提交 009273ef 编写于 作者: R Ruilong Liu 提交者: GitHub

Merge branch 'develop' into develop

此差异已折叠。
......@@ -28,6 +28,7 @@ namespace paddle_mobile {
namespace operators {
namespace math {
/*
// 将 A 矩阵分块复制到连续内存(ColMajor)
void PackMatrixA(int m, int k, int m_tail, const float *A, int lda,
float *buffer);
......@@ -35,6 +36,7 @@ void PackMatrixA(int m, int k, int m_tail, const float *A, int lda,
// 将 B 矩阵分块复制到连续内存(ColMajor)
void PackMatrixB(int k, int n, int n_tail, const float *B, int ldb,
float *buffer);
*/
// 将 A 矩阵分块复制到连续内存(RowMajor)
void PackMatrixA_(int m, int k, int m_tail, const float *A, int lda,
......@@ -51,7 +53,7 @@ void InnerKernel(int mc, int nc, float alpha, const float *a, const float *b,
void InnerKernelWithBn(int mc, int nc, float alpha, const float *a,
const float *b, float beta, float *c, float *C, int ldc,
bool relu, float *new_scale, float *new_bias);
/*
// 向量矩阵乘法 (M = 1)
void VectorKernel(int m, int n, int k, float alpha, const float *A, int lda,
const float *B, int ldb, float beta, float *C, int ldc,
......@@ -60,6 +62,7 @@ void VectorKernel(int m, int n, int k, float alpha, const float *A, int lda,
void VectorKernelWithBn(int m, int n, int k, float alpha, const float *A,
int lda, const float *B, int ldb, float beta, float *C,
int ldc, bool relu, float *new_scale, float *new_bias);
*/
// 计算一个更小的 C 矩阵分块
void AddDot4x4(int k, const float *a, const float *b, float *c, int ldc);
......@@ -81,6 +84,7 @@ void WriteWithBn(int mc, int nc, float *c, float *C, int ldc, float *new_scale,
void WriteWithBnRelu(int mc, int nc, float *c, float *C, int ldc,
float *new_scale, float *new_bias);
/*
// 向量矩阵乘法结果回写
// C = A * B
void VecWriteBasic(int n, float *c, float *C, int ldc);
......@@ -96,6 +100,7 @@ void VecWriteWithBn(int n, float *c, float *C, int ldc, float *new_scale,
// C = A * B, batchnorm(C), relu(C)
void VecWriteWithBnRelu(int n, float *c, float *C, int ldc, float *new_scale,
float *new_bias);
*/
// 32位 float 矩阵乘法
void Sgemm(int m, int n, int k, float alpha, const float *A, int lda,
......
Markdown is supported
0% .
You are about to add 0 people to the discussion. Proceed with caution.
先完成此消息的编辑!
想要评论请 注册