package caffe

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View/edit binary Protocol Buffers messages

Used in: BlobProtoVector, LayerParameter, SolverState

• optional int32 num = 1

• optional int32 channels = 2

• optional int32 height = 3

• optional int32 width = 4

• repeated float data = 5

• repeated float diff = 6

The BlobProtoVector is simply a way to pass multiple blobproto instances around.

• repeated BlobProto blobs = 1

• optional int32 channels = 1

• optional int32 height = 2

• optional int32 width = 3

• optional bytes data = 4

  the actual image data, in bytes

• optional int32 label = 5

• repeated float float_data = 6

  Optionally, the datum could also hold float data.

Used in: LayerParameter

• optional string type = 1

  The filler type.

• optional float value = 2

  the value in constant filler

• optional float min = 3

  the min value in uniform filler

• optional float max = 4

  the max value in uniform filler

• optional float mean = 5

  the mean value in gaussian filler

• optional float std = 6

  the std value in gaussian filler

• optional string snapshot = 7

  the snapshot file path in from_other filler

• optional string layer = 8

  the layer name in from_other filler

• optional uint32 source_index = 9

  the index of blob in the layer in from_other filler

• optional string binary = 10

  the binary file to load weights from

Used in: SolverParameter

• optional string type = 1

  the type of the info

• optional int32 interval = 2

  how long it is notified once

Used in: NetParameter

• 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

Used in: LayerConnection

• optional string name = 1

  the layer name

• optional string type = 2

  the string to specify the layer type

• optional uint32 num_output = 3

  Parameters to specify layers with inner products.

  The number of outputs for the layer

• optional bool biasterm = 4

  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

  The padding size

• optional uint32 kernelsize = 8

  The kernel size

• optional uint32 group = 9

  The group size for group conv

• optional uint32 stride = 10

  The stride

• optional LayerParameter.PoolMethod pool = 11

  The pooling method

• optional float dropout_ratio = 12

  dropout ratio

• optional uint32 local_size = 13

  for local response norm

• optional float alpha = 14

  for local response norm

• optional float beta = 15

  for local response norm

• optional string source = 16

  For data layers, specify the data source

• optional float scale = 17

  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 string meanfile = 18

• optional uint32 batchsize = 19

  For data layers, specify the batch size.

• optional uint32 cropsize = 20

  For data layers, specify if we would like to randomly crop an image.

• optional bool mirror = 21

  For data layers, specify if we want to randomly mirror data.

• repeated BlobProto blobs = 50

  The blobs containing the numeric parameters of the layer

• repeated float blobs_lr = 51

  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 weight_decay = 52

  The weight decay that is multiplied on the global weight decay.

• repeated string blobs_lr_policy = 56

  Learning rate local policy

• optional uint32 rand_skip = 53

  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 bool mean_on_test = 54

  mean on train and mean on test for dropout layer which is for debuging purpose

• optional bool mean_on_train = 55

• optional uint32 concat_dim = 65

  Concat Layer need 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

Used in: LayerParameter

• MAX = 0

• AVE = 1

• STOCHASTIC = 2

• optional string name = 1

  consider giving the network a name

• repeated LayerConnection layers = 2

  a bunch of layers.

• repeated string input = 3

  The input blobs to the network.

• repeated int32 input_dim = 4

  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.

• optional bool force_backward = 5

  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 string train_net = 1

  The proto file for the training net.

• optional string test_net = 2

  The proto file for the testing net.

• optional int32 test_iter = 3

  The number of iterations for each testing phase.

• optional int32 test_interval = 4

  The number of iterations between two testing phases.

• optional float base_lr = 5

  The base learning rate

• optional int32 display = 6

  the number of iterations between displaying info. If display = 0, no info will be displayed.

• 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

  The snapshot interval

• optional string snapshot_prefix = 15

  The prefix for the snapshot.

• optional bool snapshot_diff = 16

  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 int32 solver_mode = 17

  the mode solver will use: 0 for CPU and 1 for GPU. Use GPU in default.

• optional int32 device_id = 18

  the device_id will that be used in GPU mode. Use device_id=0 in default.

• repeated InfoParameter info = 19

  The infomation printer to print information of the net

• optional float localgamma = 50

• optional float localpower = 51

• optional int32 localstepsize = 52

• optional int32 epoch_size = 53

A message that stores the solver snapshots

• 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