1 name: "LeNet-test"
2 layers {
3 layer {
4 name: "mnist"
5 type: "data"
6 source: "mnist-test-leveldb"
7 batchsize: 100
8 scale: 0.00390625
9 }
10 top: "data"
11 top: "label"
12 }
13 layers {
14 layer {
15 name: "conv1"
16 type: "conv"
17 num_output: 20
18 kernelsize: 5
19 stride: 1
20 weight_filler {
21 type: "xavier"
22 }
23 bias_filler {
24 type: "constant"
25 }
26 }
27 bottom: "data"
28 top: "conv1"
29 }
30 layers {
31 layer {
32 name: "pool1"
33 type: "pool"
34 kernelsize: 2
35 stride: 2
36 pool: MAX
37 }
38 bottom: "conv1"
39 top: "pool1"
40 }
41 layers {
42 layer {
43 name: "conv2"
44 type: "conv"
45 num_output: 50
46 kernelsize: 5
47 stride: 1
48 weight_filler {
49 type: "xavier"
50 }
51 bias_filler {
52 type: "constant"
53 }
54 }
55 bottom: "pool1"
56 top: "conv2"
57 }
58 layers {
59 layer {
60 name: "pool2"
61 type: "pool"
62 kernelsize: 2
63 stride: 2
64 pool: MAX
65 }
66 bottom: "conv2"
67 top: "pool2"
68 }
69 layers {
70 layer {
71 name: "ip1"
72 type: "innerproduct"
73 num_output: 500
74 weight_filler {
75 type: "xavier"
76 }
77 bias_filler {
78 type: "constant"
79 }
80 }
81 bottom: "pool2"
82 top: "ip1"
83 }
84 layers {
85 layer {
86 name: "relu1"
87 type: "relu"
88 }
89 bottom: "ip1"
90 top: "ip1"
91 }
92 layers {
93 layer {
94 name: "ip2"
95 type: "innerproduct"
96 num_output: 10
97 weight_filler {
98 type: "xavier"
99 }
100 bias_filler {
101 type: "constant"
102 }
103 }
104 bottom: "ip1"
105 top: "ip2"
106 }
107 layers {
108 layer {
109 name: "prob"
110 type: "softmax"
111 }
112 bottom: "ip2"
113 top: "prob"
114 }
115 layers {
116 layer {
117 name: "accuracy"
118 type: "accuracy"
119 }
120 bottom: "prob"
121 bottom: "label"
122 top: "accuracy"
123 }