From ae43c2bc32fbb838bfebeeaf2c2b058ccab5c83c Mon Sep 17 00:00:00 2001
From: Joseph Redmon <pjreddie@burninator.cs.washington.edu>
Date: Thu, 23 Jun 2016 05:31:14 +0000
Subject: [PATCH] hi
---
src/network_kernels.cu | 14 ++++++++++++++
1 files changed, 14 insertions(+), 0 deletions(-)
diff --git a/src/network_kernels.cu b/src/network_kernels.cu
index 730634e..285f72c 100644
--- a/src/network_kernels.cu
+++ b/src/network_kernels.cu
@@ -16,6 +16,7 @@
#include "crop_layer.h"
#include "connected_layer.h"
#include "rnn_layer.h"
+#include "gru_layer.h"
#include "crnn_layer.h"
#include "detection_layer.h"
#include "convolutional_layer.h"
@@ -24,6 +25,7 @@
#include "maxpool_layer.h"
#include "avgpool_layer.h"
#include "normalization_layer.h"
+#include "batchnorm_layer.h"
#include "cost_layer.h"
#include "local_layer.h"
#include "softmax_layer.h"
@@ -39,6 +41,7 @@
void forward_network_gpu(network net, network_state state)
{
+ state.workspace = net.workspace;
int i;
for(i = 0; i < net.n; ++i){
state.index = i;
@@ -60,6 +63,8 @@
forward_connected_layer_gpu(l, state);
} else if(l.type == RNN){
forward_rnn_layer_gpu(l, state);
+ } else if(l.type == GRU){
+ forward_gru_layer_gpu(l, state);
} else if(l.type == CRNN){
forward_crnn_layer_gpu(l, state);
} else if(l.type == CROP){
@@ -70,6 +75,8 @@
forward_softmax_layer_gpu(l, state);
} else if(l.type == NORMALIZATION){
forward_normalization_layer_gpu(l, state);
+ } else if(l.type == BATCHNORM){
+ forward_batchnorm_layer_gpu(l, state);
} else if(l.type == MAXPOOL){
forward_maxpool_layer_gpu(l, state);
} else if(l.type == AVGPOOL){
@@ -87,6 +94,7 @@
void backward_network_gpu(network net, network_state state)
{
+ state.workspace = net.workspace;
int i;
float * original_input = state.input;
float * original_delta = state.delta;
@@ -119,12 +127,16 @@
backward_detection_layer_gpu(l, state);
} else if(l.type == NORMALIZATION){
backward_normalization_layer_gpu(l, state);
+ } else if(l.type == BATCHNORM){
+ backward_batchnorm_layer_gpu(l, state);
} else if(l.type == SOFTMAX){
if(i != 0) backward_softmax_layer_gpu(l, state);
} else if(l.type == CONNECTED){
backward_connected_layer_gpu(l, state);
} else if(l.type == RNN){
backward_rnn_layer_gpu(l, state);
+ } else if(l.type == GRU){
+ backward_gru_layer_gpu(l, state);
} else if(l.type == CRNN){
backward_crnn_layer_gpu(l, state);
} else if(l.type == COST){
@@ -150,6 +162,8 @@
update_deconvolutional_layer_gpu(l, rate, net.momentum, net.decay);
} else if(l.type == CONNECTED){
update_connected_layer_gpu(l, update_batch, rate, net.momentum, net.decay);
+ } else if(l.type == GRU){
+ update_gru_layer_gpu(l, update_batch, rate, net.momentum, net.decay);
} else if(l.type == RNN){
update_rnn_layer_gpu(l, update_batch, rate, net.momentum, net.decay);
} else if(l.type == CRNN){
--
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