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Producer.hpp 5.78 KiB
/********************************************************************************
 * 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_PRODUCER_H_
#define AIDGE_CORE_OPERATOR_PRODUCER_H_

#include <array>
#include <vector>

#include "aidge/utils/Types.h"
#include "aidge/data/Tensor.hpp"
#include "aidge/graph/Node.hpp"
#include "aidge/operator/Operator.hpp"
#include "aidge/utils/Parameter.hpp"
#include "aidge/utils/Registrar.hpp"

namespace Aidge {

class Producer_Op
    : public Operator,
      public Registrable<Producer_Op, std::string, std::unique_ptr<OperatorImpl>(
                                          const Producer_Op &)> {
private:
    std::shared_ptr<Tensor> mOutput = std::make_shared<Tensor>();

public:
    static constexpr const char* Type = "Producer";

    template <std::size_t DIM>
    Producer_Op(const std::array<DimSize_t, DIM>& dims)
        : Operator(Type)
    {
        //ctor
        setDatatype(DataType::Float32);
        mOutput->resize(dims);
    }

    Producer_Op(const std::shared_ptr<Tensor> tensor)
        : Operator(Type),
          mOutput(tensor)
    {
        setDatatype(tensor->dataType());
    }

    /**
     * @brief Copy-constructor. Copy the operator parameters and its output tensor(s), but not its input tensors (the new operator has no input associated).
     * @param op Operator to copy.
     */
    Producer_Op(const Producer_Op& op)
        : Operator(Type),
          mOutput(std::make_shared<Tensor>(*op.mOutput))
    {
        // cpy-ctor
        setDatatype(op.mOutput->dataType());
    }

    /**
     * @brief Clone the operator using its copy-constructor.
     * @see Operator::Producer_Op
     */
    std::shared_ptr<Operator> clone() const override {
        return std::make_shared<Producer_Op>(*this);
    }

    void associateInput(const IOIndex_t /*inputIdx*/, std::shared_ptr<Data> /*data*/) override final {
        assert(false && "Producer operator takes no input");
    }

    void computeOutputDims() override final {}

    bool outputDimsForwarded() const override final {return true;}


    [[noreturn]] inline Tensor& input(const IOIndex_t /*inputIdx*/) const override final {
      assert(false);
      exit(-1);
    }
    inline Tensor& output(const IOIndex_t /*outputIdx*/) const override final { return *(mOutput.get()); }


    inline std::shared_ptr<Tensor> getInput(const IOIndex_t /*inputIdx*/) const override final {
      assert(false && "Producer Operator has no input");
      return nullptr;
    }
    inline std::shared_ptr<Tensor> getOutput(const IOIndex_t outputIdx) const override final {
      assert((outputIdx == 0) && "Producer Operator has only 1 output");
      (void) outputIdx; // avoid unused warning
      return mOutput;
    }


    std::shared_ptr<Data> getRawInput(const IOIndex_t /*inputIdx*/) const override final {
        assert(false && "Producer operator takes no input");
        return nullptr;
    }

    std::shared_ptr<Data> getRawOutput(const IOIndex_t outputIdx) const override final {
        assert(outputIdx == 0 && "operator supports only 1 output");
        (void) outputIdx; // avoid unused warning
        return std::static_pointer_cast<Data>(mOutput);
    }

    inline const std::vector<DimSize_t> dims() const noexcept { return mOutput->dims(); }

    void setBackend(const std::string& name) {
        mImpl = Registrar<Producer_Op>::create(name)(*this);
        mOutput->setBackend(name);
    }
    void setDatatype(const DataType& datatype) {
        mOutput->setDatatype(datatype);
    }

    inline IOIndex_t nbInputs() const noexcept override final { return 0; };
    inline IOIndex_t nbDataInputs() const noexcept override final { return 0; };
    inline IOIndex_t nbOutputs() const noexcept override final { return 1; };

public:
  void forward() override final {
    printf("Basic Producer forward() function.\n");
  }
  void backward() override final {
    printf("Basic Producer backward() function.\n");
  }
};

template <std::array<DimSize_t, 1>::size_type DIM>
inline std::shared_ptr<Node> Producer(const std::array<DimSize_t, DIM> &dims, const std::string& name = "") {
  static_assert(DIM<=MaxDim,"Too many tensor dimensions required by Producer, not supported");
  return std::make_shared<Node>(std::make_shared<Producer_Op>(dims), name);
}

template <std::size_t DIM>
inline std::shared_ptr<Node> Producer(DimSize_t const (&dims)[DIM], const std::string& name = "") {
  return Producer(to_array(dims), name);
}

inline std::shared_ptr<Node> Producer(const std::shared_ptr<Tensor> tensor, const std::string& name = "") {
  return std::make_shared<Node>(std::make_shared<Producer_Op>(tensor), name);
}

template <std::array<DimSize_t, 1>::size_type DIM>
void addProducer(std::shared_ptr<Node>& otherNode, const IOIndex_t inputIdx, const std::array<DimSize_t, DIM>& dims, const std::string& extension) {
    assert(inputIdx != gk_IODefaultIndex);
    static_assert(DIM<=MaxDim,"Too many tensor dimensions required by addProducer, not supported");
    const std::string prodName = (otherNode->name().empty()) ? "" : (otherNode->name() + std::string("_") + extension);
    auto prod = Producer(dims, prodName);
    prod->addChild(otherNode, 0, inputIdx);
    otherNode->getOperator()->associateInput(inputIdx, prod->getOperator()->getRawOutput(0));
}

template <std::size_t DIM>
void addProducer(std::shared_ptr<Node>& otherNode, const IOIndex_t inputIdx, DimSize_t const (&dims)[DIM], const std::string& extension) {
    addProducer(otherNode, inputIdx, to_array(dims), extension);
}
} // namespace Aidge

#endif /* AIDGE_CORE_OPERATOR_PRODUCER_H_ */