#include "cumulativesum.h"
namespace ncnn {
CumulativeSum::CumulativeSum()
{
one_blob_only = true;
support_inplace = true;
}
int CumulativeSum::load_param(const ParamDict& pd)
{
axis = pd.get(0, 0);
return 0;
}
int CumulativeSum::forward_inplace(Mat& bottom_top_blob, const Option& opt) const
{
int dims = bottom_top_blob.dims;
int positive_axis = axis < 0 ? dims + axis : axis;
if (dims == 1)
{
int w = bottom_top_blob.w;
float* ptr = bottom_top_blob;
for (int i = 1; i < w; ++i)
{
ptr[i] = ptr[i] + ptr[i - 1];
}
return 0;
}
if (dims == 2 && positive_axis == 0)
{
int w = bottom_top_blob.w;
int h = bottom_top_blob.h;
for (int i = 1; i < h; ++i)
{
const float* prev_row = bottom_top_blob.row(i - 1);
float* this_row = bottom_top_blob.row(i);
for (int k = 0; k < w; ++k)
{
this_row[k] = this_row[k] + prev_row[k];
}
}
return 0;
}
if (dims == 2 && positive_axis == 1)
{
int w = bottom_top_blob.w;
int h = bottom_top_blob.h;
#pragma omp parallel for num_threads(opt.num_threads)
for (int i = 0; i < h; ++i)
{
float* ptr = bottom_top_blob.row(i);
for (int k = 1; k < w; ++k)
{
ptr[k] = ptr[k] + ptr[k - 1];
}
}
return 0;
}
if (dims == 3 && positive_axis == 0)
{
int w = bottom_top_blob.w;
int h = bottom_top_blob.h;
int c = bottom_top_blob.c;
int size = w * h;
for (int i = 1; i < c; ++i)
{
const float* prev = bottom_top_blob.channel(i - 1);
float* cur = bottom_top_blob.channel(i);
for (int k = 0; k < size; ++k)
{
cur[k] = cur[k] + prev[k];
}
}
return 0;
}
if (dims == 3 && positive_axis == 1)
{
int w = bottom_top_blob.w;
int h = bottom_top_blob.h;
int c = bottom_top_blob.c;
#pragma omp parallel for num_threads(opt.num_threads)
for (int q = 0; q < c; ++q)
{
Mat this_channel = bottom_top_blob.channel(q);
for (int i = 1; i < h; ++i)
{
const float* prev_row = this_channel.row(i - 1);
float* this_row = this_channel.row(i);
for (int k = 0; k < w; ++k)
{
this_row[k] = this_row[k] + prev_row[k];
}
}
}
return 0;
}
if (dims == 3 && positive_axis == 2)
{
int w = bottom_top_blob.w;
int h = bottom_top_blob.h;
int c = bottom_top_blob.c;
#pragma omp parallel for num_threads(opt.num_threads)
for (int q = 0; q < c; ++q)
{
Mat this_channel = bottom_top_blob.channel(q);
for (int i = 0; i < h; ++i)
{
float* ptr = this_channel.row(i);
for (int k = 1; k < w; ++k)
{
ptr[k] = ptr[k] + ptr[k - 1];
}
}
}
return 0;
}
return -100;
}
}