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- name: "LeNetSimplifie2"
- layer {
- name: "data"
- type: "MemoryData"
- top: "data"
- top: "label"
- include {
- phase: TRAIN
- }
- transform_param {
- scale: 0.00390625
- }
- memory_data_param
- {
- batch_size: 50
- channels: 1
- height: 28
- width: 28
- }
- }
- layer {
- name: "test_inputdata"
- type: "MemoryData"
- top: "data"
- top: "label"
- include {
- phase: TEST
- }
- transform_param {
- scale: 0.00390625
- }
- memory_data_param
- {
- batch_size: 50
- channels: 1
- height: 28
- width: 28
- }
- }
- layer {
- name: "conv1a"
- type: "Convolution"
- bottom: "data"
- top: "conv1a"
- param {
- lr_mult: 1
- }
- param {
- lr_mult: 2
- }
- convolution_param {
- num_output: 6
- kernel_size: 5
- stride: 1
- weight_filler {
- type: "xavier"
- }
- bias_filler {
- type: "constant"
- }
- }
- }
- layer {
- name: "pool1"
- type: "Pooling"
- bottom: "conv1a"
- top: "pool1"
- pooling_param {
- pool: MAX
- kernel_size: 2
- stride: 2
- }
- }
- layer {
- name: "ip1a"
- type: "InnerProduct"
- bottom: "pool1"
- top: "ip1a"
- param {
- lr_mult: 1
- }
- param {
- lr_mult: 2
- }
- inner_product_param {
- num_output: 120
- weight_filler {
- type: "xavier"
- }
- bias_filler {
- type: "constant"
- }
- }
- }
- layer {
- name: "sigmoid"
- type: "Sigmoid"
- bottom: "ip1a"
- top: "sigmoid"
- }
- layer {
- name: "ip2"
- type: "InnerProduct"
- bottom: "sigmoid"
- top: "ip2"
- param {
- lr_mult: 1
- }
- param {
- lr_mult: 2
- }
- inner_product_param {
- num_output: 10
- weight_filler {
- type: "xavier"
- }
- bias_filler {
- type: "constant"
- }
- }
- }
- layer {
- name: "accuracy"
- type: "Accuracy"
- bottom: "ip2"
- bottom: "label"
- top: "accuracy"
- include {
- phase: TEST
- }
- }
- layer {
- name: "loss"
- type: "SoftmaxWithLoss"
- bottom: "ip2"
- bottom: "label"
- top: "loss"
- }
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