From 76615a5edd55b890acdd5fb078d9242e1e719a45 Mon Sep 17 00:00:00 2001
From: Sadik Armagan <sadik.armagan@arm.com>
Date: Tue, 4 Aug 2020 14:01:05 +0100
Subject: IVGCVSW-5108 Allow Concat to use subtensor on x and y

* Updated ConcatLayer to allow using subtensors on x/y if padding is not required

Signed-off-by: Sadik Armagan <sadik.armagan@arm.com>
Change-Id: I46a8fb9f17b976b76e069bb82614b6628a206717
---
 src/backends/neon/NeonTensorHandleFactory.cpp    | 11 ----
 src/backends/neon/test/NeonTensorHandleTests.cpp | 83 ++++++++++++++++++++++++
 2 files changed, 83 insertions(+), 11 deletions(-)

(limited to 'src/backends/neon')

diff --git a/src/backends/neon/NeonTensorHandleFactory.cpp b/src/backends/neon/NeonTensorHandleFactory.cpp
index 4e013a37a1..53d5a04b32 100644
--- a/src/backends/neon/NeonTensorHandleFactory.cpp
+++ b/src/backends/neon/NeonTensorHandleFactory.cpp
@@ -34,17 +34,6 @@ std::unique_ptr<ITensorHandle> NeonTensorHandleFactory::CreateSubTensorHandle(IT
 
     const arm_compute::TensorShape parentShape = armcomputetensorutils::BuildArmComputeTensorShape(parent.GetShape());
 
-    // In order for ACL to support subtensors the concat axis cannot be on x or y and the values of x and y
-    // must match the parent shapes
-    if (coords.x() != 0 || coords.y() != 0)
-    {
-        return nullptr;
-    }
-    if ((parentShape.x() != shape.x()) || (parentShape.y() != shape.y()))
-    {
-        return nullptr;
-    }
-
     if (!::arm_compute::error_on_invalid_subtensor(__func__, __FILE__, __LINE__, parentShape, coords, shape))
     {
         return nullptr;
diff --git a/src/backends/neon/test/NeonTensorHandleTests.cpp b/src/backends/neon/test/NeonTensorHandleTests.cpp
index fe5e8f9fb3..8b3e3fdc99 100644
--- a/src/backends/neon/test/NeonTensorHandleTests.cpp
+++ b/src/backends/neon/test/NeonTensorHandleTests.cpp
@@ -2,9 +2,17 @@
 // Copyright © 2020 Arm Ltd and Contributors. All rights reserved.
 // SPDX-License-Identifier: MIT
 //
+
+#include <Graph.hpp>
+#include <Network.hpp>
+
 #include <neon/NeonTensorHandle.hpp>
 #include <neon/NeonTensorHandleFactory.hpp>
 
+#include <armnn/utility/PolymorphicDowncast.hpp>
+
+#include <test/GraphUtils.hpp>
+
 #include <boost/test/unit_test.hpp>
 
 BOOST_AUTO_TEST_SUITE(NeonTensorHandleTests)
@@ -77,4 +85,79 @@ BOOST_AUTO_TEST_CASE(NeonTensorHandleGetCapabilitiesPadding)
     BOOST_TEST(capabilities[0].m_Value);
 }
 
+BOOST_AUTO_TEST_CASE(ConcatOnXorYSubTensorsNoPaddinRequiredTest)
+{
+    armnn::INetworkPtr net(armnn::INetwork::Create());
+
+    // Set up tensor infos
+    const armnn::TensorInfo inputInfo = armnn::TensorInfo({2, 3, 2, 2}, armnn::DataType::Float32);
+    const armnn::TensorInfo intermediateInfo = armnn::TensorInfo({2, 3, 2, 2}, armnn::DataType::Float32);
+    const armnn::TensorInfo outputInfo = armnn::TensorInfo({2, 3, 4, 2}, armnn::DataType::Float32);
+
+    armnn::ElementwiseUnaryDescriptor descriptor(armnn::UnaryOperation::Abs);
+
+    // Create the network
+    armnn::IConnectableLayer* const input0Layer = net->AddInputLayer(0, "input_0");
+    input0Layer->GetOutputSlot(0).SetTensorInfo(inputInfo);
+    armnn::IConnectableLayer* elementwiseUnaryLayer0 = net->AddElementwiseUnaryLayer(descriptor, "elementwiseUnary_0");
+    elementwiseUnaryLayer0->GetOutputSlot(0).SetTensorInfo(intermediateInfo);
+    input0Layer->GetOutputSlot(0).Connect(elementwiseUnaryLayer0->GetInputSlot(0));
+
+    armnn::IConnectableLayer* const input1Layer = net->AddInputLayer(1, "input_1");
+    input1Layer->GetOutputSlot(0).SetTensorInfo(inputInfo);
+    armnn::IConnectableLayer* elementwiseUnaryLayer1 = net->AddElementwiseUnaryLayer(descriptor, "elementwiseUnary_1");
+    elementwiseUnaryLayer1->GetOutputSlot(0).SetTensorInfo(intermediateInfo);
+    input1Layer->GetOutputSlot(0).Connect(elementwiseUnaryLayer1->GetInputSlot(0));
+
+    std::array<armnn::TensorShape, 2> concatInputShapes = { intermediateInfo.GetShape(), intermediateInfo.GetShape() };
+    armnn::IConnectableLayer* const concatLayer = net->AddConcatLayer(armnn::CreateDescriptorForConcatenation(
+        concatInputShapes.begin(), concatInputShapes.end(), 2), "concatenation");
+    concatLayer->GetOutputSlot(0).SetTensorInfo(outputInfo);
+    elementwiseUnaryLayer0->GetOutputSlot(0).Connect(concatLayer->GetInputSlot(0));
+    elementwiseUnaryLayer1->GetOutputSlot(0).Connect(concatLayer->GetInputSlot(1));
+
+    armnn::IConnectableLayer* const outputLayer = net->AddOutputLayer(0, "output");
+    concatLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0));
+
+    armnn::IRuntime::CreationOptions options;
+    armnn::IRuntimePtr runtime(armnn::IRuntime::Create(options));
+
+    std::vector<armnn::BackendId> backends = { armnn::Compute::CpuAcc };
+    armnn::IOptimizedNetworkPtr optimizedNet = armnn::Optimize(*net, backends, runtime->GetDeviceSpec());
+
+    const armnn::Graph& theGraph = static_cast<armnn::OptimizedNetwork*>(optimizedNet.get())->GetGraph();
+
+    // Load graph into runtime
+    armnn::NetworkId networkIdentifier;
+    runtime->LoadNetwork(networkIdentifier, std::move(optimizedNet));
+
+    // now check the concat how many sub-tensors it is using..
+    auto TraceSubTensorHandleAncestry = [](armnn::ITensorHandle* const subTensorHandle)
+    {
+        if (subTensorHandle && subTensorHandle->GetParent())
+        {
+            return true;
+        }
+        return false;
+    };
+
+    for (auto&& layer : theGraph)
+    {
+        if(layer->GetType() == armnn::LayerType::Concat)
+        {
+            unsigned int numberOfSubTensors = 0;
+            for (unsigned int i = 0; i < layer->GetNumInputSlots(); ++i)
+            {
+                const armnn::OutputSlot* slot = layer->GetInputSlot(i).GetConnectedOutputSlot();
+                if (TraceSubTensorHandleAncestry(slot->GetOutputHandler().GetData()))
+                {
+                    ++numberOfSubTensors;
+                }
+            }
+            // sub-tensors should be supported in this configuration
+            BOOST_CHECK(numberOfSubTensors > 0);
+        }
+    }
+}
+
 BOOST_AUTO_TEST_SUITE_END()
-- 
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