MegEngine/dnn/src/rocm/batched_matrix_mul/opr_impl.cpp

/**
 * \file dnn/src/rocm/batched_matrix_mul/opr_impl.cpp
 * MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
 *
 * Copyright (c) 2014-2021 Megvii Inc. All rights reserved.
 *
 * Unless required by applicable law or agreed to in writing,
 * software distributed under the License is distributed on an
 * "AS IS" BASIS, WITHOUT ARRANTIES OR CONDITIONS OF ANY KIND, either express or
 * implied.
 */
#include "./opr_impl.h"
#include "./algos.h"
#include "hcc_detail/hcc_defs_prologue.h"

#include "src/common/algo_chooser.h"
#include "src/common/utils.cuh"
#include "src/rocm/handle.h"
#include "src/rocm/utils.h"

using namespace megdnn;
using namespace rocm;

std::vector<BatchedMatrixMulForwardImpl::Algorithm*>
BatchedMatrixMulForwardImpl::get_all_algorithms(const TensorLayout& A,
                                                const TensorLayout& B,
                                                const TensorLayout& C) {
    AlgoBase::SizeArgs args{this, A, B, C};
    return megdnn::get_all_algorithms<BatchedMatrixMulForwardImpl>(args);
}

BatchedMatrixMulForwardImpl::Algorithm*
BatchedMatrixMulForwardImpl::get_algorithm_heuristic(
        const TensorLayout& A, const TensorLayout& B, const TensorLayout& C,
        size_t workspace_limit_in_bytes,
            const AlgoAttribute& positive_attr,
            const AlgoAttribute& negative_attr) {
    AlgoBase::SizeArgs args{this, A, B, C};
    if (sm_algo_pack.blas.is_available_attribute(
                args, positive_attr, negative_attr, workspace_limit_in_bytes)) {
        return &sm_algo_pack.blas;
    }
    return megdnn::get_algo_match_attribute<BatchedMatrixMulForwardImpl>(
            sm_algo_pack.all_algos, args, workspace_limit_in_bytes,
            "batched matrix mul forward", positive_attr, negative_attr);
}

size_t BatchedMatrixMulForwardImpl::get_workspace_in_bytes(
        const TensorLayout& A, const TensorLayout& B, const TensorLayout& C) {
    return get_dnn_workspace(this, A, B, C);
}

void BatchedMatrixMulForwardImpl::exec(_megdnn_tensor_in A, _megdnn_tensor_in B,
                                       _megdnn_tensor_out C,
                                       _megdnn_workspace workspace) {
    check_exec(A.layout, B.layout, C.layout, workspace.size);
    AlgoBase::ExecArgs args(this, A, B, C, workspace);
    auto&& algo = get_algorithm(this, A.layout, B.layout, C.layout);
    algo->exec(args);
}

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