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#include <stdlib.h>
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#include <stdio.h>
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#include <math.h>
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#include <time.h>
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#include <string.h>
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#include "mini_blas.h"
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void pm(int M, int N, float *A)
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{
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int i,j;
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for(i =0 ; i < M; ++i){
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for(j = 0; j < N; ++j){
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printf("%10.6f, ", A[i*N+j]);
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}
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printf("\n");
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}
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printf("\n");
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}
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void gemm(int TA, int TB, int M, int N, int K, float ALPHA,
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float *A, int lda,
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float *B, int ldb,
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float BETA,
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float *C, int ldc)
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{
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gpu_gemm( TA, TB, M, N, K, ALPHA,A,lda, B, ldb,BETA,C,ldc);
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}
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void im2row(float *image, int h, int w, int c, int size, int stride, float *matrix)
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{
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int i;
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int mc = c;
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int mw = (size*size);
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int mh = ((h-size)/stride+1)*((w-size)/stride+1);
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int msize = mc*mw*mh;
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for(i = 0; i < msize; ++i){
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int channel = i/(mh*mw);
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int block = (i%(mh*mw))/mw;
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int position = i%mw;
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int block_h = block/((w-size)/stride+1);
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int block_w = block%((w-size)/stride+1);
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int ph, pw, pc;
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ph = position/size+block_h;
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pw = position%size+block_w;
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pc = channel;
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matrix[i] = image[pc*h*w+ph*w+pw];
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}
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}
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void im2col(float *image, int h, int w, int c, int size, int stride, float *matrix)
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{
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int b,p;
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int blocks = ((h-size)/stride+1)*((w-size)/stride+1);
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int pixels = (size*size*c);
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for(b = 0; b < blocks; ++b){
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int block_h = b/((w-size)/stride+1);
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int block_w = b%((w-size)/stride+1);
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for(p = 0; p < pixels; ++p){
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int ph, pw, pc;
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int position = p%(size*size);
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pc = p/(size*size);
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ph = position/size+block_h;
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pw = position%size+block_w;
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matrix[b+p*blocks] = image[pc*h*w+ph*w+pw];
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}
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}
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}
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//From Berkeley Vision's Caffe!
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void im2col_cpu(float* data_im, const int channels,
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const int height, const int width, const int ksize, const int stride,
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float* data_col)
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{
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int c,h,w;
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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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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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data_col[(c * height_col + h) * width_col + w] =
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data_im[(c_im * height + h * stride + h_offset) * width
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+ w * stride + w_offset];
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}
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}
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}
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}
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void col2im_cpu(float* data_col, const int channels,
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const int height, const int width, const int ksize, const int stride,
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float* data_im)
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{
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int c,h,w;
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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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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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data_im[(c_im * height + h * stride + h_offset) * width
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+ w * stride + w_offset]+= data_col[(c * height_col + h) * width_col + w];
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}
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}
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}
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}
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float *random_matrix(int rows, int cols)
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{
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int i;
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float *m = calloc(rows*cols, sizeof(float));
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for(i = 0; i < rows*cols; ++i){
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m[i] = (float)rand()/RAND_MAX;
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}
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return m;
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}
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void time_random_matrix(int TA, int TB, int m, int k, int n)
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{
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float *a;
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if(!TA) a = random_matrix(m,k);
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else a = random_matrix(k,m);
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int lda = (!TA)?k:m;
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float *b;
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if(!TB) b = random_matrix(k,n);
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else b = random_matrix(n,k);
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int ldb = (!TB)?n:k;
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float *c = random_matrix(m,n);
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int i;
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clock_t start = clock(), end;
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for(i = 0; i<1000; ++i){
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cpu_gemm(TA,TB,m,n,k,1,a,lda,b,ldb,1,c,n);
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}
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end = clock();
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printf("Matrix Multiplication %dx%d * %dx%d, TA=%d, TB=%d: %lf ms\n",m,k,k,n, TA, TB, (float)(end-start)/CLOCKS_PER_SEC);
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free(a);
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free(b);
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free(c);
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}
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void test_blas()
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{
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time_random_matrix(0,0,100,100,100);
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time_random_matrix(1,0,100,100,100);
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time_random_matrix(0,1,100,100,100);
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time_random_matrix(1,1,100,100,100);
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time_random_matrix(0,0,1000,100,100);
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time_random_matrix(1,0,1000,100,100);
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time_random_matrix(0,1,1000,100,100);
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time_random_matrix(1,1,1000,100,100);
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}
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