adding scaling operator

include/aidge/operator/Scaling.hpp

+/********************************************************************************
+ * 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_Scaling_H__
+#define __AIDGE_CORE_OPERATOR_Scaling_H__
+
+#include <vector>
+#include <memory>
+
+#include <memory>
+
+#include <iostream>
+
+#include "aidge/utils/Parameter.hpp"
+#include "aidge/utils/Registrar.hpp"
+#include "aidge/operator/Operator.hpp"
+#include "aidge/backend/OperatorImpl.hpp"
+#include "aidge/data/Tensor.hpp"
+#include "aidge/data/Data.hpp"
+#include "aidge/graph/Node.hpp"
+#include "aidge/utils/Types.h"
+
+namespace Aidge {
+enum class ScalingParam {
+    scalingFactor
+};
+
+class Scaling_Op : public Operator,
+    public Registrable<Scaling_Op, std::string, std::unique_ptr<OperatorImpl>(const Scaling_Op&)>,
+    public Parameterizable<ScalingParam, float> {
+public:
+    // FIXME: change accessibility
+    std::shared_ptr<Tensor> mInput = std::make_shared<Tensor>();
+    const std::shared_ptr<Tensor> mOutput = std::make_shared<Tensor>();
+
+public:
+    static constexpr const char* Type = "Scaling";
+
+    Scaling_Op() = delete;
+
+    using Parameterizable_ = Parameterizable<ScalingParam, float>;
+    template <ScalingParam e> using param = typename Parameterizable_::template param<e>;
+
+    Scaling_Op(float scalingFactor)
+            : Operator(Type),
+            Parameterizable_(
+                param<ScalingParam::scalingFactor>(scalingFactor))
+    {
+        setDatatype(DataType::Float32);
+    }
+
+    void associateInput(__attribute__((unused)) const IOIndex_t inputIdx, std::shared_ptr<Data> data) override final {
+        assert(inputIdx == 0 && "operator supports only 1 input");
+        assert(strcmp(data->type(), Tensor::Type)==0 && "input data must be of Tensor type");
+        mInput = std::dynamic_pointer_cast<Tensor>(data);
+    }
+
+    void computeOutputDims() override final {
+        if (!mInput->empty())
+            mOutput->resize(mInput->dims());
+    }
+
+    bool outputDimsForwarded() const override final {
+        return !(mOutput->empty());
+    }
+
+
+    inline Tensor& input(__attribute__((unused)) const IOIndex_t inputIdx) const override final { return *(mInput.get()); }
+    inline Tensor& output(__attribute__((unused)) const IOIndex_t outputIdx) const override final { return *(mOutput.get()); }
+
+
+    inline std::shared_ptr<Tensor> getInput(__attribute__((unused)) const IOIndex_t inputIdx) const override final { 
+        assert((inputIdx == 0) && "Scaling Operator has only 1 input");
+        return mInput;
+    }
+    inline std::shared_ptr<Tensor> getOutput(__attribute__((unused)) const IOIndex_t outputIdx) const override final {
+        assert((outputIdx == 0) && "Scaling Operator has only 1 output");
+        return mOutput;
+    }
+
+
+    std::shared_ptr<Data> getRawInput(__attribute__((unused)) const IOIndex_t inputIdx) const override final {
+        assert(inputIdx == 0 && "operator supports only 1 input");
+        return std::static_pointer_cast<Data>(mInput);
+    }
+    std::shared_ptr<Data> getRawOutput(__attribute__((unused)) const IOIndex_t outputIdx) const override final {
+        assert(outputIdx == 0 && "operator supports only 1 output");
+        return mOutput;
+    }
+
+
+    void setBackend(const std::string& name) {
+        mImpl = Registrar<Scaling_Op>::create(name)(*this);
+        mOutput->setBackend(name);
+        // FIXME: temporary workaround
+        mInput->setBackend(name);
+    }
+    void setDatatype(const DataType& datatype) {
+        mOutput->setDatatype(datatype);
+
+        // FIXME: temporary workaround
+        mInput->setDatatype(datatype);
+    }
+
+    inline IOIndex_t nbInputs() const noexcept override final { return 1; }
+    inline IOIndex_t nbDataInputs() const noexcept override final { return 1; }
+    inline IOIndex_t nbOutputs() const noexcept override final { return 1; }
+};
+
+inline std::shared_ptr<Node> Scaling(float scalingFactor = 1.0f, const char* name = nullptr) {
+    // FIXME: properly handle default w&b initialization in every cases
+    return std::make_shared<Node>(std::make_shared<Scaling_Op>(scalingFactor), name);
+}
+}
+
+namespace {
+template <>
+const char* const EnumStrings<Aidge::ScalingParam>::data[]
+    = {"scalingFactor"};
+}
+
+#endif /* __AIDGE_CORE_OPERATOR_RELU_H__ */