package caffe

Get desktop application:
View/edit binary Protocol Buffers messages

Message that stores parameters used by AccuracyLayer

Used in: LayerParameter

• optional uint32 top_k = 1

  When computing accuracy, count as correct by comparing the true label to the top k scoring classes. By default, only compare to the top scoring class (i.e. argmax).

Message that stores parameters used by ArgMaxLayer

Used in: LayerParameter

• optional bool out_max_val = 1

  If true produce pairs (argmax, maxval)

Used in: BlobProtoVector, LayerParameter, SolverState, V0LayerParameter

• 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

Message that stores parameters used by ConcatLayer

Used in: LayerParameter

• optional uint32 concat_dim = 1

  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

Message that stores parameters used by ConvolutionLayer

Used in: LayerParameter

• optional uint32 num_output = 1

  The number of outputs for the layer

• optional bool bias_term = 2

  whether to have bias terms

• optional uint32 pad = 3

  The padding size

• optional uint32 kernel_size = 4

  The kernel size

• optional uint32 group = 5

  The group size for group conv

• optional uint32 stride = 6

  The stride

• optional FillerParameter weight_filler = 7

  The filler for the weight

• optional FillerParameter bias_filler = 8

  The filler for the bias

Message that stores parameters used by DataLayer

Used in: LayerParameter

• optional string source = 1

  Specify the data source.

• optional float scale = 2

  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 mean_file = 3

• optional uint32 batch_size = 4

  Specify the batch size.

• optional uint32 crop_size = 5

  Specify if we would like to randomly crop an image.

• optional bool mirror = 6

  Specify if we want to randomly mirror data.

• optional uint32 rand_skip = 7

  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 DataParameter.DB backend = 8

Used in: DataParameter

• LEVELDB = 0

• LMDB = 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.

Message that stores parameters used by DropoutLayer

Used in: LayerParameter

• optional float dropout_ratio = 1

  dropout ratio

Message that stores parameters used by DummyDataLayer. DummyDataLayer fills any number of arbitrarily shaped blobs with random (or constant) data generated by "Fillers" (see "message FillerParameter").

Used in: LayerParameter

• repeated FillerParameter data_filler = 1

  This layer produces N >= 1 top blobs. DummyDataParameter must specify 1 or N num, N channels, N height, and N width fields, and must specify 0, 1 or N data_fillers. If 0 data_fillers are specified, ConstantFiller with a value of 0 is used. If 1 data_filler is specified, it is applied to all top blobs. If N are specified, the ith is applied to the ith top blob.

• repeated uint32 num = 2

• repeated uint32 channels = 3

• repeated uint32 height = 4

• repeated uint32 width = 5

Message that stores parameters used by EltwiseLayer

Used in: LayerParameter

• optional EltwiseParameter.EltwiseOp operation = 1

  element-wise operation

• repeated float coeff = 2

  blob-wise coefficient for SUM operation

Used in: EltwiseParameter

• PROD = 0

• SUM = 1

Used in: ConvolutionParameter, DummyDataParameter, InnerProductParameter, V0LayerParameter

• 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 int32 sparse = 7

  The expected number of non-zero input weights for a given output in Gaussian filler -- the default -1 means don't perform sparsification.

Message that stores parameters used by HDF5DataLayer

Used in: LayerParameter

• optional string source = 1

  Specify the data source.

• optional uint32 batch_size = 2

  Specify the batch size.

Message that stores parameters used by HDF5OutputLayer

Used in: LayerParameter, V0LayerParameter

• optional string file_name = 1

Used in: LayerParameter

• optional HingeLossParameter.Norm norm = 1

  Specify the Norm to use L1 or L2

Used in: HingeLossParameter

• L1 = 1

• L2 = 2

Message that stores parameters used by ImageDataLayer

Used in: LayerParameter

• optional string source = 1

  Specify the data source.

• optional float scale = 2

  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 mean_file = 3

• optional uint32 batch_size = 4

  Specify the batch size.

• optional uint32 crop_size = 5

  Specify if we would like to randomly crop an image.

• optional bool mirror = 6

  Specify if we want to randomly mirror data.

• optional uint32 rand_skip = 7

  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 shuffle = 8

  Whether or not ImageLayer should shuffle the list of files at every epoch.

• optional uint32 new_height = 9

  It will also resize images if new_height or new_width are not zero.

• optional uint32 new_width = 10

Message that stores parameters InfogainLossLayer

Used in: LayerParameter

• optional string source = 1

  Specify the infogain matrix source.

Message that stores parameters used by InnerProductLayer

Used in: LayerParameter

• optional uint32 num_output = 1

  The number of outputs for the layer

• optional bool bias_term = 2

  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 that stores parameters used by LRNLayer

Used in: LayerParameter

• optional uint32 local_size = 1

• optional float alpha = 2

• optional float beta = 3

• optional LRNParameter.NormRegion norm_region = 4

Used in: LRNParameter

• ACROSS_CHANNELS = 0

• WITHIN_CHANNEL = 1

NOTE Update the next available ID when you add a new LayerParameter field. LayerParameter next available ID: 31 (last added: spatial_pyramid_pooling_param)

Used in: NetParameter, NetParameterPrettyPrint

• repeated string bottom = 2

  the name of the bottom blobs

• repeated string top = 3

  the name of the top blobs

• optional string name = 4

  the layer name

• optional LayerParameter.LayerType type = 5

  the layer type from the enum above

• repeated BlobProto blobs = 6

  The blobs containing the numeric parameters of the layer

• repeated string param = 1001

  The names of the parameter blobs -- useful for sharing parameters among layers (but never required).

• repeated LayerParameter.DimCheckMode blob_share_mode = 1002

  Whether to require shared weights to have the same shape, or just the same count -- defaults to STRICT if unspecified.

• repeated float blobs_lr = 7

  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 = 8

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

• optional AccuracyParameter accuracy_param = 27

• optional ArgMaxParameter argmax_param = 23

• optional ConcatParameter concat_param = 9

• optional ConvolutionParameter convolution_param = 10

• optional DataParameter data_param = 11

• optional DropoutParameter dropout_param = 12

• optional DummyDataParameter dummy_data_param = 26

• optional EltwiseParameter eltwise_param = 24

• optional HDF5DataParameter hdf5_data_param = 13

• optional HDF5OutputParameter hdf5_output_param = 14

• optional ImageDataParameter image_data_param = 15

• optional InfogainLossParameter infogain_loss_param = 16

• optional InnerProductParameter inner_product_param = 17

• optional LRNParameter lrn_param = 18

• optional MemoryDataParameter memory_data_param = 22

• optional PoolingParameter pooling_param = 19

• optional PowerParameter power_param = 21

• optional SpatialPyramidPoolingParameter spatial_pyramid_pooling_param = 30

• optional WindowDataParameter window_data_param = 20

• optional ThresholdParameter threshold_param = 25

• optional HingeLossParameter hinge_loss_param = 29

• optional V0LayerParameter layer = 1

  DEPRECATED: The layer parameters specified as a V0LayerParameter. This should never be used by any code except to upgrade to the new LayerParameter specification.

Used in: LayerParameter

• STRICT = 0

  STRICT (default) requires that num, channels, height, width each match.

• PERMISSIVE = 1

  PERMISSIVE requires only the count (num*channels*height*width) to match.

NOTE Add new LayerTypes to the enum below in lexicographical order (other than starting with NONE), starting with the next available ID in the comment line above the enum. Update the next available ID when you add a new LayerType. LayerType next available ID: 34 (last added: SPATIAL_PYRAMID_POOLING)

Used in: LayerParameter

• NONE = 0

  "NONE" layer type is 0th enum element so that we don't cause confusion by defaulting to an existent LayerType (instead, should usually error if the type is unspecified).

• ACCURACY = 1

• ARGMAX = 30

• BNLL = 2

• CONCAT = 3

• CONVOLUTION = 4

• DATA = 5

• DROPOUT = 6

• DUMMY_DATA = 32

• EUCLIDEAN_LOSS = 7

• ELTWISE = 25

• FLATTEN = 8

• HDF5_DATA = 9

• HDF5_OUTPUT = 10

• HINGE_LOSS = 28

• IM2COL = 11

• IMAGE_DATA = 12

• INFOGAIN_LOSS = 13

• INNER_PRODUCT = 14

• LRN = 15

• MEMORY_DATA = 29

• MULTINOMIAL_LOGISTIC_LOSS = 16

• POOLING = 17

• POWER = 26

• RELU = 18

• SIGMOID = 19

• SIGMOID_CROSS_ENTROPY_LOSS = 27

• SOFTMAX = 20

• SOFTMAX_LOSS = 21

• SPATIAL_PYRAMID_POOLING = 33

• SPLIT = 22

• TANH = 23

• WINDOW_DATA = 24

• THRESHOLD = 31

Message that stores parameters used by MemoryDataLayer

Used in: LayerParameter

• optional uint32 batch_size = 1

• optional uint32 channels = 2

• optional uint32 height = 3

• optional uint32 width = 4

Used in: SolverParameter

• optional string name = 1

  consider giving the network a name

• repeated LayerParameter 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.

A near-duplicate of NetParameter with fields re-numbered to beautify automatic prototext dumps. The main practical purpose is to print inputs before layers, because having inputs at the end looks weird. NetParameterPrettyPrint should never be used in code except for conversion FROM NetParameter and subsequent dumping to proto text file.

• optional string name = 1

• optional bool force_backward = 2

• repeated string input = 3

• repeated int32 input_dim = 4

• repeated LayerParameter layers = 5

Message that stores parameters used by PoolingLayer

Used in: LayerParameter

• optional PoolingParameter.PoolMethod pool = 1

  The pooling method

• optional float pad = 4

  Pad, kernel size, and stride are all given as a single value for equal dimensions in height and width or as Y, X pairs.

  The padding size (equal in Y, X)

• optional float pad_h = 9

  The padding height

• optional float pad_w = 10

  The padding width

• optional float kernel_size = 2

  The kernel size (square)

• optional float kernel_h = 5

  The kernel height

• optional float kernel_w = 6

  The kernel width

• optional float stride = 3

  The stride (equal in Y, X)

• optional float stride_h = 7

  The stride height

• optional float stride_w = 8

  The stride width

Used in: PoolingParameter

• MAX = 0

• AVE = 1

• STOCHASTIC = 2

Message that stores parameters used by PowerLayer

Used in: LayerParameter

• optional float power = 1

  PowerLayer computes outputs y = (shift + scale * x) ^ power.

• optional float scale = 2

• optional float shift = 3

• optional string train_net = 1

  {train,test}_net specify a path to a file containing the {train,test} net parameters; {train,test}_net_param specify the net parameters directly inside the SolverParameter. Only either train_net or train_net_param (not both) should be specified. You may specify 0 or more test_net and/or test_net_param. All nets specified using test_net_param will be tested first, followed by all nets specified using test_net (each processed in the order specified in the prototxt).

  The proto filename for the train net.

• repeated string test_net = 2

  The proto filenames for the test nets.

• optional NetParameter train_net_param = 21

  Full params for the train net.

• repeated NetParameter test_net_param = 22

  Full params for the test nets.

• repeated 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 bool test_compute_loss = 19

• 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 SolverParameter.SolverMode solver_mode = 17

• optional int32 device_id = 18

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

• optional int64 random_seed = 20

  If non-negative, the seed with which the Solver will initialize the Caffe random number generator -- useful for reproducible results. Otherwise, (and by default) initialize using a seed derived from the system clock.

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

Used in: SolverParameter

• CPU = 0

• GPU = 1

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

Message that stores parameters used by PoolingLayer

Used in: LayerParameter

• optional SpatialPyramidPoolingParameter.PoolMethod pool = 1

  The pooling method

• repeated uint32 spatial_bin = 2

  The number of spatial bins of each pyramid level

• repeated float scale = 3

  The number of image scales to apply spatial pyramid pooling

Used in: SpatialPyramidPoolingParameter

• MAX = 0

• AVE = 1

• STOCHASTIC = 2

Message that stores parameters used by ThresholdLayer

Used in: LayerParameter

• optional float threshold = 1

  Strictly Positive values

DEPRECATED: V0LayerParameter is the old way of specifying layer parameters in Caffe. We keep this message type around for legacy support.

Used in: LayerParameter

• 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 V0LayerParameter.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.

• 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 float det_fg_threshold = 54

  Fields related to detection (det_*) foreground (object) overlap threshold

• optional float det_bg_threshold = 55

  background (non-object) overlap threshold

• optional float det_fg_fraction = 56

  Fraction of batch that should be foreground objects

• optional uint32 det_context_pad = 58

  Amount of contextual padding to add around a window (used only by the window_data_layer)

• optional string det_crop_mode = 59

  Mode for cropping out a detection window warp: cropped window is warped to a fixed size and aspect ratio square: the tightest square around the window is cropped

• optional int32 new_num = 60

  For ReshapeLayer, one needs to specify the new dimensions.

• optional int32 new_channels = 61

• optional int32 new_height = 62

• optional int32 new_width = 63

• optional bool shuffle_images = 64

  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 uint32 concat_dim = 65

  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 HDF5OutputParameter hdf5_output_param = 1001

Used in: V0LayerParameter

• MAX = 0

• AVE = 1

• STOCHASTIC = 2

Message that stores parameters used by WindowDataLayer

Used in: LayerParameter

• optional string source = 1

  Specify the data source.

• optional float scale = 2

  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 mean_file = 3

• optional uint32 batch_size = 4

  Specify the batch size.

• optional uint32 crop_size = 5

  Specify if we would like to randomly crop an image.

• optional bool mirror = 6

  Specify if we want to randomly mirror data.

• optional float fg_threshold = 7

  Foreground (object) overlap threshold

• optional float bg_threshold = 8

  Background (non-object) overlap threshold

• optional float fg_fraction = 9

  Fraction of batch that should be foreground objects

• optional uint32 context_pad = 10

  Amount of contextual padding to add around a window (used only by the window_data_layer)

• optional string crop_mode = 11

  Mode for cropping out a detection window warp: cropped window is warped to a fixed size and aspect ratio square: the tightest square around the window is cropped