#ifdef NERV_GENERIC_CUKERNEL
#include <assert.h>
#include <stdio.h>
#include "matrix.h"
#include "cuda.h"
#define CUDA_THREADS_N 16
#define CUDA_THREADS_NN ((CUDA_THREADS_N) * (CUDA_THREADS_N))
#define CEIL_DIV(a, b) (((a) + (b) - 1) / (b))
__global__ void cudak_(log_elem)(const MATRIX_ELEM *a, MATRIX_ELEM *b,
int nrow, int ncol, int stride) {
int j = blockIdx.x * blockDim.x + threadIdx.x;
int i = blockIdx.y * blockDim.y + threadIdx.y;
long idx;
if (i >= nrow || j >= ncol) return;
idx = j + i * stride;
b[idx] = log(a[idx]);
}
__global__ void cudak_(mul_elem)(const MATRIX_ELEM *a, const MATRIX_ELEM *b,
MATRIX_ELEM *c,
int nrow, int ncol, int stride) {
int j = blockIdx.x * blockDim.x + threadIdx.x;
int i = blockIdx.y * blockDim.y + threadIdx.y;
long idx;
if (i >= nrow || j >= ncol) return;
idx = j + i * stride;
c[idx] = a[idx] * b[idx];
}
__global__ void cudak_(sigmoid)(const MATRIX_ELEM *a, MATRIX_ELEM *b,
int nrow, int ncol, int stride) {
int j = blockIdx.x * blockDim.x + threadIdx.x;
int i = blockIdx.y * blockDim.y + threadIdx.y;
long idx;
if (i >= nrow || j >= ncol) return;
idx = j + i * stride;
b[idx] = 1.0 / (1.0 + exp(-a[idx]));
}
__global__ void cudak_(sigmoid_grad)(const MATRIX_ELEM *output,
const MATRIX_ELEM *err,
MATRIX_ELEM *nerr,
int nrow, int ncol, int stride) {
int j = blockIdx.x * blockDim.x + threadIdx.x;
int i = blockIdx.y * blockDim.y + threadIdx.y;
long id