| name: "mlp" |
| train_steps: 1000 |
| test_steps:10 |
| test_freq:60 |
| disp_freq:10 |
| train_one_batch { |
| alg: kBP |
| } |
| updater{ |
| type: kSGD |
| learning_rate{ |
| type : kStep |
| base_lr: 0.001 |
| step_conf{ |
| change_freq: 60 |
| gamma: 0.997 |
| } |
| } |
| } |
| |
| neuralnet { |
| layer { |
| name: "data" |
| type: kRecordInput |
| store_conf { |
| backend: "kvfile" |
| path: "examples/mnist/train_data.bin" |
| random_skip: 5000 |
| batchsize: 64 |
| shape: 784 |
| std_value: 127.5 |
| mean_value: 127.5 |
| } |
| include: kTrain |
| } |
| |
| layer { |
| name: "data" |
| type: kRecordInput |
| store_conf { |
| backend: "kvfile" |
| path: "examples/mnist/test_data.bin" |
| batchsize: 100 |
| shape: 784 |
| std_value: 127.5 |
| mean_value: 127.5 |
| } |
| include: kTest |
| } |
| |
| layer{ |
| name: "fc1" |
| type: kInnerProduct |
| srclayers:"data" |
| innerproduct_conf{ |
| num_output: 2500 |
| } |
| param{ |
| name: "w1" |
| init { |
| type: kUniform |
| low:-0.05 |
| high:0.05 |
| } |
| } |
| param{ |
| name: "b1" |
| init { |
| type : kUniform |
| low: -0.05 |
| high:0.05 |
| } |
| } |
| } |
| |
| layer{ |
| name: "tanh1" |
| type: kSTanh |
| srclayers:"fc1" |
| } |
| layer{ |
| name: "fc2" |
| type: kInnerProduct |
| srclayers:"tanh1" |
| innerproduct_conf{ |
| num_output: 2000 |
| } |
| param{ |
| name: "w2" |
| init { |
| type: kUniform |
| low:-0.05 |
| high:0.05 |
| } |
| } |
| param{ |
| name: "b2" |
| init { |
| type: kUniform |
| low: -0.05 |
| high:0.05 |
| } |
| } |
| } |
| |
| layer{ |
| name: "tanh2" |
| type: kSTanh |
| srclayers:"fc2" |
| } |
| layer{ |
| name: "fc3" |
| type: kInnerProduct |
| srclayers:"tanh2" |
| innerproduct_conf{ |
| num_output: 1500 |
| } |
| param{ |
| name: "w3" |
| init{ |
| type: kUniform |
| low:-0.05 |
| high:0.05 |
| } |
| } |
| param{ |
| name: "b3" |
| init { |
| type : kUniform |
| low: -0.05 |
| high:0.05 |
| } |
| } |
| |
| } |
| |
| layer{ |
| name: "tanh3" |
| type: kSTanh |
| srclayers:"fc3" |
| } |
| layer{ |
| name: "fc4" |
| type: kInnerProduct |
| srclayers:"tanh3" |
| innerproduct_conf{ |
| num_output: 1000 |
| } |
| param{ |
| name: "w4" |
| init { |
| type : kUniform |
| low:-0.05 |
| high:0.05 |
| } |
| } |
| param{ |
| name: "b4" |
| init { |
| type : kUniform |
| low: -0.05 |
| high:0.05 |
| } |
| } |
| |
| } |
| |
| layer{ |
| name: "tanh4" |
| type: kSTanh |
| srclayers:"fc4" |
| } |
| layer{ |
| name: "fc5" |
| type: kInnerProduct |
| srclayers:"tanh4" |
| innerproduct_conf{ |
| num_output: 500 |
| } |
| param{ |
| name: "w5" |
| init { |
| type : kUniform |
| low:-0.05 |
| high:0.05 |
| } |
| } |
| param{ |
| name: "b5" |
| init { |
| type : kUniform |
| low: -0.05 |
| high:0.05 |
| } |
| } |
| } |
| |
| layer{ |
| name: "tanh5" |
| type: kSTanh |
| srclayers:"fc5" |
| } |
| layer{ |
| name: "fc6" |
| type: kInnerProduct |
| srclayers:"tanh5" |
| innerproduct_conf{ |
| num_output: 10 |
| } |
| param{ |
| name: "w6" |
| init { |
| type : kUniform |
| low:-0.05 |
| high:0.05 |
| } |
| } |
| param{ |
| name: "b6" |
| init { |
| type : kUniform |
| low: -0.05 |
| high:0.05 |
| } |
| } |
| } |
| layer{ |
| name: "loss" |
| type:kSoftmaxLoss |
| softmaxloss_conf{ |
| topk:1 |
| } |
| srclayers:"fc6" |
| srclayers:"data" |
| } |
| } |
| cluster { |
| nworker_groups: 1 |
| nserver_groups: 1 |
| workspace: "examples/mnist" |
| } |