/********************************************************************************
 * Copyright (c) 2023 CEA-List
 *
 * This program and the accompanying materials are made available under the
 * terms of the Eclipse Public License 2.0 which is available at
 * http://www.eclipse.org/legal/epl-2.0.
 *
 * SPDX-License-Identifier: EPL-2.0
 *
 ********************************************************************************/

#include <cassert>
#include <numeric> // std::accumulate
#include <vector>

#include "aidge/utils/Types.h"
#include "aidge/data/Data.hpp"
#include "aidge/data/Tensor.hpp"

#include "aidge/backend/cpu/operator/AddImpl.hpp"
#include "aidge/backend/cpu/operator/AddImpl_forward_kernels.hpp"

Aidge::NbElts_t  Aidge::AddImpl_cpu::getNbRequiredProtected(const Aidge::IOIndex_t /*inputIdx*/) const {
    // this implementation can be in-place
    return 0;
}

void  Aidge::AddImpl_cpu::forward() {
    assert(mOp.getRawInput(0) && "missing input in Add operator");
    DataType datatypeFirstInput = std::static_pointer_cast<Tensor>(mOp.getRawInput(0))->dataType();
    for (IOIndex_t i = 1; i < mOp.nbInputs(); ++i) {
        assert(mOp.getRawInput(i) && "missing input in Add operator");
        assert(std::static_pointer_cast<Tensor>(mOp.getRawInput(i))->dataType() == datatypeFirstInput);
    }

    auto kernelFunc = Registrar<AddImplForward_cpu>::create({
        datatypeFirstInput,
        std::static_pointer_cast<Tensor>(mOp.getRawOutput(0))->dataType()});

    std::vector<const void*> opInputs;
    for (IOIndex_t i = 0; i < mOp.nbInputs(); ++i) {
        opInputs.push_back(std::static_pointer_cast<Tensor>(mOp.getRawInput(i))->getImpl()->rawPtr());
    }

    kernelFunc(std::static_pointer_cast<Tensor>(mOp.getRawInput(0))->size(),
               opInputs,
               std::static_pointer_cast<Tensor>(mOp.getRawOutput(0))->getImpl()->rawPtr());
}