Merge branch 'feat_145_GridSample' into 'dev'

Add GridSample impl for 1D and 2D

See merge request eclipse/aidge/aidge_backend_cpu!77

include/aidge/backend/cpu/operator/GridSampleImpl.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_CPU_OPERATOR_GRIDSAMPLEIMPL_H_
+#define AIDGE_CPU_OPERATOR_GRIDSAMPLEIMPL_H_
+
+#include <array>
+#include <memory>
+#include <tuple>
+#include <vector>
+
+#include "aidge/backend/OperatorImpl.hpp"
+#include "aidge/operator/GridSample.hpp"
+#include "aidge/utils/Registrar.hpp"
+#include "aidge/utils/Types.h"
+#include "aidge/backend/cpu/data/GetCPUPtr.h"
+
+namespace Aidge {
+
+// compute kernel registry for forward and backward
+class GridSampleImpl1DForward_cpu
+    : public Registrable<GridSampleImpl1DForward_cpu,
+                         std::tuple<DataType, DataType>,
+                         void(const GridSample_Op&,
+                            const std::shared_ptr<Tensor>&,
+                            const std::shared_ptr<Tensor>&,
+                            const std::shared_ptr<Tensor>&)> {};
+
+class GridSampleImpl2DForward_cpu
+    : public Registrable<GridSampleImpl2DForward_cpu,
+                         std::tuple<DataType, DataType>,
+                         void(const GridSample_Op&,
+                            const std::shared_ptr<Tensor>&,
+                            const std::shared_ptr<Tensor>&,
+                            const std::shared_ptr<Tensor>&)> {};
+
+class GridSampleImpl_cpu : public OperatorImpl {
+   public:
+    GridSampleImpl_cpu(const GridSample_Op& op) : OperatorImpl(op, "cpu") {}
+
+    static std::unique_ptr<GridSampleImpl_cpu> create(const GridSample_Op &op) {
+        return std::make_unique<GridSampleImpl_cpu>(op);
+    }
+
+   public:
+    Elts_t getNbRequiredProtected(const IOIndex_t inputIdx) const override final;
+    void forward() override;
+};
+
+namespace {
+// add cpu backend to GridSample_Op<1> implementation registry
+static Registrar<GridSample_Op> registrarGridSampleImpl_cpu("cpu", Aidge::GridSampleImpl_cpu::create);
+}  // namespace
+
+}  // namespace Aidge
+
+#endif /* AIDGE_CPU_OPERATOR_GRIDSAMPLEIMPL_H_ */

src/operator/GridSampleImpl.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 "aidge/backend/cpu/operator/GridSampleImpl.hpp"
+
+#include <functional>
+#include <vector>
+
+#include "aidge/backend/cpu/data/GetCPUPtr.h"
+#include "aidge/backend/cpu/operator/GridSampleImpl_forward_kernels.hpp"
+#include "aidge/operator/GridSample.hpp"
+#include "aidge/utils/Types.h"
+
+Aidge::Elts_t Aidge::GridSampleImpl_cpu::getNbRequiredProtected(IOIndex_t /*inputIdx*/) const {
+    // this implementation can be in-place
+    return Elts_t::DataElts(0);
+}
+
+void Aidge::GridSampleImpl_cpu::forward() {
+    const auto& op_ = static_cast<const GridSample_Op&>(mOp);
+
+    // Find the correct kernel type
+    const auto outputDataType = op_.getOutput(0)->dataType();
+
+    const Registrar<GridSampleImpl1DForward_cpu>::registrar_key registrarKey = {
+        op_.getInput(0)->dataType(),
+        outputDataType};
+
+    std::function<void(const GridSample_Op&,
+                            const std::shared_ptr<Tensor>&,
+                            const std::shared_ptr<Tensor>&,
+                            const std::shared_ptr<Tensor>&)> kernelFunc;
+
+    const std::size_t nbSpatialFeat = op_.getInput(0)->nbDims();
+    switch (nbSpatialFeat)
+    {
+    case 1:
+        kernelFunc = Registrar<GridSampleImpl1DForward_cpu>::create(registrarKey);
+        break;
+    case 2:
+        kernelFunc = Registrar<GridSampleImpl2DForward_cpu>::create(registrarKey);
+        break;
+    default:
+        AIDGE_THROW_OR_ABORT(std::runtime_error, "No CPU {} kernel available for {} dimensions.", op_.type(), nbSpatialFeat);
+        break;
+    }
+
+    // Convert input data (no overhead if not needed!)
+    // TODO: right now, if needed, memory will be allocated/deallocated at each
+    // call to forward(). We might put the following shared_ptr as members of
+    // this class to avoid that.
+    std::shared_ptr<Tensor> input0Fallback, input1Fallback;
+    const auto& input0 = std::make_shared<Tensor>(op_.getInput(0)->refCastFrom(input0Fallback, *op_.getOutput(0)));
+    const auto& input1 = std::make_shared<Tensor>(op_.getInput(1)->refCastFrom(input1Fallback, *op_.getOutput(0)));
+
+    // Call kernel
+    kernelFunc(op_,
+            input0, // input
+            input1, // grid
+            op_.getOutput(0) // output
+            );
+}