resnet101
Find this model in the ResNetV2 model summary
resnet101 Model Summary Plots
resnet101 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
2.10
0.08
3.03
1.44
88.49
92
0
0
7
CONV2D
64
64
1.00
1.39
0.17
0.81
0.58
83.96
1
1
0
9
CONV2D
64
64
1.00
1.91
0.05
1.50
0.78
75.74
22
0
3
11
CONV2D
256
64
4.00
2.37
0.18
2.54
1.07
75.69
2
3
0
15
CONV2D
256
64
4.00
3.84
0.08
5.56
1.45
78.65
8
0
0
18
CONV2D
256
64
4.00
1.87
0.14
1.18
0.63
81.86
0
0
0
20
CONV2D
64
64
1.00
2.69
0.08
1.58
0.59
81.31
18
0
4
22
CONV2D
256
64
4.00
2.87
0.19
1.70
0.59
89.00
0
6
0
26
CONV2D
256
64
4.00
2.26
0.17
1.15
0.51
83.99
0
8
0
28
CONV2D
64
64
1.00
2.29
0.10
0.75
0.33
83.83
16
0
2
30
CONV2D
256
64
4.00
5.74
0.09
2.81
0.49
87.61
0
0
0
35
CONV2D
256
128
2.00
1.68
0.14
1.28
0.77
81.17
0
1
0
37
CONV2D
128
128
1.00
2.64
0.10
0.78
0.30
85.61
14
1
6
39
CONV2D
512
128
4.00
3.10
0.11
1.68
0.54
84.62
1
0
0
43
CONV2D
512
256
2.00
1.93
0.08
1.83
0.95
71.87
6
0
0
46
CONV2D
512
128
4.00
2.02
0.12
0.90
0.45
77.98
0
3
0
48
CONV2D
128
128
1.00
1.77
0.07
0.63
0.36
75.68
23
0
9
50
CONV2D
512
128
4.00
1.62
0.15
1.16
0.71
83.07
1
4
0
54
CONV2D
512
128
4.00
3.58
0.08
1.89
0.53
84.30
0
0
1
56
CONV2D
128
128
1.00
2.39
0.07
0.73
0.31
80.81
22
0
10
58
CONV2D
512
128
4.00
2.06
0.15
1.24
0.60
84.67
0
8
0
62
CONV2D
512
128
4.00
2.72
0.09
1.58
0.58
80.93
0
0
0
64
CONV2D
128
128
1.00
2.11
0.09
0.37
0.18
83.31
21
1
5
66
CONV2D
512
128
4.00
4.07
0.09
2.19
0.54
83.65
2
0
0
71
CONV2D
512
256
2.00
3.34
0.13
3.01
0.90
82.29
0
1
0
73
CONV2D
256
256
1.00
3.79
0.08
0.22
0.06
91.47
39
0
8
75
CONV2D
1024
256
4.00
3.61
0.11
2.51
0.70
84.57
0
1
0
79
CONV2D
1024
512
2.00
2.59
0.05
2.34
0.90
74.15
7
0
0
82
CONV2D
1024
256
4.00
1.56
0.11
0.67
0.43
70.44
0
0
0
84
CONV2D
256
256
1.00
1.98
0.06
0.40
0.20
75.27
31
0
13
86
CONV2D
1024
256
4.00
3.64
0.07
1.94
0.53
78.14
1
0
0
90
CONV2D
1024
256
4.00
1.66
0.12
0.80
0.48
75.83
1
3
0
92
CONV2D
256
256
1.00
2.27
0.06
0.59
0.26
79.33
38
0
8
94
CONV2D
1024
256
4.00
2.55
0.08
1.75
0.68
78.13
2
0
0
98
CONV2D
1024
256
4.00
1.61
0.11
0.57
0.36
74.69
0
0
0
100
CONV2D
256
256
1.00
2.07
0.05
0.80
0.39
75.09
36
0
12
102
CONV2D
1024
256
4.00
2.71
0.11
1.68
0.62
77.69
2
1
0
106
CONV2D
1024
256
4.00
1.69
0.07
0.71
0.42
69.97
3
0
0
108
CONV2D
256
256
1.00
1.98
0.05
0.42
0.21
73.39
24
0
12
110
CONV2D
1024
256
4.00
1.78
0.11
0.79
0.44
74.07
0
1
0
114
CONV2D
1024
256
4.00
1.93
0.11
0.76
0.39
76.68
0
2
0
116
CONV2D
256
256
1.00
2.28
0.08
0.17
0.08
80.54
23
0
10
118
CONV2D
1024
256
4.00
1.89
0.12
0.97
0.51
78.32
1
4
0
122
CONV2D
1024
256
4.00
1.67
0.10
0.57
0.34
76.19
0
0
0
124
CONV2D
256
256
1.00
2.24
0.07
0.37
0.16
79.84
24
0
12
126
CONV2D
1024
256
4.00
1.76
0.13
0.69
0.39
79.64
0
8
0
130
CONV2D
1024
256
4.00
4.50
0.08
1.52
0.34
82.43
0
0
0
132
CONV2D
256
256
1.00
2.97
0.08
0.18
0.06
84.55
23
1
10
134
CONV2D
1024
256
4.00
4.91
0.06
2.18
0.44
83.34
1
0
0
138
CONV2D
1024
256
4.00
3.61
0.10
1.57
0.44
82.98
0
0
0
140
CONV2D
256
256
1.00
2.59
0.05
0.47
0.18
83.59
24
0
7
142
CONV2D
1024
256
4.00
2.54
0.13
1.29
0.51
82.44
1
5
0
146
CONV2D
1024
256
4.00
2.09
0.13
0.88
0.42
84.04
0
4
0
148
CONV2D
256
256
1.00
2.54
0.07
0.16
0.06
83.56
20
0
14
150
CONV2D
1024
256
4.00
2.26
0.11
1.20
0.53
82.46
1
1
0
154
CONV2D
1024
256
4.00
3.22
0.09
1.11
0.34
84.73
1
0
0
156
CONV2D
256
256
1.00
2.36
0.05
0.06
0.03
80.71
13
0
8
158
CONV2D
1024
256
4.00
2.42
0.10
1.15
0.48
81.35
1
1
0
162
CONV2D
1024
256
4.00
1.97
0.10
0.64
0.32
81.11
0
0
0
164
CONV2D
256
256
1.00
2.26
0.05
0.19
0.08
77.27
8
0
10
166
CONV2D
1024
256
4.00
2.01
0.11
1.02
0.50
76.63
1
1
0
170
CONV2D
1024
256
4.00
2.37
0.10
0.79
0.33
82.70
0
1
0
172
CONV2D
256
256
1.00
2.20
0.06
0.24
0.11
79.64
19
0
13
174
CONV2D
1024
256
4.00
2.09
0.11
0.96
0.46
81.35
1
2
0
178
CONV2D
1024
256
4.00
2.66
0.07
1.73
0.65
79.39
0
0
0
180
CONV2D
256
256
1.00
2.62
0.07
0.49
0.19
85.02
31
5
11
182
CONV2D
1024
256
4.00
3.69
0.08
1.99
0.54
82.13
0
0
0
186
CONV2D
1024
256
4.00
2.43
0.11
0.85
0.35
83.97
0
1
0
188
CONV2D
256
256
1.00
2.66
0.07
0.01
0.00
85.05
24
1
10
190
CONV2D
1024
256
4.00
3.74
0.12
1.95
0.52
85.41
1
1
0
194
CONV2D
1024
256
4.00
3.04
0.07
1.44
0.47
84.20
0
0
0
196
CONV2D
256
256
1.00
3.62
0.03
-0.18
-0.05
91.42
33
0
10
198
CONV2D
1024
256
4.00
5.43
0.11
2.00
0.37
88.86
0
1
0
202
CONV2D
1024
256
4.00
3.60
0.13
1.40
0.39
88.62
0
3
0
204
CONV2D
256
256
1.00
2.89
0.04
-0.54
-0.19
87.38
8
0
12
206
CONV2D
1024
256
4.00
5.06
0.04
2.20
0.43
88.64
1
0
0
210
CONV2D
1024
256
4.00
4.52
0.10
2.23
0.49
89.86
0
1
0
212
CONV2D
256
256
1.00
3.05
0.04
0.28
0.09
88.56
19
0
12
214
CONV2D
1024
256
4.00
4.24
0.03
2.65
0.63
87.25
1
0
0
218
CONV2D
1024
256
4.00
3.61
0.09
1.95
0.54
89.25
1
1
0
220
CONV2D
256
256
1.00
3.51
0.04
0.26
0.07
91.52
27
0
11
222
CONV2D
1024
256
4.00
5.93
0.08
2.91
0.49
90.29
1
0
0
226
CONV2D
1024
256
4.00
3.77
0.10
1.85
0.49
89.46
0
1
0
228
CONV2D
256
256
1.00
4.12
0.03
-0.24
-0.06
92.63
15
0
9
230
CONV2D
1024
256
4.00
4.08
0.16
2.54
0.62
88.99
1
8
0
234
CONV2D
1024
256
4.00
2.97
0.07
1.70
0.57
85.89
0
0
0
236
CONV2D
256
256
1.00
4.03
0.03
-0.35
-0.09
91.04
11
0
10
238
CONV2D
1024
256
4.00
5.90
0.05
2.67
0.45
88.04
0
0
0
242
CONV2D
1024
256
4.00
3.10
0.06
1.54
0.50
86.33
2
0
0
244
CONV2D
256
256
1.00
2.70
0.04
0.14
0.05
84.75
12
0
12
246
CONV2D
1024
256
4.00
3.55
0.05
2.27
0.64
82.21
0
0
0
250
CONV2D
1024
256
4.00
3.74
0.07
1.82
0.49
88.99
0
0
0
252
CONV2D
256
256
1.00
3.20
0.03
0.05
0.02
87.09
13
0
9
254
CONV2D
1024
256
4.00
3.80
0.04
2.96
0.78
84.32
1
0
0
259
CONV2D
1024
512
2.00
3.13
0.05
3.01
0.96
85.75
0
0
0
261
CONV2D
512
512
1.00
6.26
0.04
2.29
0.37
96.58
32
0
11
263
CONV2D
2048
512
4.00
6.75
0.08
7.54
1.12
94.56
1
0
0
267
CONV2D
2048
1024
2.00
4.63
0.03
4.97
1.07
89.56
1
0
0
270
CONV2D
2048
512
4.00
6.59
0.06
5.70
0.87
91.72
1
0
0
272
CONV2D
512
512
1.00
3.67
0.03
3.00
0.82
87.49
14
0
12
274
CONV2D
2048
512
4.00
4.42
0.04
5.64
1.28
88.93
1
0
0
278
CONV2D
2048
512
4.00
4.43
0.08
6.79
1.53
86.54
2
0
0
280
CONV2D
512
512
1.00
3.48
0.06
2.77
0.80
85.24
32
0
16
282
CONV2D
2048
512
4.00
3.23
0.03
5.90
1.83
81.70
1
0
0
286
DENSE
2048
1000
2.05
4.57
0.04
6.69
1.46
93.55
21
0
1
resnet101 Layer Plots
Layer 1
Layer=1 | N=64 | M=3 | Q=21.33 | alpha=2.10 | D_ks=0.08 | alpha-hat=3.03 | num traps=92
Layer 7
Layer=7 | N=64 | M=64 | Q=1.00 | alpha=1.39 | D_ks=0.17 | alpha-hat=0.81 | num traps=1
Layer 9
Layer=9 | N=64 | M=64 | Q=1.00 | alpha=1.91 | D_ks=0.05 | alpha-hat=1.50 | num traps=22
Layer 11
Layer=11 | N=256 | M=64 | Q=4.00 | alpha=2.37 | D_ks=0.18 | alpha-hat=2.54 | num traps=2
Layer 15
Layer=15 | N=256 | M=64 | Q=4.00 | alpha=3.84 | D_ks=0.08 | alpha-hat=5.56 | num traps=8
Layer 18
Layer=18 | N=256 | M=64 | Q=4.00 | alpha=1.87 | D_ks=0.14 | alpha-hat=1.18 | num traps=0
Layer 20
Layer=20 | N=64 | M=64 | Q=1.00 | alpha=2.69 | D_ks=0.08 | alpha-hat=1.58 | num traps=18
Layer 22
Layer=22 | N=256 | M=64 | Q=4.00 | alpha=2.87 | D_ks=0.19 | alpha-hat=1.70 | num traps=0
Layer 26
Layer=26 | N=256 | M=64 | Q=4.00 | alpha=2.26 | D_ks=0.17 | alpha-hat=1.15 | num traps=0
Layer 28
Layer=28 | N=64 | M=64 | Q=1.00 | alpha=2.29 | D_ks=0.10 | alpha-hat=0.75 | num traps=16
Layer 30
Layer=30 | N=256 | M=64 | Q=4.00 | alpha=5.74 | D_ks=0.09 | alpha-hat=2.81 | num traps=0
Layer 35
Layer=35 | N=256 | M=128 | Q=2.00 | alpha=1.68 | D_ks=0.14 | alpha-hat=1.28 | num traps=0
Layer 37
Layer=37 | N=128 | M=128 | Q=1.00 | alpha=2.64 | D_ks=0.10 | alpha-hat=0.78 | num traps=14
Layer 39
Layer=39 | N=512 | M=128 | Q=4.00 | alpha=3.10 | D_ks=0.11 | alpha-hat=1.68 | num traps=1
Layer 43
Layer=43 | N=512 | M=256 | Q=2.00 | alpha=1.93 | D_ks=0.08 | alpha-hat=1.83 | num traps=6
Layer 46
Layer=46 | N=512 | M=128 | Q=4.00 | alpha=2.02 | D_ks=0.12 | alpha-hat=0.90 | num traps=0
Layer 48
Layer=48 | N=128 | M=128 | Q=1.00 | alpha=1.77 | D_ks=0.07 | alpha-hat=0.63 | num traps=23
Layer 50
Layer=50 | N=512 | M=128 | Q=4.00 | alpha=1.62 | D_ks=0.15 | alpha-hat=1.16 | num traps=1
Layer 54
Layer=54 | N=512 | M=128 | Q=4.00 | alpha=3.58 | D_ks=0.08 | alpha-hat=1.89 | num traps=0
Layer 56
Layer=56 | N=128 | M=128 | Q=1.00 | alpha=2.39 | D_ks=0.07 | alpha-hat=0.73 | num traps=22
Layer 58
Layer=58 | N=512 | M=128 | Q=4.00 | alpha=2.06 | D_ks=0.15 | alpha-hat=1.24 | num traps=0
Layer 62
Layer=62 | N=512 | M=128 | Q=4.00 | alpha=2.72 | D_ks=0.09 | alpha-hat=1.58 | num traps=0
Layer 64
Layer=64 | N=128 | M=128 | Q=1.00 | alpha=2.11 | D_ks=0.09 | alpha-hat=0.37 | num traps=21
Layer 66
Layer=66 | N=512 | M=128 | Q=4.00 | alpha=4.07 | D_ks=0.09 | alpha-hat=2.19 | num traps=2
Layer 71
Layer=71 | N=512 | M=256 | Q=2.00 | alpha=3.34 | D_ks=0.13 | alpha-hat=3.01 | num traps=0
Layer 73
Layer=73 | N=256 | M=256 | Q=1.00 | alpha=3.79 | D_ks=0.08 | alpha-hat=0.22 | num traps=39
Layer 75
Layer=75 | N=1024 | M=256 | Q=4.00 | alpha=3.61 | D_ks=0.11 | alpha-hat=2.51 | num traps=0
Layer 79
Layer=79 | N=1024 | M=512 | Q=2.00 | alpha=2.59 | D_ks=0.05 | alpha-hat=2.34 | num traps=7
Layer 82
Layer=82 | N=1024 | M=256 | Q=4.00 | alpha=1.56 | D_ks=0.11 | alpha-hat=0.67 | num traps=0
Layer 84
Layer=84 | N=256 | M=256 | Q=1.00 | alpha=1.98 | D_ks=0.06 | alpha-hat=0.40 | num traps=31
Layer 86
Layer=86 | N=1024 | M=256 | Q=4.00 | alpha=3.64 | D_ks=0.07 | alpha-hat=1.94 | num traps=1
Layer 90
Layer=90 | N=1024 | M=256 | Q=4.00 | alpha=1.66 | D_ks=0.12 | alpha-hat=0.80 | num traps=1
Layer 92
Layer=92 | N=256 | M=256 | Q=1.00 | alpha=2.27 | D_ks=0.06 | alpha-hat=0.59 | num traps=38
Layer 94
Layer=94 | N=1024 | M=256 | Q=4.00 | alpha=2.55 | D_ks=0.08 | alpha-hat=1.75 | num traps=2
Layer 98
Layer=98 | N=1024 | M=256 | Q=4.00 | alpha=1.61 | D_ks=0.11 | alpha-hat=0.57 | num traps=0
Layer 100
Layer=100 | N=256 | M=256 | Q=1.00 | alpha=2.07 | D_ks=0.05 | alpha-hat=0.80 | num traps=36
Layer 102
Layer=102 | N=1024 | M=256 | Q=4.00 | alpha=2.71 | D_ks=0.11 | alpha-hat=1.68 | num traps=2
Layer 106
Layer=106 | N=1024 | M=256 | Q=4.00 | alpha=1.69 | D_ks=0.07 | alpha-hat=0.71 | num traps=3
Layer 108
Layer=108 | N=256 | M=256 | Q=1.00 | alpha=1.98 | D_ks=0.05 | alpha-hat=0.42 | num traps=24
Layer 110
Layer=110 | N=1024 | M=256 | Q=4.00 | alpha=1.78 | D_ks=0.11 | alpha-hat=0.79 | num traps=0
Layer 114
Layer=114 | N=1024 | M=256 | Q=4.00 | alpha=1.93 | D_ks=0.11 | alpha-hat=0.76 | num traps=0
Layer 116
Layer=116 | N=256 | M=256 | Q=1.00 | alpha=2.28 | D_ks=0.08 | alpha-hat=0.17 | num traps=23
Layer 118
Layer=118 | N=1024 | M=256 | Q=4.00 | alpha=1.89 | D_ks=0.12 | alpha-hat=0.97 | num traps=1
Layer 122
Layer=122 | N=1024 | M=256 | Q=4.00 | alpha=1.67 | D_ks=0.10 | alpha-hat=0.57 | num traps=0
Layer 124
Layer=124 | N=256 | M=256 | Q=1.00 | alpha=2.24 | D_ks=0.07 | alpha-hat=0.37 | num traps=24
Layer 126
Layer=126 | N=1024 | M=256 | Q=4.00 | alpha=1.76 | D_ks=0.13 | alpha-hat=0.69 | num traps=0
Layer 130
Layer=130 | N=1024 | M=256 | Q=4.00 | alpha=4.50 | D_ks=0.08 | alpha-hat=1.52 | num traps=0
Layer 132
Layer=132 | N=256 | M=256 | Q=1.00 | alpha=2.97 | D_ks=0.08 | alpha-hat=0.18 | num traps=23
Layer 134
Layer=134 | N=1024 | M=256 | Q=4.00 | alpha=4.91 | D_ks=0.06 | alpha-hat=2.18 | num traps=1
Layer 138
Layer=138 | N=1024 | M=256 | Q=4.00 | alpha=3.61 | D_ks=0.10 | alpha-hat=1.57 | num traps=0
Layer 140
Layer=140 | N=256 | M=256 | Q=1.00 | alpha=2.59 | D_ks=0.05 | alpha-hat=0.47 | num traps=24
Layer 142
Layer=142 | N=1024 | M=256 | Q=4.00 | alpha=2.54 | D_ks=0.13 | alpha-hat=1.29 | num traps=1
Layer 146
Layer=146 | N=1024 | M=256 | Q=4.00 | alpha=2.09 | D_ks=0.13 | alpha-hat=0.88 | num traps=0
Layer 148
Layer=148 | N=256 | M=256 | Q=1.00 | alpha=2.54 | D_ks=0.07 | alpha-hat=0.16 | num traps=20
Layer 150
Layer=150 | N=1024 | M=256 | Q=4.00 | alpha=2.26 | D_ks=0.11 | alpha-hat=1.20 | num traps=1
Layer 154
Layer=154 | N=1024 | M=256 | Q=4.00 | alpha=3.22 | D_ks=0.09 | alpha-hat=1.11 | num traps=1
Layer 156
Layer=156 | N=256 | M=256 | Q=1.00 | alpha=2.36 | D_ks=0.05 | alpha-hat=0.06 | num traps=13
Layer 158
Layer=158 | N=1024 | M=256 | Q=4.00 | alpha=2.42 | D_ks=0.10 | alpha-hat=1.15 | num traps=1
Layer 162
Layer=162 | N=1024 | M=256 | Q=4.00 | alpha=1.97 | D_ks=0.10 | alpha-hat=0.64 | num traps=0
Layer 164
Layer=164 | N=256 | M=256 | Q=1.00 | alpha=2.26 | D_ks=0.05 | alpha-hat=0.19 | num traps=8
Layer 166
Layer=166 | N=1024 | M=256 | Q=4.00 | alpha=2.01 | D_ks=0.11 | alpha-hat=1.02 | num traps=1
Layer 170
Layer=170 | N=1024 | M=256 | Q=4.00 | alpha=2.37 | D_ks=0.10 | alpha-hat=0.79 | num traps=0
Layer 172
Layer=172 | N=256 | M=256 | Q=1.00 | alpha=2.20 | D_ks=0.06 | alpha-hat=0.24 | num traps=19
Layer 174
Layer=174 | N=1024 | M=256 | Q=4.00 | alpha=2.09 | D_ks=0.11 | alpha-hat=0.96 | num traps=1
Layer 178
Layer=178 | N=1024 | M=256 | Q=4.00 | alpha=2.66 | D_ks=0.07 | alpha-hat=1.73 | num traps=0
Layer 180
Layer=180 | N=256 | M=256 | Q=1.00 | alpha=2.62 | D_ks=0.07 | alpha-hat=0.49 | num traps=31
Layer 182
Layer=182 | N=1024 | M=256 | Q=4.00 | alpha=3.69 | D_ks=0.08 | alpha-hat=1.99 | num traps=0
Layer 186
Layer=186 | N=1024 | M=256 | Q=4.00 | alpha=2.43 | D_ks=0.11 | alpha-hat=0.85 | num traps=0
Layer 188
Layer=188 | N=256 | M=256 | Q=1.00 | alpha=2.66 | D_ks=0.07 | alpha-hat=0.01 | num traps=24
Layer 190
Layer=190 | N=1024 | M=256 | Q=4.00 | alpha=3.74 | D_ks=0.12 | alpha-hat=1.95 | num traps=1
Layer 194
Layer=194 | N=1024 | M=256 | Q=4.00 | alpha=3.04 | D_ks=0.07 | alpha-hat=1.44 | num traps=0
Layer 196
Layer=196 | N=256 | M=256 | Q=1.00 | alpha=3.62 | D_ks=0.03 | alpha-hat=-0.18 | num traps=33
Layer 198
Layer=198 | N=1024 | M=256 | Q=4.00 | alpha=5.43 | D_ks=0.11 | alpha-hat=2.00 | num traps=0
Layer 202
Layer=202 | N=1024 | M=256 | Q=4.00 | alpha=3.60 | D_ks=0.13 | alpha-hat=1.40 | num traps=0
Layer 204
Layer=204 | N=256 | M=256 | Q=1.00 | alpha=2.89 | D_ks=0.04 | alpha-hat=-0.54 | num traps=8
Layer 206
Layer=206 | N=1024 | M=256 | Q=4.00 | alpha=5.06 | D_ks=0.04 | alpha-hat=2.20 | num traps=1
Layer 210
Layer=210 | N=1024 | M=256 | Q=4.00 | alpha=4.52 | D_ks=0.10 | alpha-hat=2.23 | num traps=0
Layer 212
Layer=212 | N=256 | M=256 | Q=1.00 | alpha=3.05 | D_ks=0.04 | alpha-hat=0.28 | num traps=19
Layer 214
Layer=214 | N=1024 | M=256 | Q=4.00 | alpha=4.24 | D_ks=0.03 | alpha-hat=2.65 | num traps=1
Layer 218
Layer=218 | N=1024 | M=256 | Q=4.00 | alpha=3.61 | D_ks=0.09 | alpha-hat=1.95 | num traps=1
Layer 220
Layer=220 | N=256 | M=256 | Q=1.00 | alpha=3.51 | D_ks=0.04 | alpha-hat=0.26 | num traps=27
Layer 222
Layer=222 | N=1024 | M=256 | Q=4.00 | alpha=5.93 | D_ks=0.08 | alpha-hat=2.91 | num traps=1
Layer 226
Layer=226 | N=1024 | M=256 | Q=4.00 | alpha=3.77 | D_ks=0.10 | alpha-hat=1.85 | num traps=0
Layer 228
Layer=228 | N=256 | M=256 | Q=1.00 | alpha=4.12 | D_ks=0.03 | alpha-hat=-0.24 | num traps=15
Layer 230
Layer=230 | N=1024 | M=256 | Q=4.00 | alpha=4.08 | D_ks=0.16 | alpha-hat=2.54 | num traps=1
Layer 234
Layer=234 | N=1024 | M=256 | Q=4.00 | alpha=2.97 | D_ks=0.07 | alpha-hat=1.70 | num traps=0
Layer 236
Layer=236 | N=256 | M=256 | Q=1.00 | alpha=4.03 | D_ks=0.03 | alpha-hat=-0.35 | num traps=11
Layer 238
Layer=238 | N=1024 | M=256 | Q=4.00 | alpha=5.90 | D_ks=0.05 | alpha-hat=2.67 | num traps=0
Layer 242
Layer=242 | N=1024 | M=256 | Q=4.00 | alpha=3.10 | D_ks=0.06 | alpha-hat=1.54 | num traps=2
Layer 244
Layer=244 | N=256 | M=256 | Q=1.00 | alpha=2.70 | D_ks=0.04 | alpha-hat=0.14 | num traps=12
Layer 246
Layer=246 | N=1024 | M=256 | Q=4.00 | alpha=3.55 | D_ks=0.05 | alpha-hat=2.27 | num traps=0
Layer 250
Layer=250 | N=1024 | M=256 | Q=4.00 | alpha=3.74 | D_ks=0.07 | alpha-hat=1.82 | num traps=0
Layer 252
Layer=252 | N=256 | M=256 | Q=1.00 | alpha=3.20 | D_ks=0.03 | alpha-hat=0.05 | num traps=13
Layer 254
Layer=254 | N=1024 | M=256 | Q=4.00 | alpha=3.80 | D_ks=0.04 | alpha-hat=2.96 | num traps=1
Layer 259
Layer=259 | N=1024 | M=512 | Q=2.00 | alpha=3.13 | D_ks=0.05 | alpha-hat=3.01 | num traps=0
Layer 261
Layer=261 | N=512 | M=512 | Q=1.00 | alpha=6.26 | D_ks=0.04 | alpha-hat=2.29 | num traps=32
Layer 263
Layer=263 | N=2048 | M=512 | Q=4.00 | alpha=6.75 | D_ks=0.08 | alpha-hat=7.54 | num traps=1
Layer 267
Layer=267 | N=2048 | M=1024 | Q=2.00 | alpha=4.63 | D_ks=0.03 | alpha-hat=4.97 | num traps=1
Layer 270
Layer=270 | N=2048 | M=512 | Q=4.00 | alpha=6.59 | D_ks=0.06 | alpha-hat=5.70 | num traps=1
Layer 272
Layer=272 | N=512 | M=512 | Q=1.00 | alpha=3.67 | D_ks=0.03 | alpha-hat=3.00 | num traps=14
Layer 274
Layer=274 | N=2048 | M=512 | Q=4.00 | alpha=4.42 | D_ks=0.04 | alpha-hat=5.64 | num traps=1
Layer 278
Layer=278 | N=2048 | M=512 | Q=4.00 | alpha=4.43 | D_ks=0.08 | alpha-hat=6.79 | num traps=2
Layer 280
Layer=280 | N=512 | M=512 | Q=1.00 | alpha=3.48 | D_ks=0.06 | alpha-hat=2.77 | num traps=32
Layer 282
Layer=282 | N=2048 | M=512 | Q=4.00 | alpha=3.23 | D_ks=0.03 | alpha-hat=5.90 | num traps=1
Layer 286
Layer=286 | N=2048 | M=1000 | Q=2.05 | alpha=4.57 | D_ks=0.04 | alpha-hat=6.69 | num traps=21
resnet101 Model Summary Plots
resnet101 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 | 2.10 | 0.08 | 3.03 | 1.44 | 88.49 | 92 | 0 | 0 |
| 7 | CONV2D | 64 | 64 | 1.00 | 1.39 | 0.17 | 0.81 | 0.58 | 83.96 | 1 | 1 | 0 |
| 9 | CONV2D | 64 | 64 | 1.00 | 1.91 | 0.05 | 1.50 | 0.78 | 75.74 | 22 | 0 | 3 |
| 11 | CONV2D | 256 | 64 | 4.00 | 2.37 | 0.18 | 2.54 | 1.07 | 75.69 | 2 | 3 | 0 |
| 15 | CONV2D | 256 | 64 | 4.00 | 3.84 | 0.08 | 5.56 | 1.45 | 78.65 | 8 | 0 | 0 |
| 18 | CONV2D | 256 | 64 | 4.00 | 1.87 | 0.14 | 1.18 | 0.63 | 81.86 | 0 | 0 | 0 |
| 20 | CONV2D | 64 | 64 | 1.00 | 2.69 | 0.08 | 1.58 | 0.59 | 81.31 | 18 | 0 | 4 |
| 22 | CONV2D | 256 | 64 | 4.00 | 2.87 | 0.19 | 1.70 | 0.59 | 89.00 | 0 | 6 | 0 |
| 26 | CONV2D | 256 | 64 | 4.00 | 2.26 | 0.17 | 1.15 | 0.51 | 83.99 | 0 | 8 | 0 |
| 28 | CONV2D | 64 | 64 | 1.00 | 2.29 | 0.10 | 0.75 | 0.33 | 83.83 | 16 | 0 | 2 |
| 30 | CONV2D | 256 | 64 | 4.00 | 5.74 | 0.09 | 2.81 | 0.49 | 87.61 | 0 | 0 | 0 |
| 35 | CONV2D | 256 | 128 | 2.00 | 1.68 | 0.14 | 1.28 | 0.77 | 81.17 | 0 | 1 | 0 |
| 37 | CONV2D | 128 | 128 | 1.00 | 2.64 | 0.10 | 0.78 | 0.30 | 85.61 | 14 | 1 | 6 |
| 39 | CONV2D | 512 | 128 | 4.00 | 3.10 | 0.11 | 1.68 | 0.54 | 84.62 | 1 | 0 | 0 |
| 43 | CONV2D | 512 | 256 | 2.00 | 1.93 | 0.08 | 1.83 | 0.95 | 71.87 | 6 | 0 | 0 |
| 46 | CONV2D | 512 | 128 | 4.00 | 2.02 | 0.12 | 0.90 | 0.45 | 77.98 | 0 | 3 | 0 |
| 48 | CONV2D | 128 | 128 | 1.00 | 1.77 | 0.07 | 0.63 | 0.36 | 75.68 | 23 | 0 | 9 |
| 50 | CONV2D | 512 | 128 | 4.00 | 1.62 | 0.15 | 1.16 | 0.71 | 83.07 | 1 | 4 | 0 |
| 54 | CONV2D | 512 | 128 | 4.00 | 3.58 | 0.08 | 1.89 | 0.53 | 84.30 | 0 | 0 | 1 |
| 56 | CONV2D | 128 | 128 | 1.00 | 2.39 | 0.07 | 0.73 | 0.31 | 80.81 | 22 | 0 | 10 |
| 58 | CONV2D | 512 | 128 | 4.00 | 2.06 | 0.15 | 1.24 | 0.60 | 84.67 | 0 | 8 | 0 |
| 62 | CONV2D | 512 | 128 | 4.00 | 2.72 | 0.09 | 1.58 | 0.58 | 80.93 | 0 | 0 | 0 |
| 64 | CONV2D | 128 | 128 | 1.00 | 2.11 | 0.09 | 0.37 | 0.18 | 83.31 | 21 | 1 | 5 |
| 66 | CONV2D | 512 | 128 | 4.00 | 4.07 | 0.09 | 2.19 | 0.54 | 83.65 | 2 | 0 | 0 |
| 71 | CONV2D | 512 | 256 | 2.00 | 3.34 | 0.13 | 3.01 | 0.90 | 82.29 | 0 | 1 | 0 |
| 73 | CONV2D | 256 | 256 | 1.00 | 3.79 | 0.08 | 0.22 | 0.06 | 91.47 | 39 | 0 | 8 |
| 75 | CONV2D | 1024 | 256 | 4.00 | 3.61 | 0.11 | 2.51 | 0.70 | 84.57 | 0 | 1 | 0 |
| 79 | CONV2D | 1024 | 512 | 2.00 | 2.59 | 0.05 | 2.34 | 0.90 | 74.15 | 7 | 0 | 0 |
| 82 | CONV2D | 1024 | 256 | 4.00 | 1.56 | 0.11 | 0.67 | 0.43 | 70.44 | 0 | 0 | 0 |
| 84 | CONV2D | 256 | 256 | 1.00 | 1.98 | 0.06 | 0.40 | 0.20 | 75.27 | 31 | 0 | 13 |
| 86 | CONV2D | 1024 | 256 | 4.00 | 3.64 | 0.07 | 1.94 | 0.53 | 78.14 | 1 | 0 | 0 |
| 90 | CONV2D | 1024 | 256 | 4.00 | 1.66 | 0.12 | 0.80 | 0.48 | 75.83 | 1 | 3 | 0 |
| 92 | CONV2D | 256 | 256 | 1.00 | 2.27 | 0.06 | 0.59 | 0.26 | 79.33 | 38 | 0 | 8 |
| 94 | CONV2D | 1024 | 256 | 4.00 | 2.55 | 0.08 | 1.75 | 0.68 | 78.13 | 2 | 0 | 0 |
| 98 | CONV2D | 1024 | 256 | 4.00 | 1.61 | 0.11 | 0.57 | 0.36 | 74.69 | 0 | 0 | 0 |
| 100 | CONV2D | 256 | 256 | 1.00 | 2.07 | 0.05 | 0.80 | 0.39 | 75.09 | 36 | 0 | 12 |
| 102 | CONV2D | 1024 | 256 | 4.00 | 2.71 | 0.11 | 1.68 | 0.62 | 77.69 | 2 | 1 | 0 |
| 106 | CONV2D | 1024 | 256 | 4.00 | 1.69 | 0.07 | 0.71 | 0.42 | 69.97 | 3 | 0 | 0 |
| 108 | CONV2D | 256 | 256 | 1.00 | 1.98 | 0.05 | 0.42 | 0.21 | 73.39 | 24 | 0 | 12 |
| 110 | CONV2D | 1024 | 256 | 4.00 | 1.78 | 0.11 | 0.79 | 0.44 | 74.07 | 0 | 1 | 0 |
| 114 | CONV2D | 1024 | 256 | 4.00 | 1.93 | 0.11 | 0.76 | 0.39 | 76.68 | 0 | 2 | 0 |
| 116 | CONV2D | 256 | 256 | 1.00 | 2.28 | 0.08 | 0.17 | 0.08 | 80.54 | 23 | 0 | 10 |
| 118 | CONV2D | 1024 | 256 | 4.00 | 1.89 | 0.12 | 0.97 | 0.51 | 78.32 | 1 | 4 | 0 |
| 122 | CONV2D | 1024 | 256 | 4.00 | 1.67 | 0.10 | 0.57 | 0.34 | 76.19 | 0 | 0 | 0 |
| 124 | CONV2D | 256 | 256 | 1.00 | 2.24 | 0.07 | 0.37 | 0.16 | 79.84 | 24 | 0 | 12 |
| 126 | CONV2D | 1024 | 256 | 4.00 | 1.76 | 0.13 | 0.69 | 0.39 | 79.64 | 0 | 8 | 0 |
| 130 | CONV2D | 1024 | 256 | 4.00 | 4.50 | 0.08 | 1.52 | 0.34 | 82.43 | 0 | 0 | 0 |
| 132 | CONV2D | 256 | 256 | 1.00 | 2.97 | 0.08 | 0.18 | 0.06 | 84.55 | 23 | 1 | 10 |
| 134 | CONV2D | 1024 | 256 | 4.00 | 4.91 | 0.06 | 2.18 | 0.44 | 83.34 | 1 | 0 | 0 |
| 138 | CONV2D | 1024 | 256 | 4.00 | 3.61 | 0.10 | 1.57 | 0.44 | 82.98 | 0 | 0 | 0 |
| 140 | CONV2D | 256 | 256 | 1.00 | 2.59 | 0.05 | 0.47 | 0.18 | 83.59 | 24 | 0 | 7 |
| 142 | CONV2D | 1024 | 256 | 4.00 | 2.54 | 0.13 | 1.29 | 0.51 | 82.44 | 1 | 5 | 0 |
| 146 | CONV2D | 1024 | 256 | 4.00 | 2.09 | 0.13 | 0.88 | 0.42 | 84.04 | 0 | 4 | 0 |
| 148 | CONV2D | 256 | 256 | 1.00 | 2.54 | 0.07 | 0.16 | 0.06 | 83.56 | 20 | 0 | 14 |
| 150 | CONV2D | 1024 | 256 | 4.00 | 2.26 | 0.11 | 1.20 | 0.53 | 82.46 | 1 | 1 | 0 |
| 154 | CONV2D | 1024 | 256 | 4.00 | 3.22 | 0.09 | 1.11 | 0.34 | 84.73 | 1 | 0 | 0 |
| 156 | CONV2D | 256 | 256 | 1.00 | 2.36 | 0.05 | 0.06 | 0.03 | 80.71 | 13 | 0 | 8 |
| 158 | CONV2D | 1024 | 256 | 4.00 | 2.42 | 0.10 | 1.15 | 0.48 | 81.35 | 1 | 1 | 0 |
| 162 | CONV2D | 1024 | 256 | 4.00 | 1.97 | 0.10 | 0.64 | 0.32 | 81.11 | 0 | 0 | 0 |
| 164 | CONV2D | 256 | 256 | 1.00 | 2.26 | 0.05 | 0.19 | 0.08 | 77.27 | 8 | 0 | 10 |
| 166 | CONV2D | 1024 | 256 | 4.00 | 2.01 | 0.11 | 1.02 | 0.50 | 76.63 | 1 | 1 | 0 |
| 170 | CONV2D | 1024 | 256 | 4.00 | 2.37 | 0.10 | 0.79 | 0.33 | 82.70 | 0 | 1 | 0 |
| 172 | CONV2D | 256 | 256 | 1.00 | 2.20 | 0.06 | 0.24 | 0.11 | 79.64 | 19 | 0 | 13 |
| 174 | CONV2D | 1024 | 256 | 4.00 | 2.09 | 0.11 | 0.96 | 0.46 | 81.35 | 1 | 2 | 0 |
| 178 | CONV2D | 1024 | 256 | 4.00 | 2.66 | 0.07 | 1.73 | 0.65 | 79.39 | 0 | 0 | 0 |
| 180 | CONV2D | 256 | 256 | 1.00 | 2.62 | 0.07 | 0.49 | 0.19 | 85.02 | 31 | 5 | 11 |
| 182 | CONV2D | 1024 | 256 | 4.00 | 3.69 | 0.08 | 1.99 | 0.54 | 82.13 | 0 | 0 | 0 |
| 186 | CONV2D | 1024 | 256 | 4.00 | 2.43 | 0.11 | 0.85 | 0.35 | 83.97 | 0 | 1 | 0 |
| 188 | CONV2D | 256 | 256 | 1.00 | 2.66 | 0.07 | 0.01 | 0.00 | 85.05 | 24 | 1 | 10 |
| 190 | CONV2D | 1024 | 256 | 4.00 | 3.74 | 0.12 | 1.95 | 0.52 | 85.41 | 1 | 1 | 0 |
| 194 | CONV2D | 1024 | 256 | 4.00 | 3.04 | 0.07 | 1.44 | 0.47 | 84.20 | 0 | 0 | 0 |
| 196 | CONV2D | 256 | 256 | 1.00 | 3.62 | 0.03 | -0.18 | -0.05 | 91.42 | 33 | 0 | 10 |
| 198 | CONV2D | 1024 | 256 | 4.00 | 5.43 | 0.11 | 2.00 | 0.37 | 88.86 | 0 | 1 | 0 |
| 202 | CONV2D | 1024 | 256 | 4.00 | 3.60 | 0.13 | 1.40 | 0.39 | 88.62 | 0 | 3 | 0 |
| 204 | CONV2D | 256 | 256 | 1.00 | 2.89 | 0.04 | -0.54 | -0.19 | 87.38 | 8 | 0 | 12 |
| 206 | CONV2D | 1024 | 256 | 4.00 | 5.06 | 0.04 | 2.20 | 0.43 | 88.64 | 1 | 0 | 0 |
| 210 | CONV2D | 1024 | 256 | 4.00 | 4.52 | 0.10 | 2.23 | 0.49 | 89.86 | 0 | 1 | 0 |
| 212 | CONV2D | 256 | 256 | 1.00 | 3.05 | 0.04 | 0.28 | 0.09 | 88.56 | 19 | 0 | 12 |
| 214 | CONV2D | 1024 | 256 | 4.00 | 4.24 | 0.03 | 2.65 | 0.63 | 87.25 | 1 | 0 | 0 |
| 218 | CONV2D | 1024 | 256 | 4.00 | 3.61 | 0.09 | 1.95 | 0.54 | 89.25 | 1 | 1 | 0 |
| 220 | CONV2D | 256 | 256 | 1.00 | 3.51 | 0.04 | 0.26 | 0.07 | 91.52 | 27 | 0 | 11 |
| 222 | CONV2D | 1024 | 256 | 4.00 | 5.93 | 0.08 | 2.91 | 0.49 | 90.29 | 1 | 0 | 0 |
| 226 | CONV2D | 1024 | 256 | 4.00 | 3.77 | 0.10 | 1.85 | 0.49 | 89.46 | 0 | 1 | 0 |
| 228 | CONV2D | 256 | 256 | 1.00 | 4.12 | 0.03 | -0.24 | -0.06 | 92.63 | 15 | 0 | 9 |
| 230 | CONV2D | 1024 | 256 | 4.00 | 4.08 | 0.16 | 2.54 | 0.62 | 88.99 | 1 | 8 | 0 |
| 234 | CONV2D | 1024 | 256 | 4.00 | 2.97 | 0.07 | 1.70 | 0.57 | 85.89 | 0 | 0 | 0 |
| 236 | CONV2D | 256 | 256 | 1.00 | 4.03 | 0.03 | -0.35 | -0.09 | 91.04 | 11 | 0 | 10 |
| 238 | CONV2D | 1024 | 256 | 4.00 | 5.90 | 0.05 | 2.67 | 0.45 | 88.04 | 0 | 0 | 0 |
| 242 | CONV2D | 1024 | 256 | 4.00 | 3.10 | 0.06 | 1.54 | 0.50 | 86.33 | 2 | 0 | 0 |
| 244 | CONV2D | 256 | 256 | 1.00 | 2.70 | 0.04 | 0.14 | 0.05 | 84.75 | 12 | 0 | 12 |
| 246 | CONV2D | 1024 | 256 | 4.00 | 3.55 | 0.05 | 2.27 | 0.64 | 82.21 | 0 | 0 | 0 |
| 250 | CONV2D | 1024 | 256 | 4.00 | 3.74 | 0.07 | 1.82 | 0.49 | 88.99 | 0 | 0 | 0 |
| 252 | CONV2D | 256 | 256 | 1.00 | 3.20 | 0.03 | 0.05 | 0.02 | 87.09 | 13 | 0 | 9 |
| 254 | CONV2D | 1024 | 256 | 4.00 | 3.80 | 0.04 | 2.96 | 0.78 | 84.32 | 1 | 0 | 0 |
| 259 | CONV2D | 1024 | 512 | 2.00 | 3.13 | 0.05 | 3.01 | 0.96 | 85.75 | 0 | 0 | 0 |
| 261 | CONV2D | 512 | 512 | 1.00 | 6.26 | 0.04 | 2.29 | 0.37 | 96.58 | 32 | 0 | 11 |
| 263 | CONV2D | 2048 | 512 | 4.00 | 6.75 | 0.08 | 7.54 | 1.12 | 94.56 | 1 | 0 | 0 |
| 267 | CONV2D | 2048 | 1024 | 2.00 | 4.63 | 0.03 | 4.97 | 1.07 | 89.56 | 1 | 0 | 0 |
| 270 | CONV2D | 2048 | 512 | 4.00 | 6.59 | 0.06 | 5.70 | 0.87 | 91.72 | 1 | 0 | 0 |
| 272 | CONV2D | 512 | 512 | 1.00 | 3.67 | 0.03 | 3.00 | 0.82 | 87.49 | 14 | 0 | 12 |
| 274 | CONV2D | 2048 | 512 | 4.00 | 4.42 | 0.04 | 5.64 | 1.28 | 88.93 | 1 | 0 | 0 |
| 278 | CONV2D | 2048 | 512 | 4.00 | 4.43 | 0.08 | 6.79 | 1.53 | 86.54 | 2 | 0 | 0 |
| 280 | CONV2D | 512 | 512 | 1.00 | 3.48 | 0.06 | 2.77 | 0.80 | 85.24 | 32 | 0 | 16 |
| 282 | CONV2D | 2048 | 512 | 4.00 | 3.23 | 0.03 | 5.90 | 1.83 | 81.70 | 1 | 0 | 0 |
| 286 | DENSE | 2048 | 1000 | 2.05 | 4.57 | 0.04 | 6.69 | 1.46 | 93.55 | 21 | 0 | 1 |
resnet101 Layer Plots
Layer 1
Layer=1 | N=64 | M=3 | Q=21.33 | alpha=2.10 | D_ks=0.08 | alpha-hat=3.03 | num traps=92
Layer 7
Layer=7 | N=64 | M=64 | Q=1.00 | alpha=1.39 | D_ks=0.17 | alpha-hat=0.81 | num traps=1
Layer 9
Layer=9 | N=64 | M=64 | Q=1.00 | alpha=1.91 | D_ks=0.05 | alpha-hat=1.50 | num traps=22
Layer 11
Layer=11 | N=256 | M=64 | Q=4.00 | alpha=2.37 | D_ks=0.18 | alpha-hat=2.54 | num traps=2
Layer 15
Layer=15 | N=256 | M=64 | Q=4.00 | alpha=3.84 | D_ks=0.08 | alpha-hat=5.56 | num traps=8
Layer 18
Layer=18 | N=256 | M=64 | Q=4.00 | alpha=1.87 | D_ks=0.14 | alpha-hat=1.18 | num traps=0
Layer 20
Layer=20 | N=64 | M=64 | Q=1.00 | alpha=2.69 | D_ks=0.08 | alpha-hat=1.58 | num traps=18
Layer 22
Layer=22 | N=256 | M=64 | Q=4.00 | alpha=2.87 | D_ks=0.19 | alpha-hat=1.70 | num traps=0
Layer 26
Layer=26 | N=256 | M=64 | Q=4.00 | alpha=2.26 | D_ks=0.17 | alpha-hat=1.15 | num traps=0
Layer 28
Layer=28 | N=64 | M=64 | Q=1.00 | alpha=2.29 | D_ks=0.10 | alpha-hat=0.75 | num traps=16
Layer 30
Layer=30 | N=256 | M=64 | Q=4.00 | alpha=5.74 | D_ks=0.09 | alpha-hat=2.81 | num traps=0
Layer 35
Layer=35 | N=256 | M=128 | Q=2.00 | alpha=1.68 | D_ks=0.14 | alpha-hat=1.28 | num traps=0
Layer 37
Layer=37 | N=128 | M=128 | Q=1.00 | alpha=2.64 | D_ks=0.10 | alpha-hat=0.78 | num traps=14
Layer 39
Layer=39 | N=512 | M=128 | Q=4.00 | alpha=3.10 | D_ks=0.11 | alpha-hat=1.68 | num traps=1
Layer 43
Layer=43 | N=512 | M=256 | Q=2.00 | alpha=1.93 | D_ks=0.08 | alpha-hat=1.83 | num traps=6
Layer 46
Layer=46 | N=512 | M=128 | Q=4.00 | alpha=2.02 | D_ks=0.12 | alpha-hat=0.90 | num traps=0
Layer 48
Layer=48 | N=128 | M=128 | Q=1.00 | alpha=1.77 | D_ks=0.07 | alpha-hat=0.63 | num traps=23
Layer 50
Layer=50 | N=512 | M=128 | Q=4.00 | alpha=1.62 | D_ks=0.15 | alpha-hat=1.16 | num traps=1
Layer 54
Layer=54 | N=512 | M=128 | Q=4.00 | alpha=3.58 | D_ks=0.08 | alpha-hat=1.89 | num traps=0
Layer 56
Layer=56 | N=128 | M=128 | Q=1.00 | alpha=2.39 | D_ks=0.07 | alpha-hat=0.73 | num traps=22
Layer 58
Layer=58 | N=512 | M=128 | Q=4.00 | alpha=2.06 | D_ks=0.15 | alpha-hat=1.24 | num traps=0
Layer 62
Layer=62 | N=512 | M=128 | Q=4.00 | alpha=2.72 | D_ks=0.09 | alpha-hat=1.58 | num traps=0
Layer 64
Layer=64 | N=128 | M=128 | Q=1.00 | alpha=2.11 | D_ks=0.09 | alpha-hat=0.37 | num traps=21
Layer 66
Layer=66 | N=512 | M=128 | Q=4.00 | alpha=4.07 | D_ks=0.09 | alpha-hat=2.19 | num traps=2
Layer 71
Layer=71 | N=512 | M=256 | Q=2.00 | alpha=3.34 | D_ks=0.13 | alpha-hat=3.01 | num traps=0
Layer 73
Layer=73 | N=256 | M=256 | Q=1.00 | alpha=3.79 | D_ks=0.08 | alpha-hat=0.22 | num traps=39
Layer 75
Layer=75 | N=1024 | M=256 | Q=4.00 | alpha=3.61 | D_ks=0.11 | alpha-hat=2.51 | num traps=0
Layer 79
Layer=79 | N=1024 | M=512 | Q=2.00 | alpha=2.59 | D_ks=0.05 | alpha-hat=2.34 | num traps=7
Layer 82
Layer=82 | N=1024 | M=256 | Q=4.00 | alpha=1.56 | D_ks=0.11 | alpha-hat=0.67 | num traps=0
Layer 84
Layer=84 | N=256 | M=256 | Q=1.00 | alpha=1.98 | D_ks=0.06 | alpha-hat=0.40 | num traps=31
Layer 86
Layer=86 | N=1024 | M=256 | Q=4.00 | alpha=3.64 | D_ks=0.07 | alpha-hat=1.94 | num traps=1
Layer 90
Layer=90 | N=1024 | M=256 | Q=4.00 | alpha=1.66 | D_ks=0.12 | alpha-hat=0.80 | num traps=1
Layer 92
Layer=92 | N=256 | M=256 | Q=1.00 | alpha=2.27 | D_ks=0.06 | alpha-hat=0.59 | num traps=38
Layer 94
Layer=94 | N=1024 | M=256 | Q=4.00 | alpha=2.55 | D_ks=0.08 | alpha-hat=1.75 | num traps=2
Layer 98
Layer=98 | N=1024 | M=256 | Q=4.00 | alpha=1.61 | D_ks=0.11 | alpha-hat=0.57 | num traps=0
Layer 100
Layer=100 | N=256 | M=256 | Q=1.00 | alpha=2.07 | D_ks=0.05 | alpha-hat=0.80 | num traps=36
Layer 102
Layer=102 | N=1024 | M=256 | Q=4.00 | alpha=2.71 | D_ks=0.11 | alpha-hat=1.68 | num traps=2
Layer 106
Layer=106 | N=1024 | M=256 | Q=4.00 | alpha=1.69 | D_ks=0.07 | alpha-hat=0.71 | num traps=3
Layer 108
Layer=108 | N=256 | M=256 | Q=1.00 | alpha=1.98 | D_ks=0.05 | alpha-hat=0.42 | num traps=24
Layer 110
Layer=110 | N=1024 | M=256 | Q=4.00 | alpha=1.78 | D_ks=0.11 | alpha-hat=0.79 | num traps=0
Layer 114
Layer=114 | N=1024 | M=256 | Q=4.00 | alpha=1.93 | D_ks=0.11 | alpha-hat=0.76 | num traps=0
Layer 116
Layer=116 | N=256 | M=256 | Q=1.00 | alpha=2.28 | D_ks=0.08 | alpha-hat=0.17 | num traps=23
Layer 118
Layer=118 | N=1024 | M=256 | Q=4.00 | alpha=1.89 | D_ks=0.12 | alpha-hat=0.97 | num traps=1
Layer 122
Layer=122 | N=1024 | M=256 | Q=4.00 | alpha=1.67 | D_ks=0.10 | alpha-hat=0.57 | num traps=0
Layer 124
Layer=124 | N=256 | M=256 | Q=1.00 | alpha=2.24 | D_ks=0.07 | alpha-hat=0.37 | num traps=24
Layer 126
Layer=126 | N=1024 | M=256 | Q=4.00 | alpha=1.76 | D_ks=0.13 | alpha-hat=0.69 | num traps=0
Layer 130
Layer=130 | N=1024 | M=256 | Q=4.00 | alpha=4.50 | D_ks=0.08 | alpha-hat=1.52 | num traps=0
Layer 132
Layer=132 | N=256 | M=256 | Q=1.00 | alpha=2.97 | D_ks=0.08 | alpha-hat=0.18 | num traps=23
Layer 134
Layer=134 | N=1024 | M=256 | Q=4.00 | alpha=4.91 | D_ks=0.06 | alpha-hat=2.18 | num traps=1
Layer 138
Layer=138 | N=1024 | M=256 | Q=4.00 | alpha=3.61 | D_ks=0.10 | alpha-hat=1.57 | num traps=0
Layer 140
Layer=140 | N=256 | M=256 | Q=1.00 | alpha=2.59 | D_ks=0.05 | alpha-hat=0.47 | num traps=24
Layer 142
Layer=142 | N=1024 | M=256 | Q=4.00 | alpha=2.54 | D_ks=0.13 | alpha-hat=1.29 | num traps=1
Layer 146
Layer=146 | N=1024 | M=256 | Q=4.00 | alpha=2.09 | D_ks=0.13 | alpha-hat=0.88 | num traps=0
Layer 148
Layer=148 | N=256 | M=256 | Q=1.00 | alpha=2.54 | D_ks=0.07 | alpha-hat=0.16 | num traps=20
Layer 150
Layer=150 | N=1024 | M=256 | Q=4.00 | alpha=2.26 | D_ks=0.11 | alpha-hat=1.20 | num traps=1
Layer 154
Layer=154 | N=1024 | M=256 | Q=4.00 | alpha=3.22 | D_ks=0.09 | alpha-hat=1.11 | num traps=1
Layer 156
Layer=156 | N=256 | M=256 | Q=1.00 | alpha=2.36 | D_ks=0.05 | alpha-hat=0.06 | num traps=13
Layer 158
Layer=158 | N=1024 | M=256 | Q=4.00 | alpha=2.42 | D_ks=0.10 | alpha-hat=1.15 | num traps=1
Layer 162
Layer=162 | N=1024 | M=256 | Q=4.00 | alpha=1.97 | D_ks=0.10 | alpha-hat=0.64 | num traps=0
Layer 164
Layer=164 | N=256 | M=256 | Q=1.00 | alpha=2.26 | D_ks=0.05 | alpha-hat=0.19 | num traps=8
Layer 166
Layer=166 | N=1024 | M=256 | Q=4.00 | alpha=2.01 | D_ks=0.11 | alpha-hat=1.02 | num traps=1
Layer 170
Layer=170 | N=1024 | M=256 | Q=4.00 | alpha=2.37 | D_ks=0.10 | alpha-hat=0.79 | num traps=0
Layer 172
Layer=172 | N=256 | M=256 | Q=1.00 | alpha=2.20 | D_ks=0.06 | alpha-hat=0.24 | num traps=19
Layer 174
Layer=174 | N=1024 | M=256 | Q=4.00 | alpha=2.09 | D_ks=0.11 | alpha-hat=0.96 | num traps=1
Layer 178
Layer=178 | N=1024 | M=256 | Q=4.00 | alpha=2.66 | D_ks=0.07 | alpha-hat=1.73 | num traps=0
Layer 180
Layer=180 | N=256 | M=256 | Q=1.00 | alpha=2.62 | D_ks=0.07 | alpha-hat=0.49 | num traps=31
Layer 182
Layer=182 | N=1024 | M=256 | Q=4.00 | alpha=3.69 | D_ks=0.08 | alpha-hat=1.99 | num traps=0
Layer 186
Layer=186 | N=1024 | M=256 | Q=4.00 | alpha=2.43 | D_ks=0.11 | alpha-hat=0.85 | num traps=0
Layer 188
Layer=188 | N=256 | M=256 | Q=1.00 | alpha=2.66 | D_ks=0.07 | alpha-hat=0.01 | num traps=24
Layer 190
Layer=190 | N=1024 | M=256 | Q=4.00 | alpha=3.74 | D_ks=0.12 | alpha-hat=1.95 | num traps=1
Layer 194
Layer=194 | N=1024 | M=256 | Q=4.00 | alpha=3.04 | D_ks=0.07 | alpha-hat=1.44 | num traps=0
Layer 196
Layer=196 | N=256 | M=256 | Q=1.00 | alpha=3.62 | D_ks=0.03 | alpha-hat=-0.18 | num traps=33
Layer 198
Layer=198 | N=1024 | M=256 | Q=4.00 | alpha=5.43 | D_ks=0.11 | alpha-hat=2.00 | num traps=0
Layer 202
Layer=202 | N=1024 | M=256 | Q=4.00 | alpha=3.60 | D_ks=0.13 | alpha-hat=1.40 | num traps=0
Layer 204
Layer=204 | N=256 | M=256 | Q=1.00 | alpha=2.89 | D_ks=0.04 | alpha-hat=-0.54 | num traps=8
Layer 206
Layer=206 | N=1024 | M=256 | Q=4.00 | alpha=5.06 | D_ks=0.04 | alpha-hat=2.20 | num traps=1
Layer 210
Layer=210 | N=1024 | M=256 | Q=4.00 | alpha=4.52 | D_ks=0.10 | alpha-hat=2.23 | num traps=0
Layer 212
Layer=212 | N=256 | M=256 | Q=1.00 | alpha=3.05 | D_ks=0.04 | alpha-hat=0.28 | num traps=19
Layer 214
Layer=214 | N=1024 | M=256 | Q=4.00 | alpha=4.24 | D_ks=0.03 | alpha-hat=2.65 | num traps=1
Layer 218
Layer=218 | N=1024 | M=256 | Q=4.00 | alpha=3.61 | D_ks=0.09 | alpha-hat=1.95 | num traps=1
Layer 220
Layer=220 | N=256 | M=256 | Q=1.00 | alpha=3.51 | D_ks=0.04 | alpha-hat=0.26 | num traps=27
Layer 222
Layer=222 | N=1024 | M=256 | Q=4.00 | alpha=5.93 | D_ks=0.08 | alpha-hat=2.91 | num traps=1
Layer 226
Layer=226 | N=1024 | M=256 | Q=4.00 | alpha=3.77 | D_ks=0.10 | alpha-hat=1.85 | num traps=0
Layer 228
Layer=228 | N=256 | M=256 | Q=1.00 | alpha=4.12 | D_ks=0.03 | alpha-hat=-0.24 | num traps=15
Layer 230
Layer=230 | N=1024 | M=256 | Q=4.00 | alpha=4.08 | D_ks=0.16 | alpha-hat=2.54 | num traps=1
Layer 234
Layer=234 | N=1024 | M=256 | Q=4.00 | alpha=2.97 | D_ks=0.07 | alpha-hat=1.70 | num traps=0
Layer 236
Layer=236 | N=256 | M=256 | Q=1.00 | alpha=4.03 | D_ks=0.03 | alpha-hat=-0.35 | num traps=11
Layer 238
Layer=238 | N=1024 | M=256 | Q=4.00 | alpha=5.90 | D_ks=0.05 | alpha-hat=2.67 | num traps=0
Layer 242
Layer=242 | N=1024 | M=256 | Q=4.00 | alpha=3.10 | D_ks=0.06 | alpha-hat=1.54 | num traps=2
Layer 244
Layer=244 | N=256 | M=256 | Q=1.00 | alpha=2.70 | D_ks=0.04 | alpha-hat=0.14 | num traps=12
Layer 246
Layer=246 | N=1024 | M=256 | Q=4.00 | alpha=3.55 | D_ks=0.05 | alpha-hat=2.27 | num traps=0
Layer 250
Layer=250 | N=1024 | M=256 | Q=4.00 | alpha=3.74 | D_ks=0.07 | alpha-hat=1.82 | num traps=0
Layer 252
Layer=252 | N=256 | M=256 | Q=1.00 | alpha=3.20 | D_ks=0.03 | alpha-hat=0.05 | num traps=13
Layer 254
Layer=254 | N=1024 | M=256 | Q=4.00 | alpha=3.80 | D_ks=0.04 | alpha-hat=2.96 | num traps=1
Layer 259
Layer=259 | N=1024 | M=512 | Q=2.00 | alpha=3.13 | D_ks=0.05 | alpha-hat=3.01 | num traps=0
Layer 261
Layer=261 | N=512 | M=512 | Q=1.00 | alpha=6.26 | D_ks=0.04 | alpha-hat=2.29 | num traps=32
Layer 263
Layer=263 | N=2048 | M=512 | Q=4.00 | alpha=6.75 | D_ks=0.08 | alpha-hat=7.54 | num traps=1
Layer 267
Layer=267 | N=2048 | M=1024 | Q=2.00 | alpha=4.63 | D_ks=0.03 | alpha-hat=4.97 | num traps=1
Layer 270
Layer=270 | N=2048 | M=512 | Q=4.00 | alpha=6.59 | D_ks=0.06 | alpha-hat=5.70 | num traps=1
Layer 272
Layer=272 | N=512 | M=512 | Q=1.00 | alpha=3.67 | D_ks=0.03 | alpha-hat=3.00 | num traps=14
Layer 274
Layer=274 | N=2048 | M=512 | Q=4.00 | alpha=4.42 | D_ks=0.04 | alpha-hat=5.64 | num traps=1
Layer 278
Layer=278 | N=2048 | M=512 | Q=4.00 | alpha=4.43 | D_ks=0.08 | alpha-hat=6.79 | num traps=2
Layer 280
Layer=280 | N=512 | M=512 | Q=1.00 | alpha=3.48 | D_ks=0.06 | alpha-hat=2.77 | num traps=32
Layer 282
Layer=282 | N=2048 | M=512 | Q=4.00 | alpha=3.23 | D_ks=0.03 | alpha-hat=5.90 | num traps=1
Layer 286
Layer=286 | N=2048 | M=1000 | Q=2.05 | alpha=4.57 | D_ks=0.04 | alpha-hat=6.69 | num traps=21