move individual layer parameters to individual proto messages

src/caffe/proto/caffe.proto

@@ -42,56 +42,85 @@ message LayerParameter {
   optional string name = 1; // the layer name
   optional string type = 2; // the string to specify the layer type
 
-  // Parameters to specify layers with inner products.
-  optional uint32 num_output = 3; // The number of outputs for the layer
-  optional bool biasterm = 4 [default = true]; // whether to have bias terms
-  optional FillerParameter weight_filler = 5; // The filler for the weight
-  optional FillerParameter bias_filler = 6; // The filler for the bias
+  // The blobs containing the numeric parameters of the layer
+  repeated BlobProto blobs = 3;
+  // The ratio that is multiplied on the global learning rate. If you want to
+  // set the learning ratio for one blob, you need to set it for all blobs.
+  repeated float blobs_lr = 4;
+  // The weight decay that is multiplied on the global weight decay.
+  repeated float weight_decay = 5;
 
-  optional uint32 pad = 7 [default = 0]; // The padding size
-  optional uint32 kernelsize = 8; // The kernel size
-  optional uint32 group = 9 [default = 1]; // The group size for group conv
-  optional uint32 stride = 10 [default = 1]; // The stride
+  // Parameters for particular layer types.
+  optional DataParameter data_param = 6;
+  optional InnerProductParameter inner_product_param = 7;
+  optional ConvolutionParameter convolution_param = 8;
+  optional PoolParameter pool_param = 9;
+  optional DropoutParameter dropout_param = 10;
+  optional LRNParameter lrn_param = 11;
+}
+
+message DataParameter {
+  // Specify the data source.
+  optional string source = 1;
+  // For data pre-processing, we can do simple scaling and subtracting the
+  // data mean, if provided. Note that the mean subtraction is always carried
+  // out before scaling.
+  optional float scale = 2 [default = 1];
+  optional string meanfile = 3;
+  // Specify the batch size.
+  optional uint32 batchsize = 4;
+  // Specify if we would like to randomly crop an image.
+  optional uint32 cropsize = 5 [default = 0];
+  // Specify if we want to randomly mirror data.
+  optional bool mirror = 6 [default = false];
+  // The rand_skip variable is for the data layer to skip a few data points
+  // to avoid all asynchronous sgd clients to start at the same point. The skip
+  // point would be set as rand_skip * rand(0,1). Note that rand_skip should not
+  // be larger than the number of keys in the leveldb.
+  optional uint32 rand_skip = 7 [default = 0];
+}
+
+message InnerProductParameter {
+  optional uint32 num_output = 1; // The number of outputs for the layer
+  optional bool biasterm = 2 [default = true]; // whether to have bias terms
+  optional FillerParameter weight_filler = 3; // The filler for the weight
+  optional FillerParameter bias_filler = 4; // The filler for the bias
+}
+
+message ConvolutionParameter {
+  optional uint32 pad = 1 [default = 0]; // The padding size
+  optional uint32 kernelsize = 2; // The kernel size
+  optional uint32 group = 3 [default = 1]; // The group size for group conv
+  optional uint32 stride = 4 [default = 1]; // The stride
+}
+
+message PoolParameter {
   enum PoolMethod {
     MAX = 0;
     AVE = 1;
     STOCHASTIC = 2;
   }
-  optional PoolMethod pool = 11 [default = MAX]; // The pooling method
-  optional float dropout_ratio = 12 [default = 0.5]; // dropout ratio
+  optional PoolMethod pool = 1 [default = MAX]; // The pooling method
+}
 
-  optional uint32 local_size = 13 [default = 5]; // for local response norm
-  optional float alpha = 14 [default = 1.]; // for local response norm
-  optional float beta = 15 [default = 0.75]; // for local response norm
+message DropoutParameter {
+  optional float dropout_ratio = 1 [default = 0.5]; // dropout ratio
+}
 
-  // For data layers, specify the data source
-  optional string source = 16;
-  // For data pre-processing, we can do simple scaling and subtracting the
-  // data mean, if provided. Note that the mean subtraction is always carried
-  // out before scaling.
-  optional float scale = 17 [default = 1];
-  optional string meanfile = 18;
-  // For data layers, specify the batch size.
-  optional uint32 batchsize = 19;
-  // For data layers, specify if we would like to randomly crop an image.
-  optional uint32 cropsize = 20 [default = 0];
-  // For data layers, specify if we want to randomly mirror data.
-  optional bool mirror = 21 [default = false];
+message LRNParameter {
+  optional uint32 local_size = 1 [default = 5]; // for local response norm
+  optional float alpha = 2 [default = 1.]; // for local response norm
+  optional float beta = 3 [default = 0.75]; // for local response norm
+}
 
-  // The blobs containing the numeric parameters of the layer
-  repeated BlobProto blobs = 50;
-  // The ratio that is multiplied on the global learning rate. If you want to
-  // set the learning ratio for one blob, you need to set it for all blobs.
-  repeated float blobs_lr = 51;
-  // The weight decay that is multiplied on the global weight decay.
-  repeated float weight_decay = 52;
-
-  // The rand_skip variable is for the data layer to skip a few data points
-  // to avoid all asynchronous sgd clients to start at the same point. The skip
-  // point would be set as rand_skip * rand(0,1). Note that rand_skip should not
-  // be larger than the number of keys in the leveldb.
-  optional uint32 rand_skip = 53 [default = 0];
+message ConcatParameter {
+  // Concat Layer needs to specify the dimension along the concat will happen,
+  // the other dimensions must be the same for all the bottom blobs
+  // By default it will concatenate blobs along channels dimension
+  optional uint32 concat_dim = 1 [default = 1];
+}
 
+message WindowDataParameter {
   // Fields related to detection (det_*)
   // foreground (object) overlap threshold
   optional float det_fg_threshold = 54 [default = 0.5];
@@ -110,23 +139,6 @@ message LayerParameter {
   // warp: cropped window is warped to a fixed size and aspect ratio
   // square: the tightest square around the window is cropped
   optional string det_crop_mode = 59 [default = "warp"];
-
-  // For ReshapeLayer, one needs to specify the new dimensions.
-  optional int32 new_num = 60 [default = 0];
-  optional int32 new_channels = 61 [default = 0];
-  optional int32 new_height = 62 [default = 0];
-  optional int32 new_width = 63 [default = 0];
-
-  // Whether or not ImageLayer should shuffle the list of files at every epoch.
-  // It will also resize images if new_height or new_width are not zero.
-  optional bool shuffle_images = 64 [default = false];
-
-  // For ConcatLayer, one needs to specify the dimension for concatenation, and
-  // the other dimensions must be the same for all the bottom blobs.
-  // By default it will concatenate blobs along the channels dimension.
-  optional uint32 concat_dim = 65 [default = 1];
-
-  optional HDF5OutputParameter hdf5_output_param = 1001;
 }
 
 message HDF5OutputParameter {