static void conv1x1s1_sgemm_pack4_lsx(const Mat& bottom_blob, Mat& top_blob, const Mat& kernel, const Mat& _bias, const Option& opt)
{
int w = bottom_blob.w;
int h = bottom_blob.h;
const int size = w * h;
Mat bottom_im2col = bottom_blob;
bottom_im2col.w = size;
bottom_im2col.h = 1;
im2col_sgemm_pack4_lsx(bottom_im2col, top_blob, kernel, _bias, opt);
}
static void conv1x1s2_sgemm_pack4_lsx(const Mat& bottom_blob, Mat& top_blob, const Mat& kernel, const Mat& _bias, const Option& opt)
{
int w = bottom_blob.w;
int channels = bottom_blob.c;
size_t elemsize = bottom_blob.elemsize;
int elempack = bottom_blob.elempack;
int outw = top_blob.w;
int outh = top_blob.h;
const int tailstep = (w - 2 * outw + w) * 4;
Mat bottom_blob_shrinked;
bottom_blob_shrinked.create(outw, outh, channels, elemsize, elempack, opt.workspace_allocator);
#pragma omp parallel for num_threads(opt.num_threads)
for (int p = 0; p < channels; p++)
{
const float* r0 = bottom_blob.channel(p);
float* outptr = bottom_blob_shrinked.channel(p);
for (int i = 0; i < outh; i++)
{
for (int j = 0; j < outw; j++)
{
__m128 _val = (__m128)__lsx_vld(r0, 0);
__lsx_vst(_val, outptr, 0);
r0 += 4 * 2;
outptr += 4;
}
r0 += tailstep;
}
}
conv1x1s1_sgemm_pack4_lsx(bottom_blob_shrinked, top_blob, kernel, _bias, opt);
}