add Transpose operator

include/aidge/operator/Transpose.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_TRANSPOSE_H_
+#define AIDGE_CORE_OPERATOR_TRANSPOSE_H_
+
+#include <array>
+#include <cmath>
+#include <numeric>
+#include <vector>
+
+#include "aidge/data/Tensor.hpp"
+#include "aidge/graph/Node.hpp"
+#include "aidge/operator/Operator.hpp"
+#include "aidge/operator/Producer.hpp"
+#include "aidge/utils/StaticAttributes.hpp"
+#include "aidge/utils/Registrar.hpp"
+#include "aidge/utils/Types.h"
+
+namespace Aidge {
+enum class TransposeAttr { OutputDimsOrder };
+
+template <DimIdx_t DIM>
+class Transpose_Op : public Operator,
+                public Registrable<Transpose_Op<DIM>, std::string, std::unique_ptr<OperatorImpl>(const Transpose_Op<DIM> &)>,
+                public StaticAttributes<TransposeAttr,
+                                       std::array<DimSize_t, DIM>> {
+   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 = "Transpose";
+
+    Transpose_Op() = delete;
+
+    using Attributes_ = StaticAttributes<TransposeAttr,
+                                             std::array<DimSize_t, DIM>>;
+    template <TransposeAttr e>
+    using attr = typename Attributes_::template attr<e>;
+
+    constexpr Transpose_Op(const std::array<DimSize_t, DIM> &output_dims_order)
+        : Operator(Type),
+          Attributes_(attr<TransposeAttr::OutputDimsOrder>(output_dims_order)) {
+        setDatatype(DataType::Float32);
+    }
+
+    /**
+     * @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.
+     */
+    Transpose_Op(const Transpose_Op<DIM>& op)
+        : Operator(Type),
+          Attributes_(op),
+          mOutput(std::make_shared<Tensor>(*op.mOutput))
+    {
+        // cpy-ctor
+        setDatatype(op.mOutput->dataType());
+        mImpl = op.mImpl ? Registrar<Transpose_Op<DIM>>::create(mOutput->getImpl()->backend())(*this) : nullptr;
+    }
+
+    /**
+     * @brief Clone the operator using its copy-constructor.
+     * @see Operator::Transpose_Op
+     */
+    std::shared_ptr<Operator> clone() const override {
+        return std::make_shared<Transpose_Op<DIM>>(*this);
+    }
+
+    void associateInput(const IOIndex_t inputIdx, std::shared_ptr<Data> data) override final {
+        assert(inputIdx == 0 && "Transpose 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()) {
+            auto attr = (this)->getStaticAttributes();
+            const std::array<DimSize_t, DIM>& outDimsOrder = static_cast<const std::array<DimSize_t, DIM>&>(std::get<0>(attr));
+            std::vector<DimSize_t> outputDims;
+            for (std::size_t i = 0; i < DIM; ++i) {
+                outputDims.push_back(mInput->dims()[outDimsOrder[i]]);
+            }
+            mOutput->resize(outputDims);
+        }
+    }
+
+    bool outputDimsForwarded() const override final { return !(mOutput->empty()); }
+
+
+    inline Tensor& input(const IOIndex_t /*inputIdx*/) const override final { return *(mInput.get()); }
+    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((inputIdx == 0)  && "Transpose Operators supports only 1 input");
+        (void) inputIdx; // avoid unused warning
+        return mInput;
+    }
+    inline std::shared_ptr<Tensor> getOutput(const IOIndex_t outputIdx) const override final {
+        assert((outputIdx == 0) && "Transpose 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((inputIdx == 0) && "Transpose Operator supports only 1 input");
+        return std::static_pointer_cast<Data>(mInput);
+    }
+    std::shared_ptr<Data> getRawOutput(const IOIndex_t outputIdx) const override final {
+        assert((outputIdx == 0) && "Transpose operator supports only 1 output");
+        (void) outputIdx; // avoid unused warning
+        return std::static_pointer_cast<Data>(mOutput);
+    }
+
+
+
+    void setBackend(const std::string &name) override {
+        mImpl = Registrar<Transpose_Op<DIM>>::create(name)(*this);
+        mOutput->setBackend(name);
+
+        // FIXME: temporary workaround
+        mInput->setBackend(name);
+    }
+
+    void setDatatype(const DataType &datatype) override {
+        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; }
+    static const std::vector<std::string> getInputsName(){
+        return {"data_input"};
+    }
+    static const std::vector<std::string> getOutputsName(){
+        return {"data_output"};
+    }
+};
+
+template <std::array<DimSize_t, 1>::size_type DIM>
+inline std::shared_ptr<Node> Transpose(const std::array<DimSize_t, DIM> &output_dims_order,
+                                           const std::string& name = "") {
+    // FIXME: properly handle default w&b initialization in every cases
+    static_assert(DIM<=MaxDim,"Too many kernel dimensions required by Transpose, not supported");
+    return std::make_shared<Node>(std::make_shared<Transpose_Op<static_cast<DimIdx_t>(DIM)>>(output_dims_order), name);
+}
+
+// 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> Transpose(
+    DimSize_t const (&output_dims_order)[DIM],
+    const std::string& name = "") {
+    static_assert(DIM<=MaxDim,"Too many kernel dimensions required by Transpose, not supported");
+    return Transpose(to_array(output_dims_order), name);
+}
+}  // namespace Aidge
+
+namespace {
+template <>
+const char *const EnumStrings<Aidge::TransposeAttr>::data[] = {"OutputDimsOrder"};
+}
+
+#endif /* AIDGE_CORE_OPERATOR_TRANSPOSE_H_ */

python_binding/operator/pybind_Transpose.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 <pybind11/pybind11.h>
+#include <pybind11/stl.h>
+
+#include <string>
+#include <vector>
+#include <array>
+
+#include "aidge/backend/OperatorImpl.hpp"
+#include "aidge/operator/Transpose.hpp"
+#include "aidge/operator/Operator.hpp"
+#include "aidge/utils/Types.h"
+#include "aidge/data/Tensor.hpp"
+
+namespace py = pybind11;
+namespace Aidge {
+
+template <DimIdx_t DIM> 
+void init_Transpose(py::module &m) {
+  py::class_<Transpose_Op<DIM>, std::shared_ptr<Transpose_Op<DIM>>, Operator, Attributes>(
+    m, ("TransposeOp" + std::to_string(DIM) + "D").c_str(), py::multiple_inheritance())
+  .def("get_inputs_name", &Transpose_Op<DIM>::getInputsName)
+  .def("get_outputs_name", &Transpose_Op<DIM>::getOutputsName);
+
+  m.def(("Transpose" + std::to_string(DIM) + "D").c_str(), [](const std::vector<DimSize_t>& output_dims_order,
+                                                                  const std::string& name) {
+        AIDGE_ASSERT(output_dims_order.size() == DIM, "output_dims_order size [%ld] does not match DIM [%d]", output_dims_order.size(), DIM);
+        return Transpose<DIM>(to_array<DIM>(output_dims_order.begin()), name);
+    }, py::arg("output_dims_order"),
+       py::arg("name") = "");
+
+}
+
+} // namespace Aidge