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#pragma once
#include <ATen/OpMathType.h>
#include <ATen/native/DispatchStub.h>
#include <ATen/native/TransposeType.h>
#include <c10/util/complex.h>
#include <c10/core/ScalarType.h>
#include <c10/core/Scalar.h>
namespace at::native::cpublas {
namespace internal {
void normalize_last_dims(
TransposeType transa, TransposeType transb,
int64_t m, int64_t n, int64_t k,
int64_t *lda, int64_t *ldb, int64_t *ldc);
} // namespace internal
using gemm_fn = void(*)(
at::ScalarType type,
TransposeType transa, TransposeType transb,
int64_t m, int64_t n, int64_t k,
const Scalar& alpha,
const void *a, int64_t lda,
const void *b, int64_t ldb,
const Scalar& beta,
void *c, int64_t ldc);
DECLARE_DISPATCH(gemm_fn, gemm_stub)
using gemm_no_downcast_fn = void(*)(
at::ScalarType type,
TransposeType transa, TransposeType transb,
int64_t m, int64_t n, int64_t k,
const Scalar& alpha,
const void *a, int64_t lda,
const void *b, int64_t ldb,
const Scalar& beta,
void *c, int64_t ldc);
DECLARE_DISPATCH(gemm_no_downcast_fn, gemm_no_downcast_stub)
template <typename scalar_t>
void gemm(
TransposeType transa, TransposeType transb,
int64_t m, int64_t n, int64_t k,
at::opmath_type<scalar_t> alpha,
const scalar_t *a, int64_t lda,
const scalar_t *b, int64_t ldb,
at::opmath_type<scalar_t> beta,
scalar_t *c, int64_t ldc) {
internal::normalize_last_dims(transa, transb, m, n, k, &lda, &ldb, &ldc);
gemm_stub(
kCPU, c10::CppTypeToScalarType<scalar_t>::value,
transa, transb, m, n, k, alpha, a, lda, b, ldb, beta, c, ldc);
}
void gemm(
TransposeType transa, TransposeType transb,
int64_t m, int64_t n, int64_t k,
double alpha,
const double *a, int64_t lda,
const double *b, int64_t ldb,
double beta,
double *c, int64_t ldc);
void gemm(
TransposeType transa, TransposeType transb,
int64_t m, int64_t n, int64_t k,
float alpha,
const float *a, int64_t lda,
const float *b, int64_t ldb,
float beta,
float *c, int64_t ldc);
void gemm(
TransposeType transa, TransposeType transb,
int64_t m, int64_t n, int64_t k,
float alpha,
const at::BFloat16 *a, int64_t lda,
const at::BFloat16 *b, int64_t ldb,
float beta,
at::BFloat16 *c, int64_t ldc);
void gemm(
TransposeType transa, TransposeType transb,
int64_t m, int64_t n, int64_t k,
const float alpha,
const at::BFloat16 *a, int64_t lda,
const at::BFloat16 *b, int64_t ldb,
const float beta,
float *c, int64_t ldc);
void gemm(
TransposeType transa, TransposeType transb,
int64_t m, int64_t n, int64_t k,
float alpha,
const at::Half *a, int64_t lda,
const at::Half *b, int64_t ldb,
float beta,
at::Half *c, int64_t ldc);
void gemm(
TransposeType transa, TransposeType transb,
int64_t m, int64_t n, int64_t k,
const float alpha,
const at::Half *a, int64_t lda,
const at::Half *b, int64_t ldb,
const float beta,
float *c, int64_t ldc);
void gemm(
TransposeType transa, TransposeType transb,
int64_t m, int64_t n, int64_t k,
c10::complex<double> alpha,
const c10::complex<double> *a, int64_t lda,
const c10::complex<double> *b, int64_t ldb,
c10::complex<double> beta,
c10::complex<double> *c, int64_t ldc);
void gemm(
TransposeType transa, TransposeType transb,
int64_t m, int64_t n, int64_t k,
c10::complex<float> alpha,
const c10::complex<float> *a, int64_t lda,
const c10::complex<float> *b, int64_t ldb,
c10::complex<float> beta,
c10::complex<float> *c, int64_t ldc);
void gemm(
TransposeType transa, TransposeType transb,
int64_t m, int64_t n, int64_t k,
int64_t alpha,
const int64_t *a, int64_t lda,
const int64_t *b, int64_t ldb,
int64_t beta,
int64_t *c, int64_t ldc);
template <typename scalar_t>
void gemm_batched(
TransposeType transa, TransposeType transb,
int64_t batch_size, int64_t m, int64_t n, int64_t k,
scalar_t alpha,
const scalar_t * const *a, int64_t lda,
const scalar_t * const *b, int64_t ldb,
const scalar_t beta,
scalar_t * const *c, int64_t ldc);
template <typename scalar_t>
void gemm_batched_with_stride(
TransposeType transa, TransposeType transb,
int64_t batch_size, int64_t m, int64_t n, int64_t k,
scalar_t alpha,
const scalar_t *a, int64_t lda, int64_t batch_stride_a,
const scalar_t *b, int64_t ldb, int64_t batch_stride_b,
scalar_t beta,
scalar_t *c, int64_t ldc, int64_t batch_stride_c);
using axpy_fn = void(*)(at::ScalarType type, int64_t n, const Scalar& a, const void *x, int64_t incx, void *y, int64_t incy);
DECLARE_DISPATCH(axpy_fn, axpy_stub)
template<typename scalar_t>
void axpy(int64_t n, scalar_t a, const scalar_t *x, int64_t incx, scalar_t *y, int64_t incy){
if(n == 1)
{
incx = 1;
incy = 1;
}
axpy_stub(
kCPU, c10::CppTypeToScalarType<scalar_t>::value,
n, a, x, incx, y, incy);
}
void axpy(int64_t n, double a, const double *x, int64_t incx, double *y, int64_t incy);
void axpy(int64_t n, float a, const float *x, int64_t incx, float *y, int64_t incy);
void axpy(int64_t n, c10::complex<double> a, const c10::complex<double> *x, int64_t incx, c10::complex<double> *y, int64_t incy);
void axpy(int64_t n, c10::complex<float> a, const c10::complex<float> *x, int64_t incx, c10::complex<float> *y, int64_t incy);
using copy_fn = void(*)(at::ScalarType type, int64_t n, const void *x, int64_t incx, void *y, int64_t incy);
DECLARE_DISPATCH(copy_fn, copy_stub)
template<typename scalar_t>
void copy(int64_t n, const scalar_t *x, int64_t incx, scalar_t *y, int64_t incy) {
if(n == 1)
{
incx = 1;
incy = 1;
}
copy_stub(
kCPU, c10::CppTypeToScalarType<scalar_t>::value,
n, x, incx, y, incy);
}
void copy(int64_t n, const double *x, int64_t incx, double *y, int64_t incy);
void copy(int64_t n, const float *x, int64_t incx, float *y, int64_t incy);
void copy(int64_t n, const c10::complex<double> *x, int64_t incx, c10::complex<double> *y, int64_t incy);
void copy(int64_t n, const c10::complex<float> *x, int64_t incx, c10::complex<float> *y, int64_t incy);
// Batch-reduce GEMM
// Operates by the following formula:
// C = SUM(A[i] x B[i]) + C if add_C is true, i = 0 to batch size
// A Base pointer to a tensor A.
// B Base pointer to a tensor B.
// C Pointer to a tensor C (accumulation buffer).
// Note only batch size 1 is used currently
TORCH_API void brgemm(
int64_t M,
int64_t N,
int64_t K,
int64_t ld_a,
int64_t ld_b,
int64_t ld_c,
const bool add_C,
const at::Half* A,
const at::Half* B,
float* C,
bool is_vnni = true);
TORCH_API void brgemm(
int64_t M,
int64_t N,
int64_t K,
int64_t ld_a,
int64_t ld_b,
int64_t ld_c,
const bool add_C,
const at::BFloat16* A,
const at::BFloat16* B,
float* C,
bool is_vnni = true);
TORCH_API void brgemm(
int64_t M,
int64_t N,
int64_t K,
int64_t ld_a,
int64_t ld_b,
int64_t ld_c,
const bool add_C,
const float* A,
const float* B,
float* C,
bool is_vnni = false);
TORCH_API void brgemm(
int64_t M,
int64_t N,
int64_t K,
int64_t ld_a,
int64_t ld_b,
int64_t ld_c,
const bool add_C,
const unsigned char* A,
const unsigned char* B,
int32_t* C,
bool is_vnni = true);
TORCH_API void brgemm(
int64_t M,
int64_t N,
int64_t K,
int64_t ld_a,
int64_t ld_b,
int64_t ld_c,
const bool add_C,
const unsigned char* A,
const signed char* B,
int32_t* C,
bool is_vnni = true);
TORCH_API void brgemm(
int64_t M,
int64_t N,
int64_t K,
int64_t ld_a,
int64_t ld_b,
int64_t ld_c,
const bool add_C,
const signed char* A,
const signed char* B,
int32_t* C,
bool is_vnni = true);
// Release brgemm hardware context
TORCH_API void brgemm_release(bool is_vnni = true);
// Pack B matrix to get better performance if needed
TORCH_API void pack(
int64_t K,
int64_t N,
int64_t ld_in,
int64_t ld_out,
ScalarType dt_in,
ScalarType dt_out,
const void* in,
void* out);
// Whether pack is supported in the platform.
TORCH_API bool could_pack(ScalarType dt_in);
} // namespace at::native::cpublas
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