1 files changed, 84 insertions, 0 deletions
diff --git a/src/armnn/layers/DepthToSpaceLayer.cpp b/src/armnn/layers/DepthToSpaceLayer.cpp
new file mode 100644
index 0000000000..e964c32865
--- /dev/null
+++ b/src/armnn/layers/DepthToSpaceLayer.cpp
@@ -0,0 +1,84 @@
+//
+// Copyright © 2019 Arm Ltd. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+
+#include "DepthToSpaceLayer.hpp"
+
+#include "LayerCloneBase.hpp"
+
+#include <armnn/TypesUtils.hpp>
+
+#include <backendsCommon/WorkloadData.hpp>
+#include <backendsCommon/WorkloadFactory.hpp>
+
+#include <DataLayoutIndexed.hpp>
+
+#include <numeric>
+
+namespace armnn
+{
+
+DepthToSpaceLayer::DepthToSpaceLayer(const DepthToSpaceDescriptor& param, const char* name)
+    : LayerWithParameters(1, 1, LayerType::DepthToSpace, param, name)
+{}
+
+std::unique_ptr<IWorkload> DepthToSpaceLayer::CreateWorkload(const Graph& graph,
+                                                             const IWorkloadFactory& factory) const
+{
+    DepthToSpaceQueueDescriptor descriptor;
+    descriptor.m_Parameters.m_BlockSize  = m_Param.m_BlockSize;
+    descriptor.m_Parameters.m_DataLayout = m_Param.m_DataLayout;
+
+    return factory.CreateDepthToSpace(descriptor, PrepInfoAndDesc(descriptor, graph));
+}
+
+DepthToSpaceLayer* DepthToSpaceLayer::Clone(Graph& graph) const
+{
+    return CloneBase<DepthToSpaceLayer>(graph, m_Param, GetName());
+}
+
+std::vector<TensorShape> DepthToSpaceLayer::InferOutputShapes(const std::vector<TensorShape>& inputShapes) const
+{
+    throw UnimplementedException("DepthToSpaceLayer::InferOutputShapes is not implemented");
+
+    BOOST_ASSERT(inputShapes.size() == 1);
+
+    TensorShape inputShape = inputShapes[0];
+    TensorShape outputShape(inputShape);
+
+    armnnUtils::DataLayoutIndexed dimensionIndices(m_Param.m_DataLayout);
+
+    unsigned int hIndex = dimensionIndices.GetHeightIndex();
+    unsigned int wIndex = dimensionIndices.GetWidthIndex();
+    unsigned int cIndex = dimensionIndices.GetChannelsIndex();
+
+    outputShape[hIndex] = inputShape[hIndex] * m_Param.m_BlockSize;
+    outputShape[wIndex] = inputShape[wIndex] * m_Param.m_BlockSize;
+
+    outputShape[cIndex] = inputShape[cIndex] / (m_Param.m_BlockSize * m_Param.m_BlockSize);
+
+    return std::vector<TensorShape>({ outputShape });
+}
+
+void DepthToSpaceLayer::ValidateTensorShapesFromInputs()
+{
+    VerifyLayerConnections(1, CHECK_LOCATION());
+
+    std::vector<TensorShape> inferredShapes = InferOutputShapes({
+        GetInputSlot(0).GetConnection()->GetTensorInfo().GetShape() });
+
+    BOOST_ASSERT(inferredShapes.size() == 1);
+
+    ConditionalThrowIfNotEqual<LayerValidationException>(
+        "DepthToSpaceLayer: TensorShape set on OutputSlot[0] does not match the inferred shape.",
+        GetOutputSlot(0).GetTensorInfo().GetShape(),
+        inferredShapes[0]);
+}
+
+void DepthToSpaceLayer::Accept(ILayerVisitor& visitor) const
+{
+    visitor.VisitDepthToSpaceLayer(this, GetParameters(), GetName());
+}
+
+} // namespace armnn