darknet/src/im2col_kernels.cu

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#include "cuda_runtime.h"
#include "curand.h"
#include "cublas_v2.h"
extern "C" {
#include "im2col.h"
#include "cuda.h"
}
// src: https://github.com/BVLC/caffe/blob/master/src/caffe/util/im2col.cu
// You may also want to read: https://github.com/BVLC/caffe/blob/master/LICENSE
__global__ void im2col_gpu_kernel(const int n, const float* data_im,
const int height, const int width, const int ksize,
const int pad,
const int stride,
const int height_col, const int width_col,
float *data_col) {
int index = blockIdx.x*blockDim.x+threadIdx.x;
for(; index < n; index += blockDim.x*gridDim.x){
int w_out = index % width_col;
int h_index = index / width_col;
int h_out = h_index % height_col;
int channel_in = h_index / height_col;
int channel_out = channel_in * ksize * ksize;
int h_in = h_out * stride - pad;
int w_in = w_out * stride - pad;
float* data_col_ptr = data_col;
data_col_ptr += (channel_out * height_col + h_out) * width_col + w_out;
const float* data_im_ptr = data_im;
data_im_ptr += (channel_in * height + h_in) * width + w_in;
for (int i = 0; i < ksize; ++i) {
for (int j = 0; j < ksize; ++j) {
int h = h_in + i;
int w = w_in + j;
*data_col_ptr = (h >= 0 && w >= 0 && h < height && w < width) ?
data_im_ptr[i * width + j] : 0;
//*data_col_ptr = data_im_ptr[ii * width + jj];
data_col_ptr += height_col * width_col;
}
}
}
}
void im2col_gpu(float *im,
int channels, int height, int width,
int ksize, int stride, int pad, float *data_col){
// We are going to launch channels * height_col * width_col kernels, each
// kernel responsible for copying a single-channel grid.
int height_col = (height + 2 * pad - ksize) / stride + 1;
int width_col = (width + 2 * pad - ksize) / stride + 1;
int num_kernels = channels * height_col * width_col;
im2col_gpu_kernel<<<(num_kernels+BLOCK-1)/BLOCK,
BLOCK>>>(
num_kernels, im, height, width, ksize, pad,
stride, height_col,
width_col, data_col);
}