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#include <cmath>
#include <cstdlib>
#include <cstring>
#include <vector>
#include "caffe/util/im2col.hpp"
#include "caffe/util/math_functions.hpp"
namespace caffe {
template <typename Dtype>
void im2col_cpu(const Dtype* data_im, const int channels,
const int height, const int width, const int kernel_h, const int kernel_w,
const int pad_h, const int pad_w,
const int stride_h, const int stride_w,
Dtype* data_col) {
int height_col = (height + 2 * pad_h - kernel_h) / stride_h + 1;
int width_col = (width + 2 * pad_w - kernel_w) / stride_w + 1;
int channels_col = channels * kernel_h * kernel_w;
for (int c = 0; c < channels_col; ++c) {
int w_offset = c % kernel_w;
int h_offset = (c / kernel_w) % kernel_h;
int c_im = c / kernel_h / kernel_w;
for (int h = 0; h < height_col; ++h) {
for (int w = 0; w < width_col; ++w) {
int h_pad = h * stride_h - pad_h + h_offset;
int w_pad = w * stride_w - pad_w + w_offset;
if (h_pad >= 0 && h_pad < height && w_pad >= 0 && w_pad < width)
data_col[(c * height_col + h) * width_col + w] =
data_im[(c_im * height + h_pad) * width + w_pad];
else
data_col[(c * height_col + h) * width_col + w] = 0;
}
}
}
}
// Explicit instantiation
template void im2col_cpu<float>(const float* data_im, const int channels,
const int height, const int width, const int kernel_h, const int kernel_w,
const int pad_h, const int pad_w, const int stride_h,
const int stride_w, float* data_col);
template void im2col_cpu<double>(const double* data_im, const int channels,
const int height, const int width, const int kernel_h, const int kernel_w,
const int pad_h, const int pad_w, const int stride_h,
const int stride_w, double* data_col);
template <typename Dtype>
inline void im2col_nd_core_cpu(const Dtype* data_input, const bool im2col,
const int num_spatial_axes, const int* im_shape, const int* col_shape,
const int* kernel_shape, const int* pad, const int* stride,
Dtype* data_output) {
if (!im2col) {
int im_size = im_shape[0];
for (int i = 0; i < num_spatial_axes; ++i) {
im_size *= im_shape[1 + i];
}
caffe_set(im_size, Dtype(0), data_output);
}
int kernel_size = 1;
for (int i = 0; i < num_spatial_axes; ++i) {
kernel_size *= kernel_shape[i];
}
const int channels_col = col_shape[0];
vector<int> d_offset(num_spatial_axes, 0);
vector<int> d_iter(num_spatial_axes, 0);
for (int c = 0; c < channels_col; ++c) {
// Loop over spatial axes in reverse order to compute a per-axis offset.
int offset = c;
for (int d_i = num_spatial_axes - 1; d_i >= 0; --d_i) {
if (d_i < num_spatial_axes - 1) {
offset /= kernel_shape[d_i + 1];
}
d_offset[d_i] = offset % kernel_shape[d_i];
}
for (bool incremented = true; incremented; ) {
// Loop over spatial axes in forward order to compute the indices in the
// image and column, and whether the index lies in the padding.
int index_col = c;
int index_im = c / kernel_size;
bool is_padding = false;
for (int d_i = 0; d_i < num_spatial_axes; ++d_i) {
const int d = d_iter[d_i];
const int d_pad = d * stride[d_i] - pad[d_i] + d_offset[d_i];
is_padding |= d_pad < 0 || d_pad >= im_shape[d_i + 1];
index_col *= col_shape[d_i + 1];
index_col += d;
index_im *= im_shape[d_i + 1];
index_im += d_pad;
}
if (im2col) {
if (is_padding) {
data_output[index_col] = 0;
} else {
data_output[index_col] = data_input[index_im];
}
} else if (!is_padding) { // col2im
data_output[index_im] += data_input[index_col];
}
// Loop over spatial axes in reverse order to choose an index,
// like counting.
incremented = false;
for (int d_i = num_spatial_axes - 1; d_i >= 0; --d_i) {
const int d_max = col_shape[d_i + 1];
DCHECK_LT(d_iter[d_i], d_max);
if (d_iter[d_i] == d_max - 1) {
d_iter[d_i] = 0;
} else { // d_iter[d_i] < d_max - 1
++d_iter[d_i];
incremented = true;
break;
}
}
} // while(incremented) {
} // for (int c = 0; c < channels_col; ++c) {
}
template <typename Dtype>
void im2col_nd_cpu(const Dtype* data_im, const int num_spatial_axes,
const int* im_shape, const int* col_shape,
const int* kernel_shape, const int* pad, const int* stride,
Dtype* data_col) {
const bool kIm2Col = true;
im2col_nd_core_cpu(data_im, kIm2Col, num_spatial_axes, im_shape, col_shape,
kernel_shape, pad, stride, data_col);
}
// Explicit instantiation
template void im2col_nd_cpu<float>(const float* data_im,
const int num_spatial_axes,
const int* im_shape, const int* col_shape,
const int* kernel_shape, const int* pad, const int* stride,
float* data_col);
template void im2col_nd_cpu<double>(const double* data_im,
const int num_spatial_axes,
const int* im_shape, const int* col_shape,
const int* kernel_shape, const int* pad, const int* stride,
double* data_col);
template <typename Dtype>
void col2im_cpu(const Dtype* data_col, const int channels,
const int height, const int width, const int patch_h, const int patch_w,
const int pad_h, const int pad_w,
const int stride_h, const int stride_w,
Dtype* data_im) {
caffe_set(height * width * channels, Dtype(0), data_im);
int height_col = (height + 2 * pad_h - patch_h) / stride_h + 1;
int width_col = (width + 2 * pad_w - patch_w) / stride_w + 1;
int channels_col = channels * patch_h * patch_w;
for (int c = 0; c < channels_col; ++c) {
int w_offset = c % patch_w;
int h_offset = (c / patch_w) % patch_h;
int c_im = c / patch_h / patch_w;
for (int h = 0; h < height_col; ++h) {
for (int w = 0; w < width_col; ++w) {
int h_pad = h * stride_h - pad_h + h_offset;
int w_pad = w * stride_w - pad_w + w_offset;
if (h_pad >= 0 && h_pad < height && w_pad >= 0 && w_pad < width)
data_im[(c_im * height + h_pad) * width + w_pad] +=
data_col[(c * height_col + h) * width_col + w];
}
}
}
}
// Explicit instantiation
template void col2im_cpu<float>(const float* data_col, const int channels,
const int height, const int width, const int patch_h, const int patch_w,
const int pad_h, const int pad_w, const int stride_h,
const int stride_w, float* data_im);
template void col2im_cpu<double>(const double* data_col, const int channels,
const int height, const int width, const int patch_h, const int patch_w,
const int pad_h, const int pad_w, const int stride_h,
const int stride_w, double* data_im);
template <typename Dtype>
void col2im_nd_cpu(const Dtype* data_col, const int num_spatial_axes,
const int* im_shape, const int* col_shape,
const int* kernel_shape, const int* pad, const int* stride,
Dtype* data_im) {
const bool kIm2Col = false;
im2col_nd_core_cpu(data_col, kIm2Col, num_spatial_axes, im_shape, col_shape,
kernel_shape, pad, stride, data_im);
}
// Explicit instantiation
template void col2im_nd_cpu<float>(const float* data_col,
const int num_spatial_axes,
const int* im_shape, const int* col_shape,
const int* kernel_shape, const int* pad, const int* stride,
float* data_im);
template void col2im_nd_cpu<double>(const double* data_col,
const int num_spatial_axes,
const int* im_shape, const int* col_shape,
const int* kernel_shape, const int* pad, const int* stride,
double* data_im);
} // namespace caffe
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