--- /dev/null
+// Copyright 2013 Yangqing Jia
+
+package caffe;
+
+message BlobProto {
+ optional int32 num = 1 [default = 0];
+ optional int32 channels = 2 [default = 0];
+ optional int32 height = 3 [default = 0];
+ optional int32 width = 4 [default = 0];
+ repeated float data = 5 [packed = true];
+ repeated float diff = 6 [packed = true];
+}
+
+// The BlobProtoVector is simply a way to pass multiple blobproto instances
+// around.
+message BlobProtoVector {
+ repeated BlobProto blobs = 1;
+}
+
+message Datum {
+ optional int32 channels = 1;
+ optional int32 height = 2;
+ optional int32 width = 3;
+ // the actual image data, in bytes
+ optional bytes data = 4;
+ optional int32 label = 5;
+ // Optionally, the datum could also hold float data.
+ repeated float float_data = 6;
+}
+
+message FillerParameter {
+ // The filler type.
+ optional string type = 1 [default = 'constant'];
+ optional float value = 2 [default = 0]; // the value in constant filler
+ optional float min = 3 [default = 0]; // the min value in uniform filler
+ optional float max = 4 [default = 1]; // the max value in uniform filler
+ optional float mean = 5 [default = 0]; // the mean value in gaussian filler
+ optional float std = 6 [default = 1]; // the std value in gaussian filler
+}
+
+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
+
+ 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
+ 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 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
+
+ // 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];
+
+ // 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];
+
+ // 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 = 65 [default = 1];
+}
+
+message LayerConnection {
+ optional LayerParameter layer = 1; // the layer parameter
+ repeated string bottom = 2; // the name of the bottom blobs
+ repeated string top = 3; // the name of the top blobs
+}
+
+message NetParameter {
+ optional string name = 1; // consider giving the network a name
+ repeated LayerConnection layers = 2; // a bunch of layers.
+ // The input blobs to the network.
+ repeated string input = 3;
+ // The dim of the input blobs. For each input blob there should be four
+ // values specifying the num, channels, height and width of the input blob.
+ // Thus, there should be a total of (4 * #input) numbers.
+ repeated int32 input_dim = 4;
+ // Whether the network will force every layer to carry out backward operation.
+ // If set False, then whether to carry out backward is determined
+ // automatically according to the net structure and learning rates.
+ optional bool force_backward = 5 [default = false];
+}
+
+message SolverParameter {
+ optional string train_net = 1; // The proto file for the training net.
+ optional string test_net = 2; // The proto file for the testing net.
+ // The number of iterations for each testing phase.
+ optional int32 test_iter = 3 [default = 0];
+ // The number of iterations between two testing phases.
+ optional int32 test_interval = 4 [default = 0];
+ optional float base_lr = 5; // The base learning rate
+ // the number of iterations between displaying info. If display = 0, no info
+ // will be displayed.
+ optional int32 display = 6;
+ optional int32 max_iter = 7; // the maximum number of iterations
+ optional string lr_policy = 8; // The learning rate decay policy.
+ optional float gamma = 9; // The parameter to compute the learning rate.
+ optional float power = 10; // The parameter to compute the learning rate.
+ optional float momentum = 11; // The momentum value.
+ optional float weight_decay = 12; // The weight decay.
+ optional int32 stepsize = 13; // the stepsize for learning rate policy "step"
+ optional int32 snapshot = 14 [default = 0]; // The snapshot interval
+ optional string snapshot_prefix = 15; // The prefix for the snapshot.
+ // whether to snapshot diff in the results or not. Snapshotting diff will help
+ // debugging but the final protocol buffer size will be much larger.
+ optional bool snapshot_diff = 16 [default = false];
+ // the mode solver will use: 0 for CPU and 1 for GPU. Use GPU in default.
+ optional int32 solver_mode = 17 [default = 1];
+ // the device_id will that be used in GPU mode. Use device_id = 0 in default.
+ optional int32 device_id = 18 [default = 0];
+}
+
+// A message that stores the solver snapshots
+message SolverState {
+ optional int32 iter = 1; // The current iteration
+ optional string learned_net = 2; // The file that stores the learned net.
+ repeated BlobProto history = 3; // The history for sgd solvers
+}