IVGCVSW-7883 Front end and reference implementation for TILE

Signed-off-by: Teresa Charlin <teresa.charlinreyes@arm.com>
Signed-off-by: Cian McGriskin <cian.mcgriskin@arm.com>

Change-Id: I0afb2403fee11c5c1e58ea65e2525e99594d8f2d

1 files changed, 71 insertions, 0 deletions

diff --git a/src/armnn/layers/TileLayer.cpp b/src/armnn/layers/TileLayer.cpp
new file mode 100644
index 0000000000..3c313905fe
--- /dev/null
+++ b/src/armnn/layers/TileLayer.cpp
@@ -0,0 +1,71 @@
+//
+// Copyright © 2023 Arm Ltd and Contributors. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+
+#include "TileLayer.hpp"
+
+#include <armnn/backends/WorkloadFactory.hpp>
+#include "layers/LayerCloneBase.hpp"
+
+namespace armnn
+{
+TileLayer::TileLayer(const TileDescriptor &param, const char *name)
+    : LayerWithParameters(1, 1, LayerType::Tile, param, name)
+{}
+
+std::unique_ptr<IWorkload> TileLayer::CreateWorkload(const IWorkloadFactory &factory) const
+{
+    TileQueueDescriptor descriptor;
+    SetAdditionalInfo(descriptor);
+
+    return factory.CreateWorkload(LayerType::Tile, descriptor, PrepInfoAndDesc(descriptor));
+}
+
+TileLayer* TileLayer::Clone(armnn::Graph &graph) const
+{
+    auto layer = CloneBase<TileLayer>(graph, m_Param, GetName());
+
+    return std::move(layer);
+}
+
+std::vector<TensorShape> TileLayer::InferOutputShapes(const std::vector<TensorShape>& inputShapes) const
+{
+    ARMNN_ASSERT(inputShapes.size() == 1);
+    const TensorShape& inputShape = inputShapes[0];
+    const std::vector<uint32_t> multipleShape = m_Param.m_Multiples;
+
+    std::vector<unsigned int> dimSizes;
+
+    // Check input shape and multiples have same length and multiply them together to get output shape
+    if(inputShape.GetNumDimensions() == multipleShape.size())
+    {
+        for(uint32_t i = 0; i < inputShape.GetNumDimensions(); ++i)
+        {
+            dimSizes.insert(dimSizes.begin(), inputShape[i] * multipleShape[i]);
+        }
+    }
+    else
+    {
+        throw LayerValidationException("TileLayer: input rank and length of multiples are different.");
+    }
+
+    return std::vector<TensorShape>({TensorShape({inputShape.GetNumElements(), dimSizes.data()})});
+}
+
+void TileLayer::ValidateTensorShapesFromInputs()
+{
+    VerifyLayerConnections(1, CHECK_LOCATION());
+
+    const TensorShape& outputShape = GetOutputSlot(0).GetTensorInfo().GetShape();
+
+    VerifyShapeInferenceType(outputShape, m_ShapeInferenceMethod);
+
+    auto inferredShapes = InferOutputShapes({ GetInputSlot(0).GetTensorInfo().GetShape() });
+
+    ARMNN_ASSERT(inferredShapes.size() == 1);
+
+    ValidateAndCopyShape(outputShape, inferredShapes[0], m_ShapeInferenceMethod, "TileLayer");
+}
+
+}
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