1 files changed, 104 insertions, 0 deletions
diff --git a/src/armnn/layers/GatherNdLayer.cpp b/src/armnn/layers/GatherNdLayer.cpp
new file mode 100644
index 0000000000..1ca2cbbae3
--- /dev/null
+++ b/src/armnn/layers/GatherNdLayer.cpp
@@ -0,0 +1,104 @@
+//
+// Copyright © 2022 Arm Ltd and Contributors. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+
+#include "GatherNdLayer.hpp"
+#include "LayerCloneBase.hpp"
+
+#include <armnn/TypesUtils.hpp>
+#include <armnn/backends/WorkloadData.hpp>
+#include <armnn/backends/WorkloadFactory.hpp>
+
+namespace armnn
+{
+
+GatherNdLayer::GatherNdLayer(const char* name)
+    : Layer(2, 1, LayerType::GatherNd, name)
+{
+}
+
+std::unique_ptr<IWorkload> GatherNdLayer::CreateWorkload(const armnn::IWorkloadFactory& factory) const
+{
+    GatherNdQueueDescriptor descriptor;
+    SetAdditionalInfo(descriptor);
+
+    return factory.CreateWorkload(LayerType::GatherNd, descriptor, PrepInfoAndDesc(descriptor));
+}
+
+GatherNdLayer* GatherNdLayer::Clone(Graph& graph) const
+{
+    return CloneBase<GatherNdLayer>(graph, GetName());
+}
+
+std::vector<TensorShape> GatherNdLayer::InferOutputShapes(const std::vector<TensorShape>& inputShapes) const
+{
+    ARMNN_ASSERT(inputShapes.size() == 2);
+    const TensorShape& params = inputShapes[0];
+    const TensorShape& indices = inputShapes[1];
+
+    if (indices.GetDimensionality() == Dimensionality::Scalar && indices.GetNumDimensions() == 1)
+    {
+         return std::vector<TensorShape>({ TensorShape(Dimensionality::Scalar)});
+    }
+
+    const unsigned int paramsDim = params.GetNumDimensions();
+    const unsigned int indicesDim = indices.GetNumDimensions();
+
+    // last dimension of indices
+    unsigned int index_depth = indices[indicesDim - 1];
+    ARMNN_ASSERT(index_depth <= paramsDim);
+
+    // all but the last dimension of indices
+    std::vector<unsigned int> outer_shape;
+    outer_shape.reserve(indicesDim - 1);
+    for (unsigned int i = 0; i < indicesDim - 1; ++i)
+    {
+        outer_shape.emplace_back(indices[i]);
+    }
+
+    // elements after index_depth
+    std::vector<unsigned int> inner_shape;
+    inner_shape.reserve(paramsDim - index_depth);
+    for (unsigned int i = index_depth; i < paramsDim; ++i)
+    {
+        inner_shape.emplace_back(params[i]);
+    }
+
+    // concatenate outer_shape + inner_shape
+    std::vector<unsigned int> output_shape;
+    output_shape.reserve( outer_shape.size() + inner_shape.size() );
+    output_shape.insert( output_shape.end(), outer_shape.begin(), outer_shape.end() );
+    output_shape.insert( output_shape.end(), inner_shape.begin(), inner_shape.end() );
+
+    const auto outputDim = static_cast<unsigned int>(output_shape.size());
+    return std::vector<TensorShape>({ TensorShape({outputDim, output_shape.data()})});
+}
+
+void GatherNdLayer::ValidateTensorShapesFromInputs()
+{
+    VerifyLayerConnections(2, CHECK_LOCATION());
+
+    const TensorShape& outputShape = GetOutputSlot(0).GetTensorInfo().GetShape();
+
+    VerifyShapeInferenceType(outputShape, m_ShapeInferenceMethod);
+
+    std::vector<TensorShape> inferredShapes = InferOutputShapes(
+            {GetInputSlot(0).GetConnection()->GetTensorInfo().GetShape(),
+             GetInputSlot(1).GetConnection()->GetTensorInfo().GetShape()});
+    ARMNN_ASSERT(inferredShapes.size() == 1);
+    ARMNN_ASSERT(inferredShapes[0].GetDimensionality() == Dimensionality::Specified ||
+                 inferredShapes[0].GetDimensionality() == Dimensionality::Scalar);
+
+    ValidateAndCopyShape(outputShape, inferredShapes[0], m_ShapeInferenceMethod, "GatherNdLayer");
+}
+
+ARMNN_NO_DEPRECATE_WARN_BEGIN
+void GatherNdLayer::Accept(ILayerVisitor& visitor) const
+{
+    IgnoreUnused(visitor);
+    throw armnn::Exception("GatherNdLayer VisitGatherNdLayer is not implemented");
+}
+ARMNN_NO_DEPRECATE_WARN_END
+
+} // namespace armnn