| | |
| | | |
| | | #include <math.h> |
| | | #include <stdio.h> |
| | | #include <stdlib.h> |
| | | #include <string.h> |
| | | |
| | | char *get_activation_string(ACTIVATION a) |
| | |
| | | return RELU; |
| | | } |
| | | |
| | | float activate(float x, ACTIVATION a){ |
| | | float linear_activate(float x){return x;} |
| | | float sigmoid_activate(float x){return 1./(1. + exp(-x));} |
| | | 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 activate(float x, ACTIVATION a, float dropout) |
| | | { |
| | | if((float)rand()/RAND_MAX < dropout) return 0; |
| | | switch(a){ |
| | | case LINEAR: |
| | | return x; |
| | | return linear_activate(x)/(1-dropout); |
| | | case SIGMOID: |
| | | return 1./(1.+exp(-x)); |
| | | return sigmoid_activate(x)/(1-dropout); |
| | | case RELU: |
| | | return x*(x>0); |
| | | return relu_activate(x)/(1-dropout); |
| | | case RAMP: |
| | | return x*(x>0) + .1*x; |
| | | return ramp_activate(x)/(1-dropout); |
| | | case TANH: |
| | | return (exp(2*x)-1)/(exp(2*x)+1); |
| | | return tanh_activate(x)/(1-dropout); |
| | | } |
| | | return 0; |
| | | } |
| | | |
| | | void activate_array(float *x, const int n, const ACTIVATION a, float dropout) |
| | | { |
| | | int i; |
| | | for(i = 0; i < n; ++i){ |
| | | x[i] = activate(x[i], a, dropout); |
| | | } |
| | | } |
| | | |
| | | |
| | | float gradient(float x, ACTIVATION a){ |
| | | switch(a){ |
| | | case LINEAR: |
| | |
| | | return 0; |
| | | } |
| | | |
| | | void gradient_array(const float *x, const int n, const ACTIVATION a, float *delta) |
| | | { |
| | | int i; |
| | | for(i = 0; i < n; ++i){ |
| | | delta[i] *= gradient(x[i], a); |
| | | } |
| | | } |
| | | |
| | | #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 |