#include "blas.h" #include "math.h" #include #include #include #include void reorg(float *x, int size, int layers, int batch, int forward) { float *swap = calloc(size*layers*batch, sizeof(float)); int i,c,b; for(b = 0; b < batch; ++b){ for(c = 0; c < layers; ++c){ for(i = 0; i < size; ++i){ int i1 = b*layers*size + c*size + i; int i2 = b*layers*size + i*layers + c; if (forward) swap[i2] = x[i1]; else swap[i1] = x[i2]; } } } memcpy(x, swap, size*layers*batch*sizeof(float)); free(swap); } void weighted_sum_cpu(float *a, float *b, float *s, int n, float *c) { int i; for(i = 0; i < n; ++i){ c[i] = s[i]*a[i] + (1-s[i])*(b ? b[i] : 0); } } void shortcut_cpu(int batch, int w1, int h1, int c1, float *add, int w2, int h2, int c2, float *out) { int stride = w1/w2; int sample = w2/w1; assert(stride == h1/h2); assert(sample == h2/h1); if(stride < 1) stride = 1; if(sample < 1) sample = 1; int minw = (w1 < w2) ? w1 : w2; int minh = (h1 < h2) ? h1 : h2; int minc = (c1 < c2) ? c1 : c2; int i,j,k,b; for(b = 0; b < batch; ++b){ for(k = 0; k < minc; ++k){ for(j = 0; j < minh; ++j){ for(i = 0; i < minw; ++i){ int out_index = i*sample + w2*(j*sample + h2*(k + c2*b)); int add_index = i*stride + w1*(j*stride + h1*(k + c1*b)); out[out_index] += add[add_index]; } } } } } void mean_cpu(float *x, int batch, int filters, int spatial, float *mean) { float scale = 1./(batch * spatial); int i,j,k; for(i = 0; i < filters; ++i){ mean[i] = 0; for(j = 0; j < batch; ++j){ for(k = 0; k < spatial; ++k){ int index = j*filters*spatial + i*spatial + k; mean[i] += x[index]; } } mean[i] *= scale; } } void variance_cpu(float *x, float *mean, int batch, int filters, int spatial, float *variance) { float scale = 1./(batch * spatial - 1); int i,j,k; for(i = 0; i < filters; ++i){ variance[i] = 0; for(j = 0; j < batch; ++j){ for(k = 0; k < spatial; ++k){ int index = j*filters*spatial + i*spatial + k; variance[i] += pow((x[index] - mean[i]), 2); } } variance[i] *= scale; } } void normalize_cpu(float *x, float *mean, float *variance, int batch, int filters, int spatial) { int b, f, i; for(b = 0; b < batch; ++b){ for(f = 0; f < filters; ++f){ for(i = 0; i < spatial; ++i){ int index = b*filters*spatial + f*spatial + i; x[index] = (x[index] - mean[f])/(sqrt(variance[f]) + .000001f); } } } } void const_cpu(int N, float ALPHA, float *X, int INCX) { int i; for(i = 0; i < N; ++i) X[i*INCX] = ALPHA; } void mul_cpu(int N, float *X, int INCX, float *Y, int INCY) { int i; for(i = 0; i < N; ++i) Y[i*INCY] *= X[i*INCX]; } void pow_cpu(int N, float ALPHA, float *X, int INCX, float *Y, int INCY) { int i; for(i = 0; i < N; ++i) Y[i*INCY] = pow(X[i*INCX], ALPHA); } void axpy_cpu(int N, float ALPHA, float *X, int INCX, float *Y, int INCY) { int i; for(i = 0; i < N; ++i) Y[i*INCY] += ALPHA*X[i*INCX]; } void scal_cpu(int N, float ALPHA, float *X, int INCX) { int i; for(i = 0; i < N; ++i) X[i*INCX] *= ALPHA; } void fill_cpu(int N, float ALPHA, float *X, int INCX) { int i; for(i = 0; i < N; ++i) X[i*INCX] = ALPHA; } void copy_cpu(int N, float *X, int INCX, float *Y, int INCY) { int i; for(i = 0; i < N; ++i) Y[i*INCY] = X[i*INCX]; } void smooth_l1_cpu(int n, float *pred, float *truth, float *delta, float *error) { int i; for(i = 0; i < n; ++i){ float diff = truth[i] - pred[i]; float abs_val = fabs(diff); if(abs_val < 1) { error[i] = diff * diff; delta[i] = diff; } else { error[i] = 2*abs_val - 1; delta[i] = (diff < 0) ? -1 : 1; } } } void l2_cpu(int n, float *pred, float *truth, float *delta, float *error) { int i; for(i = 0; i < n; ++i){ float diff = truth[i] - pred[i]; error[i] = diff * diff; delta[i] = diff; } } float dot_cpu(int N, float *X, int INCX, float *Y, int INCY) { int i; float dot = 0; for(i = 0; i < N; ++i) dot += X[i*INCX] * Y[i*INCY]; return dot; }