Deep learning framework by BAIR
Created by Yangqing Jia Lead Developer Evan Shelhamer
Data
./include/caffe/layers/data_layer.hpp
./src/caffe/layers/data_layer.cpp
DataParameter data_param
./src/caffe/proto/caffe.proto
message DataParameter { enum DB { LEVELDB = 0; LMDB = 1; } // Specify the data source. optional string source = 1; // Specify the batch size. optional uint32 batch_size = 4; // 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 database. // DEPRECATED. Each solver accesses a different subset of the database. optional uint32 rand_skip = 7 [default = 0]; optional DB backend = 8 [default = LEVELDB]; // DEPRECATED. See TransformationParameter. 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 mean_file = 3; // DEPRECATED. See TransformationParameter. Specify if we would like to randomly // crop an image. optional uint32 crop_size = 5 [default = 0]; // DEPRECATED. See TransformationParameter. Specify if we want to randomly mirror // data. optional bool mirror = 6 [default = false]; // Force the encoded image to have 3 color channels optional bool force_encoded_color = 9 [default = false]; // Prefetch queue (Increase if data feeding bandwidth varies, within the // limit of device memory for GPU training) optional uint32 prefetch = 10 [default = 4]; }
source
batch_size
rand_skip
backend
LEVELDB
LMDB