From a9075df5b704e4f4432bf26027e3ba671d4596f0 Mon Sep 17 00:00:00 2001
From: Teresa Charlin <teresa.charlinreyes@arm.com>
Date: Thu, 27 Jun 2019 15:41:57 +0100
Subject: IVGCVSW-3363 Add frontend support for Resize Layer

Signed-off-by: Teresa Charlin <teresa.charlinreyes@arm.com>
Change-Id: I63493ddb7598515773073deb6db2eb3a635c5dfe
---
 src/armnn/layers/ResizeLayer.cpp | 76 ++++++++++++++++++++++++++++++++++++++++
 1 file changed, 76 insertions(+)
 create mode 100644 src/armnn/layers/ResizeLayer.cpp

(limited to 'src/armnn/layers/ResizeLayer.cpp')

diff --git a/src/armnn/layers/ResizeLayer.cpp b/src/armnn/layers/ResizeLayer.cpp
new file mode 100644
index 0000000000..44b4d9df5f
--- /dev/null
+++ b/src/armnn/layers/ResizeLayer.cpp
@@ -0,0 +1,76 @@
+//
+// Copyright © 2017 Arm Ltd. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+#include "ResizeLayer.hpp"
+
+#include "LayerCloneBase.hpp"
+
+#include <armnn/TypesUtils.hpp>
+
+#include <backendsCommon/WorkloadData.hpp>
+#include <backendsCommon/WorkloadFactory.hpp>
+
+#include <DataLayoutIndexed.hpp>
+
+using namespace armnnUtils;
+
+namespace armnn
+{
+
+ResizeLayer::ResizeLayer(const ResizeDescriptor& param, const char* name)
+    : LayerWithParameters(1, 1, LayerType::Resize, param, name)
+{
+}
+
+std::unique_ptr<IWorkload> ResizeLayer::CreateWorkload(const Graph& graph,
+                                                       const IWorkloadFactory& factory) const
+{
+    ResizeQueueDescriptor descriptor;
+    return factory.CreateResize(descriptor, PrepInfoAndDesc(descriptor, graph));
+}
+
+ResizeLayer* ResizeLayer::Clone(Graph& graph) const
+{
+    return CloneBase<ResizeLayer>(graph, m_Param, GetName());
+}
+
+std::vector<TensorShape> ResizeLayer::InferOutputShapes(const std::vector<TensorShape>& inputShapes) const
+{
+    BOOST_ASSERT(inputShapes.size() == 1);
+
+    const TensorShape& inputShape = inputShapes[0];
+    const DataLayoutIndexed dimensionIndices = m_Param.m_DataLayout;
+
+    unsigned int outWidth = m_Param.m_TargetWidth;
+    unsigned int outHeight = m_Param.m_TargetHeight;
+    unsigned int outChannels = inputShape[dimensionIndices.GetChannelsIndex()];
+    unsigned int outBatch = inputShape[0];
+
+    TensorShape tensorShape = m_Param.m_DataLayout == armnn::DataLayout::NHWC ?
+        TensorShape( { outBatch, outHeight, outWidth, outChannels } ) :
+        TensorShape( { outBatch, outChannels, outHeight, outWidth });
+
+    return std::vector<TensorShape>({ tensorShape });
+}
+
+void ResizeLayer::ValidateTensorShapesFromInputs()
+{
+    VerifyLayerConnections(1, CHECK_LOCATION());
+
+    auto inferredShapes = InferOutputShapes({ GetInputSlot(0).GetConnection()->GetTensorInfo().GetShape() });
+
+    BOOST_ASSERT(inferredShapes.size() == 1);
+
+    ConditionalThrowIfNotEqual<LayerValidationException>(
+        "ResizeLayer: TensorShape set on OutputSlot[0] does not match the inferred shape.",
+        GetOutputSlot(0).GetTensorInfo().GetShape(),
+        inferredShapes[0]);
+}
+
+void ResizeLayer::Accept(ILayerVisitor& visitor) const
+{
+    visitor.VisitResizeLayer(this, GetParameters(), GetName());
+}
+
+} // namespace armnn
-- 
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