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/********************************************************************************
* 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
*
********************************************************************************/
#ifndef AIDGE_CORE_OPERATOR_CONVDEPTHWISE_H_
#define AIDGE_CORE_OPERATOR_CONVDEPTHWISE_H_

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#include <cmath> // std::floor
#include <cstddef> // std::size_t
#include <string>
#include <utility> // std::pair
#include "aidge/data/Tensor.hpp"
#include "aidge/graph/Node.hpp"

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#include "aidge/operator/OperatorTensor.hpp"
#include "aidge/operator/Producer.hpp"

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#include "aidge/utils/ArrayHelpers.hpp"
#include "aidge/utils/StaticAttributes.hpp"
#include "aidge/utils/Registrar.hpp"
#include "aidge/utils/Types.h"
enum class ConvDepthWiseAttr { StrideDims, DilationDims, KernelDims, NoBias };

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class ConvDepthWise_Op : public OperatorTensor,
public Registrable<ConvDepthWise_Op<DIM>, std::string, std::shared_ptr<OperatorImpl>(const ConvDepthWise_Op<DIM> &)>,
public StaticAttributes<ConvDepthWiseAttr,
std::array<DimSize_t, DIM>,
std::array<DimSize_t, DIM>,
std::array<DimSize_t, DIM>,
bool> {

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public:
static const std::string Type;
using Attributes_ = StaticAttributes<ConvDepthWiseAttr,
std::array<DimSize_t, DIM>,
std::array<DimSize_t, DIM>,
bool>;
template <ConvDepthWiseAttr e>
using attr = typename Attributes_::template attr<e>;
constexpr ConvDepthWise_Op(const std::array<DimSize_t, DIM> &kernel_dims,
const std::array<DimSize_t, DIM> &stride_dims = create_array<DimSize_t,DIM>(1),
const std::array<DimSize_t, DIM> &dilation_dims = create_array<DimSize_t,DIM>(1),
bool no_bias=false)

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: OperatorTensor(Type, 1, 2, 1),
Attributes_(attr<ConvDepthWiseAttr::StrideDims>(stride_dims),
attr<ConvDepthWiseAttr::KernelDims>(kernel_dims),
attr<ConvDepthWiseAttr::NoBias>(no_bias)) {}
/**
* @brief Copy-constructor. Copy the operator attributes and its output tensor(s), but not its input tensors (the new operator has no input associated).
* @param op Operator to copy.
*/
ConvDepthWise_Op(const ConvDepthWise_Op<DIM>& op);
/**
* @brief Clone the operator using its copy-constructor.
* @see Operator::ConvDepthWise_Op
*/
std::shared_ptr<Operator> clone() const override {
return std::make_shared<ConvDepthWise_Op<DIM>>(*this);
}
bool forwardDims(bool /*allowDataDependency*/ = false) override final;
std::vector<std::pair<std::vector<DimSize_t>, std::vector<DimSize_t>>>
computeReceptiveField(const std::vector<DimSize_t>& firstEltDims,
const std::vector<DimSize_t>& outputDims,
const IOIndex_t outputIdx = 0) const override;
void setBackend(const std::string &name, DeviceIdx_t device = 0) override;
DimSize_t nbChannels() const {
if (!getInput(1)) {
AIDGE_THROW_OR_ABORT(std::runtime_error, "Convolution operator has no weight Tensor associated so no specific number of channel imposed.");
}
return getInput(1)->template dims<DIM+2>()[0];
static const std::vector<std::string> getInputsName(){
return {"data_input", "weight", "bias"};
}
static const std::vector<std::string> getOutputsName(){
return {"data_output"};
}
};
template <std::array<DimSize_t, 1>::size_type DIM>

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inline std::shared_ptr<Node> ConvDepthWise(const DimSize_t nbChannels,
const std::array<DimSize_t, DIM> &kernelDims,

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const std::array<DimSize_t, DIM> &strideDims = create_array<DimSize_t,DIM>(1),
const std::array<DimSize_t, DIM> &dilationDims = create_array<DimSize_t,DIM>(1),
bool noBias=false) {
// FIXME: properly handle default w&b initialization in every cases
static_assert(DIM<=MaxDim,"Too many kernel dimensions required by ConvDepthWise, not supported");
auto convDW = std::make_shared<Node>(std::make_shared<ConvDepthWise_Op<static_cast<DimIdx_t>(DIM)>>(kernelDims, strideDims, dilationDims, noBias), name);
addProducer(convDW, 1, append(nbChannels, append(DimSize_t(1), kernelDims)), "w");
addProducer(convDW, 2, {(noBias ? 0 : nbChannels)}, "b");
// helper with C-style array instead of std::array for kernel_dims to allow automatic template DIM deduction
template <DimSize_t DIM>
inline std::shared_ptr<Node> ConvDepthWise(

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const DimSize_t nbChannels,
DimSize_t const (&kernelDims)[DIM],

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const std::array<DimSize_t, DIM> &strideDims = create_array<DimSize_t,DIM>(1),
const std::array<DimSize_t, DIM> &dilationDims = create_array<DimSize_t,DIM>(1),
bool noBias=false) {
static_assert(DIM<=MaxDim,"Too many kernel dimensions required by ConvDepthWise, not supported");
return ConvDepthWise(nbChannels, to_array(kernelDims), name, strideDims, dilationDims, noBias);
extern template class Aidge::ConvDepthWise_Op<2>;
const char *const EnumStrings<Aidge::ConvDepthWiseAttr>::data[] = {"StrideDims", "DilationDims",
"KernelDims", "NoBias"};
#endif /* AIDGE_CORE_OPERATOR_CONVDEPTHWISE_H_ */