4 files changed, 161 insertions, 0 deletions
diff --git a/src/backends/backendsCommon/test/CMakeLists.txt b/src/backends/backendsCommon/test/CMakeLists.txt
index 47d52312b6..bc190dd818 100644
--- a/src/backends/backendsCommon/test/CMakeLists.txt
+++ b/src/backends/backendsCommon/test/CMakeLists.txt
@@ -34,6 +34,7 @@ list(APPEND armnnBackendsCommonUnitTests_sources
     PermuteTestImpl.hpp
     Pooling2dTestImpl.hpp
     QuantizeHelper.hpp
+    QuantizeTestImpl.hpp
     ReshapeTestImpl.hpp
     RuntimeTestImpl.hpp
     SoftmaxTestImpl.hpp
diff --git a/src/backends/backendsCommon/test/LayerTests.cpp b/src/backends/backendsCommon/test/LayerTests.cpp
index be1d43541c..e8fb84f534 100644
--- a/src/backends/backendsCommon/test/LayerTests.cpp
+++ b/src/backends/backendsCommon/test/LayerTests.cpp
@@ -44,6 +44,7 @@
 #include "ConvertFp32ToFp16TestImpl.hpp"
 #include "DebugTestImpl.hpp"
 #include "DequantizeTestImpl.hpp"
+#include "QuantizeTestImpl.hpp"
 
 // 3-channel 16x8 image used as common input data for a number of Conv2d tests.
 static std::vector<float> ConvInput3x8x16({
@@ -8977,3 +8978,24 @@ LayerTestResult<float, 4> DequantizeUint8Test(
 {
     return DequantizeSimpleTest<armnn::DataType::QuantisedAsymm8>(workloadFactory, memoryManager);
 }
+
+LayerTestResult<uint8_t, 4> QuantizeSimpleUint8Test(
+    armnn::IWorkloadFactory& workloadFactory,
+    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
+{
+    return QuantizeSimpleTest<armnn::DataType::QuantisedAsymm8>(workloadFactory, memoryManager);
+}
+
+LayerTestResult<uint8_t, 4> QuantizeClampUint8Test(
+    armnn::IWorkloadFactory& workloadFactory,
+    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
+{
+    return QuantizeClampTest<armnn::DataType::QuantisedAsymm8>(workloadFactory, memoryManager);
+}
+
+LayerTestResult<int16_t, 4> QuantizeClampInt16Test(
+    armnn::IWorkloadFactory& workloadFactory,
+    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
+{
+    return QuantizeClampTest<armnn::DataType::QuantisedSymm16>(workloadFactory, memoryManager);
+}
diff --git a/src/backends/backendsCommon/test/LayerTests.hpp b/src/backends/backendsCommon/test/LayerTests.hpp
index c14ba7b35f..b9f73a4717 100644
--- a/src/backends/backendsCommon/test/LayerTests.hpp
+++ b/src/backends/backendsCommon/test/LayerTests.hpp
@@ -1443,3 +1443,15 @@ LayerTestResult<uint8_t, 4> GatherMultiDimParamsMultiDimIndicesUint8Test(
 LayerTestResult<float, 4> DequantizeUint8Test(
     armnn::IWorkloadFactory& workloadFactory,
     const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
+
+LayerTestResult<uint8_t, 4> QuantizeSimpleUint8Test(
+    armnn::IWorkloadFactory& workloadFactory,
+    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
+
+LayerTestResult<uint8_t, 4> QuantizeClampUint8Test(
+    armnn::IWorkloadFactory& workloadFactory,
+    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
+
+LayerTestResult<int16_t, 4> QuantizeClampInt16Test(
+    armnn::IWorkloadFactory& workloadFactory,
+    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
diff --git a/src/backends/backendsCommon/test/QuantizeTestImpl.hpp b/src/backends/backendsCommon/test/QuantizeTestImpl.hpp
new file mode 100644
index 0000000000..fee68f073e
--- /dev/null
+++ b/src/backends/backendsCommon/test/QuantizeTestImpl.hpp
@@ -0,0 +1,126 @@
+//
+// Copyright © 2017 Arm Ltd. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+#pragma once
+
+#include "WorkloadTestUtils.hpp"
+
+#include <test/TensorHelpers.hpp>
+
+#include <armnn/ArmNN.hpp>
+#include <armnn/Tensor.hpp>
+#include <armnn/TypesUtils.hpp>
+
+#include <backendsCommon/CpuTensorHandle.hpp>
+#include <backendsCommon/IBackendInternal.hpp>
+#include <backendsCommon/WorkloadFactory.hpp>
+
+
+namespace
+{
+
+template<typename T, std::size_t Dim>
+LayerTestResult<T, Dim> QuantizeTestImpl(
+    armnn::IWorkloadFactory& workloadFactory,
+    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
+    const armnn::TensorInfo& inputTensorInfo,
+    const armnn::TensorInfo& outputTensorInfo,
+    const std::vector<float>& inputData,
+    const std::vector<T>& expectedOutputData,
+    armnn::QuantizeQueueDescriptor descriptor)
+{
+    boost::multi_array<float, Dim> input = MakeTensor<float, Dim>(inputTensorInfo, inputData);
+
+    LayerTestResult<T, Dim> ret(outputTensorInfo);
+    ret.outputExpected = MakeTensor<T, Dim>(outputTensorInfo, expectedOutputData);
+
+    std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo);
+    std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo);
+
+    armnn::WorkloadInfo info;
+    AddInputToWorkload(descriptor, info, inputTensorInfo, inputHandle.get());
+    AddOutputToWorkload(descriptor, info, outputTensorInfo, outputHandle.get());
+
+    std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateQuantize(descriptor, info);
+
+    inputHandle->Allocate();
+    outputHandle->Allocate();
+
+    CopyDataToITensorHandle(inputHandle.get(), input.data());
+
+    ExecuteWorkload(*workload, memoryManager);
+
+    CopyDataFromITensorHandle(ret.output.data(), outputHandle.get());
+
+    return ret;
+}
+
+template <armnn::DataType ArmnnOutputType, typename T = armnn::ResolveType<ArmnnOutputType>>
+LayerTestResult<T, 4> QuantizeSimpleTest(
+    armnn::IWorkloadFactory& workloadFactory,
+    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
+{
+    armnn::QuantizeQueueDescriptor desc;
+
+    const armnn::TensorInfo inputTensorInfo({1, 2, 2, 3}, armnn::DataType::Float32);
+    const armnn::TensorInfo outputTensorInfo({1, 2, 2, 3}, ArmnnOutputType, 0.5f, 1);
+
+    std::vector<float> inputData = 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,
+    });
+
+    std::vector<T> expectedOutputData = std::vector<T>(
+    {
+         3,  5,  7,
+         9, 11, 13,
+        15, 17, 19,
+        21, 23, 25,
+    });
+
+    return QuantizeTestImpl<T, 4>(workloadFactory,
+                                  memoryManager,
+                                  inputTensorInfo,
+                                  outputTensorInfo,
+                                  inputData,
+                                  expectedOutputData,
+                                  desc);
+}
+
+template <armnn::DataType ArmnnOutputType, typename T = armnn::ResolveType<ArmnnOutputType>>
+LayerTestResult<T, 4> QuantizeClampTest(
+    armnn::IWorkloadFactory& workloadFactory,
+    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
+{
+    armnn::QuantizeQueueDescriptor desc;
+
+    const armnn::TensorInfo inputTensorInfo({1, 1, 2, 1}, armnn::DataType::Float32);
+    const armnn::TensorInfo outputTensorInfo({1, 1, 2, 1}, ArmnnOutputType, 0.0001f, 0);
+
+    const T max = std::numeric_limits<T>::max();
+    const T min = std::numeric_limits<T>::lowest();
+
+    std::vector<float> inputData = std::vector<float>(
+    {
+        -100.0f, 100.0f
+    });
+
+    std::vector<T> expectedOutputData = std::vector<T>(
+    {
+        min, max
+    });
+
+    return QuantizeTestImpl<T, 4>(workloadFactory,
+                                  memoryManager,
+                                  inputTensorInfo,
+                                  outputTensorInfo,
+                                  inputData,
+                                  expectedOutputData,
+                                  desc);
+}
+
+} // anonymous namespace