Joseph Redmon
2015-09-01 8bcdee86585f496afe1a8a38d608ea0504a11243
src/network_kernels.cu
@@ -1,6 +1,7 @@
extern "C" {
#include <stdio.h>
#include <time.h>
#include <assert.h>
#include "network.h"
#include "image.h"
@@ -12,6 +13,7 @@
#include "crop_layer.h"
#include "connected_layer.h"
#include "detection_layer.h"
#include "region_layer.h"
#include "convolutional_layer.h"
#include "deconvolutional_layer.h"
#include "maxpool_layer.h"
@@ -21,6 +23,7 @@
#include "softmax_layer.h"
#include "dropout_layer.h"
#include "route_layer.h"
#include "blas.h"
}
float * get_network_output_gpu_layer(network net, int i);
@@ -32,12 +35,17 @@
    int i;
    for(i = 0; i < net.n; ++i){
        layer l = net.layers[i];
        if(l.delta_gpu){
            scal_ongpu(l.outputs * l.batch, 0, l.delta_gpu, 1);
        }
        if(l.type == CONVOLUTIONAL){
            forward_convolutional_layer_gpu(l, state);
        } else if(l.type == DECONVOLUTIONAL){
            forward_deconvolutional_layer_gpu(l, state);
        } else if(l.type == DETECTION){
            forward_detection_layer_gpu(l, state);
        } else if(l.type == REGION){
            forward_region_layer_gpu(l, state);
        } else if(l.type == CONNECTED){
            forward_connected_layer_gpu(l, state);
        } else if(l.type == CROP){
@@ -88,6 +96,8 @@
            backward_dropout_layer_gpu(l, state);
        } else if(l.type == DETECTION){
            backward_detection_layer_gpu(l, state);
        } else if(l.type == REGION){
            backward_region_layer_gpu(l, state);
        } else if(l.type == NORMALIZATION){
            backward_normalization_layer_gpu(l, state);
        } else if(l.type == SOFTMAX){