| | |
| | | __device__ float linear_activate_kernel(float x){return x;} |
| | | __device__ float logistic_activate_kernel(float x){return 1./(1. + exp(-x));} |
| | | __device__ float relu_activate_kernel(float x){return x*(x>0);} |
| | | __device__ float relie_activate_kernel(float x){return x*(x>0);} |
| | | __device__ float ramp_activate_kernel(float x){return x*(x>0)+.1*x;} |
| | | __device__ float tanh_activate_kernel(float x){return (exp(2*x)-1)/(exp(2*x)+1);} |
| | | __device__ float plse_activate_kernel(float x) |
| | |
| | | __device__ float linear_gradient_kernel(float x){return 1;} |
| | | __device__ float logistic_gradient_kernel(float x){return (1-x)*x;} |
| | | __device__ float relu_gradient_kernel(float x){return (x>0);} |
| | | __device__ float relie_gradient_kernel(float x){return (x>0) ? 1 : .01;} |
| | | __device__ float ramp_gradient_kernel(float x){return (x>0)+.1;} |
| | | __device__ float tanh_gradient_kernel(float x){return 1-x*x;} |
| | | __device__ float plse_gradient_kernel(float x){return (x < 0 || x > 1) ? .01 : .125;} |
| | |
| | | return logistic_activate_kernel(x); |
| | | case RELU: |
| | | return relu_activate_kernel(x); |
| | | case RELIE: |
| | | return relie_activate_kernel(x); |
| | | case RAMP: |
| | | return ramp_activate_kernel(x); |
| | | case TANH: |
| | |
| | | return logistic_gradient_kernel(x); |
| | | case RELU: |
| | | return relu_gradient_kernel(x); |
| | | case RELIE: |
| | | return relie_gradient_kernel(x); |
| | | case RAMP: |
| | | return ramp_gradient_kernel(x); |
| | | case TANH: |