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https://github.com/pjreddie/darknet.git
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141 lines
4.6 KiB
C
141 lines
4.6 KiB
C
#include "mini_blas.h"
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#include <stdio.h>
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inline float im2col_get_pixel(float *im, int height, int width, int channels,
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int row, int col, int channel, int pad)
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{
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row -= pad;
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col -= pad;
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if (row < 0 || col < 0 ||
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row >= height || col >= width) return 0;
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return im[col + width*(row + channel*height)];
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}
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//From Berkeley Vision's Caffe!
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//https://github.com/BVLC/caffe/blob/master/LICENSE
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void im2col_cpu(float* data_im,
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const int batch, const int channels, const int height, const int width,
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const int ksize, const int stride, int pad, float* data_col)
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{
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int c,h,w,b;
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int height_col = (height - ksize) / stride + 1;
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int width_col = (width - ksize) / stride + 1;
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if (pad){
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height_col = 1 + (height-1) / stride;
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width_col = 1 + (width-1) / stride;
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pad = ksize/2;
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}
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int channels_col = channels * ksize * ksize;
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int im_size = height*width*channels;
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//int col_size = height_col*width_col*channels_col;
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for (b = 0; b < batch; ++b) {
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for (c = 0; c < channels_col; ++c) {
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int w_offset = c % ksize;
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int h_offset = (c / ksize) % ksize;
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int c_im = c / ksize / ksize;
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for (h = 0; h < height_col; ++h) {
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for (w = 0; w < width_col; ++w) {
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int im_row = h_offset + h * stride;
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int im_col = w_offset + w * stride;
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int col_index = (c * height_col + h) * width_col + w + (batch-1) * c * height_col*width_col;
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data_col[col_index] = im2col_get_pixel(data_im, height, width, channels,
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im_row, im_col, c_im, pad);
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}
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}
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}
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data_im += im_size;
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data_col+= channels_col;
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}
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}
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#ifdef GPU
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#include "opencl.h"
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#include <math.h>
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cl_kernel get_im2col_kernel()
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{
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static int init = 0;
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static cl_kernel im2col_kernel;
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if(!init){
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im2col_kernel = get_kernel("src/im2col.cl", "im2col", 0);
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init = 1;
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}
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return im2col_kernel;
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}
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void im2col_ongpu(cl_mem data_im, const int batch,
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const int channels, const int height, const int width,
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const int ksize, const int stride, cl_mem data_col)
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{
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cl_setup();
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cl_kernel im2col_kernel = get_im2col_kernel();
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cl_command_queue queue = cl.queue;
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cl_uint i = 0;
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cl.error = clSetKernelArg(im2col_kernel, i++, sizeof(data_im), (void*) &data_im);
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cl.error = clSetKernelArg(im2col_kernel, i++, sizeof(batch), (void*) &batch);
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cl.error = clSetKernelArg(im2col_kernel, i++, sizeof(channels), (void*) &channels);
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cl.error = clSetKernelArg(im2col_kernel, i++, sizeof(height), (void*) &height);
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cl.error = clSetKernelArg(im2col_kernel, i++, sizeof(width), (void*) &width);
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cl.error = clSetKernelArg(im2col_kernel, i++, sizeof(ksize), (void*) &ksize);
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cl.error = clSetKernelArg(im2col_kernel, i++, sizeof(stride), (void*) &stride);
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cl.error = clSetKernelArg(im2col_kernel, i++, sizeof(data_col), (void*) &data_col);
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check_error(cl);
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int height_col = (height - ksize) / stride + 1;
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int width_col = (width - ksize) / stride + 1;
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int channels_col = channels * ksize * ksize;
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size_t global_size[2];
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size_t local_size[2];
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global_size[0] = batch;
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global_size[1] = channels_col;
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local_size[0] = height_col;
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local_size[1] = width_col;
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clEnqueueNDRangeKernel(queue, im2col_kernel, 2, 0,
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global_size, local_size, 0, 0, 0);
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check_error(cl);
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}
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void im2col_gpu(float *data_im,
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const int batch, const int channels, const int height, const int width,
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const int ksize, const int stride,
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float *data_col)
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{
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cl_setup();
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cl_context context = cl.context;
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cl_command_queue queue = cl.queue;
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size_t size = sizeof(float)*(channels*height*width*batch);
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cl_mem im_gpu = clCreateBuffer(context,
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CL_MEM_READ_ONLY|CL_MEM_COPY_HOST_PTR,
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size, data_im, &cl.error);
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check_error(cl);
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int height_col = (height - ksize) / stride + 1;
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int width_col = (width - ksize) / stride + 1;
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int channels_col = channels * ksize * ksize;
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size = sizeof(float)*(height_col*width_col*channels_col*batch);
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cl_mem col_gpu = clCreateBuffer(context,
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CL_MEM_WRITE_ONLY|CL_MEM_COPY_HOST_PTR,
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size, data_col, &cl.error);
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check_error(cl);
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im2col_ongpu(im_gpu, batch, channels, height, width,
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ksize, stride, col_gpu);
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clEnqueueReadBuffer(queue, col_gpu, CL_TRUE, 0, size, data_col, 0, 0, 0);
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check_error(cl);
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clReleaseMemObject(col_gpu);
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clReleaseMemObject(im_gpu);
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}
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#endif
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