From 0f7f2899b65343e56b0a1188f703d459d824d398 Mon Sep 17 00:00:00 2001
From: Joseph Redmon <pjreddie@gmail.com>
Date: Mon, 16 Nov 2015 03:51:26 +0000
Subject: [PATCH] Fix for cuda 7.5

---
 src/network.c |   26 ++++++++++++--------------
 1 files changed, 12 insertions(+), 14 deletions(-)

diff --git a/src/network.c b/src/network.c
index 7f19318..6c7461d 100644
--- a/src/network.c
+++ b/src/network.c
@@ -8,10 +8,10 @@
 
 #include "crop_layer.h"
 #include "connected_layer.h"
+#include "local_layer.h"
 #include "convolutional_layer.h"
 #include "deconvolutional_layer.h"
 #include "detection_layer.h"
-#include "region_layer.h"
 #include "normalization_layer.h"
 #include "maxpool_layer.h"
 #include "avgpool_layer.h"
@@ -60,6 +60,8 @@
     switch(a){
         case CONVOLUTIONAL:
             return "convolutional";
+        case LOCAL:
+            return "local";
         case DECONVOLUTIONAL:
             return "deconvolutional";
         case CONNECTED:
@@ -72,8 +74,6 @@
             return "softmax";
         case DETECTION:
             return "detection";
-        case REGION:
-            return "region";
         case DROPOUT:
             return "dropout";
         case CROP:
@@ -115,12 +115,12 @@
             forward_convolutional_layer(l, state);
         } else if(l.type == DECONVOLUTIONAL){
             forward_deconvolutional_layer(l, state);
+        } else if(l.type == LOCAL){
+            forward_local_layer(l, state);
         } else if(l.type == NORMALIZATION){
             forward_normalization_layer(l, state);
         } else if(l.type == DETECTION){
             forward_detection_layer(l, state);
-        } else if(l.type == REGION){
-            forward_region_layer(l, state);
         } else if(l.type == CONNECTED){
             forward_connected_layer(l, state);
         } else if(l.type == CROP){
@@ -155,6 +155,8 @@
             update_deconvolutional_layer(l, rate, net.momentum, net.decay);
         } else if(l.type == CONNECTED){
             update_connected_layer(l, update_batch, rate, net.momentum, net.decay);
+        } else if(l.type == LOCAL){
+            update_local_layer(l, update_batch, rate, net.momentum, net.decay);
         }
     }
 }
@@ -180,10 +182,6 @@
             sum += net.layers[i].cost[0];
             ++count;
         }
-        if(net.layers[i].type == REGION){
-            sum += net.layers[i].cost[0];
-            ++count;
-        }
     }
     return sum/count;
 }
@@ -224,12 +222,12 @@
             backward_dropout_layer(l, state);
         } else if(l.type == DETECTION){
             backward_detection_layer(l, state);
-        } else if(l.type == REGION){
-            backward_region_layer(l, state);
         } else if(l.type == SOFTMAX){
             if(i != 0) backward_softmax_layer(l, state);
         } else if(l.type == CONNECTED){
             backward_connected_layer(l, state);
+        } else if(l.type == LOCAL){
+            backward_local_layer(l, state);
         } else if(l.type == COST){
             backward_cost_layer(l, state);
         } else if(l.type == ROUTE){
@@ -540,12 +538,12 @@
     return acc;
 }
 
-float *network_accuracies(network net, data d)
+float *network_accuracies(network net, data d, int n)
 {
     static float acc[2];
     matrix guess = network_predict_data(net, d);
-    acc[0] = matrix_topk_accuracy(d.y, guess,1);
-    acc[1] = matrix_topk_accuracy(d.y, guess,5);
+    acc[0] = matrix_topk_accuracy(d.y, guess, 1);
+    acc[1] = matrix_topk_accuracy(d.y, guess, n);
     free_matrix(guess);
     return acc;
 }

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