#include "src/rocm/batched_matrix_mul/algos.h"
#include "src/common/algo_base.h"
using namespace megdnn;
using namespace rocm;
BatchedMatrixMulForwardImpl::AlgoPack::AlgoPack() {
all_algos.push_back(&blas);
for (auto&& algo : all_algos) {
m_all_algos_map.emplace(algo->info().desc, algo);
}
}
BatchedMatrixMulForwardImpl::AlgoPack BatchedMatrixMulForwardImpl::sm_algo_pack;
MEGDNN_DEF_GET_ALGO_FROM_DESC(BatchedMatrixMulForwardImpl)
BatchedMatrixMulForwardImpl::AlgoBase::SizeArgs::SizeArgs(
BatchedMatrixMulForwardImpl* o, const TensorLayout& A, const TensorLayout& B,
const TensorLayout& C)
: opr{o}, layout_a{A}, layout_b{B}, layout_c{C} {}
BatchedMatrixMulForwardImpl::AlgoBase::ExecArgs::ExecArgs(
BatchedMatrixMulForwardImpl* opr, _megdnn_tensor_in A, _megdnn_tensor_in B,
_megdnn_tensor_out C, _megdnn_workspace workspace)
: SizeArgs(opr, A.layout, B.layout, C.layout),
tensor_a{A},
tensor_b{B},
tensor_c{C},
workspace{workspace} {}
std::string BatchedMatrixMulForwardImpl::AlgoBase::SizeArgs::to_string() const {
auto&& param = opr->param();
size_t m = layout_a.shape[0], n = layout_b.shape[1],
k = layout_a.shape[param.transposeA ? 0 : 1];
MEGDNN_MARK_USED_VAR(m);
MEGDNN_MARK_USED_VAR(n);
MEGDNN_MARK_USED_VAR(k);
return ssprintf(
"A={%zux%zu},B={%zux%zu},C={%zux%zu},Transpose A=%d,Transpose "
"B=%d,ldA=%zu,ldB=%zu,ldC=%zu",
m, k, k, n, m, n, param.transposeA, param.transposeB, layout_a.stride[0],
layout_b.stride[0], layout_c.stride[0]);
}