1 files changed, 101 insertions, 0 deletions
diff --git a/src/backends/backendsCommon/test/DequantizeEndToEndTestImpl.hpp b/src/backends/backendsCommon/test/DequantizeEndToEndTestImpl.hpp
new file mode 100644
index 0000000000..e62415904c
--- /dev/null
+++ b/src/backends/backendsCommon/test/DequantizeEndToEndTestImpl.hpp
@@ -0,0 +1,101 @@
+//
+// Copyright © 2017 Arm Ltd. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+
+#pragma once
+
+#include "CommonTestUtils.hpp"
+
+#include <armnn/INetwork.hpp>
+#include <ResolveType.hpp>
+
+namespace
+{
+
+template<typename T>
+armnn::INetworkPtr CreateDequantizeNetwork(const armnn::TensorInfo& inputInfo,
+                                           const armnn::TensorInfo& outputInfo)
+{
+    armnn::INetworkPtr net(armnn::INetwork::Create());
+
+    armnn::IConnectableLayer* inputLayer = net->AddInputLayer(0);
+    armnn::IConnectableLayer* dequantizeLayer = net->AddDequantizeLayer("Dequantize");
+    armnn::IConnectableLayer* outputLayer = net->AddOutputLayer(0, "output");
+    Connect(inputLayer, dequantizeLayer, inputInfo, 0, 0);
+    Connect(dequantizeLayer, outputLayer, outputInfo, 0, 0);
+
+    return net;
+}
+
+template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
+void DequantizeEndToEndLayerTestImpl(const std::vector<BackendId>& backends,
+                                     const armnn::TensorShape& tensorShape,
+                                     const std::vector<T>& input,
+                                     const std::vector<float>& expectedOutput,
+                                     float scale,
+                                     int32_t offset)
+{
+    armnn::TensorInfo inputInfo(tensorShape, ArmnnType);
+    armnn::TensorInfo outputInfo(tensorShape, armnn::DataType::Float32);
+
+    inputInfo.SetQuantizationScale(scale);
+    inputInfo.SetQuantizationOffset(offset);
+
+    // Builds up the structure of the network
+    armnn::INetworkPtr net = CreateDequantizeNetwork<T>(inputInfo, outputInfo);
+
+    BOOST_TEST_CHECKPOINT("create a network");
+
+    std::map<int, std::vector<T>> inputTensorData = { { 0, input } };
+    std::map<int, std::vector<float>> expectedOutputData = { { 0, expectedOutput } };
+
+    EndToEndLayerTestImpl<ArmnnType, armnn::DataType::Float32>(
+            move(net), inputTensorData, expectedOutputData, backends);
+}
+
+template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
+void DequantizeEndToEndSimple(const std::vector<BackendId>& backends)
+{
+    const armnn::TensorShape tensorShape({ 1, 2, 2, 4 });
+    std::vector<T> inputData = std::vector<T>(
+    {
+        2, 4, 6, 8,
+        10, 12, 14, 16,
+        18, 20, 22, 24,
+        26, 28, 30, 32
+    });
+
+    std::vector<float> expectedOutputData = std::vector<float>(
+    {
+        1.0f, 2.0f, 3.0f, 4.0f,
+        5.0f, 6.0f, 7.0f,  8.0f,
+        9.0f, 10.0f, 11.0f, 12.0f,
+        13.0f, 14.0f, 15.0f, 16.0f
+    });
+    DequantizeEndToEndLayerTestImpl<ArmnnType>(backends, tensorShape, inputData, expectedOutputData, 0.5f, 0);
+};
+
+template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
+void DequantizeEndToEndOffset(const std::vector<BackendId>& backends)
+{
+    const armnn::TensorShape tensorShape({ 1, 2, 2, 4 });
+    std::vector<T> inputData = std::vector<T>(
+    {
+        3, 5, 7, 9,
+        11, 13, 15, 17,
+        19, 21, 23, 25,
+        27, 29, 31, 33
+    });
+
+    std::vector<float> expectedOutputData = std::vector<float>(
+    {
+        1.0f, 2.0f, 3.0f, 4.0f,
+        5.0f, 6.0f, 7.0f,  8.0f,
+        9.0f, 10.0f, 11.0f, 12.0f,
+        13.0f, 14.0f, 15.0f, 16.0f
+    });
+    DequantizeEndToEndLayerTestImpl<ArmnnType>(backends, tensorShape, inputData, expectedOutputData, 0.5f, 1);
+};
+
+} // anonymous namespace