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

/**
 * \file dnn/src/naive/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 "src/naive/batched_matrix_mul/opr_impl.h"
#include "src/naive/matrix_mul/opr_impl.h"
#include "src/naive/handle.h"
#include "src/common/utils.h"

namespace megdnn {
namespace naive {
BatchedMatrixMulForwardImpl::BatchedMatrixMulForwardImpl(Handle *handle):
    BatchedMatrixMulForward(handle),
    m_opr(this->handle()->create_operator<MatrixMulForward>())
{
}

size_t BatchedMatrixMulForwardImpl::get_workspace_in_bytes(
        const TensorLayout &A, const TensorLayout &B,
        const TensorLayout &C) {
    MEGDNN_MARK_USED_VAR(A);
    MEGDNN_MARK_USED_VAR(B);
    MEGDNN_MARK_USED_VAR(C);
    return 0;
}

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);

    m_opr->param() = this->param();
    auto N = A.layout.shape[0];
    TensorND A_, B_, C_;
    A_.raw_ptr = A.raw_ptr;
    A_.layout = A.layout.remove_axis(0);
    B_.raw_ptr = B.raw_ptr;
    B_.layout = B.layout.remove_axis(0);
    C_.raw_ptr = C.raw_ptr;
    C_.layout = C.layout.remove_axis(0);

    auto Astrd = A.layout.dtype.size() * A.layout.stride[0],
         Bstrd = B.layout.dtype.size() * B.layout.stride[0],
         Cstrd = C.layout.dtype.size() * C.layout.stride[0];

    auto advance_ptr = [](TensorND &dest, ptrdiff_t d) {
        dest.raw_ptr = static_cast<void*>(
                static_cast<dt_byte*>(dest.raw_ptr) + d);
    };

    rep(n, N) {
        m_opr->exec(A_, B_, C_, workspace);
        advance_ptr(A_, Astrd);
        advance_ptr(B_, Bstrd);
        advance_ptr(C_, Cstrd);
    }

}

std::vector<BatchedMatrixMulForward::Algorithm*>
BatchedMatrixMulForwardImpl::get_all_algorithms(const TensorLayout& /*A*/,
                                                const TensorLayout& /*B*/,
                                                const TensorLayout& /*C*/) {
    return {static_cast<HandleImpl*>(handle())
                    ->default_batched_matmul_fwd_algo()};
}

BatchedMatrixMulForward::Algorithm*
BatchedMatrixMulForwardImpl::get_algorithm_heuristic(
        const TensorLayout& /*A*/, const TensorLayout& /*B*/,
        const TensorLayout& /*C*/, size_t /*workspace_limit_in_bytes*/,
        const AlgoAttribute& /*attr*/) {
    return static_cast<HandleImpl*>(handle())
            ->default_batched_matmul_fwd_algo();
}

BatchedMatrixMulForward::Algorithm*
BatchedMatrixMulForwardImpl::get_algorithm_from_desc(
        const AlgorithmDesc& desc) {
    Algorithm* ret = static_cast<HandleImpl*>(handle())
                             ->default_batched_matmul_fwd_algo();
    megdnn_assert(desc == ret->info().desc);
    return ret;
}

}  // namespace naive
}  // namespace megdnn

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