提交 aae994fd 编写于 作者: T tensor-tang

refine im2col no padding

上级 03d70c1f
...@@ -40,22 +40,46 @@ class Im2ColFunctor<paddle::operators::math::ColFormat::kCFO, ...@@ -40,22 +40,46 @@ class Im2ColFunctor<paddle::operators::math::ColFormat::kCFO,
int im_width = im.dims()[2]; int im_width = im.dims()[2];
int filter_height = col->dims()[1]; int filter_height = col->dims()[1];
int filter_width = col->dims()[2]; int filter_width = col->dims()[2];
int col_height = col->dims()[3]; int output_height = col->dims()[3];
int col_width = col->dims()[4]; int output_width = col->dims()[4];
int channels_col = im_channels * filter_height * filter_width; int channels_col = im_channels * filter_height * filter_width;
const T* im_data = im.data<T>(); const T* im_data = im.data<T>();
T* col_data = col->data<T>(); T* col_data = col->data<T>();
// TODO(TJ): change me to template
// further optimaze:
// 1. padding != 1
// 2. could also support stride_h != 1
if (stride[0] == 1 && stride[1] == 1 && dilation[0] == 1 &&
dilation[1] == 1 && padding[0] == 0 && padding[1] == 0) {
int col_matrix_width = output_width * output_height;
for (int oh = 0; oh < output_height; ++oh) {
const T* im_data_start = im_data + oh * im_width;
T* dst_data = col_data + oh * output_width;
for (int ic = 0; ic < im_channels; ++ic) {
const T* src_data = im_data_start + ic * im_height * im_width;
for (int kh = 0; kh < filter_height; ++kh) {
for (int kw = 0; kw < filter_width; ++kw) {
std::memcpy(dst_data, src_data + kw, sizeof(T) * output_width);
dst_data = dst_data + col_matrix_width;
}
src_data = src_data + im_width;
}
}
}
return;
}
for (int c = 0; c < channels_col; ++c) { for (int c = 0; c < channels_col; ++c) {
int w_offset = c % filter_width; int w_offset = c % filter_width;
int h_offset = (c / filter_width) % filter_height; int h_offset = (c / filter_width) % filter_height;
int c_im = c / (filter_width * filter_height); int c_im = c / (filter_width * filter_height);
for (int h = 0; h < col_height; ++h) { for (int h = 0; h < output_height; ++h) {
int im_row_idx = h * stride[0] - padding[0] + h_offset * dilation[0]; int im_row_idx = h * stride[0] - padding[0] + h_offset * dilation[0];
for (int w = 0; w < col_width; ++w) { for (int w = 0; w < output_width; ++w) {
int im_col_idx = w * stride[1] - padding[1] + w_offset * dilation[1]; int im_col_idx = w * stride[1] - padding[1] + w_offset * dilation[1];
int col_idx = (c * col_height + h) * col_width + w; int col_idx = (c * output_height + h) * output_width + w;
int im_idx = (im_row_idx + c_im * im_height) * im_width + im_col_idx; int im_idx = (im_row_idx + c_im * im_height) * im_width + im_col_idx;
col_data[col_idx] = (im_row_idx < 0 || im_row_idx >= im_height || col_data[col_idx] = (im_row_idx < 0 || im_row_idx >= im_height ||
......
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