col2vol Class — pytorch Architecture
Architecture documentation for the col2vol class in vol2col.h from the pytorch codebase.
Entity Profile
Source Code
aten/src/ATen/native/vol2col.h lines 58–107
template <typename T>
void col2vol(
const T* data_col,
const int64_t channels,
const int64_t depth,
const int64_t height,
const int64_t width,
const int64_t out_depth,
const int64_t out_height,
const int64_t out_width,
const int64_t kT,
const int64_t kernel_height,
const int64_t kernel_width,
const int64_t pT,
const int64_t pH,
const int64_t pW,
const int64_t dT,
const int64_t dH,
const int64_t dW,
const int64_t dilationT,
const int64_t dilationH,
const int64_t dilationW,
T* data_vol) {
memset(data_vol, 0, sizeof(T) * depth * height * width * channels);
int64_t depth_col = out_depth;
int64_t height_col = out_height;
int64_t width_col = out_width;
int64_t channels_col = channels * kT * kernel_height * kernel_width;
for (int64_t c = 0; c < channels_col; ++c) {
int64_t w_offset = c % kernel_width;
int64_t h_offset = (c / kernel_width) % kernel_height;
int64_t t_offset = (c / kernel_width / kernel_height) % kT;
int64_t c_vol = c / kT / kernel_height / kernel_width;
for (int64_t t = 0; t < depth_col; ++t) {
int64_t t_pad = t * dT - pT + t_offset * dilationT;
for (int64_t h = 0; h < height_col; ++h) {
int64_t h_pad = h * dH - pH + h_offset * dilationH;
for (int64_t w = 0; w < width_col; ++w) {
int64_t w_pad = w * dW - pW + w_offset * dilationW;
if (t_pad >= 0 && t_pad < depth && h_pad >= 0 && h_pad < height &&
w_pad >= 0 && w_pad < width)
data_vol
[((c_vol * depth + t_pad) * height + h_pad) * width + w_pad] +=
data_col
[((c * depth_col + t) * height_col + h) * width_col + w];
}
}
}
}
}
Source
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