IVGCVSW-3418 Add Arm NN front end support for the new Stack layer

 * Added new StackLayer class
 * Made necessary changes to Descriptors, ILayerSupport, ILayerVisitor, etc.
 * Added unit tests

Signed-off-by: Matthew Jackson <matthew.jackson@arm.com>
Change-Id: Ieb97a928a342ffe1901c6058eb895711c358fd3d

1 files changed, 98 insertions, 0 deletions

diff --git a/src/armnn/layers/StackLayer.cpp b/src/armnn/layers/StackLayer.cpp
new file mode 100644
index 0000000000..59bc8d5a13
--- /dev/null
+++ b/src/armnn/layers/StackLayer.cpp
@@ -0,0 +1,98 @@
+//
+// Copyright © 2017 Arm Ltd. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+#include "StackLayer.hpp"
+#include "LayerCloneBase.hpp"
+
+#include <armnn/TypesUtils.hpp>
+#include <backendsCommon/WorkloadData.hpp>
+#include <backendsCommon/WorkloadFactory.hpp>
+
+#include <queue>
+
+namespace armnn
+{
+
+StackLayer::StackLayer(const StackDescriptor& param, const char* name)
+    : LayerWithParameters(param.m_NumInputs, 1, LayerType::Stack, param, name)
+{
+}
+
+std::unique_ptr<IWorkload> StackLayer::CreateWorkload(const Graph& graph, const IWorkloadFactory& factory) const
+{
+    StackQueueDescriptor descriptor;
+    return factory.CreateStack(descriptor, PrepInfoAndDesc(descriptor, graph));
+}
+
+StackLayer* StackLayer::Clone(Graph& graph) const
+{
+    return CloneBase<StackLayer>(graph, m_Param, GetName());
+}
+
+std::vector<TensorShape> StackLayer::InferOutputShapes(const std::vector<TensorShape>& inputShapes) const
+{
+    const TensorShape& inputShape = m_Param.m_InputShape;
+    const unsigned int inputNumDimensions = inputShape.GetNumDimensions();
+    const unsigned int axis = m_Param.m_Axis;
+
+    BOOST_ASSERT(axis <= inputNumDimensions);
+
+    unsigned int dimensionSizes[inputNumDimensions + 1];
+    for (unsigned int i = 0; i < axis; ++i)
+    {
+        dimensionSizes[i] = inputShape[i];
+    }
+
+    dimensionSizes[axis] = m_Param.m_NumInputs;
+
+    for (unsigned int i = axis + 1; i < inputNumDimensions + 1; ++i)
+    {
+        dimensionSizes[i] = inputShape[i-1];
+    }
+
+    TensorShape targetShape = TensorShape(inputNumDimensions + 1, dimensionSizes);
+
+    return std::vector<TensorShape>({ targetShape });
+}
+
+void StackLayer::ValidateTensorShapesFromInputs()
+{
+    // Validates Stack layer.
+    ConditionalThrowIfNotEqual<LayerValidationException>(
+        "StackLayer: Num Input Slots must match Num Inputs.",
+        m_Param.m_NumInputs,
+        GetNumInputSlots());
+
+    VerifyLayerConnections(m_Param.m_NumInputs, CHECK_LOCATION());
+
+    // Constructs and validates input shapes
+    std::vector<TensorShape> inputShapes;
+    for (unsigned int i = 0; i < GetNumInputSlots(); ++i)
+    {
+        TensorShape inputShape = GetInputSlot(i).GetConnection()->GetTensorInfo().GetShape();
+        if (inputShape != m_Param.m_InputShape)
+        {
+            throw LayerValidationException("ConcatLayer: TensorShape set on InputSlot[" +
+                                           std::to_string(i) +
+                                           "] does not match defined input shape");
+        }
+        inputShapes.push_back(inputShape);
+    }
+
+    auto inferredShapes = InferOutputShapes(inputShapes);
+
+    BOOST_ASSERT(inferredShapes.size() == 1);
+
+    ConditionalThrowIfNotEqual<LayerValidationException>(
+        "StackLayer: TensorShape set on OutputSlot[0] does not match the inferred shape.",
+        GetOutputSlot(0).GetTensorInfo().GetShape(),
+        inferredShapes[0]);
+}
+
+void StackLayer::Accept(ILayerVisitor& visitor) const
+{
+    visitor.VisitStackLayer(this, GetParameters(), GetName());
+}
+
+} // namespace armnn armnn