0
292
CONV2D
256
256
1.00
3.20
0.03
-0.82
-0.26
88.22
13
0
14
294
CONV2D
1024
256
4.00
2.90
0.14
0.87
0.30
88.12
1
7
0
298
CONV2D
1024
256
4.00
3.60
0.08
1.47
0.41
86.70
0
0
0
300
CONV2D
256
256
1.00
4.10
0.04
-0.71
-0.17
94.19
26
0
12
302
CONV2D
1024
256
4.00
3.90
0.13
0.46
0.12
90.27
1
3
0
306
CONV2D
1024
256
4.00
2.62
0.13
0.93
0.35
88.28
1
2
0
308
CONV2D
256
256
1.00
3.46
0.04
0.33
0.09
89.53
17
0
12
310
CONV2D
1024
256
4.00
4.97
0.07
2.74
0.55
88.17
2
0
0
314
CONV2D
1024
256
4.00
3.67
0.09
1.34
0.36
88.95
0
0
0
316
CONV2D
256
256
1.00
5.30
0.03
-0.92
-0.17
95.42
17
0
12
318
CONV2D
1024
256
4.00
3.80
0.15
0.65
0.17
91.04
1
1
0
322
CONV2D
1024
256
4.00
2.94
0.07
1.71
0.58
83.80
0
0
0
324
CONV2D
256
256
1.00
4.90
0.04
-0.45
-0.09
92.46
14
0
11
326
CONV2D
1024
256
4.00
7.17
0.07
2.15
0.30
87.48
0
0
0
330
CONV2D
1024
256
4.00
4.21
0.06
1.75
0.42
88.02
1
0
0
332
CONV2D
256
256
1.00
2.90
0.02
0.73
0.25
84.59
18
0
12
334
CONV2D
1024
256
4.00
3.71
0.04
2.62
0.71
84.84
2
0
0
338
CONV2D
1024
256
4.00
3.39
0.10
1.25
0.37
90.45
0
1
0
340
CONV2D
256
256
1.00
5.01
0.05
-1.65
-0.33
95.83
11
0
11
342
CONV2D
1024
256
4.00
9.04
0.06
1.81
0.20
91.42
1
0
0
346
CONV2D
1024
256
4.00
4.65
0.07
2.23
0.48
91.90
0
0
0
348
CONV2D
256
256
1.00
3.34
0.07
-0.30
-0.09
89.59
13
0
14
350
CONV2D
1024
256
4.00
4.25
0.08
2.52
0.59
86.11
0
0
0
354
CONV2D
1024
256
4.00
2.85
0.05
1.68
0.59
83.73
0
0
0
356
CONV2D
256
256
1.00
4.18
0.02
-0.01
-0.00
91.43
10
0
11
358
CONV2D
1024
256
4.00
5.79
0.05
2.57
0.44
88.18
0
0
0
362
CONV2D
1024
256
4.00
3.91
0.13
2.03
0.52
93.19
0
2
0
364
CONV2D
256
256
1.00
3.91
0.08
-0.08
-0.02
91.89
19
0
10
366
CONV2D
1024
256
4.00
5.89
0.08
2.22
0.38
89.32
0
0
0
370
CONV2D
1024
256
4.00
4.58
0.05
2.23
0.49
91.36
0
0
0
372
CONV2D
256
256
1.00
2.98
0.05
0.10
0.03
86.30
14
0
9
374
CONV2D
1024
256
4.00
4.05
0.07
2.99
0.74
85.25
1
0
0
378
CONV2D
1024
256
4.00
5.77
0.04
2.48
0.43
92.12
0
0
0
380
CONV2D
256
256
1.00
3.55
0.07
-0.17
-0.05
90.26
20
0
11
382
CONV2D
1024
256
4.00
7.01
0.07
2.18
0.31
90.91
1
0
0
386
CONV2D
1024
256
4.00
2.19
0.08
1.21
0.55
77.60
4
0
0
388
CONV2D
256
256
1.00
2.82
0.06
0.62
0.22
78.43
21
0
12
390
CONV2D
1024
256
4.00
2.49
0.08
2.02
0.81
67.25
1
0
0
395
CONV2D
1024
512
2.00
3.74
0.05
3.20
0.85
86.71
0
0
0
397
CONV2D
512
512
1.00
6.00
0.05
2.29
0.38
96.31
22
0
11
399
CONV2D
2048
512
4.00
7.28
0.06
7.02
0.96
94.89
1
0
0
403
CONV2D
2048
1024
2.00
4.87
0.04
5.79
1.19
90.01
0
0
0
406
CONV2D
2048
512
4.00
6.67
0.05
5.35
0.80
89.51
1
0
0
408
CONV2D
512
512
1.00
3.58
0.03
2.94
0.82
86.04
19
0
14
410
CONV2D
2048
512
4.00
3.71
0.05
4.58
1.23
86.95
1
0
0
414
CONV2D
2048
512
4.00
4.27
0.09
6.10
1.43
86.90
1
0
0
416
CONV2D
512
512
1.00
3.56
0.07
2.44
0.68
84.86
25
0
16
418
CONV2D
2048
512
4.00
3.25
0.05
5.76
1.77
81.53
1
0
0
422
DENSE
2048
1000
2.05
4.64
0.03
6.67
1.44
93.28
30
0
1
resnet152 Layer Plots
Layer 1
Layer=1 | N=64 | M=3 | Q=21.33 | alpha=2.02 | D_ks=0.08 | alpha-hat=2.87 | num traps=94
Layer 7
Layer=7 | N=64 | M=64 | Q=1.00 | alpha=1.44 | D_ks=0.16 | alpha-hat=0.92 | num traps=5
Layer 9
Layer=9 | N=64 | M=64 | Q=1.00 | alpha=2.01 | D_ks=0.05 | alpha-hat=1.48 | num traps=26
Layer 11
Layer=11 | N=256 | M=64 | Q=4.00 | alpha=3.10 | D_ks=0.06 | alpha-hat=3.21 | num traps=4
Layer 15
Layer=15 | N=256 | M=64 | Q=4.00 | alpha=2.20 | D_ks=0.20 | alpha-hat=3.18 | num traps=6
Layer 18
Layer=18 | N=256 | M=64 | Q=4.00 | alpha=2.62 | D_ks=0.14 | alpha-hat=1.71 | num traps=1
Layer 20
Layer=20 | N=64 | M=64 | Q=1.00 | alpha=1.86 | D_ks=0.09 | alpha-hat=1.00 | num traps=20
Layer 22
Layer=22 | N=256 | M=64 | Q=4.00 | alpha=1.91 | D_ks=0.19 | alpha-hat=1.07 | num traps=3
Layer 26
Layer=26 | N=256 | M=64 | Q=4.00 | alpha=2.46 | D_ks=0.15 | alpha-hat=1.24 | num traps=0
Layer 28
Layer=28 | N=64 | M=64 | Q=1.00 | alpha=1.77 | D_ks=0.10 | alpha-hat=0.53 | num traps=12
Layer 30
Layer=30 | N=256 | M=64 | Q=4.00 | alpha=4.61 | D_ks=0.15 | alpha-hat=2.03 | num traps=1
Layer 35
Layer=35 | N=256 | M=128 | Q=2.00 | alpha=2.38 | D_ks=0.12 | alpha-hat=1.70 | num traps=0
Layer 37
Layer=37 | N=128 | M=128 | Q=1.00 | alpha=2.99 | D_ks=0.09 | alpha-hat=0.66 | num traps=15
Layer 39
Layer=39 | N=512 | M=128 | Q=4.00 | alpha=3.26 | D_ks=0.12 | alpha-hat=1.71 | num traps=0
Layer 43
Layer=43 | N=512 | M=256 | Q=2.00 | alpha=1.90 | D_ks=0.07 | alpha-hat=2.11 | num traps=6
Layer 46
Layer=46 | N=512 | M=128 | Q=4.00 | alpha=2.15 | D_ks=0.10 | alpha-hat=1.46 | num traps=1
Layer 48
Layer=48 | N=128 | M=128 | Q=1.00 | alpha=1.85 | D_ks=0.05 | alpha-hat=0.99 | num traps=30
Layer 50
Layer=50 | N=512 | M=128 | Q=4.00 | alpha=1.55 | D_ks=0.15 | alpha-hat=0.92 | num traps=1
Layer 54
Layer=54 | N=512 | M=128 | Q=4.00 | alpha=2.09 | D_ks=0.13 | alpha-hat=1.02 | num traps=1
Layer 56
Layer=56 | N=128 | M=128 | Q=1.00 | alpha=2.28 | D_ks=0.07 | alpha-hat=0.48 | num traps=25
Layer 58
Layer=58 | N=512 | M=128 | Q=4.00 | alpha=2.15 | D_ks=0.16 | alpha-hat=1.04 | num traps=0
Layer 62
Layer=62 | N=512 | M=128 | Q=4.00 | alpha=3.14 | D_ks=0.10 | alpha-hat=1.40 | num traps=0
Layer 64
Layer=64 | N=128 | M=128 | Q=1.00 | alpha=1.89 | D_ks=0.07 | alpha-hat=0.66 | num traps=18
Layer 66
Layer=66 | N=512 | M=128 | Q=4.00 | alpha=1.89 | D_ks=0.13 | alpha-hat=0.95 | num traps=1
Layer 70
Layer=70 | N=512 | M=128 | Q=4.00 | alpha=1.59 | D_ks=0.12 | alpha-hat=0.90 | num traps=0
Layer 72
Layer=72 | N=128 | M=128 | Q=1.00 | alpha=1.99 | D_ks=0.05 | alpha-hat=0.63 | num traps=18
Layer 74
Layer=74 | N=512 | M=128 | Q=4.00 | alpha=1.54 | D_ks=0.15 | alpha-hat=0.59 | num traps=1
Layer 78
Layer=78 | N=512 | M=128 | Q=4.00 | alpha=2.67 | D_ks=0.12 | alpha-hat=0.93 | num traps=0
Layer 80
Layer=80 | N=128 | M=128 | Q=1.00 | alpha=2.09 | D_ks=0.08 | alpha-hat=0.15 | num traps=15
Layer 82
Layer=82 | N=512 | M=128 | Q=4.00 | alpha=3.10 | D_ks=0.10 | alpha-hat=1.13 | num traps=0
Layer 86
Layer=86 | N=512 | M=128 | Q=4.00 | alpha=2.57 | D_ks=0.10 | alpha-hat=1.56 | num traps=0
Layer 88
Layer=88 | N=128 | M=128 | Q=1.00 | alpha=2.13 | D_ks=0.05 | alpha-hat=0.54 | num traps=20
Layer 90
Layer=90 | N=512 | M=128 | Q=4.00 | alpha=3.53 | D_ks=0.12 | alpha-hat=1.26 | num traps=1
Layer 94
Layer=94 | N=512 | M=128 | Q=4.00 | alpha=2.38 | D_ks=0.13 | alpha-hat=1.07 | num traps=0
Layer 96
Layer=96 | N=128 | M=128 | Q=1.00 | alpha=2.85 | D_ks=0.07 | alpha-hat=0.52 | num traps=17
Layer 98
Layer=98 | N=512 | M=128 | Q=4.00 | alpha=3.29 | D_ks=0.07 | alpha-hat=1.70 | num traps=1
Layer 103
Layer=103 | N=512 | M=256 | Q=2.00 | alpha=2.94 | D_ks=0.10 | alpha-hat=2.44 | num traps=0
Layer 105
Layer=105 | N=256 | M=256 | Q=1.00 | alpha=4.17 | D_ks=0.08 | alpha-hat=0.04 | num traps=39
Layer 107
Layer=107 | N=1024 | M=256 | Q=4.00 | alpha=3.88 | D_ks=0.12 | alpha-hat=2.46 | num traps=0
Layer 111
Layer=111 | N=1024 | M=512 | Q=2.00 | alpha=2.59 | D_ks=0.06 | alpha-hat=2.40 | num traps=6
Layer 114
Layer=114 | N=1024 | M=256 | Q=4.00 | alpha=1.57 | D_ks=0.10 | alpha-hat=0.75 | num traps=1
Layer 116
Layer=116 | N=256 | M=256 | Q=1.00 | alpha=2.03 | D_ks=0.07 | alpha-hat=0.33 | num traps=30
Layer 118
Layer=118 | N=1024 | M=256 | Q=4.00 | alpha=2.90 | D_ks=0.11 | alpha-hat=1.80 | num traps=4
Layer 122
Layer=122 | N=1024 | M=256 | Q=4.00 | alpha=1.55 | D_ks=0.11 | alpha-hat=0.41 | num traps=1
Layer 124
Layer=124 | N=256 | M=256 | Q=1.00 | alpha=2.13 | D_ks=0.05 | alpha-hat=0.49 | num traps=26
Layer 126
Layer=126 | N=1024 | M=256 | Q=4.00 | alpha=2.02 | D_ks=0.11 | alpha-hat=1.01 | num traps=0
Layer 130
Layer=130 | N=1024 | M=256 | Q=4.00 | alpha=1.62 | D_ks=0.10 | alpha-hat=0.41 | num traps=2
Layer 132
Layer=132 | N=256 | M=256 | Q=1.00 | alpha=2.05 | D_ks=0.08 | alpha-hat=0.15 | num traps=20
Layer 134
Layer=134 | N=1024 | M=256 | Q=4.00 | alpha=1.66 | D_ks=0.11 | alpha-hat=0.68 | num traps=2
Layer 138
Layer=138 | N=1024 | M=256 | Q=4.00 | alpha=1.68 | D_ks=0.06 | alpha-hat=0.76 | num traps=0
Layer 140
Layer=140 | N=256 | M=256 | Q=1.00 | alpha=2.03 | D_ks=0.05 | alpha-hat=0.51 | num traps=29
Layer 142
Layer=142 | N=1024 | M=256 | Q=4.00 | alpha=1.69 | D_ks=0.11 | alpha-hat=0.79 | num traps=1
Layer 146
Layer=146 | N=1024 | M=256 | Q=4.00 | alpha=1.64 | D_ks=0.11 | alpha-hat=0.61 | num traps=2
Layer 148
Layer=148 | N=256 | M=256 | Q=1.00 | alpha=2.23 | D_ks=0.07 | alpha-hat=-0.08 | num traps=26
Layer 150
Layer=150 | N=1024 | M=256 | Q=4.00 | alpha=2.01 | D_ks=0.11 | alpha-hat=0.63 | num traps=0
Layer 154
Layer=154 | N=1024 | M=256 | Q=4.00 | alpha=2.80 | D_ks=0.10 | alpha-hat=1.04 | num traps=1
Layer 156
Layer=156 | N=256 | M=256 | Q=1.00 | alpha=2.13 | D_ks=0.06 | alpha-hat=0.31 | num traps=19
Layer 158
Layer=158 | N=1024 | M=256 | Q=4.00 | alpha=1.94 | D_ks=0.12 | alpha-hat=0.89 | num traps=1
Layer 162
Layer=162 | N=1024 | M=256 | Q=4.00 | alpha=1.80 | D_ks=0.10 | alpha-hat=0.64 | num traps=1
Layer 164
Layer=164 | N=256 | M=256 | Q=1.00 | alpha=1.94 | D_ks=0.08 | alpha-hat=-0.04 | num traps=10
Layer 166
Layer=166 | N=1024 | M=256 | Q=4.00 | alpha=2.15 | D_ks=0.09 | alpha-hat=0.69 | num traps=1
Layer 170
Layer=170 | N=1024 | M=256 | Q=4.00 | alpha=1.76 | D_ks=0.11 | alpha-hat=0.49 | num traps=2
Layer 172
Layer=172 | N=256 | M=256 | Q=1.00 | alpha=2.08 | D_ks=0.07 | alpha-hat=-0.06 | num traps=20
Layer 174
Layer=174 | N=1024 | M=256 | Q=4.00 | alpha=2.22 | D_ks=0.09 | alpha-hat=1.06 | num traps=1
Layer 178
Layer=178 | N=1024 | M=256 | Q=4.00 | alpha=2.34 | D_ks=0.10 | alpha-hat=0.92 | num traps=0
Layer 180
Layer=180 | N=256 | M=256 | Q=1.00 | alpha=3.28 | D_ks=0.05 | alpha-hat=0.36 | num traps=32
Layer 182
Layer=182 | N=1024 | M=256 | Q=4.00 | alpha=3.34 | D_ks=0.07 | alpha-hat=1.79 | num traps=0
Layer 186
Layer=186 | N=1024 | M=256 | Q=4.00 | alpha=1.74 | D_ks=0.10 | alpha-hat=0.76 | num traps=3
Layer 188
Layer=188 | N=256 | M=256 | Q=1.00 | alpha=1.99 | D_ks=0.08 | alpha-hat=0.23 | num traps=23
Layer 190
Layer=190 | N=1024 | M=256 | Q=4.00 | alpha=1.95 | D_ks=0.11 | alpha-hat=0.88 | num traps=0
Layer 194
Layer=194 | N=1024 | M=256 | Q=4.00 | alpha=2.80 | D_ks=0.09 | alpha-hat=1.14 | num traps=0
Layer 196
Layer=196 | N=256 | M=256 | Q=1.00 | alpha=2.10 | D_ks=0.05 | alpha-hat=0.32 | num traps=14
Layer 198
Layer=198 | N=1024 | M=256 | Q=4.00 | alpha=1.74 | D_ks=0.12 | alpha-hat=0.48 | num traps=1
Layer 202
Layer=202 | N=1024 | M=256 | Q=4.00 | alpha=2.60 | D_ks=0.10 | alpha-hat=0.69 | num traps=1
Layer 204
Layer=204 | N=256 | M=256 | Q=1.00 | alpha=2.48 | D_ks=0.05 | alpha-hat=-0.14 | num traps=15
Layer 206
Layer=206 | N=1024 | M=256 | Q=4.00 | alpha=2.21 | D_ks=0.08 | alpha-hat=0.74 | num traps=1
Layer 210
Layer=210 | N=1024 | M=256 | Q=4.00 | alpha=4.00 | D_ks=0.12 | alpha-hat=1.46 | num traps=0
Layer 212
Layer=212 | N=256 | M=256 | Q=1.00 | alpha=2.67 | D_ks=0.04 | alpha-hat=-0.04 | num traps=33
Layer 214
Layer=214 | N=1024 | M=256 | Q=4.00 | alpha=2.61 | D_ks=0.12 | alpha-hat=1.15 | num traps=2
Layer 218
Layer=218 | N=1024 | M=256 | Q=4.00 | alpha=1.92 | D_ks=0.11 | alpha-hat=0.79 | num traps=0
Layer 220
Layer=220 | N=256 | M=256 | Q=1.00 | alpha=2.20 | D_ks=0.05 | alpha-hat=0.53 | num traps=20
Layer 222
Layer=222 | N=1024 | M=256 | Q=4.00 | alpha=3.55 | D_ks=0.11 | alpha-hat=1.54 | num traps=1
Layer 226
Layer=226 | N=1024 | M=256 | Q=4.00 | alpha=1.97 | D_ks=0.09 | alpha-hat=0.65 | num traps=0
Layer 228
Layer=228 | N=256 | M=256 | Q=1.00 | alpha=1.98 | D_ks=0.07 | alpha-hat=-0.16 | num traps=10
Layer 230
Layer=230 | N=1024 | M=256 | Q=4.00 | alpha=1.91 | D_ks=0.10 | alpha-hat=0.77 | num traps=1
Layer 234
Layer=234 | N=1024 | M=256 | Q=4.00 | alpha=2.21 | D_ks=0.10 | alpha-hat=0.64 | num traps=0
Layer 236
Layer=236 | N=256 | M=256 | Q=1.00 | alpha=2.34 | D_ks=0.05 | alpha-hat=0.16 | num traps=23
Layer 238
Layer=238 | N=1024 | M=256 | Q=4.00 | alpha=2.07 | D_ks=0.11 | alpha-hat=0.79 | num traps=1
Layer 242
Layer=242 | N=1024 | M=256 | Q=4.00 | alpha=2.41 | D_ks=0.08 | alpha-hat=0.92 | num traps=0
Layer 244
Layer=244 | N=256 | M=256 | Q=1.00 | alpha=3.45 | D_ks=0.03 | alpha-hat=-0.20 | num traps=36
Layer 246
Layer=246 | N=1024 | M=256 | Q=4.00 | alpha=4.38 | D_ks=0.09 | alpha-hat=0.88 | num traps=0
Layer 250
Layer=250 | N=1024 | M=256 | Q=4.00 | alpha=4.14 | D_ks=0.10 | alpha-hat=1.27 | num traps=0
Layer 252
Layer=252 | N=256 | M=256 | Q=1.00 | alpha=3.20 | D_ks=0.06 | alpha-hat=-0.82 | num traps=26
Layer 254
Layer=254 | N=1024 | M=256 | Q=4.00 | alpha=4.05 | D_ks=0.09 | alpha-hat=0.71 | num traps=1
Layer 258
Layer=258 | N=1024 | M=256 | Q=4.00 | alpha=2.87 | D_ks=0.10 | alpha-hat=0.91 | num traps=0
Layer 260
Layer=260 | N=256 | M=256 | Q=1.00 | alpha=2.84 | D_ks=0.06 | alpha-hat=-0.28 | num traps=24
Layer 262
Layer=262 | N=1024 | M=256 | Q=4.00 | alpha=2.93 | D_ks=0.13 | alpha-hat=1.08 | num traps=1
Layer 266
Layer=266 | N=1024 | M=256 | Q=4.00 | alpha=3.49 | D_ks=0.06 | alpha-hat=1.14 | num traps=0
Layer 268
Layer=268 | N=256 | M=256 | Q=1.00 | alpha=2.62 | D_ks=0.03 | alpha-hat=0.08 | num traps=14
Layer 270
Layer=270 | N=1024 | M=256 | Q=4.00 | alpha=3.06 | D_ks=0.05 | alpha-hat=1.30 | num traps=1
Layer 274
Layer=274 | N=1024 | M=256 | Q=4.00 | alpha=2.08 | D_ks=0.08 | alpha-hat=1.26 | num traps=0
Layer 276
Layer=276 | N=256 | M=256 | Q=1.00 | alpha=3.17 | D_ks=0.05 | alpha-hat=0.14 | num traps=31
Layer 278
Layer=278 | N=1024 | M=256 | Q=4.00 | alpha=3.45 | D_ks=0.08 | alpha-hat=1.39 | num traps=0
Layer 282
Layer=282 | N=1024 | M=256 | Q=4.00 | alpha=2.40 | D_ks=0.13 | alpha-hat=0.80 | num traps=0
Layer 284
Layer=284 | N=256 | M=256 | Q=1.00 | alpha=2.94 | D_ks=0.03 | alpha-hat=-0.12 | num traps=25
Layer 286
Layer=286 | N=1024 | M=256 | Q=4.00 | alpha=3.59 | D_ks=0.14 | alpha-hat=1.71 | num traps=1
Layer 290
Layer=290 | N=1024 | M=256 | Q=4.00 | alpha=2.97 | D_ks=0.11 | alpha-hat=0.68 | num traps=0
Layer 292
Layer=292 | N=256 | M=256 | Q=1.00 | alpha=3.20 | D_ks=0.03 | alpha-hat=-0.82 | num traps=13
Layer 294
Layer=294 | N=1024 | M=256 | Q=4.00 | alpha=2.90 | D_ks=0.14 | alpha-hat=0.87 | num traps=1
Layer 298
Layer=298 | N=1024 | M=256 | Q=4.00 | alpha=3.60 | D_ks=0.08 | alpha-hat=1.47 | num traps=0
Layer 300
Layer=300 | N=256 | M=256 | Q=1.00 | alpha=4.10 | D_ks=0.04 | alpha-hat=-0.71 | num traps=26
Layer 302
Layer=302 | N=1024 | M=256 | Q=4.00 | alpha=3.90 | D_ks=0.13 | alpha-hat=0.46 | num traps=1
Layer 306
Layer=306 | N=1024 | M=256 | Q=4.00 | alpha=2.62 | D_ks=0.13 | alpha-hat=0.93 | num traps=1
Layer 308
Layer=308 | N=256 | M=256 | Q=1.00 | alpha=3.46 | D_ks=0.04 | alpha-hat=0.33 | num traps=17
Layer 310
Layer=310 | N=1024 | M=256 | Q=4.00 | alpha=4.97 | D_ks=0.07 | alpha-hat=2.74 | num traps=2
Layer 314
Layer=314 | N=1024 | M=256 | Q=4.00 | alpha=3.67 | D_ks=0.09 | alpha-hat=1.34 | num traps=0
Layer 316
Layer=316 | N=256 | M=256 | Q=1.00 | alpha=5.30 | D_ks=0.03 | alpha-hat=-0.92 | num traps=17
Layer 318
Layer=318 | N=1024 | M=256 | Q=4.00 | alpha=3.80 | D_ks=0.15 | alpha-hat=0.65 | num traps=1
Layer 322
Layer=322 | N=1024 | M=256 | Q=4.00 | alpha=2.94 | D_ks=0.07 | alpha-hat=1.71 | num traps=0
Layer 324
Layer=324 | N=256 | M=256 | Q=1.00 | alpha=4.90 | D_ks=0.04 | alpha-hat=-0.45 | num traps=14
Layer 326
Layer=326 | N=1024 | M=256 | Q=4.00 | alpha=7.17 | D_ks=0.07 | alpha-hat=2.15 | num traps=0
Layer 330
Layer=330 | N=1024 | M=256 | Q=4.00 | alpha=4.21 | D_ks=0.06 | alpha-hat=1.75 | num traps=1
Layer 332
Layer=332 | N=256 | M=256 | Q=1.00 | alpha=2.90 | D_ks=0.02 | alpha-hat=0.73 | num traps=18
Layer 334
Layer=334 | N=1024 | M=256 | Q=4.00 | alpha=3.71 | D_ks=0.04 | alpha-hat=2.62 | num traps=2
Layer 338
Layer=338 | N=1024 | M=256 | Q=4.00 | alpha=3.39 | D_ks=0.10 | alpha-hat=1.25 | num traps=0
Layer 340
Layer=340 | N=256 | M=256 | Q=1.00 | alpha=5.01 | D_ks=0.05 | alpha-hat=-1.65 | num traps=11
Layer 342
Layer=342 | N=1024 | M=256 | Q=4.00 | alpha=9.04 | D_ks=0.06 | alpha-hat=1.81 | num traps=1
Layer 346
Layer=346 | N=1024 | M=256 | Q=4.00 | alpha=4.65 | D_ks=0.07 | alpha-hat=2.23 | num traps=0
Layer 348
Layer=348 | N=256 | M=256 | Q=1.00 | alpha=3.34 | D_ks=0.07 | alpha-hat=-0.30 | num traps=13
Layer 350
Layer=350 | N=1024 | M=256 | Q=4.00 | alpha=4.25 | D_ks=0.08 | alpha-hat=2.52 | num traps=0
Layer 354
Layer=354 | N=1024 | M=256 | Q=4.00 | alpha=2.85 | D_ks=0.05 | alpha-hat=1.68 | num traps=0
Layer 356
Layer=356 | N=256 | M=256 | Q=1.00 | alpha=4.18 | D_ks=0.02 | alpha-hat=-0.01 | num traps=10
Layer 358
Layer=358 | N=1024 | M=256 | Q=4.00 | alpha=5.79 | D_ks=0.05 | alpha-hat=2.57 | num traps=0
Layer 362
Layer=362 | N=1024 | M=256 | Q=4.00 | alpha=3.91 | D_ks=0.13 | alpha-hat=2.03 | num traps=0
Layer 364
Layer=364 | N=256 | M=256 | Q=1.00 | alpha=3.91 | D_ks=0.08 | alpha-hat=-0.08 | num traps=19
Layer 366
Layer=366 | N=1024 | M=256 | Q=4.00 | alpha=5.89 | D_ks=0.08 | alpha-hat=2.22 | num traps=0
Layer 370
Layer=370 | N=1024 | M=256 | Q=4.00 | alpha=4.58 | D_ks=0.05 | alpha-hat=2.23 | num traps=0
Layer 372
Layer=372 | N=256 | M=256 | Q=1.00 | alpha=2.98 | D_ks=0.05 | alpha-hat=0.10 | num traps=14
Layer 374
Layer=374 | N=1024 | M=256 | Q=4.00 | alpha=4.05 | D_ks=0.07 | alpha-hat=2.99 | num traps=1
Layer 378
Layer=378 | N=1024 | M=256 | Q=4.00 | alpha=5.77 | D_ks=0.04 | alpha-hat=2.48 | num traps=0
Layer 380
Layer=380 | N=256 | M=256 | Q=1.00 | alpha=3.55 | D_ks=0.07 | alpha-hat=-0.17 | num traps=20
Layer 382
Layer=382 | N=1024 | M=256 | Q=4.00 | alpha=7.01 | D_ks=0.07 | alpha-hat=2.18 | num traps=1
Layer 386
Layer=386 | N=1024 | M=256 | Q=4.00 | alpha=2.19 | D_ks=0.08 | alpha-hat=1.21 | num traps=4
Layer 388
Layer=388 | N=256 | M=256 | Q=1.00 | alpha=2.82 | D_ks=0.06 | alpha-hat=0.62 | num traps=21
Layer 390
Layer=390 | N=1024 | M=256 | Q=4.00 | alpha=2.49 | D_ks=0.08 | alpha-hat=2.02 | num traps=1
Layer 395
Layer=395 | N=1024 | M=512 | Q=2.00 | alpha=3.74 | D_ks=0.05 | alpha-hat=3.20 | num traps=0
Layer 397
Layer=397 | N=512 | M=512 | Q=1.00 | alpha=6.00 | D_ks=0.05 | alpha-hat=2.29 | num traps=22
Layer 399
Layer=399 | N=2048 | M=512 | Q=4.00 | alpha=7.28 | D_ks=0.06 | alpha-hat=7.02 | num traps=1
Layer 403
Layer=403 | N=2048 | M=1024 | Q=2.00 | alpha=4.87 | D_ks=0.04 | alpha-hat=5.79 | num traps=0
Layer 406
Layer=406 | N=2048 | M=512 | Q=4.00 | alpha=6.67 | D_ks=0.05 | alpha-hat=5.35 | num traps=1
Layer 408
Layer=408 | N=512 | M=512 | Q=1.00 | alpha=3.58 | D_ks=0.03 | alpha-hat=2.94 | num traps=19
Layer 410
Layer=410 | N=2048 | M=512 | Q=4.00 | alpha=3.71 | D_ks=0.05 | alpha-hat=4.58 | num traps=1
Layer 414
Layer=414 | N=2048 | M=512 | Q=4.00 | alpha=4.27 | D_ks=0.09 | alpha-hat=6.10 | num traps=1
Layer 416
Layer=416 | N=512 | M=512 | Q=1.00 | alpha=3.56 | D_ks=0.07 | alpha-hat=2.44 | num traps=25
Layer 418
Layer=418 | N=2048 | M=512 | Q=4.00 | alpha=3.25 | D_ks=0.05 | alpha-hat=5.76 | num traps=1
Layer 422
Layer=422 | N=2048 | M=1000 | Q=2.05 | alpha=4.64 | D_ks=0.03 | alpha-hat=6.67 | num traps=30
resnet152 Model Summary Plots
resnet152 Model Selected Details
| layer_type | N | M | Q | alpha | D | alpha-hat | log_SN | % Rand | num_traps | num_fingers | rank_loss | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| layer_id | ||||||||||||
| 1 | CONV2D | 64 | 3 | 21.33 | 2.02 | 0.08 | 2.87 | 1.42 | 87.67 | 94 | 0 | 0 |
| 7 | CONV2D | 64 | 64 | 1.00 | 1.44 | 0.16 | 0.92 | 0.64 | 78.35 | 5 | 0 | 2 |
| 9 | CONV2D | 64 | 64 | 1.00 | 2.01 | 0.05 | 1.48 | 0.73 | 74.36 | 26 | 0 | 46 |
| 11 | CONV2D | 256 | 64 | 4.00 | 3.10 | 0.06 | 3.21 | 1.03 | 69.63 | 4 | 0 | 5 |
| 15 | CONV2D | 256 | 64 | 4.00 | 2.20 | 0.20 | 3.18 | 1.44 | 78.79 | 6 | 8 | 0 |
| 18 | CONV2D | 256 | 64 | 4.00 | 2.62 | 0.14 | 1.71 | 0.65 | 79.73 | 1 | 1 | 1 |
| 20 | CONV2D | 64 | 64 | 1.00 | 1.86 | 0.09 | 1.00 | 0.54 | 79.46 | 20 | 1 | 9 |
| 22 | CONV2D | 256 | 64 | 4.00 | 1.91 | 0.19 | 1.07 | 0.56 | 86.59 | 3 | 3 | 0 |
| 26 | CONV2D | 256 | 64 | 4.00 | 2.46 | 0.15 | 1.24 | 0.51 | 83.75 | 0 | 2 | 0 |
| 28 | CONV2D | 64 | 64 | 1.00 | 1.77 | 0.10 | 0.53 | 0.30 | 82.82 | 12 | 0 | 5 |
| 30 | CONV2D | 256 | 64 | 4.00 | 4.61 | 0.15 | 2.03 | 0.44 | 87.58 | 1 | 1 | 0 |
| 35 | CONV2D | 256 | 128 | 2.00 | 2.38 | 0.12 | 1.70 | 0.72 | 83.34 | 0 | 0 | 0 |
| 37 | CONV2D | 128 | 128 | 1.00 | 2.99 | 0.09 | 0.66 | 0.22 | 85.35 | 15 | 0 | 7 |
| 39 | CONV2D | 512 | 128 | 4.00 | 3.26 | 0.12 | 1.71 | 0.52 | 83.78 | 0 | 0 | 0 |
| 43 | CONV2D | 512 | 256 | 2.00 | 1.90 | 0.07 | 2.11 | 1.11 | 67.04 | 6 | 0 | 0 |
| 46 | CONV2D | 512 | 128 | 4.00 | 2.15 | 0.10 | 1.46 | 0.68 | 67.44 | 1 | 0 | 0 |
| 48 | CONV2D | 128 | 128 | 1.00 | 1.85 | 0.05 | 0.99 | 0.53 | 66.46 | 30 | 0 | 9 |
| 50 | CONV2D | 512 | 128 | 4.00 | 1.55 | 0.15 | 0.92 | 0.59 | 75.19 | 1 | 4 | 0 |
| 54 | CONV2D | 512 | 128 | 4.00 | 2.09 | 0.13 | 1.02 | 0.49 | 77.66 | 1 | 1 | 0 |
| 56 | CONV2D | 128 | 128 | 1.00 | 2.28 | 0.07 | 0.48 | 0.21 | 77.62 | 25 | 0 | 7 |
| 58 | CONV2D | 512 | 128 | 4.00 | 2.15 | 0.16 | 1.04 | 0.48 | 80.30 | 0 | 4 | 0 |
| 62 | CONV2D | 512 | 128 | 4.00 | 3.14 | 0.10 | 1.40 | 0.45 | 79.27 | 0 | 0 | 0 |
| 64 | CONV2D | 128 | 128 | 1.00 | 1.89 | 0.07 | 0.66 | 0.35 | 77.58 | 18 | 0 | 5 |
| 66 | CONV2D | 512 | 128 | 4.00 | 1.89 | 0.13 | 0.95 | 0.50 | 80.03 | 1 | 1 | 0 |
| 70 | CONV2D | 512 | 128 | 4.00 | 1.59 | 0.12 | 0.90 | 0.57 | 72.55 | 0 | 3 | 0 |
| 72 | CONV2D | 128 | 128 | 1.00 | 1.99 | 0.05 | 0.63 | 0.32 | 74.77 | 18 | 0 | 5 |
| 74 | CONV2D | 512 | 128 | 4.00 | 1.54 | 0.15 | 0.59 | 0.38 | 76.95 | 1 | 2 | 0 |
| 78 | CONV2D | 512 | 128 | 4.00 | 2.67 | 0.12 | 0.93 | 0.35 | 80.07 | 0 | 0 | 1 |
| 80 | CONV2D | 128 | 128 | 1.00 | 2.09 | 0.08 | 0.15 | 0.07 | 82.03 | 15 | 0 | 12 |
| 82 | CONV2D | 512 | 128 | 4.00 | 3.10 | 0.10 | 1.13 | 0.36 | 81.06 | 0 | 0 | 0 |
| 86 | CONV2D | 512 | 128 | 4.00 | 2.57 | 0.10 | 1.56 | 0.61 | 76.41 | 0 | 0 | 0 |
| 88 | CONV2D | 128 | 128 | 1.00 | 2.13 | 0.05 | 0.54 | 0.25 | 77.74 | 20 | 0 | 8 |
| 90 | CONV2D | 512 | 128 | 4.00 | 3.53 | 0.12 | 1.26 | 0.36 | 80.92 | 1 | 0 | 0 |
| 94 | CONV2D | 512 | 128 | 4.00 | 2.38 | 0.13 | 1.07 | 0.45 | 82.34 | 0 | 2 | 0 |
| 96 | CONV2D | 128 | 128 | 1.00 | 2.85 | 0.07 | 0.52 | 0.18 | 86.11 | 17 | 0 | 7 |
| 98 | CONV2D | 512 | 128 | 4.00 | 3.29 | 0.07 | 1.70 | 0.52 | 81.14 | 1 | 0 | 0 |
| 103 | CONV2D | 512 | 256 | 2.00 | 2.94 | 0.10 | 2.44 | 0.83 | 80.92 | 0 | 0 | 0 |
| 105 | CONV2D | 256 | 256 | 1.00 | 4.17 | 0.08 | 0.04 | 0.01 | 91.21 | 39 | 0 | 9 |
| 107 | CONV2D | 1024 | 256 | 4.00 | 3.88 | 0.12 | 2.46 | 0.63 | 82.92 | 0 | 1 | 0 |
| 111 | CONV2D | 1024 | 512 | 2.00 | 2.59 | 0.06 | 2.40 | 0.93 | 74.34 | 6 | 0 | 0 |
| 114 | CONV2D | 1024 | 256 | 4.00 | 1.57 | 0.10 | 0.75 | 0.48 | 69.05 | 1 | 0 | 0 |
| 116 | CONV2D | 256 | 256 | 1.00 | 2.03 | 0.07 | 0.33 | 0.16 | 75.55 | 30 | 0 | 14 |
| 118 | CONV2D | 1024 | 256 | 4.00 | 2.90 | 0.11 | 1.80 | 0.62 | 76.82 | 4 | 1 | 0 |
| 122 | CONV2D | 1024 | 256 | 4.00 | 1.55 | 0.11 | 0.41 | 0.26 | 72.38 | 1 | 0 | 0 |
| 124 | CONV2D | 256 | 256 | 1.00 | 2.13 | 0.05 | 0.49 | 0.23 | 71.80 | 26 | 0 | 15 |
| 126 | CONV2D | 1024 | 256 | 4.00 | 2.02 | 0.11 | 1.01 | 0.50 | 76.96 | 0 | 1 | 0 |
| 130 | CONV2D | 1024 | 256 | 4.00 | 1.62 | 0.10 | 0.41 | 0.25 | 73.05 | 2 | 1 | 0 |
| 132 | CONV2D | 256 | 256 | 1.00 | 2.05 | 0.08 | 0.15 | 0.07 | 75.34 | 20 | 1 | 16 |
| 134 | CONV2D | 1024 | 256 | 4.00 | 1.66 | 0.11 | 0.68 | 0.41 | 76.40 | 2 | 1 | 0 |
| 138 | CONV2D | 1024 | 256 | 4.00 | 1.68 | 0.06 | 0.76 | 0.45 | 66.50 | 0 | 0 | 0 |
| 140 | CONV2D | 256 | 256 | 1.00 | 2.03 | 0.05 | 0.51 | 0.25 | 73.66 | 29 | 0 | 16 |
| 142 | CONV2D | 1024 | 256 | 4.00 | 1.69 | 0.11 | 0.79 | 0.46 | 71.56 | 1 | 0 | 0 |
| 146 | CONV2D | 1024 | 256 | 4.00 | 1.64 | 0.11 | 0.61 | 0.38 | 76.51 | 2 | 0 | 0 |
| 148 | CONV2D | 256 | 256 | 1.00 | 2.23 | 0.07 | -0.08 | -0.04 | 79.64 | 26 | 0 | 14 |
| 150 | CONV2D | 1024 | 256 | 4.00 | 2.01 | 0.11 | 0.63 | 0.31 | 80.09 | 0 | 1 | 0 |
| 154 | CONV2D | 1024 | 256 | 4.00 | 2.80 | 0.10 | 1.04 | 0.37 | 76.72 | 1 | 0 | 0 |
| 156 | CONV2D | 256 | 256 | 1.00 | 2.13 | 0.06 | 0.31 | 0.14 | 77.65 | 19 | 0 | 16 |
| 158 | CONV2D | 1024 | 256 | 4.00 | 1.94 | 0.12 | 0.89 | 0.46 | 77.72 | 1 | 1 | 0 |
| 162 | CONV2D | 1024 | 256 | 4.00 | 1.80 | 0.10 | 0.64 | 0.36 | 75.39 | 1 | 1 | 0 |
| 164 | CONV2D | 256 | 256 | 1.00 | 1.94 | 0.08 | -0.04 | -0.02 | 77.48 | 10 | 0 | 14 |
| 166 | CONV2D | 1024 | 256 | 4.00 | 2.15 | 0.09 | 0.69 | 0.32 | 75.56 | 1 | 0 | 0 |
| 170 | CONV2D | 1024 | 256 | 4.00 | 1.76 | 0.11 | 0.49 | 0.28 | 77.65 | 2 | 0 | 0 |
| 172 | CONV2D | 256 | 256 | 1.00 | 2.08 | 0.07 | -0.06 | -0.03 | 78.67 | 20 | 0 | 12 |
| 174 | CONV2D | 1024 | 256 | 4.00 | 2.22 | 0.09 | 1.06 | 0.48 | 75.47 | 1 | 0 | 0 |
| 178 | CONV2D | 1024 | 256 | 4.00 | 2.34 | 0.10 | 0.92 | 0.39 | 78.93 | 0 | 0 | 0 |
| 180 | CONV2D | 256 | 256 | 1.00 | 3.28 | 0.05 | 0.36 | 0.11 | 82.69 | 32 | 0 | 11 |
| 182 | CONV2D | 1024 | 256 | 4.00 | 3.34 | 0.07 | 1.79 | 0.54 | 78.47 | 0 | 0 | 0 |
| 186 | CONV2D | 1024 | 256 | 4.00 | 1.74 | 0.10 | 0.76 | 0.44 | 76.76 | 3 | 0 | 0 |
| 188 | CONV2D | 256 | 256 | 1.00 | 1.99 | 0.08 | 0.23 | 0.11 | 79.20 | 23 | 0 | 12 |
| 190 | CONV2D | 1024 | 256 | 4.00 | 1.95 | 0.11 | 0.88 | 0.45 | 77.32 | 0 | 2 | 0 |
| 194 | CONV2D | 1024 | 256 | 4.00 | 2.80 | 0.09 | 1.14 | 0.41 | 77.40 | 0 | 0 | 0 |
| 196 | CONV2D | 256 | 256 | 1.00 | 2.10 | 0.05 | 0.32 | 0.15 | 77.97 | 14 | 0 | 15 |
| 198 | CONV2D | 1024 | 256 | 4.00 | 1.74 | 0.12 | 0.48 | 0.28 | 78.28 | 1 | 1 | 0 |
| 202 | CONV2D | 1024 | 256 | 4.00 | 2.60 | 0.10 | 0.69 | 0.26 | 82.25 | 1 | 0 | 0 |
| 204 | CONV2D | 256 | 256 | 1.00 | 2.48 | 0.05 | -0.14 | -0.06 | 80.13 | 15 | 0 | 15 |
| 206 | CONV2D | 1024 | 256 | 4.00 | 2.21 | 0.08 | 0.74 | 0.33 | 77.60 | 1 | 0 | 0 |
| 210 | CONV2D | 1024 | 256 | 4.00 | 4.00 | 0.12 | 1.46 | 0.37 | 84.09 | 0 | 1 | 0 |
| 212 | CONV2D | 256 | 256 | 1.00 | 2.67 | 0.04 | -0.04 | -0.01 | 85.63 | 33 | 0 | 13 |
| 214 | CONV2D | 1024 | 256 | 4.00 | 2.61 | 0.12 | 1.15 | 0.44 | 84.08 | 2 | 1 | 0 |
| 218 | CONV2D | 1024 | 256 | 4.00 | 1.92 | 0.11 | 0.79 | 0.41 | 79.99 | 0 | 1 | 0 |
| 220 | CONV2D | 256 | 256 | 1.00 | 2.20 | 0.05 | 0.53 | 0.24 | 78.80 | 20 | 0 | 14 |
| 222 | CONV2D | 1024 | 256 | 4.00 | 3.55 | 0.11 | 1.54 | 0.43 | 78.55 | 1 | 1 | 0 |
| 226 | CONV2D | 1024 | 256 | 4.00 | 1.97 | 0.09 | 0.65 | 0.33 | 78.01 | 0 | 0 | 0 |
| 228 | CONV2D | 256 | 256 | 1.00 | 1.98 | 0.07 | -0.16 | -0.08 | 76.28 | 10 | 0 | 15 |
| 230 | CONV2D | 1024 | 256 | 4.00 | 1.91 | 0.10 | 0.77 | 0.40 | 75.86 | 1 | 1 | 0 |
| 234 | CONV2D | 1024 | 256 | 4.00 | 2.21 | 0.10 | 0.64 | 0.29 | 81.71 | 0 | 1 | 0 |
| 236 | CONV2D | 256 | 256 | 1.00 | 2.34 | 0.05 | 0.16 | 0.07 | 80.10 | 23 | 0 | 17 |
| 238 | CONV2D | 1024 | 256 | 4.00 | 2.07 | 0.11 | 0.79 | 0.38 | 80.64 | 1 | 1 | 0 |
| 242 | CONV2D | 1024 | 256 | 4.00 | 2.41 | 0.08 | 0.92 | 0.38 | 81.94 | 0 | 0 | 0 |
| 244 | CONV2D | 256 | 256 | 1.00 | 3.45 | 0.03 | -0.20 | -0.06 | 88.93 | 36 | 0 | 11 |
| 246 | CONV2D | 1024 | 256 | 4.00 | 4.38 | 0.09 | 0.88 | 0.20 | 85.62 | 0 | 0 | 0 |
| 250 | CONV2D | 1024 | 256 | 4.00 | 4.14 | 0.10 | 1.27 | 0.31 | 83.76 | 0 | 0 | 0 |
| 252 | CONV2D | 256 | 256 | 1.00 | 3.20 | 0.06 | -0.82 | -0.26 | 88.04 | 26 | 0 | 10 |
| 254 | CONV2D | 1024 | 256 | 4.00 | 4.05 | 0.09 | 0.71 | 0.18 | 85.77 | 1 | 0 | 0 |
| 258 | CONV2D | 1024 | 256 | 4.00 | 2.87 | 0.10 | 0.91 | 0.32 | 82.81 | 0 | 0 | 0 |
| 260 | CONV2D | 256 | 256 | 1.00 | 2.84 | 0.06 | -0.28 | -0.10 | 85.69 | 24 | 0 | 12 |
| 262 | CONV2D | 1024 | 256 | 4.00 | 2.93 | 0.13 | 1.08 | 0.37 | 86.01 | 1 | 1 | 0 |
| 266 | CONV2D | 1024 | 256 | 4.00 | 3.49 | 0.06 | 1.14 | 0.33 | 85.30 | 0 | 0 | 0 |
| 268 | CONV2D | 256 | 256 | 1.00 | 2.62 | 0.03 | 0.08 | 0.03 | 82.83 | 14 | 0 | 11 |
| 270 | CONV2D | 1024 | 256 | 4.00 | 3.06 | 0.05 | 1.30 | 0.43 | 82.67 | 1 | 0 | 0 |
| 274 | CONV2D | 1024 | 256 | 4.00 | 2.08 | 0.08 | 1.26 | 0.61 | 79.15 | 0 | 0 | 0 |
| 276 | CONV2D | 256 | 256 | 1.00 | 3.17 | 0.05 | 0.14 | 0.04 | 86.68 | 31 | 0 | 8 |
| 278 | CONV2D | 1024 | 256 | 4.00 | 3.45 | 0.08 | 1.39 | 0.40 | 83.58 | 0 | 0 | 0 |
| 282 | CONV2D | 1024 | 256 | 4.00 | 2.40 | 0.13 | 0.80 | 0.33 | 86.11 | 0 | 4 | 0 |
| 284 | CONV2D | 256 | 256 | 1.00 | 2.94 | 0.03 | -0.12 | -0.04 | 87.32 | 25 | 0 | 12 |
| 286 | CONV2D | 1024 | 256 | 4.00 | 3.59 | 0.14 | 1.71 | 0.47 | 88.92 | 1 | 2 | 0 |
| 290 | CONV2D | 1024 | 256 | 4.00 | 2.97 | 0.11 | 0.68 | 0.23 | 87.33 | 0 | 0 | 0 |
| 292 | CONV2D | 256 | 256 | 1.00 | 3.20 | 0.03 | -0.82 | -0.26 | 88.22 | 13 | 0 | 14 |
| 294 | CONV2D | 1024 | 256 | 4.00 | 2.90 | 0.14 | 0.87 | 0.30 | 88.12 | 1 | 7 | 0 |
| 298 | CONV2D | 1024 | 256 | 4.00 | 3.60 | 0.08 | 1.47 | 0.41 | 86.70 | 0 | 0 | 0 |
| 300 | CONV2D | 256 | 256 | 1.00 | 4.10 | 0.04 | -0.71 | -0.17 | 94.19 | 26 | 0 | 12 |
| 302 | CONV2D | 1024 | 256 | 4.00 | 3.90 | 0.13 | 0.46 | 0.12 | 90.27 | 1 | 3 | 0 |
| 306 | CONV2D | 1024 | 256 | 4.00 | 2.62 | 0.13 | 0.93 | 0.35 | 88.28 | 1 | 2 | 0 |
| 308 | CONV2D | 256 | 256 | 1.00 | 3.46 | 0.04 | 0.33 | 0.09 | 89.53 | 17 | 0 | 12 |
| 310 | CONV2D | 1024 | 256 | 4.00 | 4.97 | 0.07 | 2.74 | 0.55 | 88.17 | 2 | 0 | 0 |
| 314 | CONV2D | 1024 | 256 | 4.00 | 3.67 | 0.09 | 1.34 | 0.36 | 88.95 | 0 | 0 | 0 |
| 316 | CONV2D | 256 | 256 | 1.00 | 5.30 | 0.03 | -0.92 | -0.17 | 95.42 | 17 | 0 | 12 |
| 318 | CONV2D | 1024 | 256 | 4.00 | 3.80 | 0.15 | 0.65 | 0.17 | 91.04 | 1 | 1 | 0 |
| 322 | CONV2D | 1024 | 256 | 4.00 | 2.94 | 0.07 | 1.71 | 0.58 | 83.80 | 0 | 0 | 0 |
| 324 | CONV2D | 256 | 256 | 1.00 | 4.90 | 0.04 | -0.45 | -0.09 | 92.46 | 14 | 0 | 11 |
| 326 | CONV2D | 1024 | 256 | 4.00 | 7.17 | 0.07 | 2.15 | 0.30 | 87.48 | 0 | 0 | 0 |
| 330 | CONV2D | 1024 | 256 | 4.00 | 4.21 | 0.06 | 1.75 | 0.42 | 88.02 | 1 | 0 | 0 |
| 332 | CONV2D | 256 | 256 | 1.00 | 2.90 | 0.02 | 0.73 | 0.25 | 84.59 | 18 | 0 | 12 |
| 334 | CONV2D | 1024 | 256 | 4.00 | 3.71 | 0.04 | 2.62 | 0.71 | 84.84 | 2 | 0 | 0 |
| 338 | CONV2D | 1024 | 256 | 4.00 | 3.39 | 0.10 | 1.25 | 0.37 | 90.45 | 0 | 1 | 0 |
| 340 | CONV2D | 256 | 256 | 1.00 | 5.01 | 0.05 | -1.65 | -0.33 | 95.83 | 11 | 0 | 11 |
| 342 | CONV2D | 1024 | 256 | 4.00 | 9.04 | 0.06 | 1.81 | 0.20 | 91.42 | 1 | 0 | 0 |
| 346 | CONV2D | 1024 | 256 | 4.00 | 4.65 | 0.07 | 2.23 | 0.48 | 91.90 | 0 | 0 | 0 |
| 348 | CONV2D | 256 | 256 | 1.00 | 3.34 | 0.07 | -0.30 | -0.09 | 89.59 | 13 | 0 | 14 |
| 350 | CONV2D | 1024 | 256 | 4.00 | 4.25 | 0.08 | 2.52 | 0.59 | 86.11 | 0 | 0 | 0 |
| 354 | CONV2D | 1024 | 256 | 4.00 | 2.85 | 0.05 | 1.68 | 0.59 | 83.73 | 0 | 0 | 0 |
| 356 | CONV2D | 256 | 256 | 1.00 | 4.18 | 0.02 | -0.01 | -0.00 | 91.43 | 10 | 0 | 11 |
| 358 | CONV2D | 1024 | 256 | 4.00 | 5.79 | 0.05 | 2.57 | 0.44 | 88.18 | 0 | 0 | 0 |
| 362 | CONV2D | 1024 | 256 | 4.00 | 3.91 | 0.13 | 2.03 | 0.52 | 93.19 | 0 | 2 | 0 |
| 364 | CONV2D | 256 | 256 | 1.00 | 3.91 | 0.08 | -0.08 | -0.02 | 91.89 | 19 | 0 | 10 |
| 366 | CONV2D | 1024 | 256 | 4.00 | 5.89 | 0.08 | 2.22 | 0.38 | 89.32 | 0 | 0 | 0 |
| 370 | CONV2D | 1024 | 256 | 4.00 | 4.58 | 0.05 | 2.23 | 0.49 | 91.36 | 0 | 0 | 0 |
| 372 | CONV2D | 256 | 256 | 1.00 | 2.98 | 0.05 | 0.10 | 0.03 | 86.30 | 14 | 0 | 9 |
| 374 | CONV2D | 1024 | 256 | 4.00 | 4.05 | 0.07 | 2.99 | 0.74 | 85.25 | 1 | 0 | 0 |
| 378 | CONV2D | 1024 | 256 | 4.00 | 5.77 | 0.04 | 2.48 | 0.43 | 92.12 | 0 | 0 | 0 |
| 380 | CONV2D | 256 | 256 | 1.00 | 3.55 | 0.07 | -0.17 | -0.05 | 90.26 | 20 | 0 | 11 |
| 382 | CONV2D | 1024 | 256 | 4.00 | 7.01 | 0.07 | 2.18 | 0.31 | 90.91 | 1 | 0 | 0 |
| 386 | CONV2D | 1024 | 256 | 4.00 | 2.19 | 0.08 | 1.21 | 0.55 | 77.60 | 4 | 0 | 0 |
| 388 | CONV2D | 256 | 256 | 1.00 | 2.82 | 0.06 | 0.62 | 0.22 | 78.43 | 21 | 0 | 12 |
| 390 | CONV2D | 1024 | 256 | 4.00 | 2.49 | 0.08 | 2.02 | 0.81 | 67.25 | 1 | 0 | 0 |
| 395 | CONV2D | 1024 | 512 | 2.00 | 3.74 | 0.05 | 3.20 | 0.85 | 86.71 | 0 | 0 | 0 |
| 397 | CONV2D | 512 | 512 | 1.00 | 6.00 | 0.05 | 2.29 | 0.38 | 96.31 | 22 | 0 | 11 |
| 399 | CONV2D | 2048 | 512 | 4.00 | 7.28 | 0.06 | 7.02 | 0.96 | 94.89 | 1 | 0 | 0 |
| 403 | CONV2D | 2048 | 1024 | 2.00 | 4.87 | 0.04 | 5.79 | 1.19 | 90.01 | 0 | 0 | 0 |
| 406 | CONV2D | 2048 | 512 | 4.00 | 6.67 | 0.05 | 5.35 | 0.80 | 89.51 | 1 | 0 | 0 |
| 408 | CONV2D | 512 | 512 | 1.00 | 3.58 | 0.03 | 2.94 | 0.82 | 86.04 | 19 | 0 | 14 |
| 410 | CONV2D | 2048 | 512 | 4.00 | 3.71 | 0.05 | 4.58 | 1.23 | 86.95 | 1 | 0 | 0 |
| 414 | CONV2D | 2048 | 512 | 4.00 | 4.27 | 0.09 | 6.10 | 1.43 | 86.90 | 1 | 0 | 0 |
| 416 | CONV2D | 512 | 512 | 1.00 | 3.56 | 0.07 | 2.44 | 0.68 | 84.86 | 25 | 0 | 16 |
| 418 | CONV2D | 2048 | 512 | 4.00 | 3.25 | 0.05 | 5.76 | 1.77 | 81.53 | 1 | 0 | 0 |
| 422 | DENSE | 2048 | 1000 | 2.05 | 4.64 | 0.03 | 6.67 | 1.44 | 93.28 | 30 | 0 | 1 |
resnet152 Layer Plots
Layer 1
Layer=1 | N=64 | M=3 | Q=21.33 | alpha=2.02 | D_ks=0.08 | alpha-hat=2.87 | num traps=94
Layer 7
Layer=7 | N=64 | M=64 | Q=1.00 | alpha=1.44 | D_ks=0.16 | alpha-hat=0.92 | num traps=5
Layer 9
Layer=9 | N=64 | M=64 | Q=1.00 | alpha=2.01 | D_ks=0.05 | alpha-hat=1.48 | num traps=26
Layer 11
Layer=11 | N=256 | M=64 | Q=4.00 | alpha=3.10 | D_ks=0.06 | alpha-hat=3.21 | num traps=4
Layer 15
Layer=15 | N=256 | M=64 | Q=4.00 | alpha=2.20 | D_ks=0.20 | alpha-hat=3.18 | num traps=6
Layer 18
Layer=18 | N=256 | M=64 | Q=4.00 | alpha=2.62 | D_ks=0.14 | alpha-hat=1.71 | num traps=1
Layer 20
Layer=20 | N=64 | M=64 | Q=1.00 | alpha=1.86 | D_ks=0.09 | alpha-hat=1.00 | num traps=20
Layer 22
Layer=22 | N=256 | M=64 | Q=4.00 | alpha=1.91 | D_ks=0.19 | alpha-hat=1.07 | num traps=3
Layer 26
Layer=26 | N=256 | M=64 | Q=4.00 | alpha=2.46 | D_ks=0.15 | alpha-hat=1.24 | num traps=0
Layer 28
Layer=28 | N=64 | M=64 | Q=1.00 | alpha=1.77 | D_ks=0.10 | alpha-hat=0.53 | num traps=12
Layer 30
Layer=30 | N=256 | M=64 | Q=4.00 | alpha=4.61 | D_ks=0.15 | alpha-hat=2.03 | num traps=1
Layer 35
Layer=35 | N=256 | M=128 | Q=2.00 | alpha=2.38 | D_ks=0.12 | alpha-hat=1.70 | num traps=0
Layer 37
Layer=37 | N=128 | M=128 | Q=1.00 | alpha=2.99 | D_ks=0.09 | alpha-hat=0.66 | num traps=15
Layer 39
Layer=39 | N=512 | M=128 | Q=4.00 | alpha=3.26 | D_ks=0.12 | alpha-hat=1.71 | num traps=0
Layer 43
Layer=43 | N=512 | M=256 | Q=2.00 | alpha=1.90 | D_ks=0.07 | alpha-hat=2.11 | num traps=6
Layer 46
Layer=46 | N=512 | M=128 | Q=4.00 | alpha=2.15 | D_ks=0.10 | alpha-hat=1.46 | num traps=1
Layer 48
Layer=48 | N=128 | M=128 | Q=1.00 | alpha=1.85 | D_ks=0.05 | alpha-hat=0.99 | num traps=30
Layer 50
Layer=50 | N=512 | M=128 | Q=4.00 | alpha=1.55 | D_ks=0.15 | alpha-hat=0.92 | num traps=1
Layer 54
Layer=54 | N=512 | M=128 | Q=4.00 | alpha=2.09 | D_ks=0.13 | alpha-hat=1.02 | num traps=1
Layer 56
Layer=56 | N=128 | M=128 | Q=1.00 | alpha=2.28 | D_ks=0.07 | alpha-hat=0.48 | num traps=25
Layer 58
Layer=58 | N=512 | M=128 | Q=4.00 | alpha=2.15 | D_ks=0.16 | alpha-hat=1.04 | num traps=0
Layer 62
Layer=62 | N=512 | M=128 | Q=4.00 | alpha=3.14 | D_ks=0.10 | alpha-hat=1.40 | num traps=0
Layer 64
Layer=64 | N=128 | M=128 | Q=1.00 | alpha=1.89 | D_ks=0.07 | alpha-hat=0.66 | num traps=18
Layer 66
Layer=66 | N=512 | M=128 | Q=4.00 | alpha=1.89 | D_ks=0.13 | alpha-hat=0.95 | num traps=1
Layer 70
Layer=70 | N=512 | M=128 | Q=4.00 | alpha=1.59 | D_ks=0.12 | alpha-hat=0.90 | num traps=0
Layer 72
Layer=72 | N=128 | M=128 | Q=1.00 | alpha=1.99 | D_ks=0.05 | alpha-hat=0.63 | num traps=18
Layer 74
Layer=74 | N=512 | M=128 | Q=4.00 | alpha=1.54 | D_ks=0.15 | alpha-hat=0.59 | num traps=1
Layer 78
Layer=78 | N=512 | M=128 | Q=4.00 | alpha=2.67 | D_ks=0.12 | alpha-hat=0.93 | num traps=0
Layer 80
Layer=80 | N=128 | M=128 | Q=1.00 | alpha=2.09 | D_ks=0.08 | alpha-hat=0.15 | num traps=15
Layer 82
Layer=82 | N=512 | M=128 | Q=4.00 | alpha=3.10 | D_ks=0.10 | alpha-hat=1.13 | num traps=0
Layer 86
Layer=86 | N=512 | M=128 | Q=4.00 | alpha=2.57 | D_ks=0.10 | alpha-hat=1.56 | num traps=0
Layer 88
Layer=88 | N=128 | M=128 | Q=1.00 | alpha=2.13 | D_ks=0.05 | alpha-hat=0.54 | num traps=20
Layer 90
Layer=90 | N=512 | M=128 | Q=4.00 | alpha=3.53 | D_ks=0.12 | alpha-hat=1.26 | num traps=1
Layer 94
Layer=94 | N=512 | M=128 | Q=4.00 | alpha=2.38 | D_ks=0.13 | alpha-hat=1.07 | num traps=0
Layer 96
Layer=96 | N=128 | M=128 | Q=1.00 | alpha=2.85 | D_ks=0.07 | alpha-hat=0.52 | num traps=17
Layer 98
Layer=98 | N=512 | M=128 | Q=4.00 | alpha=3.29 | D_ks=0.07 | alpha-hat=1.70 | num traps=1
Layer 103
Layer=103 | N=512 | M=256 | Q=2.00 | alpha=2.94 | D_ks=0.10 | alpha-hat=2.44 | num traps=0
Layer 105
Layer=105 | N=256 | M=256 | Q=1.00 | alpha=4.17 | D_ks=0.08 | alpha-hat=0.04 | num traps=39
Layer 107
Layer=107 | N=1024 | M=256 | Q=4.00 | alpha=3.88 | D_ks=0.12 | alpha-hat=2.46 | num traps=0
Layer 111
Layer=111 | N=1024 | M=512 | Q=2.00 | alpha=2.59 | D_ks=0.06 | alpha-hat=2.40 | num traps=6
Layer 114
Layer=114 | N=1024 | M=256 | Q=4.00 | alpha=1.57 | D_ks=0.10 | alpha-hat=0.75 | num traps=1
Layer 116
Layer=116 | N=256 | M=256 | Q=1.00 | alpha=2.03 | D_ks=0.07 | alpha-hat=0.33 | num traps=30
Layer 118
Layer=118 | N=1024 | M=256 | Q=4.00 | alpha=2.90 | D_ks=0.11 | alpha-hat=1.80 | num traps=4
Layer 122
Layer=122 | N=1024 | M=256 | Q=4.00 | alpha=1.55 | D_ks=0.11 | alpha-hat=0.41 | num traps=1
Layer 124
Layer=124 | N=256 | M=256 | Q=1.00 | alpha=2.13 | D_ks=0.05 | alpha-hat=0.49 | num traps=26
Layer 126
Layer=126 | N=1024 | M=256 | Q=4.00 | alpha=2.02 | D_ks=0.11 | alpha-hat=1.01 | num traps=0
Layer 130
Layer=130 | N=1024 | M=256 | Q=4.00 | alpha=1.62 | D_ks=0.10 | alpha-hat=0.41 | num traps=2
Layer 132
Layer=132 | N=256 | M=256 | Q=1.00 | alpha=2.05 | D_ks=0.08 | alpha-hat=0.15 | num traps=20
Layer 134
Layer=134 | N=1024 | M=256 | Q=4.00 | alpha=1.66 | D_ks=0.11 | alpha-hat=0.68 | num traps=2
Layer 138
Layer=138 | N=1024 | M=256 | Q=4.00 | alpha=1.68 | D_ks=0.06 | alpha-hat=0.76 | num traps=0
Layer 140
Layer=140 | N=256 | M=256 | Q=1.00 | alpha=2.03 | D_ks=0.05 | alpha-hat=0.51 | num traps=29
Layer 142
Layer=142 | N=1024 | M=256 | Q=4.00 | alpha=1.69 | D_ks=0.11 | alpha-hat=0.79 | num traps=1
Layer 146
Layer=146 | N=1024 | M=256 | Q=4.00 | alpha=1.64 | D_ks=0.11 | alpha-hat=0.61 | num traps=2
Layer 148
Layer=148 | N=256 | M=256 | Q=1.00 | alpha=2.23 | D_ks=0.07 | alpha-hat=-0.08 | num traps=26
Layer 150
Layer=150 | N=1024 | M=256 | Q=4.00 | alpha=2.01 | D_ks=0.11 | alpha-hat=0.63 | num traps=0
Layer 154
Layer=154 | N=1024 | M=256 | Q=4.00 | alpha=2.80 | D_ks=0.10 | alpha-hat=1.04 | num traps=1
Layer 156
Layer=156 | N=256 | M=256 | Q=1.00 | alpha=2.13 | D_ks=0.06 | alpha-hat=0.31 | num traps=19
Layer 158
Layer=158 | N=1024 | M=256 | Q=4.00 | alpha=1.94 | D_ks=0.12 | alpha-hat=0.89 | num traps=1
Layer 162
Layer=162 | N=1024 | M=256 | Q=4.00 | alpha=1.80 | D_ks=0.10 | alpha-hat=0.64 | num traps=1
Layer 164
Layer=164 | N=256 | M=256 | Q=1.00 | alpha=1.94 | D_ks=0.08 | alpha-hat=-0.04 | num traps=10
Layer 166
Layer=166 | N=1024 | M=256 | Q=4.00 | alpha=2.15 | D_ks=0.09 | alpha-hat=0.69 | num traps=1
Layer 170
Layer=170 | N=1024 | M=256 | Q=4.00 | alpha=1.76 | D_ks=0.11 | alpha-hat=0.49 | num traps=2
Layer 172
Layer=172 | N=256 | M=256 | Q=1.00 | alpha=2.08 | D_ks=0.07 | alpha-hat=-0.06 | num traps=20
Layer 174
Layer=174 | N=1024 | M=256 | Q=4.00 | alpha=2.22 | D_ks=0.09 | alpha-hat=1.06 | num traps=1
Layer 178
Layer=178 | N=1024 | M=256 | Q=4.00 | alpha=2.34 | D_ks=0.10 | alpha-hat=0.92 | num traps=0
Layer 180
Layer=180 | N=256 | M=256 | Q=1.00 | alpha=3.28 | D_ks=0.05 | alpha-hat=0.36 | num traps=32
Layer 182
Layer=182 | N=1024 | M=256 | Q=4.00 | alpha=3.34 | D_ks=0.07 | alpha-hat=1.79 | num traps=0
Layer 186
Layer=186 | N=1024 | M=256 | Q=4.00 | alpha=1.74 | D_ks=0.10 | alpha-hat=0.76 | num traps=3
Layer 188
Layer=188 | N=256 | M=256 | Q=1.00 | alpha=1.99 | D_ks=0.08 | alpha-hat=0.23 | num traps=23
Layer 190
Layer=190 | N=1024 | M=256 | Q=4.00 | alpha=1.95 | D_ks=0.11 | alpha-hat=0.88 | num traps=0
Layer 194
Layer=194 | N=1024 | M=256 | Q=4.00 | alpha=2.80 | D_ks=0.09 | alpha-hat=1.14 | num traps=0
Layer 196
Layer=196 | N=256 | M=256 | Q=1.00 | alpha=2.10 | D_ks=0.05 | alpha-hat=0.32 | num traps=14
Layer 198
Layer=198 | N=1024 | M=256 | Q=4.00 | alpha=1.74 | D_ks=0.12 | alpha-hat=0.48 | num traps=1
Layer 202
Layer=202 | N=1024 | M=256 | Q=4.00 | alpha=2.60 | D_ks=0.10 | alpha-hat=0.69 | num traps=1
Layer 204
Layer=204 | N=256 | M=256 | Q=1.00 | alpha=2.48 | D_ks=0.05 | alpha-hat=-0.14 | num traps=15
Layer 206
Layer=206 | N=1024 | M=256 | Q=4.00 | alpha=2.21 | D_ks=0.08 | alpha-hat=0.74 | num traps=1
Layer 210
Layer=210 | N=1024 | M=256 | Q=4.00 | alpha=4.00 | D_ks=0.12 | alpha-hat=1.46 | num traps=0
Layer 212
Layer=212 | N=256 | M=256 | Q=1.00 | alpha=2.67 | D_ks=0.04 | alpha-hat=-0.04 | num traps=33
Layer 214
Layer=214 | N=1024 | M=256 | Q=4.00 | alpha=2.61 | D_ks=0.12 | alpha-hat=1.15 | num traps=2
Layer 218
Layer=218 | N=1024 | M=256 | Q=4.00 | alpha=1.92 | D_ks=0.11 | alpha-hat=0.79 | num traps=0
Layer 220
Layer=220 | N=256 | M=256 | Q=1.00 | alpha=2.20 | D_ks=0.05 | alpha-hat=0.53 | num traps=20
Layer 222
Layer=222 | N=1024 | M=256 | Q=4.00 | alpha=3.55 | D_ks=0.11 | alpha-hat=1.54 | num traps=1
Layer 226
Layer=226 | N=1024 | M=256 | Q=4.00 | alpha=1.97 | D_ks=0.09 | alpha-hat=0.65 | num traps=0
Layer 228
Layer=228 | N=256 | M=256 | Q=1.00 | alpha=1.98 | D_ks=0.07 | alpha-hat=-0.16 | num traps=10
Layer 230
Layer=230 | N=1024 | M=256 | Q=4.00 | alpha=1.91 | D_ks=0.10 | alpha-hat=0.77 | num traps=1
Layer 234
Layer=234 | N=1024 | M=256 | Q=4.00 | alpha=2.21 | D_ks=0.10 | alpha-hat=0.64 | num traps=0
Layer 236
Layer=236 | N=256 | M=256 | Q=1.00 | alpha=2.34 | D_ks=0.05 | alpha-hat=0.16 | num traps=23
Layer 238
Layer=238 | N=1024 | M=256 | Q=4.00 | alpha=2.07 | D_ks=0.11 | alpha-hat=0.79 | num traps=1
Layer 242
Layer=242 | N=1024 | M=256 | Q=4.00 | alpha=2.41 | D_ks=0.08 | alpha-hat=0.92 | num traps=0
Layer 244
Layer=244 | N=256 | M=256 | Q=1.00 | alpha=3.45 | D_ks=0.03 | alpha-hat=-0.20 | num traps=36
Layer 246
Layer=246 | N=1024 | M=256 | Q=4.00 | alpha=4.38 | D_ks=0.09 | alpha-hat=0.88 | num traps=0
Layer 250
Layer=250 | N=1024 | M=256 | Q=4.00 | alpha=4.14 | D_ks=0.10 | alpha-hat=1.27 | num traps=0
Layer 252
Layer=252 | N=256 | M=256 | Q=1.00 | alpha=3.20 | D_ks=0.06 | alpha-hat=-0.82 | num traps=26
Layer 254
Layer=254 | N=1024 | M=256 | Q=4.00 | alpha=4.05 | D_ks=0.09 | alpha-hat=0.71 | num traps=1
Layer 258
Layer=258 | N=1024 | M=256 | Q=4.00 | alpha=2.87 | D_ks=0.10 | alpha-hat=0.91 | num traps=0
Layer 260
Layer=260 | N=256 | M=256 | Q=1.00 | alpha=2.84 | D_ks=0.06 | alpha-hat=-0.28 | num traps=24
Layer 262
Layer=262 | N=1024 | M=256 | Q=4.00 | alpha=2.93 | D_ks=0.13 | alpha-hat=1.08 | num traps=1
Layer 266
Layer=266 | N=1024 | M=256 | Q=4.00 | alpha=3.49 | D_ks=0.06 | alpha-hat=1.14 | num traps=0
Layer 268
Layer=268 | N=256 | M=256 | Q=1.00 | alpha=2.62 | D_ks=0.03 | alpha-hat=0.08 | num traps=14
Layer 270
Layer=270 | N=1024 | M=256 | Q=4.00 | alpha=3.06 | D_ks=0.05 | alpha-hat=1.30 | num traps=1
Layer 274
Layer=274 | N=1024 | M=256 | Q=4.00 | alpha=2.08 | D_ks=0.08 | alpha-hat=1.26 | num traps=0
Layer 276
Layer=276 | N=256 | M=256 | Q=1.00 | alpha=3.17 | D_ks=0.05 | alpha-hat=0.14 | num traps=31
Layer 278
Layer=278 | N=1024 | M=256 | Q=4.00 | alpha=3.45 | D_ks=0.08 | alpha-hat=1.39 | num traps=0
Layer 282
Layer=282 | N=1024 | M=256 | Q=4.00 | alpha=2.40 | D_ks=0.13 | alpha-hat=0.80 | num traps=0
Layer 284
Layer=284 | N=256 | M=256 | Q=1.00 | alpha=2.94 | D_ks=0.03 | alpha-hat=-0.12 | num traps=25
Layer 286
Layer=286 | N=1024 | M=256 | Q=4.00 | alpha=3.59 | D_ks=0.14 | alpha-hat=1.71 | num traps=1
Layer 290
Layer=290 | N=1024 | M=256 | Q=4.00 | alpha=2.97 | D_ks=0.11 | alpha-hat=0.68 | num traps=0
Layer 292
Layer=292 | N=256 | M=256 | Q=1.00 | alpha=3.20 | D_ks=0.03 | alpha-hat=-0.82 | num traps=13
Layer 294
Layer=294 | N=1024 | M=256 | Q=4.00 | alpha=2.90 | D_ks=0.14 | alpha-hat=0.87 | num traps=1
Layer 298
Layer=298 | N=1024 | M=256 | Q=4.00 | alpha=3.60 | D_ks=0.08 | alpha-hat=1.47 | num traps=0
Layer 300
Layer=300 | N=256 | M=256 | Q=1.00 | alpha=4.10 | D_ks=0.04 | alpha-hat=-0.71 | num traps=26
Layer 302
Layer=302 | N=1024 | M=256 | Q=4.00 | alpha=3.90 | D_ks=0.13 | alpha-hat=0.46 | num traps=1
Layer 306
Layer=306 | N=1024 | M=256 | Q=4.00 | alpha=2.62 | D_ks=0.13 | alpha-hat=0.93 | num traps=1
Layer 308
Layer=308 | N=256 | M=256 | Q=1.00 | alpha=3.46 | D_ks=0.04 | alpha-hat=0.33 | num traps=17
Layer 310
Layer=310 | N=1024 | M=256 | Q=4.00 | alpha=4.97 | D_ks=0.07 | alpha-hat=2.74 | num traps=2
Layer 314
Layer=314 | N=1024 | M=256 | Q=4.00 | alpha=3.67 | D_ks=0.09 | alpha-hat=1.34 | num traps=0
Layer 316
Layer=316 | N=256 | M=256 | Q=1.00 | alpha=5.30 | D_ks=0.03 | alpha-hat=-0.92 | num traps=17
Layer 318
Layer=318 | N=1024 | M=256 | Q=4.00 | alpha=3.80 | D_ks=0.15 | alpha-hat=0.65 | num traps=1
Layer 322
Layer=322 | N=1024 | M=256 | Q=4.00 | alpha=2.94 | D_ks=0.07 | alpha-hat=1.71 | num traps=0
Layer 324
Layer=324 | N=256 | M=256 | Q=1.00 | alpha=4.90 | D_ks=0.04 | alpha-hat=-0.45 | num traps=14
Layer 326
Layer=326 | N=1024 | M=256 | Q=4.00 | alpha=7.17 | D_ks=0.07 | alpha-hat=2.15 | num traps=0
Layer 330
Layer=330 | N=1024 | M=256 | Q=4.00 | alpha=4.21 | D_ks=0.06 | alpha-hat=1.75 | num traps=1
Layer 332
Layer=332 | N=256 | M=256 | Q=1.00 | alpha=2.90 | D_ks=0.02 | alpha-hat=0.73 | num traps=18
Layer 334
Layer=334 | N=1024 | M=256 | Q=4.00 | alpha=3.71 | D_ks=0.04 | alpha-hat=2.62 | num traps=2
Layer 338
Layer=338 | N=1024 | M=256 | Q=4.00 | alpha=3.39 | D_ks=0.10 | alpha-hat=1.25 | num traps=0
Layer 340
Layer=340 | N=256 | M=256 | Q=1.00 | alpha=5.01 | D_ks=0.05 | alpha-hat=-1.65 | num traps=11
Layer 342
Layer=342 | N=1024 | M=256 | Q=4.00 | alpha=9.04 | D_ks=0.06 | alpha-hat=1.81 | num traps=1
Layer 346
Layer=346 | N=1024 | M=256 | Q=4.00 | alpha=4.65 | D_ks=0.07 | alpha-hat=2.23 | num traps=0
Layer 348
Layer=348 | N=256 | M=256 | Q=1.00 | alpha=3.34 | D_ks=0.07 | alpha-hat=-0.30 | num traps=13
Layer 350
Layer=350 | N=1024 | M=256 | Q=4.00 | alpha=4.25 | D_ks=0.08 | alpha-hat=2.52 | num traps=0
Layer 354
Layer=354 | N=1024 | M=256 | Q=4.00 | alpha=2.85 | D_ks=0.05 | alpha-hat=1.68 | num traps=0
Layer 356
Layer=356 | N=256 | M=256 | Q=1.00 | alpha=4.18 | D_ks=0.02 | alpha-hat=-0.01 | num traps=10
Layer 358
Layer=358 | N=1024 | M=256 | Q=4.00 | alpha=5.79 | D_ks=0.05 | alpha-hat=2.57 | num traps=0
Layer 362
Layer=362 | N=1024 | M=256 | Q=4.00 | alpha=3.91 | D_ks=0.13 | alpha-hat=2.03 | num traps=0
Layer 364
Layer=364 | N=256 | M=256 | Q=1.00 | alpha=3.91 | D_ks=0.08 | alpha-hat=-0.08 | num traps=19
Layer 366
Layer=366 | N=1024 | M=256 | Q=4.00 | alpha=5.89 | D_ks=0.08 | alpha-hat=2.22 | num traps=0
Layer 370
Layer=370 | N=1024 | M=256 | Q=4.00 | alpha=4.58 | D_ks=0.05 | alpha-hat=2.23 | num traps=0
Layer 372
Layer=372 | N=256 | M=256 | Q=1.00 | alpha=2.98 | D_ks=0.05 | alpha-hat=0.10 | num traps=14
Layer 374
Layer=374 | N=1024 | M=256 | Q=4.00 | alpha=4.05 | D_ks=0.07 | alpha-hat=2.99 | num traps=1
Layer 378
Layer=378 | N=1024 | M=256 | Q=4.00 | alpha=5.77 | D_ks=0.04 | alpha-hat=2.48 | num traps=0
Layer 380
Layer=380 | N=256 | M=256 | Q=1.00 | alpha=3.55 | D_ks=0.07 | alpha-hat=-0.17 | num traps=20
Layer 382
Layer=382 | N=1024 | M=256 | Q=4.00 | alpha=7.01 | D_ks=0.07 | alpha-hat=2.18 | num traps=1
Layer 386
Layer=386 | N=1024 | M=256 | Q=4.00 | alpha=2.19 | D_ks=0.08 | alpha-hat=1.21 | num traps=4
Layer 388
Layer=388 | N=256 | M=256 | Q=1.00 | alpha=2.82 | D_ks=0.06 | alpha-hat=0.62 | num traps=21
Layer 390
Layer=390 | N=1024 | M=256 | Q=4.00 | alpha=2.49 | D_ks=0.08 | alpha-hat=2.02 | num traps=1
Layer 395
Layer=395 | N=1024 | M=512 | Q=2.00 | alpha=3.74 | D_ks=0.05 | alpha-hat=3.20 | num traps=0
Layer 397
Layer=397 | N=512 | M=512 | Q=1.00 | alpha=6.00 | D_ks=0.05 | alpha-hat=2.29 | num traps=22
Layer 399
Layer=399 | N=2048 | M=512 | Q=4.00 | alpha=7.28 | D_ks=0.06 | alpha-hat=7.02 | num traps=1
Layer 403
Layer=403 | N=2048 | M=1024 | Q=2.00 | alpha=4.87 | D_ks=0.04 | alpha-hat=5.79 | num traps=0
Layer 406
Layer=406 | N=2048 | M=512 | Q=4.00 | alpha=6.67 | D_ks=0.05 | alpha-hat=5.35 | num traps=1
Layer 408
Layer=408 | N=512 | M=512 | Q=1.00 | alpha=3.58 | D_ks=0.03 | alpha-hat=2.94 | num traps=19
Layer 410
Layer=410 | N=2048 | M=512 | Q=4.00 | alpha=3.71 | D_ks=0.05 | alpha-hat=4.58 | num traps=1
Layer 414
Layer=414 | N=2048 | M=512 | Q=4.00 | alpha=4.27 | D_ks=0.09 | alpha-hat=6.10 | num traps=1
Layer 416
Layer=416 | N=512 | M=512 | Q=1.00 | alpha=3.56 | D_ks=0.07 | alpha-hat=2.44 | num traps=25
Layer 418
Layer=418 | N=2048 | M=512 | Q=4.00 | alpha=3.25 | D_ks=0.05 | alpha-hat=5.76 | num traps=1
Layer 422
Layer=422 | N=2048 | M=1000 | Q=2.05 | alpha=4.64 | D_ks=0.03 | alpha-hat=6.67 | num traps=30