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https://github.com/ilyakooo0/grenade.git
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129 lines
5.4 KiB
C
129 lines
5.4 KiB
C
#include "im2col.h"
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void im2col_cpu(const double* data_im, const int channels,
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const int height, const int width, const int kernel_h, const int kernel_w,
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const int stride_h, const int stride_w,
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double* data_col) {
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const int channel_size = height * width;
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for (int fitting_height = 0; fitting_height <= (height - kernel_h); fitting_height += stride_h) {
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for (int fitting_width = 0; fitting_width <= (width - kernel_w); fitting_width += stride_w) {
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for (int channel = 0; channel < channels; channel++) {
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for (int kernel_row = 0; kernel_row < kernel_h; kernel_row++) {
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for (int kernel_col = 0; kernel_col < kernel_w; kernel_col++) {
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int input_row = fitting_height + kernel_row;
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int input_col = fitting_width + kernel_col;
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*(data_col++) = data_im[input_row * width + input_col + channel_size * channel];
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}
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}
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}
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}
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}
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}
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void col2im_cpu(const double* data_col, const int channels,
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const int height, const int width, const int kernel_h, const int kernel_w,
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const int stride_h, const int stride_w,
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double* data_im) {
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memset(data_im, 0, height * width * channels * sizeof(double));
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const int channel_size = height * width;
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for (int fitting_height = 0; fitting_height <= (height - kernel_h); fitting_height += stride_h) {
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for (int fitting_width = 0; fitting_width <= (width - kernel_w); fitting_width += stride_w) {
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for (int channel = 0; channel < channels; channel++) {
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for (int kernel_row = 0; kernel_row < kernel_h; kernel_row++) {
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for (int kernel_col = 0; kernel_col < kernel_w; kernel_col++) {
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int input_row = fitting_height + kernel_row;
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int input_col = fitting_width + kernel_col;
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data_im[input_row * width + input_col + channel_size * channel] += *(data_col++);
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}
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}
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}
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}
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}
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}
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inline double max ( double a, double b ) { return a > b ? a : b; }
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void pool_forwards_cpu(const double* data_im, const int channels,
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const int height, const int width, const int kernel_h, const int kernel_w,
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const int stride_h, const int stride_w,
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double* data_pooled) {
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const int channel_size = height * width;
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for (int channel = 0; channel < channels; channel++) {
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for (int fitting_height = 0; fitting_height <= (height - kernel_h); fitting_height += stride_h) {
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for (int fitting_width = 0; fitting_width <= (width - kernel_w); fitting_width += stride_w) {
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// Start with the value in 0,0
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int max_index = fitting_height * width + fitting_width + channel_size * channel;
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double max_value = data_im[max_index];
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// Initial row, skipping the corner we've done
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for (int kernel_col = 1; kernel_col < kernel_w; kernel_col++) {
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int input_row = fitting_height;
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int input_col = fitting_width + kernel_col;
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int data_index = input_row * width + input_col + channel_size * channel;
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double data_value = data_im[data_index];
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max_value = max ( max_value, data_value );
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}
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// The remaining rows
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for (int kernel_row = 1; kernel_row < kernel_h; kernel_row++) {
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for (int kernel_col = 0; kernel_col < kernel_w; kernel_col++) {
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int input_row = fitting_height + kernel_row;
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int input_col = fitting_width + kernel_col;
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int data_index = input_row * width + input_col + channel_size * channel;
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double data_value = data_im[data_index];
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max_value = max ( max_value, data_value );
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}
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}
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*(data_pooled++) = max_value;
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}
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}
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}
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}
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void pool_backwards_cpu(const double* data_im, const double* data_pooled,
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const int channels, const int height, const int width, const int kernel_h,
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const int kernel_w, const int stride_h, const int stride_w,
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double* data_backgrad ) {
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memset(data_backgrad, 0, height * width * channels * sizeof(double));
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const int channel_size = height * width;
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for (int channel = 0; channel < channels; channel++) {
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for (int fitting_height = 0; fitting_height <= (height - kernel_h); fitting_height += stride_h) {
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for (int fitting_width = 0; fitting_width <= (width - kernel_w); fitting_width += stride_w) {
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int max_index = fitting_height * width + fitting_width + channel_size * channel;
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double max_value = data_im[max_index];
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for (int kernel_col = 1; kernel_col < kernel_w; kernel_col++) {
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int input_row = fitting_height;
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int input_col = fitting_width + kernel_col;
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int data_index = input_row * width + input_col + channel_size * channel;
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double data_value = data_im[data_index];
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if ( data_value > max_value ) {
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max_index = data_index;
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max_value = data_value;
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}
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}
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for (int kernel_row = 1; kernel_row < kernel_h; kernel_row++) {
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for (int kernel_col = 0; kernel_col < kernel_w; kernel_col++) {
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int input_row = fitting_height + kernel_row;
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int input_col = fitting_width + kernel_col;
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int data_index = input_row * width + input_col + channel_size * channel;
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double data_value = data_im[data_index];
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if ( data_value > max_value ) {
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max_index = data_index;
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max_value = data_value;
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}
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}
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}
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data_backgrad[max_index] += *(data_pooled++);
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}
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}
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}
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}
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