From ccde487525fc89a1d4bc3e1cf11a18971e8451c9 Mon Sep 17 00:00:00 2001
From: Joseph Redmon <pjreddie@users.noreply.github.com>
Date: Sat, 11 Jul 2015 00:33:24 +0000
Subject: [PATCH] Create README.md

---
 src/cost_layer.c |   69 +++++++++++++++++++++-------------
 1 files changed, 42 insertions(+), 27 deletions(-)

diff --git a/src/cost_layer.c b/src/cost_layer.c
index 1ea03bb..24f6ffa 100644
--- a/src/cost_layer.c
+++ b/src/cost_layer.c
@@ -10,6 +10,7 @@
 COST_TYPE get_cost_type(char *s)
 {
     if (strcmp(s, "sse")==0) return SSE;
+    if (strcmp(s, "masked")==0) return MASKED;
     fprintf(stderr, "Couldn't find activation function %s, going with SSE\n", s);
     return SSE;
 }
@@ -19,65 +20,79 @@
     switch(a){
         case SSE:
             return "sse";
+        case MASKED:
+            return "masked";
     }
     return "sse";
 }
 
-cost_layer *make_cost_layer(int batch, int inputs, COST_TYPE type)
+cost_layer make_cost_layer(int batch, int inputs, COST_TYPE cost_type)
 {
     fprintf(stderr, "Cost Layer: %d inputs\n", inputs);
-    cost_layer *layer = calloc(1, sizeof(cost_layer));
-    layer->batch = batch;
-    layer->inputs = inputs;
-    layer->type = type;
-    layer->delta = calloc(inputs*batch, sizeof(float));
-    layer->output = calloc(1, sizeof(float));
+    cost_layer l = {0};
+    l.type = COST;
+
+    l.batch = batch;
+    l.inputs = inputs;
+    l.outputs = inputs;
+    l.cost_type = cost_type;
+    l.delta = calloc(inputs*batch, sizeof(float));
+    l.output = calloc(1, sizeof(float));
     #ifdef GPU
-    layer->delta_gpu = cuda_make_array(layer->delta, inputs*batch);
+    l.delta_gpu = cuda_make_array(l.delta, inputs*batch);
     #endif
-    return layer;
+    return l;
 }
 
-void forward_cost_layer(cost_layer layer, network_state state)
+void forward_cost_layer(cost_layer l, network_state state)
 {
     if (!state.truth) return;
-    copy_cpu(layer.batch*layer.inputs, state.truth, 1, layer.delta, 1);
-    axpy_cpu(layer.batch*layer.inputs, -1, state.input, 1, layer.delta, 1);
-    *(layer.output) = dot_cpu(layer.batch*layer.inputs, layer.delta, 1, layer.delta, 1);
-    //printf("cost: %f\n", *layer.output);
+    if(l.cost_type == MASKED){
+        int i;
+        for(i = 0; i < l.batch*l.inputs; ++i){
+            if(state.truth[i] == 0) state.input[i] = 0;
+        }
+    }
+    copy_cpu(l.batch*l.inputs, state.truth, 1, l.delta, 1);
+    axpy_cpu(l.batch*l.inputs, -1, state.input, 1, l.delta, 1);
+    *(l.output) = dot_cpu(l.batch*l.inputs, l.delta, 1, l.delta, 1);
+    //printf("cost: %f\n", *l.output);
 }
 
-void backward_cost_layer(const cost_layer layer, network_state state)
+void backward_cost_layer(const cost_layer l, network_state state)
 {
-    copy_cpu(layer.batch*layer.inputs, layer.delta, 1, state.delta, 1);
+    copy_cpu(l.batch*l.inputs, l.delta, 1, state.delta, 1);
 }
 
 #ifdef GPU
 
-void pull_cost_layer(cost_layer layer)
+void pull_cost_layer(cost_layer l)
 {
-    cuda_pull_array(layer.delta_gpu, layer.delta, layer.batch*layer.inputs);
+    cuda_pull_array(l.delta_gpu, l.delta, l.batch*l.inputs);
 }
 
-void push_cost_layer(cost_layer layer)
+void push_cost_layer(cost_layer l)
 {
-    cuda_push_array(layer.delta_gpu, layer.delta, layer.batch*layer.inputs);
+    cuda_push_array(l.delta_gpu, l.delta, l.batch*l.inputs);
 }
 
-void forward_cost_layer_gpu(cost_layer layer, network_state state)
+void forward_cost_layer_gpu(cost_layer l, network_state state)
 {
     if (!state.truth) return;
+    if (l.cost_type == MASKED) {
+        mask_ongpu(l.batch*l.inputs, state.input, state.truth);
+    }
     
-    copy_ongpu(layer.batch*layer.inputs, state.truth, 1, layer.delta_gpu, 1);
-    axpy_ongpu(layer.batch*layer.inputs, -1, state.input, 1, layer.delta_gpu, 1);
+    copy_ongpu(l.batch*l.inputs, state.truth, 1, l.delta_gpu, 1);
+    axpy_ongpu(l.batch*l.inputs, -1, state.input, 1, l.delta_gpu, 1);
 
-    cuda_pull_array(layer.delta_gpu, layer.delta, layer.batch*layer.inputs);
-    *(layer.output) = dot_cpu(layer.batch*layer.inputs, layer.delta, 1, layer.delta, 1);
+    cuda_pull_array(l.delta_gpu, l.delta, l.batch*l.inputs);
+    *(l.output) = dot_cpu(l.batch*l.inputs, l.delta, 1, l.delta, 1);
 }
 
-void backward_cost_layer_gpu(const cost_layer layer, network_state state)
+void backward_cost_layer_gpu(const cost_layer l, network_state state)
 {
-    copy_ongpu(layer.batch*layer.inputs, layer.delta_gpu, 1, state.delta, 1);
+    copy_ongpu(l.batch*l.inputs, l.delta_gpu, 1, state.delta, 1);
 }
 #endif
 

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