IVGCVSW-3993 Add frontend and reference workload for ComparisonLayer

* Added frontend for ComparisonLayer
* Added RefComparisonWorkload
* Deprecated and removed Equal and Greater layers and workloads
* Updated tests to ensure backward compatibility

Signed-off-by: Aron Virginas-Tar <Aron.Virginas-Tar@arm.com>
Change-Id: Id50c880be1b567c531efff919c0c366d0a71cbe9

1 files changed, 103 insertions, 0 deletions

diff --git a/src/backends/backendsCommon/test/ComparisonEndToEndTestImpl.hpp b/src/backends/backendsCommon/test/ComparisonEndToEndTestImpl.hpp
new file mode 100644
index 0000000000..dc53b7b246
--- /dev/null
+++ b/src/backends/backendsCommon/test/ComparisonEndToEndTestImpl.hpp
@@ -0,0 +1,103 @@
+//
+// Copyright © 2017 Arm Ltd. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+#pragma once
+
+#include "CommonTestUtils.hpp"
+
+#include <ResolveType.hpp>
+
+#include <armnn/INetwork.hpp>
+
+#include <boost/test/unit_test.hpp>
+
+#include <vector>
+
+namespace
+{
+
+template<armnn::DataType ArmnnTypeInput>
+INetworkPtr CreateComparisonNetwork(const std::vector<TensorShape>& inputShapes,
+                                    const TensorShape& outputShape,
+                                    ComparisonOperation operation,
+                                    const float qScale = 1.0f,
+                                    const int32_t qOffset = 0)
+{
+    using namespace armnn;
+
+    INetworkPtr net(INetwork::Create());
+
+    ComparisonDescriptor descriptor(operation);
+    IConnectableLayer* comparisonLayer = net->AddComparisonLayer(descriptor, "comparison");
+
+    for (unsigned int i = 0; i < inputShapes.size(); ++i)
+    {
+        TensorInfo inputTensorInfo(inputShapes[i], ArmnnTypeInput, qScale, qOffset);
+        IConnectableLayer* input = net->AddInputLayer(boost::numeric_cast<LayerBindingId>(i));
+        Connect(input, comparisonLayer, inputTensorInfo, 0, i);
+    }
+
+    TensorInfo outputTensorInfo(outputShape, DataType::Boolean, qScale, qOffset);
+    IConnectableLayer* output = net->AddOutputLayer(0, "output");
+    Connect(comparisonLayer, output, outputTensorInfo, 0, 0);
+
+    return net;
+}
+
+template<armnn::DataType ArmnnInType,
+         typename TInput = armnn::ResolveType<ArmnnInType>>
+void ComparisonSimpleEndToEnd(const std::vector<BackendId>& backends,
+                              ComparisonOperation operation,
+                              const std::vector<uint8_t> expectedOutput)
+{
+    using namespace armnn;
+
+    const std::vector<TensorShape> inputShapes{{ 2, 2, 2, 2 }, { 2, 2, 2, 2 }};
+    const TensorShape& outputShape = { 2, 2, 2, 2 };
+
+    // Builds up the structure of the network
+    INetworkPtr net = CreateComparisonNetwork<ArmnnInType>(inputShapes, outputShape, operation);
+
+    BOOST_TEST_CHECKPOINT("create a network");
+
+    const std::vector<TInput> input0({ 1, 1, 1, 1,  5, 5, 5, 5,
+                                       3, 3, 3, 3,  4, 4, 4, 4 });
+
+    const std::vector<TInput> input1({ 1, 1, 1, 1,  3, 3, 3, 3,
+                                       5, 5, 5, 5,  4, 4, 4, 4 });
+
+    std::map<int, std::vector<TInput>>  inputTensorData    = {{ 0, input0 }, { 1, input1 }};
+    std::map<int, std::vector<uint8_t>> expectedOutputData = {{ 0, expectedOutput }};
+
+    EndToEndLayerTestImpl<ArmnnInType, DataType::Boolean>(move(net), inputTensorData, expectedOutputData, backends);
+}
+
+template<armnn::DataType ArmnnInType,
+         typename TInput = armnn::ResolveType<ArmnnInType>>
+void ComparisonBroadcastEndToEnd(const std::vector<BackendId>& backends,
+                                 ComparisonOperation operation,
+                                 const std::vector<uint8_t> expectedOutput)
+{
+    using namespace armnn;
+
+    const std::vector<TensorShape> inputShapes{{ 1, 2, 2, 3 }, { 1, 1, 1, 3 }};
+    const TensorShape& outputShape = { 1, 2, 2, 3 };
+
+    // Builds up the structure of the network
+    INetworkPtr net = CreateComparisonNetwork<ArmnnInType>(inputShapes, outputShape, operation);
+
+    BOOST_TEST_CHECKPOINT("create a network");
+
+    const std::vector<TInput> input0({ 1, 2, 3, 1, 0, 6,
+                                       7, 8, 9, 10, 11, 12 });
+
+    const std::vector<TInput> input1({ 1, 1, 3 });
+
+    std::map<int, std::vector<TInput>>  inputTensorData    = {{ 0, input0 }, { 1, input1 }};
+    std::map<int, std::vector<uint8_t>> expectedOutputData = {{ 0, expectedOutput }};
+
+    EndToEndLayerTestImpl<ArmnnInType, DataType::Boolean>(move(net), inputTensorData, expectedOutputData, backends);
+}
+
+} // anonymous namespace