examples/mnist/job.conf

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"
}