From cb1f33c6ae840e8dc0f43518daf76e6ed01034f0 Mon Sep 17 00:00:00 2001
From: Joseph Redmon <pjreddie@gmail.com>
Date: Mon, 08 Dec 2014 19:48:57 +0000
Subject: [PATCH] Fixed race condition in server

---
 src/connected_layer.c |   36 +++++++++++++++++++-----------------
 1 files changed, 19 insertions(+), 17 deletions(-)

diff --git a/src/connected_layer.c b/src/connected_layer.c
index ac4c417..85bf5c8 100644
--- a/src/connected_layer.c
+++ b/src/connected_layer.c
@@ -9,7 +9,6 @@
 
 connected_layer *make_connected_layer(int batch, int inputs, int outputs, ACTIVATION activation, float learning_rate, float momentum, float decay)
 {
-    fprintf(stderr, "Connected Layer: %d inputs, %d outputs\n", inputs, outputs);
     int i;
     connected_layer *layer = calloc(1, sizeof(connected_layer));
 
@@ -25,22 +24,20 @@
     layer->delta = calloc(batch*outputs, sizeof(float*));
 
     layer->weight_updates = calloc(inputs*outputs, sizeof(float));
-    //layer->weight_adapt = calloc(inputs*outputs, sizeof(float));
     layer->weights = calloc(inputs*outputs, sizeof(float));
     float scale = 1./inputs;
-    scale = .05;
-    for(i = 0; i < inputs*outputs; ++i)
-        layer->weights[i] = scale*2*(rand_uniform()-.5);
-
-    layer->bias_updates = calloc(outputs, sizeof(float));
-    //layer->bias_adapt = calloc(outputs, sizeof(float));
-    layer->biases = calloc(outputs, sizeof(float));
-    for(i = 0; i < outputs; ++i){
-        //layer->biases[i] = rand_normal()*scale + scale;
-        layer->biases[i] = 1;
+    scale = .01;
+    for(i = 0; i < inputs*outputs; ++i){
+        layer->weights[i] = scale*rand_normal();
     }
 
-    #ifdef GPU
+    layer->bias_updates = calloc(outputs, sizeof(float));
+    layer->biases = calloc(outputs, sizeof(float));
+    for(i = 0; i < outputs; ++i){
+        layer->biases[i] = .01;
+    }
+
+#ifdef GPU
     layer->weights_cl = cl_make_array(layer->weights, inputs*outputs);
     layer->biases_cl = cl_make_array(layer->biases, outputs);
 
@@ -49,8 +46,9 @@
 
     layer->output_cl = cl_make_array(layer->output, outputs*batch);
     layer->delta_cl = cl_make_array(layer->delta, outputs*batch);
-    #endif
+#endif
     layer->activation = activation;
+    fprintf(stderr, "Connected Layer: %d inputs, %d outputs\n", inputs, outputs);
     return layer;
 }
 
@@ -59,7 +57,7 @@
     axpy_cpu(layer.outputs, layer.learning_rate, layer.bias_updates, 1, layer.biases, 1);
     scal_cpu(layer.outputs, layer.momentum, layer.bias_updates, 1);
 
-    scal_cpu(layer.inputs*layer.outputs, 1.-layer.learning_rate*layer.decay, layer.weights, 1);
+    axpy_cpu(layer.inputs*layer.outputs, -layer.decay, layer.weights, 1, layer.weight_updates, 1);
     axpy_cpu(layer.inputs*layer.outputs, layer.learning_rate, layer.weight_updates, 1, layer.weights, 1);
     scal_cpu(layer.inputs*layer.outputs, layer.momentum, layer.weight_updates, 1);
 }
@@ -112,12 +110,16 @@
 {
     cl_read_array(layer.weights_cl, layer.weights, layer.inputs*layer.outputs);
     cl_read_array(layer.biases_cl, layer.biases, layer.outputs);
+    cl_read_array(layer.weight_updates_cl, layer.weight_updates, layer.inputs*layer.outputs);
+    cl_read_array(layer.bias_updates_cl, layer.bias_updates, layer.outputs);
 }
 
 void push_connected_layer(connected_layer layer)
 {
     cl_write_array(layer.weights_cl, layer.weights, layer.inputs*layer.outputs);
     cl_write_array(layer.biases_cl, layer.biases, layer.outputs);
+    cl_write_array(layer.weight_updates_cl, layer.weight_updates, layer.inputs*layer.outputs);
+    cl_write_array(layer.bias_updates_cl, layer.bias_updates, layer.outputs);
 }
 
 void update_connected_layer_gpu(connected_layer layer)
@@ -125,7 +127,7 @@
     axpy_ongpu(layer.outputs, layer.learning_rate, layer.bias_updates_cl, 1, layer.biases_cl, 1);
     scal_ongpu(layer.outputs, layer.momentum, layer.bias_updates_cl, 1);
 
-    scal_ongpu(layer.inputs*layer.outputs, 1.-layer.learning_rate*layer.decay, layer.weights_cl, 1);
+    axpy_ongpu(layer.inputs*layer.outputs, -layer.decay, layer.weights_cl, 1, layer.weight_updates_cl, 1);
     axpy_ongpu(layer.inputs*layer.outputs, layer.learning_rate, layer.weight_updates_cl, 1, layer.weights_cl, 1);
     scal_ongpu(layer.inputs*layer.outputs, layer.momentum, layer.weight_updates_cl, 1);
     pull_connected_layer(layer);
@@ -172,4 +174,4 @@
 
     if(c) gemm_ongpu(0,1,m,n,k,1,a,k,b,k,0,c,n);
 }
-    #endif
+#endif

--
Gitblit v1.10.0