| library(mxnet) |
| |
| ConvFactory <- function(data, num_filter, kernel, stride = c(1, 1), pad = c(0, 0), |
| name = '', suffix = '') { |
| conv <- mx.symbol.Convolution(data = data, num_filter = num_filter, kernel = kernel, stride = stride, |
| pad = pad, name = paste('conv_', name, suffix, sep = "")) |
| act <- mx.symbol.Activation(data = conv, act_type = 'relu', name = paste('relu_', name, suffix, sep = '')) |
| return(act) |
| } |
| |
| InceptionFactory <- function(data, num_1x1, num_3x3red, num_3x3, |
| num_d5x5red, num_d5x5, pool, proj, name) { |
| # 1x1 |
| c1x1 <- ConvFactory(data = data, num_filter = num_1x1, kernel = c(1, 1), |
| name = paste(name, '_1x1', sep = '')) |
| # 3x3 reduce + 3x3 |
| c3x3r = ConvFactory(data = data, num_filter = num_3x3red, kernel = c(1, 1), |
| name = paste(name, '_3x3', sep = ''), suffix = '_reduce') |
| c3x3 = ConvFactory(data = c3x3r, num_filter = num_3x3, kernel = c(3, 3), |
| pad = c(1, 1), name = paste(name, '_3x3', sep = '')) |
| # double 3x3 reduce + double 3x3 |
| cd5x5r = ConvFactory(data = data, num_filter = num_d5x5red, kernel = c(1, 1), |
| name = paste(name, '_5x5', sep = ''), suffix = '_reduce') |
| cd5x5 = ConvFactory(data = cd5x5r, num_filter = num_d5x5, kernel = c(5, 5), pad = c(2, 2), |
| name = paste(name, '_5x5', sep = '')) |
| # pool + proj |
| pooling = mx.symbol.Pooling(data = data, kernel = c(3, 3), stride = c(1, 1), |
| pad = c(1, 1), pool_type = pool, |
| name = paste(pool, '_pool_', name, '_pool', sep = '')) |
| |
| cproj = ConvFactory(data = pooling, num_filter = proj, kernel = c(1, 1), |
| name = paste(name, '_proj', sep = '')) |
| # concat |
| concat_lst <- list() |
| concat_lst <- c(c1x1, c3x3, cd5x5, cproj) |
| concat_lst$num.args = 4 |
| concat_lst$name = paste('ch_concat_', name, '_chconcat', sep = '') |
| concat = mxnet:::mx.varg.symbol.Concat(concat_lst) |
| return(concat) |
| } |
| |
| |
| get_symbol <- function(num_classes = 1000) { |
| data <- mx.symbol.Variable("data") |
| conv1 <- ConvFactory(data, 64, kernel = c(7, 7), stride = c(2, 2), pad = c(3, 3), name = "conv1") |
| pool1 <- mx.symbol.Pooling(conv1, kernel = c(3, 3), stride = c(2, 2), pool_type = "max") |
| conv2 <- ConvFactory(pool1, 64, kernel = c(1, 1), stride = c(1, 1), name = "conv2") |
| conv3 <- ConvFactory(conv2, 192, kernel = c(3, 3), stride = c(1, 1), pad = c(1, 1), name = "conv3") |
| pool3 <- mx.symbol.Pooling(conv3, kernel = c(3, 3), stride = c(2, 2), pool_type = "max") |
| |
| in3a <- InceptionFactory(pool3, 64, 96, 128, 16, 32, "max", 32, name = "in3a") |
| in3b <- InceptionFactory(in3a, 128, 128, 192, 32, 96, "max", 64, name = "in3b") |
| pool4 <- mx.symbol.Pooling(in3b, kernel = c(3, 3), stride = c(2, 2), pool_type = "max") |
| in4a <- InceptionFactory(pool4, 192, 96, 208, 16, 48, "max", 64, name = "in4a") |
| in4b <- InceptionFactory(in4a, 160, 112, 224, 24, 64, "max", 64, name = "in4b") |
| in4c <- InceptionFactory(in4b, 128, 128, 256, 24, 64, "max", 64, name = "in4c") |
| in4d <- InceptionFactory(in4c, 112, 144, 288, 32, 64, "max", 64, name = "in4d") |
| in4e <- InceptionFactory(in4d, 256, 160, 320, 32, 128, "max", 128, name = "in4e") |
| pool5 <- mx.symbol.Pooling(in4e, kernel = c(3, 3), stride = c(2, 2), pool_type = "max") |
| in5a <- InceptionFactory(pool5, 256, 160, 320, 32, 128, "max", 128, name = "in5a") |
| in5b <- InceptionFactory(in5a, 384, 192, 384, 48, 128, "max", 128, name = "in5b") |
| pool6 <- mx.symbol.Pooling(in5b, kernel = c(7, 7), stride = c(1, 1), pool_type = "avg" ) |
| flatten <- mx.symbol.Flatten(data = pool6, name = 'flatten0') |
| fc1 <- mx.symbol.FullyConnected(data = flatten, num_hidden = num_classes) |
| softmax <- mx.symbol.SoftmaxOutput(data = fc1, name = 'softmax') |
| return(softmax) |
| } |
