everything in its right place

8 files changed, 8 insertions, 935 deletions

diff --git a/models/.gitignore b/models/.gitignore
new file mode 100644
index 00000000..e69de29b
--- /dev/null
+++ b/models/.gitignore
diff --git a/models/imagenet.prototxt b/models/imagenet.prototxt
index 5db585b7..62579140 100644
--- a/models/imagenet.prototxt
+++ b/models/imagenet.prototxt
@@ -1,17 +1,8 @@
-name: "CaffeNet"
-layers {
-  layer {
-    name: "data"
-    type: "data"
-    source: "/home/jiayq/Data/ILSVRC12/train-leveldb"
-    meanfile: "/home/jiayq/Data/ILSVRC12/image_mean.binaryproto"
-    batchsize: 256
-    cropsize: 227
-    mirror: true
-  }
-  top: "data"
-  top: "label"
-}
+input: "data"
+input_dim: 10
+input_dim: 3
+input_dim: 227
+input_dim: 227
 layers {
   layer {
     name: "conv1"
@@ -356,9 +347,9 @@ layers {
 }
 layers {
   layer {
-    name: "loss"
-    type: "softmax_loss"
+    name: "prob"
+    type: "softmax"
   }
   bottom: "fc8"
-  bottom: "label"
+  top: "prob"
 }
diff --git a/models/imagenet_deploy.prototxt b/models/imagenet_deploy.prototxt
deleted file mode 100644
index 62579140..00000000
--- a/models/imagenet_deploy.prototxt
+++ /dev/null
@@ -1,355 +0,0 @@
-input: "data"
-input_dim: 10
-input_dim: 3
-input_dim: 227
-input_dim: 227
-layers {
-  layer {
-    name: "conv1"
-    type: "conv"
-    num_output: 96
-    kernelsize: 11
-    stride: 4
-    weight_filler {
-      type: "gaussian"
-      std: 0.01
-    }
-    bias_filler {
-      type: "constant"
-      value: 0.
-    }
-    blobs_lr: 1.
-    blobs_lr: 2.
-    weight_decay: 1.
-    weight_decay: 0.
-  }
-  bottom: "data"
-  top: "conv1"
-}
-layers {
-  layer {
-    name: "relu1"
-    type: "relu"
-  }
-  bottom: "conv1"
-  top: "conv1"
-}
-layers {
-  layer {
-    name: "pool1"
-    type: "pool"
-    pool: MAX
-    kernelsize: 3
-    stride: 2
-  }
-  bottom: "conv1"
-  top: "pool1"
-}
-layers {
-  layer {
-    name: "norm1"
-    type: "lrn"
-    local_size: 5
-    alpha: 0.0001
-    beta: 0.75
-  }
-  bottom: "pool1"
-  top: "norm1"
-}
-layers {
-  layer {
-    name: "pad2"
-    type: "padding"
-    pad: 2
-  }
-  bottom: "norm1"
-  top: "pad2"
-}
-layers {
-  layer {
-    name: "conv2"
-    type: "conv"
-    num_output: 256
-    group: 2
-    kernelsize: 5
-    weight_filler {
-      type: "gaussian"
-      std: 0.01
-    }
-    bias_filler {
-      type: "constant"
-      value: 1.
-    }
-    blobs_lr: 1.
-    blobs_lr: 2.
-    weight_decay: 1.
-    weight_decay: 0.
-  }
-  bottom: "pad2"
-  top: "conv2"
-}
-layers {
-  layer {
-    name: "relu2"
-    type: "relu"
-  }
-  bottom: "conv2"
-  top: "conv2"
-}
-layers {
-  layer {
-    name: "pool2"
-    type: "pool"
-    pool: MAX
-    kernelsize: 3
-    stride: 2
-  }
-  bottom: "conv2"
-  top: "pool2"
-}
-layers {
-  layer {
-    name: "norm2"
-    type: "lrn"
-    local_size: 5
-    alpha: 0.0001
-    beta: 0.75
-  }
-  bottom: "pool2"
-  top: "norm2"
-}
-layers {
-  layer {
-    name: "pad3"
-    type: "padding"
-    pad: 1
-  }
-  bottom: "norm2"
-  top: "pad3"
-}
-layers {
-  layer {
-    name: "conv3"
-    type: "conv"
-    num_output: 384
-    kernelsize: 3
-    weight_filler {
-      type: "gaussian"
-      std: 0.01
-    }
-    bias_filler {
-      type: "constant"
-      value: 0.
-    }
-    blobs_lr: 1.
-    blobs_lr: 2.
-    weight_decay: 1.
-    weight_decay: 0.
-  }
-  bottom: "pad3"
-  top: "conv3"
-}
-layers {
-  layer {
-    name: "relu3"
-    type: "relu"
-  }
-  bottom: "conv3"
-  top: "conv3"
-}
-layers {
-  layer {
-    name: "pad4"
-    type: "padding"
-    pad: 1
-  }
-  bottom: "conv3"
-  top: "pad4"
-}
-layers {
-  layer {
-    name: "conv4"
-    type: "conv"
-    num_output: 384
-    group: 2
-    kernelsize: 3
-    weight_filler {
-      type: "gaussian"
-      std: 0.01
-    }
-    bias_filler {
-      type: "constant"
-      value: 1.
-    }
-    blobs_lr: 1.
-    blobs_lr: 2.
-    weight_decay: 1.
-    weight_decay: 0.
-  }
-  bottom: "pad4"
-  top: "conv4"
-}
-layers {
-  layer {
-    name: "relu4"
-    type: "relu"
-  }
-  bottom: "conv4"
-  top: "conv4"
-}
-layers {
-  layer {
-    name: "pad5"
-    type: "padding"
-    pad: 1
-  }
-  bottom: "conv4"
-  top: "pad5"
-}
-layers {
-  layer {
-    name: "conv5"
-    type: "conv"
-    num_output: 256
-    group: 2
-    kernelsize: 3
-    weight_filler {
-      type: "gaussian"
-      std: 0.01
-    }
-    bias_filler {
-      type: "constant"
-      value: 1.
-    }
-    blobs_lr: 1.
-    blobs_lr: 2.
-    weight_decay: 1.
-    weight_decay: 0.
-  }
-  bottom: "pad5"
-  top: "conv5"
-}
-layers {
-  layer {
-    name: "relu5"
-    type: "relu"
-  }
-  bottom: "conv5"
-  top: "conv5"
-}
-layers {
-  layer {
-    name: "pool5"
-    type: "pool"
-    kernelsize: 3
-    pool: MAX
-    stride: 2
-  }
-  bottom: "conv5"
-  top: "pool5"
-}
-layers {
-  layer {
-    name: "fc6"
-    type: "innerproduct"
-    num_output: 4096
-    weight_filler {
-      type: "gaussian"
-      std: 0.005
-    }
-    bias_filler {
-      type: "constant"
-      value: 1.
-    }
-    blobs_lr: 1.
-    blobs_lr: 2.
-    weight_decay: 1.
-    weight_decay: 0.
-  }
-  bottom: "pool5"
-  top: "fc6"
-}
-layers {
-  layer {
-    name: "relu6"
-    type: "relu"
-  }
-  bottom: "fc6"
-  top: "fc6"
-}
-layers {
-  layer {
-    name: "drop6"
-    type: "dropout"
-    dropout_ratio: 0.5
-  }
-  bottom: "fc6"
-  top: "fc6"
-}
-layers {
-  layer {
-    name: "fc7"
-    type: "innerproduct"
-    num_output: 4096
-    weight_filler {
-      type: "gaussian"
-      std: 0.005
-    }
-    bias_filler {
-      type: "constant"
-      value: 1.
-    }
-    blobs_lr: 1.
-    blobs_lr: 2.
-    weight_decay: 1.
-    weight_decay: 0.
-  }
-  bottom: "fc6"
-  top: "fc7"
-}
-layers {
-  layer {
-    name: "relu7"
-    type: "relu"
-  }
-  bottom: "fc7"
-  top: "fc7"
-}
-layers {
-  layer {
-    name: "drop7"
-    type: "dropout"
-    dropout_ratio: 0.5
-  }
-  bottom: "fc7"
-  top: "fc7"
-}
-layers {
-  layer {
-    name: "fc8"
-    type: "innerproduct"
-    num_output: 1000
-    weight_filler {
-      type: "gaussian"
-      std: 0.01
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    blobs_lr: 1.
-    blobs_lr: 2.
-    weight_decay: 1.
-    weight_decay: 0.
-  }
-  bottom: "fc7"
-  top: "fc8"
-}
-layers {
-  layer {
-    name: "prob"
-    type: "softmax"
-  }
-  bottom: "fc8"
-  top: "prob"
-}
diff --git a/models/imagenet_solver.prototxt b/models/imagenet_solver.prototxt
deleted file mode 100644
index 7921d32d..00000000
--- a/models/imagenet_solver.prototxt
+++ /dev/null
@@ -1,14 +0,0 @@
-train_net: "examples/imagenet.prototxt"
-test_net: "examples/imagenet_val.prototxt"
-test_iter: 1000
-test_interval: 1000
-base_lr: 0.01
-lr_policy: "step"
-gamma: 0.1
-stepsize: 100000
-display: 20
-max_iter: 450000
-momentum: 0.9
-weight_decay: 0.0005
-snapshot: 10000
-snapshot_prefix: "caffe_imagenet_train"
diff --git a/models/imagenet_val.prototxt b/models/imagenet_val.prototxt
deleted file mode 100644
index fbc4c325..00000000
--- a/models/imagenet_val.prototxt
+++ /dev/null
@@ -1,277 +0,0 @@
-name: "CaffeNet"
-layers {
-  layer {
-    name: "data"
-    type: "data"
-    source: "/home/jiayq/Data/ILSVRC12/val-leveldb"
-    meanfile: "/home/jiayq/Data/ILSVRC12/image_mean.binaryproto"
-    batchsize: 50
-    cropsize: 227
-    mirror: false
-  }
-  top: "data"
-  top: "label"
-}
-layers {
-  layer {
-    name: "conv1"
-    type: "conv"
-    num_output: 96
-    kernelsize: 11
-    stride: 4
-  }
-  bottom: "data"
-  top: "conv1"
-}
-layers {
-  layer {
-    name: "relu1"
-    type: "relu"
-  }
-  bottom: "conv1"
-  top: "conv1"
-}
-layers {
-  layer {
-    name: "pool1"
-    type: "pool"
-    pool: MAX
-    kernelsize: 3
-    stride: 2
-  }
-  bottom: "conv1"
-  top: "pool1"
-}
-layers {
-  layer {
-    name: "norm1"
-    type: "lrn"
-    local_size: 5
-    alpha: 0.0001
-    beta: 0.75
-  }
-  bottom: "pool1"
-  top: "norm1"
-}
-layers {
-  layer {
-    name: "pad2"
-    type: "padding"
-    pad: 2
-  }
-  bottom: "norm1"
-  top: "pad2"
-}
-layers {
-  layer {
-    name: "conv2"
-    type: "conv"
-    num_output: 256
-    group: 2
-    kernelsize: 5
-  }
-  bottom: "pad2"
-  top: "conv2"
-}
-layers {
-  layer {
-    name: "relu2"
-    type: "relu"
-  }
-  bottom: "conv2"
-  top: "conv2"
-}
-layers {
-  layer {
-    name: "pool2"
-    type: "pool"
-    pool: MAX
-    kernelsize: 3
-    stride: 2
-  }
-  bottom: "conv2"
-  top: "pool2"
-}
-layers {
-  layer {
-    name: "norm2"
-    type: "lrn"
-    local_size: 5
-    alpha: 0.0001
-    beta: 0.75
-  }
-  bottom: "pool2"
-  top: "norm2"
-}
-layers {
-  layer {
-    name: "pad3"
-    type: "padding"
-    pad: 1
-  }
-  bottom: "norm2"
-  top: "pad3"
-}
-layers {
-  layer {
-    name: "conv3"
-    type: "conv"
-    num_output: 384
-    kernelsize: 3
-  }
-  bottom: "pad3"
-  top: "conv3"
-}
-layers {
-  layer {
-    name: "relu3"
-    type: "relu"
-  }
-  bottom: "conv3"
-  top: "conv3"
-}
-layers {
-  layer {
-    name: "pad4"
-    type: "padding"
-    pad: 1
-  }
-  bottom: "conv3"
-  top: "pad4"
-}
-layers {
-  layer {
-    name: "conv4"
-    type: "conv"
-    num_output: 384
-    group: 2
-    kernelsize: 3
-  }
-  bottom: "pad4"
-  top: "conv4"
-}
-layers {
-  layer {
-    name: "relu4"
-    type: "relu"
-  }
-  bottom: "conv4"
-  top: "conv4"
-}
-layers {
-  layer {
-    name: "pad5"
-    type: "padding"
-    pad: 1
-  }
-  bottom: "conv4"
-  top: "pad5"
-}
-layers {
-  layer {
-    name: "conv5"
-    type: "conv"
-    num_output: 256
-    group: 2
-    kernelsize: 3
-  }
-  bottom: "pad5"
-  top: "conv5"
-}
-layers {
-  layer {
-    name: "relu5"
-    type: "relu"
-  }
-  bottom: "conv5"
-  top: "conv5"
-}
-layers {
-  layer {
-    name: "pool5"
-    type: "pool"
-    kernelsize: 3
-    pool: MAX
-    stride: 2
-  }
-  bottom: "conv5"
-  top: "pool5"
-}
-layers {
-  layer {
-    name: "fc6"
-    type: "innerproduct"
-    num_output: 4096
-  }
-  bottom: "pool5"
-  top: "fc6"
-}
-layers {
-  layer {
-    name: "relu6"
-    type: "relu"
-  }
-  bottom: "fc6"
-  top: "fc6"
-}
-layers {
-  layer {
-    name: "drop6"
-    type: "dropout"
-    dropout_ratio: 0.5
-  }
-  bottom: "fc6"
-  top: "fc6"
-}
-layers {
-  layer {
-    name: "fc7"
-    type: "innerproduct"
-    num_output: 4096
-  }
-  bottom: "fc6"
-  top: "fc7"
-}
-layers {
-  layer {
-    name: "relu7"
-    type: "relu"
-  }
-  bottom: "fc7"
-  top: "fc7"
-}
-layers {
-  layer {
-    name: "drop7"
-    type: "dropout"
-    dropout_ratio: 0.5
-  }
-  bottom: "fc7"
-  top: "fc7"
-}
-layers {
-  layer {
-    name: "fc8"
-    type: "innerproduct"
-    num_output: 1000
-  }
-  bottom: "fc7"
-  top: "fc8"
-}
-layers {
-  layer {
-    name: "prob"
-    type: "softmax"
-  }
-  bottom: "fc8"
-  top: "prob"
-}
-layers {
-  layer {
-    name: "accuracy"
-    type: "accuracy"
-  }
-  bottom: "prob"
-  bottom: "label"
-  top: "accuracy"
-}
diff --git a/models/lenet.prototxt b/models/lenet.prototxt
deleted file mode 100644
index e1049f73..00000000
--- a/models/lenet.prototxt
+++ /dev/null
@@ -1,122 +0,0 @@
-name: "LeNet"
-layers {
-  layer {
-    name: "mnist"
-    type: "data"
-    source: "../data/mnist-train-leveldb"
-    batchsize: 64
-    scale: 0.00390625
-  }
-  top: "data"
-  top: "label"
-}
-layers {
-  layer {
-    name: "conv1"
-    type: "conv"
-    num_output: 20
-    kernelsize: 5
-    stride: 1
-    weight_filler {
-      type: "xavier"
-    }
-    bias_filler {
-      type: "constant"
-    }
-    blobs_lr: 1.
-    blobs_lr: 2.
-  }
-  bottom: "data"
-  top: "conv1"
-}
-layers {
-  layer {
-    name: "pool1"
-    type: "pool"
-    kernelsize: 2
-    stride: 2
-    pool: MAX
-  }
-  bottom: "conv1"
-  top: "pool1"
-}
-layers {
-  layer {
-    name: "conv2"
-    type: "conv"
-    num_output: 50
-    kernelsize: 5
-    stride: 1
-    weight_filler {
-      type: "xavier"
-    }
-    bias_filler {
-      type: "constant"
-    }
-    blobs_lr: 1.
-    blobs_lr: 2.
-  }
-  bottom: "pool1"
-  top: "conv2"
-}
-layers {
-  layer {
-    name: "pool2"
-    type: "pool"
-    kernelsize: 2
-    stride: 2
-    pool: MAX
-  }
-  bottom: "conv2"
-  top: "pool2"
-}
-layers {
-  layer {
-    name: "ip1"
-    type: "innerproduct"
-    num_output: 500
-    weight_filler {
-      type: "xavier"
-    }
-    bias_filler {
-      type: "constant"
-    }
-    blobs_lr: 1.
-    blobs_lr: 2.
-  }
-  bottom: "pool2"
-  top: "ip1"
-}
-layers {
-  layer {
-    name: "relu1"
-    type: "relu"
-  }
-  bottom: "ip1"
-  top: "ip1"
-}
-layers {
-  layer {
-    name: "ip2"
-    type: "innerproduct"
-    num_output: 10
-    weight_filler {
-      type: "xavier"
-    }
-    bias_filler {
-      type: "constant"
-    }
-    blobs_lr: 1.
-    blobs_lr: 2.
-  }
-  bottom: "ip1"
-  top: "ip2"
-}
-layers {
-  layer {
-    name: "loss"
-    type: "softmax_loss"
-  }
-  bottom: "ip2"
-  bottom: "label"
-}
diff --git a/models/lenet_solver.prototxt b/models/lenet_solver.prototxt
deleted file mode 100644
index d0edc0f0..00000000
--- a/models/lenet_solver.prototxt
+++ /dev/null
@@ -1,27 +0,0 @@
-# The training protocol buffer definition
-train_net: "lenet.prototxt"
-# The testing protocol buffer definition
-test_net: "lenet_test.prototxt"
-# test_iter specifies how many forward passes the test should carry out.
-# In the case of MNIST, we have test batch size 100 and 100 test iterations,
-# covering the full 10,000 testing images.
-test_iter: 100
-# Carry out testing every 500 training iterations.
-test_interval: 500
-# The base learning rate, momentum and the weight decay of the network.
-base_lr: 0.01
-momentum: 0.9
-weight_decay: 0.0005
-# The learning rate policy
-lr_policy: "inv"
-gamma: 0.0001
-power: 0.75
-# Display every 100 iterations
-display: 100
-# The maximum number of iterations
-max_iter: 10000
-# snapshot intermediate results
-snapshot: 5000
-snapshot_prefix: "lenet"
-# solver mode: 0 for CPU and 1 for GPU
-solver_mode: 1
diff --git a/models/lenet_test.prototxt b/models/lenet_test.prototxt
deleted file mode 100644
index 38f1a5e9..00000000
--- a/models/lenet_test.prototxt
+++ /dev/null
@@ -1,123 +0,0 @@
-name: "LeNet-test"
-layers {
-  layer {
-    name: "mnist"
-    type: "data"
-    source: "../data/mnist-test-leveldb"
-    batchsize: 100
-    scale: 0.00390625
-  }
-  top: "data"
-  top: "label"
-}
-layers {
-  layer {
-    name: "conv1"
-    type: "conv"
-    num_output: 20
-    kernelsize: 5
-    stride: 1
-    weight_filler {
-      type: "xavier"
-    }
-    bias_filler {
-      type: "constant"
-    }
-  }
-  bottom: "data"
-  top: "conv1"
-}
-layers {
-  layer {
-    name: "pool1"
-    type: "pool"
-    kernelsize: 2
-    stride: 2
-    pool: MAX
-  }
-  bottom: "conv1"
-  top: "pool1"
-}
-layers {
-  layer {
-    name: "conv2"
-    type: "conv"
-    num_output: 50
-    kernelsize: 5
-    stride: 1
-    weight_filler {
-      type: "xavier"
-    }
-    bias_filler {
-      type: "constant"
-    }
-  }
-  bottom: "pool1"
-  top: "conv2"
-}
-layers {
-  layer {
-    name: "pool2"
-    type: "pool"
-    kernelsize: 2
-    stride: 2
-    pool: MAX
-  }
-  bottom: "conv2"
-  top: "pool2"
-}
-layers {
-  layer {
-    name: "ip1"
-    type: "innerproduct"
-    num_output: 500
-    weight_filler {
-      type: "xavier"
-    }
-    bias_filler {
-      type: "constant"
-    }
-  }
-  bottom: "pool2"
-  top: "ip1"
-}
-layers {
-  layer {
-    name: "relu1"
-    type: "relu"
-  }
-  bottom: "ip1"
-  top: "ip1"
-}
-layers {
-  layer {
-    name: "ip2"
-    type: "innerproduct"
-    num_output: 10
-    weight_filler {
-      type: "xavier"
-    }
-    bias_filler {
-      type: "constant"
-    }
-  }
-  bottom: "ip1"
-  top: "ip2"
-}
-layers {
-  layer {
-    name: "prob"
-    type: "softmax"
-  }
-  bottom: "ip2"
-  top: "prob"
-}
-layers {
-  layer {
-    name: "accuracy"
-    type: "accuracy"
-  }
-  bottom: "prob"
-  bottom: "label"
-  top: "accuracy"
-}