GridSampleImpl.cpp

/********************************************************************************
 * 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 "aidge/backend/cpu/operator/GridSampleImpl.hpp"

#include <functional>
#include <vector>

#include "aidge/backend/cpu/data/GetCPUPtr.h"
#include "aidge/backend/cpu/operator/GridSampleImpl_kernels.hpp"
#include "aidge/operator/GridSample.hpp"
#include "aidge/utils/Types.h"

template <>
void Aidge::GridSampleImpl_cpu::forward() {
    const auto& op_ = static_cast<const GridSample_Op&>(mOp);

    // Find the correct kernel type
    const auto impl = Registrar<GridSampleImpl_cpu>::create(getBestMatch(getRequiredSpec()));

    // Convert input data (no overhead if not needed!)
    // TODO: right now, if needed, memory will be allocated/deallocated at each
    // call to forward(). We might put the following shared_ptr as members of
    // this class to avoid that.
    std::shared_ptr<Tensor> input0Fallback, input1Fallback;
    const auto& input0 = std::make_shared<Tensor>(op_.getInput(0)->refCastFrom(input0Fallback, *op_.getOutput(0)));
    const auto& input1 = std::make_shared<Tensor>(op_.getInput(1)->refCastFrom(input1Fallback, *op_.getOutput(0)));

    // Call kernel
    impl.forward(op_,
            input0, // input
            input1, // grid
            op_.getOutput(0) // output
            );
}

template <>
void Aidge::GridSampleImpl_cpu::backward() {
    AIDGE_THROW_OR_ABORT(std::runtime_error, "Backward not yet implemented for GridSample_Op on backend cpu");
}