1 files changed, 0 insertions, 113 deletions
diff --git a/src/backends/backendsCommon/test/ArithmeticTestImpl.hpp b/src/backends/backendsCommon/test/ArithmeticTestImpl.hpp
deleted file mode 100644
index d0e85dd31d..0000000000
--- a/src/backends/backendsCommon/test/ArithmeticTestImpl.hpp
+++ /dev/null
@@ -1,113 +0,0 @@
-//
-// 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, armnn::DataType ArmnnTypeOutput>
-INetworkPtr CreateArithmeticNetwork(const std::vector<TensorShape>& inputShapes,
-                                    const TensorShape& outputShape,
-                                    const LayerType type,
-                                    const float qScale = 1.0f,
-                                    const int32_t qOffset = 0)
-{
-    using namespace armnn;
-
-    // Builds up the structure of the network.
-    INetworkPtr net(INetwork::Create());
-
-    IConnectableLayer* arithmeticLayer = nullptr;
-
-    switch(type){
-        case LayerType::Equal: arithmeticLayer = net->AddEqualLayer("equal"); break;
-        case LayerType::Greater: arithmeticLayer = net->AddGreaterLayer("greater"); break;
-        default: BOOST_TEST_FAIL("Non-Arithmetic layer type called.");
-    }
-
-    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, arithmeticLayer, inputTensorInfo, 0, i);
-    }
-
-    TensorInfo outputTensorInfo(outputShape, ArmnnTypeOutput, qScale, qOffset);
-    IConnectableLayer* output = net->AddOutputLayer(0, "output");
-    Connect(arithmeticLayer, output, outputTensorInfo, 0, 0);
-
-    return net;
-}
-
-template<armnn::DataType ArmnnInputType,
-         armnn::DataType ArmnnOutputType,
-         typename TInput = armnn::ResolveType<ArmnnInputType>,
-         typename TOutput = armnn::ResolveType<ArmnnOutputType>>
-void ArithmeticSimpleEndToEnd(const std::vector<BackendId>& backends,
-                              const LayerType type,
-                              const std::vector<TOutput> 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 = CreateArithmeticNetwork<ArmnnInputType, ArmnnOutputType>(inputShapes, outputShape, type);
-
-    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<TOutput>> expectedOutputData = {{ 0, expectedOutput }};
-
-    EndToEndLayerTestImpl<ArmnnInputType, ArmnnOutputType>(move(net), inputTensorData, expectedOutputData, backends);
-}
-
-template<armnn::DataType ArmnnInputType,
-         armnn::DataType ArmnnOutputType,
-         typename TInput = armnn::ResolveType<ArmnnInputType>,
-         typename TOutput = armnn::ResolveType<ArmnnOutputType>>
-void ArithmeticBroadcastEndToEnd(const std::vector<BackendId>& backends,
-                                 const LayerType type,
-                                 const std::vector<TOutput> 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 = CreateArithmeticNetwork<ArmnnInputType, ArmnnOutputType>(inputShapes, outputShape, type);
-
-    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<TOutput>> expectedOutputData = {{ 0, expectedOutput }};
-
-    EndToEndLayerTestImpl<ArmnnInputType, ArmnnOutputType>(move(net), inputTensorData, expectedOutputData, backends);
-}
-
-} // anonymous namespace