From 44740599570c420c67a773cfacf0bacb50548f82 Mon Sep 17 00:00:00 2001
From: hrouis <houssemeddine.rouis92@gmail.com>
Date: Wed, 15 Nov 2023 15:04:29 +0100
Subject: [PATCH] add ReduceMean operator
---
include/aidge/operator/ReduceMean.hpp | 194 ++++++++++++++++++
python_binding/operator/pybind_ReduceMean.cpp | 58 ++++++
2 files changed, 252 insertions(+)
create mode 100644 include/aidge/operator/ReduceMean.hpp
create mode 100644 python_binding/operator/pybind_ReduceMean.cpp
diff --git a/include/aidge/operator/ReduceMean.hpp b/include/aidge/operator/ReduceMean.hpp
new file mode 100644
index 000000000..31456f5d9
--- /dev/null
+++ b/include/aidge/operator/ReduceMean.hpp
@@ -0,0 +1,194 @@
+/********************************************************************************
+ * 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_REDUCEMEAN_H_
+#define AIDGE_CORE_OPERATOR_REDUCEMEAN_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 ReduceMeanAttr { Axes, KeepDims };
+
+template <DimIdx_t DIM>
+class ReduceMean_Op : public Operator,
+ public Registrable<ReduceMean_Op<DIM>, std::string, std::unique_ptr<OperatorImpl>(const ReduceMean_Op<DIM> &)>,
+ public StaticAttributes<ReduceMeanAttr, std::array<DimSize_t, DIM>, DimSize_t> {
+ 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 = "ReduceMean";
+
+ ReduceMean_Op() = delete;
+
+ using Attributes_ = StaticAttributes<ReduceMeanAttr, std::array<DimSize_t, DIM>, DimSize_t>;
+ template <ReduceMeanAttr e>
+ using attr = typename Attributes_::template attr<e>;
+
+ constexpr ReduceMean_Op(const std::array<DimSize_t, DIM> &axes, DimSize_t keep_dims)
+ : Operator(Type),
+ Attributes_(attr<ReduceMeanAttr::Axes>(axes),
+ attr<ReduceMeanAttr::KeepDims>(keep_dims)) {
+ 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.
+ */
+ ReduceMean_Op(const ReduceMean_Op<DIM>& op)
+ : Operator(Type),
+ Attributes_(op),
+ mOutput(std::make_shared<Tensor>(*op.mOutput))
+ {
+ // cpy-ctor
+ setDatatype(op.mOutput->dataType());
+ mImpl = op.mImpl ? Registrar<ReduceMean_Op<DIM>>::create(mOutput->getImpl()->backend())(*this) : nullptr;
+ }
+
+ /**
+ * @brief Clone the operator using its copy-constructor.
+ * @see Operator::ReduceMean_Op
+ */
+ std::shared_ptr<Operator> clone() const override {
+ return std::make_shared<ReduceMean_Op<DIM>>(*this);
+ }
+
+ void associateInput(const IOIndex_t inputIdx, std::shared_ptr<Data> data) override final {
+ assert(inputIdx == 0 && "ReduceMean 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()) {
+ std::vector<DimSize_t> outDims;
+ for(std::size_t d=0; d<mInput->dims().size(); ++d)
+ {
+ bool reducedDim = false;
+ for(std::size_t i=0; i<DIM; ++i)
+ {
+ if(this->template getAttr<ReduceMeanAttr::Axes>()[i] == d)
+ {
+ reducedDim = true;
+ break;
+ }
+ }
+ if(!reducedDim)
+ {
+ if(this->template getAttr<ReduceMeanAttr::KeepDims>())
+ outDims.push_back(1);
+ }
+ else
+ outDims.push_back(mInput->dims()[d]);
+ }
+ mOutput->resize(outDims);
+ }
+ }
+
+ 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 && "ReduceMean 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) && "ReduceMean 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 && "ReduceMean Operators supports only 1 input");
+ (void) inputIdx; // avoid unused warning
+ return std::static_pointer_cast<Data>(mInput);
+ }
+ std::shared_ptr<Data> getRawOutput(const IOIndex_t outputIdx) const override final {
+ assert(outputIdx == 0 && "ReduceMean 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<ReduceMean_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> ReduceMean(const std::array<DimSize_t, DIM> &axes,
+ DimSize_t keep_dims,
+ const std::string& name = "") {
+ // FIXME: properly handle default w&b initialization in every cases
+ static_assert(DIM<=MaxDim,"Too many kernel dimensions required by ReduceMean, not supported");
+ return std::make_shared<Node>(std::make_shared<ReduceMean_Op<static_cast<DimIdx_t>(DIM)>>(axes, keep_dims), 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> ReduceMean(
+ DimSize_t const (&axes)[DIM],
+ DimSize_t keep_dims = 1,
+ const std::string& name = "") {
+ static_assert(DIM<=MaxDim,"Too many kernel dimensions required by ReduceMean, not supported");
+ return ReduceMean(to_array(axes), keep_dims, name);
+}
+} // namespace Aidge
+
+namespace {
+template <>
+const char *const EnumStrings<Aidge::ReduceMeanAttr>::data[] = {"Axes", "KeepDims"};
+}
+
+#endif /* AIDGE_CORE_OPERATOR_REDUCEMEAN_H_ */
diff --git a/python_binding/operator/pybind_ReduceMean.cpp b/python_binding/operator/pybind_ReduceMean.cpp
new file mode 100644
index 000000000..3322de897
--- /dev/null
+++ b/python_binding/operator/pybind_ReduceMean.cpp
@@ -0,0 +1,58 @@
+// /********************************************************************************
+// * 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 <iostream>
+// #include <string>
+// #include <vector>
+// #include <array>
+
+// #include "aidge/backend/OperatorImpl.hpp"
+// #include "aidge/operator/ReduceMean.hpp"
+// #include "aidge/operator/Operator.hpp"
+// #include "aidge/utils/Types.h"
+
+// namespace py = pybind11;
+// namespace Aidge {
+
+// template <DimIdx_t DIM> void declare_ReduceMeanOp(py::module &m) {
+// py::class_<ReduceMean_Op<DIM>, std::shared_ptr<ReduceMean_Op<DIM>>, Operator, Attributes>(
+// m, ("ReduceMeanOp" + std::to_string(DIM) + "D").c_str(),
+// py::multiple_inheritance())
+// .def(py::init<const std::array<DimSize_t, DIM> &, DimSize_t>(),
+// py::arg("axes"),
+// py::arg("keep_dims"))
+// .def("get_inputs_name", &ReduceMean_Op<DIM>::getInputsName)
+// .def("get_outputs_name", &ReduceMean_Op<DIM>::getOutputsName)
+// ;
+
+// m.def(("ReduceMean" + std::to_string(DIM) + "D").c_str(), [](const std::vector<DimSize_t>& axes,
+// DimSize_t keepDims,
+// const std::string& name) {
+// AIDGE_ASSERT(axes.size() == DIM, "axes size [%ld] does not match DIM [%d]", axes.size(), DIM);
+
+// return ReduceMean<DIM>(to_array<DIM>(axes.begin()), keepDims, name);
+// }, py::arg("axes"),
+// py::arg("keep_dims") = 1);
+// }
+
+
+// void init_ReduceMean(py::module &m) {
+// declare_ReduceMeanOp<1>(m);
+// declare_ReduceMeanOp<2>(m);
+// declare_ReduceMeanOp<3>(m);
+
+// // FIXME:
+// // m.def("ReduceMean1D", static_cast<NodeAPI(*)(const char*, int, int, int const
+// // (&)[1])>(&ReduceMean));
+// }
+// } // namespace Aidge
--
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