Merge pull request #1039 from sergeyk/dev

[example] HDF5 classification

examples/hdf5_classification/solver.prototxt

@@ -0,0 +1,14 @@
+net: "examples/hdf5_classification/train_val.prototxt"
+test_iter: 1000
+test_interval: 1000
+base_lr: 0.01
+lr_policy: "step"
+gamma: 0.1
+stepsize: 5000
+display: 1000
+max_iter: 10000
+momentum: 0.9
+weight_decay: 0.0005
+snapshot: 10000
+snapshot_prefix: "examples/hdf5_classification/data/train"
+solver_mode: CPU

examples/hdf5_classification/solver2.prototxt

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+net: "examples/hdf5_classification/train_val2.prototxt"
+test_iter: 1000
+test_interval: 1000
+base_lr: 0.01
+lr_policy: "step"
+gamma: 0.1
+stepsize: 5000
+display: 1000
+max_iter: 10000
+momentum: 0.9
+weight_decay: 0.0005
+snapshot: 10000
+snapshot_prefix: "examples/hdf5_classification/data/train"
+solver_mode: CPU

examples/hdf5_classification/train_val.prototxt

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+name: "LogisticRegressionNet"
+layers {
+  name: "data"
+  type: HDF5_DATA
+  top: "data"
+  top: "label"
+  hdf5_data_param {
+    source: "examples/hdf5_classification/data/train.txt"
+    batch_size: 10
+  }
+  include: { phase: TRAIN }
+}
+layers {
+  name: "data"
+  type: HDF5_DATA
+  top: "data"
+  top: "label"
+  hdf5_data_param {
+    source: "examples/hdf5_classification/data/test.txt"
+    batch_size: 10
+  }
+  include: { phase: TEST }
+}
+layers {
+  name: "fc1"
+  type: INNER_PRODUCT
+  bottom: "data"
+  top: "fc1"
+  blobs_lr: 1
+  blobs_lr: 2
+  weight_decay: 1
+  weight_decay: 0
+  inner_product_param {
+    num_output: 2
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+      value: 0
+    }
+  }
+}
+layers {
+  name: "loss"
+  type: SOFTMAX_LOSS
+  bottom: "fc1"
+  bottom: "label"
+  top: "loss"
+}
+layers {
+  name: "accuracy"
+  type: ACCURACY
+  bottom: "fc1"
+  bottom: "label"
+  top: "accuracy"
+  include: { phase: TEST }
+}

examples/hdf5_classification/train_val2.prototxt

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+name: "LogisticRegressionNet"
+layers {
+  name: "data"
+  type: HDF5_DATA
+  top: "data"
+  top: "label"
+  hdf5_data_param {
+    source: "examples/hdf5_classification/data/train.txt"
+    batch_size: 10
+  }
+  include: { phase: TRAIN }
+}
+layers {
+  name: "data"
+  type: HDF5_DATA
+  top: "data"
+  top: "label"
+  hdf5_data_param {
+    source: "examples/hdf5_classification/data/test.txt"
+    batch_size: 10
+  }
+  include: { phase: TEST }
+}
+layers {
+  name: "fc1"
+  type: INNER_PRODUCT
+  bottom: "data"
+  top: "fc1"
+  blobs_lr: 1
+  blobs_lr: 2
+  weight_decay: 1
+  weight_decay: 0
+  inner_product_param {
+    num_output: 40
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+      value: 0
+    }
+  }
+}
+layers {
+  name: "relu1"
+  type: RELU
+  bottom: "fc1"
+  top: "fc1"
+}
+layers {
+  name: "fc2"
+  type: INNER_PRODUCT
+  bottom: "fc1"
+  top: "fc2"
+  blobs_lr: 1
+  blobs_lr: 2
+  weight_decay: 1
+  weight_decay: 0
+  inner_product_param {
+    num_output: 2
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+      value: 0
+    }
+  }
+}
+layers {
+  name: "loss"
+  type: SOFTMAX_LOSS
+  bottom: "fc2"
+  bottom: "label"
+  top: "loss"
+}
+layers {
+  name: "accuracy"
+  type: ACCURACY
+  bottom: "fc2"
+  bottom: "label"
+  top: "accuracy"
+  include: { phase: TEST }
+}