From 0f645836f193e75c4c3b718369e6fab15b5d19c5 Mon Sep 17 00:00:00 2001
From: Joseph Redmon <pjreddie@gmail.com>
Date: Wed, 11 Feb 2015 03:41:03 +0000
Subject: [PATCH] Detection is back, baby\!

---
 src/activations.c |   75 +++++++++++--------------------------
 1 files changed, 22 insertions(+), 53 deletions(-)

diff --git a/src/activations.c b/src/activations.c
index 4674a02..48dce87 100644
--- a/src/activations.c
+++ b/src/activations.c
@@ -40,46 +40,52 @@
 float relu_activate(float x){return x*(x>0);}
 float ramp_activate(float x){return x*(x>0)+.1*x;}
 float tanh_activate(float x){return (exp(2*x)-1)/(exp(2*x)+1);}
+//float tanh_activate(float x){return x - (x*x*x)/3;}
 
-float activate(float x, ACTIVATION a, float dropout)
+float linear_gradient(float x){return 1;}
+float sigmoid_gradient(float x){return (1-x)*x;}
+float relu_gradient(float x){return (x>0);}
+float ramp_gradient(float x){return (x>0)+.1;}
+float tanh_gradient(float x){return 1-x*x;}
+
+float activate(float x, ACTIVATION a)
 {
-    if((float)rand()/RAND_MAX < dropout) return 0;
     switch(a){
         case LINEAR:
-            return linear_activate(x)/(1-dropout);
+            return linear_activate(x);
         case SIGMOID:
-            return sigmoid_activate(x)/(1-dropout);
+            return sigmoid_activate(x);
         case RELU:
-            return relu_activate(x)/(1-dropout);
+            return relu_activate(x);
         case RAMP:
-            return ramp_activate(x)/(1-dropout);
+            return ramp_activate(x);
         case TANH:
-            return tanh_activate(x)/(1-dropout);
+            return tanh_activate(x);
     }
     return 0;
 }
 
-void activate_array(float *x, const int n, const ACTIVATION a, float dropout)
+void activate_array(float *x, const int n, const ACTIVATION a)
 {
     int i;
     for(i = 0; i < n; ++i){
-        x[i] = activate(x[i], a, dropout);
+        x[i] = activate(x[i], a);
     }
 }
 
-
-float gradient(float x, ACTIVATION a){
+float gradient(float x, ACTIVATION a)
+{
     switch(a){
         case LINEAR:
-            return 1;
+            return linear_gradient(x);
         case SIGMOID:
-            return (1.-x)*x;
+            return sigmoid_gradient(x);
         case RELU:
-            return (x>0);
+            return relu_gradient(x);
         case RAMP:
-            return (x>0) + .1;
+            return ramp_gradient(x);
         case TANH:
-            return 1-x*x;
+            return tanh_gradient(x);
     }
     return 0;
 }
@@ -92,40 +98,3 @@
     }
 } 
 
-#ifdef GPU
-
-#include "opencl.h"
-#include <math.h>
-
-cl_kernel get_activation_kernel()
-{
-    static int init = 0;
-    static cl_kernel kernel;
-    if(!init){
-        kernel = get_kernel("src/activations.cl", "activate_array", 0);
-        init = 1;
-    }
-    return kernel;
-}
-
-
-void activate_array_ongpu(cl_mem x, int n, ACTIVATION a, float dropout) 
-{
-    cl_setup();
-    cl_kernel kernel = get_activation_kernel();
-    cl_command_queue queue = cl.queue;
-
-    cl_uint i = 0;
-    cl.error = clSetKernelArg(kernel, i++, sizeof(x), (void*) &x);
-    cl.error = clSetKernelArg(kernel, i++, sizeof(n), (void*) &n);
-    cl.error = clSetKernelArg(kernel, i++, sizeof(a), (void*) &a);
-    cl.error = clSetKernelArg(kernel, i++, sizeof(dropout), 
-        (void*) &dropout);
-    check_error(cl);
-
-    size_t gsize = n;
-
-    clEnqueueNDRangeKernel(queue, kernel, 1, 0, &gsize, 0, 0, 0, 0);
-    check_error(cl);
-}
-#endif

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