IVGCVSW-2087 Reference implementation and unit tests for StridedSlice

Change-Id: Ifeacc0adb4547c72537b9ea7a61bf3c4ec3673fa

1 files changed, 429 insertions, 0 deletions

diff --git a/src/backends/backendsCommon/test/StridedSliceTestImpl.hpp b/src/backends/backendsCommon/test/StridedSliceTestImpl.hpp
new file mode 100644
index 0000000000..1633151108
--- /dev/null
+++ b/src/backends/backendsCommon/test/StridedSliceTestImpl.hpp
@@ -0,0 +1,429 @@
+//
+// Copyright © 2017 Arm Ltd. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+#pragma once
+
+#include "WorkloadTestUtils.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>
+
+#include <test/TensorHelpers.hpp>
+
+namespace
+{
+
+template<typename T, std::size_t InDim, std::size_t OutDim>
+LayerTestResult<T, OutDim> StridedSliceTestImpl(
+    armnn::IWorkloadFactory& workloadFactory,
+    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
+    armnn::TensorInfo& inputTensorInfo,
+    armnn::TensorInfo& outputTensorInfo,
+    std::vector<float>& inputData,
+    std::vector<float>& outputExpectedData,
+    armnn::StridedSliceQueueDescriptor descriptor,
+    const float qScale = 1.0f,
+    const int32_t qOffset = 0)
+{
+    if(armnn::IsQuantizedType<T>())
+    {
+        inputTensorInfo.SetQuantizationScale(qScale);
+        inputTensorInfo.SetQuantizationOffset(qOffset);
+
+        outputTensorInfo.SetQuantizationScale(qScale);
+        outputTensorInfo.SetQuantizationOffset(qOffset);
+    }
+
+    boost::multi_array<T, InDim> input =
+        MakeTensor<T, InDim>(inputTensorInfo, QuantizedVector<T>(qScale, qOffset, inputData));
+
+    LayerTestResult<T, OutDim> ret(outputTensorInfo);
+    ret.outputExpected =
+        MakeTensor<T, OutDim>(outputTensorInfo, QuantizedVector<T>(qScale, qOffset, outputExpectedData));
+
+    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.CreateStridedSlice(descriptor, info);
+
+    inputHandle->Allocate();
+    outputHandle->Allocate();
+
+    CopyDataToITensorHandle(inputHandle.get(), input.data());
+
+    ExecuteWorkload(*workload, memoryManager);
+
+    CopyDataFromITensorHandle(ret.output.data(), outputHandle.get());
+
+    return ret;
+}
+
+template <typename T>
+LayerTestResult<T, 4> StridedSlice4DTest(
+    armnn::IWorkloadFactory& workloadFactory,
+    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
+{
+    armnn::TensorInfo inputTensorInfo;
+    armnn::TensorInfo outputTensorInfo;
+
+    unsigned int inputShape[]  = {3, 2, 3, 1};
+    unsigned int outputShape[] = {1, 2, 3, 1};
+
+    armnn::StridedSliceQueueDescriptor desc;
+    desc.m_Parameters.m_Begin  = {1, 0, 0, 0};
+    desc.m_Parameters.m_End    = {2, 2, 3, 1};
+    desc.m_Parameters.m_Stride = {1, 1, 1, 1};
+
+    inputTensorInfo = armnn::TensorInfo(4, inputShape, armnn::GetDataType<T>());
+    outputTensorInfo = armnn::TensorInfo(4, outputShape, armnn::GetDataType<T>());
+
+    std::vector<float> input = std::vector<float>(
+    {
+        1.0f, 1.0f, 1.0f, 2.0f, 2.0f, 2.0f,
+
+        3.0f, 3.0f, 3.0f, 4.0f, 4.0f, 4.0f,
+
+        5.0f, 5.0f, 5.0f, 6.0f, 6.0f, 6.0f
+    });
+
+    std::vector<float> outputExpected = std::vector<float>(
+    {
+        3.0f, 3.0f, 3.0f, 4.0f, 4.0f, 4.0f
+    });
+
+    return StridedSliceTestImpl<T, 4, 4>(
+        workloadFactory, memoryManager, inputTensorInfo, outputTensorInfo, input, outputExpected, desc);
+}
+
+template <typename T>
+LayerTestResult<T, 4> StridedSlice4DReverseTest(
+    armnn::IWorkloadFactory& workloadFactory,
+    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
+{
+    armnn::TensorInfo inputTensorInfo;
+    armnn::TensorInfo outputTensorInfo;
+
+    unsigned int inputShape[]  = {3, 2, 3, 1};
+    unsigned int outputShape[] = {1, 2, 3, 1};
+
+    armnn::StridedSliceQueueDescriptor desc;
+    desc.m_Parameters.m_Begin  = {1, -1, 0, 0};
+    desc.m_Parameters.m_End    = {2, -3, 3, 1};
+    desc.m_Parameters.m_Stride = {1, -1, 1, 1};
+
+    inputTensorInfo = armnn::TensorInfo(4, inputShape, armnn::GetDataType<T>());
+    outputTensorInfo = armnn::TensorInfo(4, outputShape, armnn::GetDataType<T>());
+
+    std::vector<float> input = std::vector<float>(
+    {
+        1.0f, 1.0f, 1.0f, 2.0f, 2.0f, 2.0f,
+
+        3.0f, 3.0f, 3.0f, 4.0f, 4.0f, 4.0f,
+
+        5.0f, 5.0f, 5.0f, 6.0f, 6.0f, 6.0f
+    });
+
+    std::vector<float> outputExpected = std::vector<float>(
+    {
+        4.0f, 4.0f, 4.0f, 3.0f, 3.0f, 3.0f
+    });
+
+    return StridedSliceTestImpl<T, 4, 4>(
+        workloadFactory, memoryManager, inputTensorInfo, outputTensorInfo, input, outputExpected, desc);
+}
+
+template <typename T>
+LayerTestResult<T, 4> StridedSliceSimpleStrideTest(
+    armnn::IWorkloadFactory& workloadFactory,
+    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
+{
+    armnn::TensorInfo inputTensorInfo;
+    armnn::TensorInfo outputTensorInfo;
+
+    unsigned int inputShape[]  = {3, 2, 3, 1};
+    unsigned int outputShape[] = {2, 1, 2, 1};
+
+    armnn::StridedSliceQueueDescriptor desc;
+    desc.m_Parameters.m_Begin  = {0, 0, 0, 0};
+    desc.m_Parameters.m_End    = {3, 2, 3, 1};
+    desc.m_Parameters.m_Stride = {2, 2, 2, 1};
+
+    inputTensorInfo = armnn::TensorInfo(4, inputShape, armnn::GetDataType<T>());
+    outputTensorInfo = armnn::TensorInfo(4, outputShape, armnn::GetDataType<T>());
+
+    std::vector<float> input = std::vector<float>(
+    {
+        1.0f, 1.0f, 1.0f, 2.0f, 2.0f, 2.0f,
+
+        3.0f, 3.0f, 3.0f, 4.0f, 4.0f, 4.0f,
+
+        5.0f, 5.0f, 5.0f, 6.0f, 6.0f, 6.0f
+    });
+
+    std::vector<float> outputExpected = std::vector<float>(
+    {
+        1.0f, 1.0f,
+
+        5.0f, 5.0f
+    });
+
+    return StridedSliceTestImpl<T, 4, 4>(
+        workloadFactory, memoryManager, inputTensorInfo, outputTensorInfo, input, outputExpected, desc);
+}
+
+template <typename T>
+LayerTestResult<T, 4> StridedSliceSimpleRangeMaskTest(
+    armnn::IWorkloadFactory& workloadFactory,
+    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
+{
+    armnn::TensorInfo inputTensorInfo;
+    armnn::TensorInfo outputTensorInfo;
+
+    unsigned int inputShape[]  = {3, 2, 3, 1};
+    unsigned int outputShape[] = {3, 2, 3, 1};
+
+    armnn::StridedSliceQueueDescriptor desc;
+    desc.m_Parameters.m_Begin     = {1, 1, 1, 1};
+    desc.m_Parameters.m_End       = {1, 1, 1, 1};
+    desc.m_Parameters.m_Stride    = {1, 1, 1, 1};
+    desc.m_Parameters.m_BeginMask = (1 << 4) - 1;
+    desc.m_Parameters.m_EndMask   = (1 << 4) - 1;
+
+    inputTensorInfo = armnn::TensorInfo(4, inputShape, armnn::GetDataType<T>());
+    outputTensorInfo = armnn::TensorInfo(4, outputShape, armnn::GetDataType<T>());
+
+    std::vector<float> input = std::vector<float>(
+    {
+        1.0f, 1.0f, 1.0f, 2.0f, 2.0f, 2.0f,
+
+        3.0f, 3.0f, 3.0f, 4.0f, 4.0f, 4.0f,
+
+        5.0f, 5.0f, 5.0f, 6.0f, 6.0f, 6.0f
+    });
+
+    std::vector<float> outputExpected = std::vector<float>(
+    {
+        1.0f, 1.0f, 1.0f, 2.0f, 2.0f, 2.0f,
+
+        3.0f, 3.0f, 3.0f, 4.0f, 4.0f, 4.0f,
+
+        5.0f, 5.0f, 5.0f, 6.0f, 6.0f, 6.0f
+    });
+
+    return StridedSliceTestImpl<T, 4, 4>(
+        workloadFactory, memoryManager, inputTensorInfo, outputTensorInfo, input, outputExpected, desc);
+}
+
+template <typename T>
+LayerTestResult<T, 2> StridedSliceShrinkAxisMaskTest(
+    armnn::IWorkloadFactory& workloadFactory,
+    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
+{
+    armnn::TensorInfo inputTensorInfo;
+    armnn::TensorInfo outputTensorInfo;
+
+    unsigned int inputShape[]  = {3, 2, 3, 1};
+    unsigned int outputShape[] = {3, 1};
+
+    armnn::StridedSliceQueueDescriptor desc;
+    desc.m_Parameters.m_Begin          = {0, 0, 1, 0};
+    desc.m_Parameters.m_End            = {1, 1, 1, 1};
+    desc.m_Parameters.m_Stride         = {1, 1, 1, 1};
+    desc.m_Parameters.m_EndMask        = (1 << 4) - 1;
+    desc.m_Parameters.m_ShrinkAxisMask = (1 << 1) | (1 << 2);
+
+    inputTensorInfo = armnn::TensorInfo(4, inputShape, armnn::GetDataType<T>());
+    outputTensorInfo = armnn::TensorInfo(2, outputShape, armnn::GetDataType<T>());
+
+    std::vector<float> input = 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, 17.0f, 18.0f
+    });
+
+    std::vector<float> outputExpected = std::vector<float>(
+    {
+        2.0f, 8.0f, 14.0f
+    });
+
+    return StridedSliceTestImpl<T, 4, 2>(
+        workloadFactory, memoryManager, inputTensorInfo, outputTensorInfo, input, outputExpected, desc);
+}
+
+template <typename T>
+LayerTestResult<T, 3> StridedSlice3DTest(
+    armnn::IWorkloadFactory& workloadFactory,
+    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
+{
+    armnn::TensorInfo inputTensorInfo;
+    armnn::TensorInfo outputTensorInfo;
+
+    unsigned int inputShape[]  = {3, 3, 3};
+    unsigned int outputShape[] = {2, 2, 2};
+
+    armnn::StridedSliceQueueDescriptor desc;
+    desc.m_Parameters.m_Begin   = {0, 0, 0};
+    desc.m_Parameters.m_End     = {1, 1, 1};
+    desc.m_Parameters.m_Stride  = {2, 2, 2};
+    desc.m_Parameters.m_EndMask = (1 << 3) - 1;
+
+    inputTensorInfo = armnn::TensorInfo(3, inputShape, armnn::GetDataType<T>());
+    outputTensorInfo = armnn::TensorInfo(3, outputShape, armnn::GetDataType<T>());
+
+    std::vector<float> input = 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, 17.0f, 18.0f,
+
+        19.0f, 20.0f, 21.0f, 22.0f, 23.0f, 24.0f, 25.0f, 26.0f, 27.0f
+    });
+
+    std::vector<float> outputExpected = std::vector<float>(
+    {
+        1.0f, 3.0f, 7.0f, 9.0f,
+
+        19.0f, 21.0f, 25.0f, 27.0f
+    });
+
+    return StridedSliceTestImpl<T, 3, 3>(
+        workloadFactory, memoryManager, inputTensorInfo, outputTensorInfo, input, outputExpected, desc);
+}
+
+template <typename T>
+LayerTestResult<T, 3> StridedSlice3DReverseTest(
+    armnn::IWorkloadFactory& workloadFactory,
+    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
+{
+    armnn::TensorInfo inputTensorInfo;
+    armnn::TensorInfo outputTensorInfo;
+
+    unsigned int inputShape[]  = {3, 3, 3};
+    unsigned int outputShape[] = {2, 2, 2};
+
+    armnn::StridedSliceQueueDescriptor desc;
+    desc.m_Parameters.m_Begin  = {-1, -1, -1};
+    desc.m_Parameters.m_End    = {-4, -4, -4};
+    desc.m_Parameters.m_Stride = {-2, -2, -2};
+
+    inputTensorInfo = armnn::TensorInfo(3, inputShape, armnn::GetDataType<T>());
+    outputTensorInfo = armnn::TensorInfo(3, outputShape, armnn::GetDataType<T>());
+
+    std::vector<float> input = 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, 17.0f, 18.0f,
+
+        19.0f, 20.0f, 21.0f, 22.0f, 23.0f, 24.0f, 25.0f, 26.0f, 27.0f
+    });
+
+    std::vector<float> outputExpected = std::vector<float>(
+    {
+        27.0f, 25.0f, 21.0f, 19.0f,
+
+        9.0f, 7.0f, 3.0f, 1.0f
+    });
+
+    return StridedSliceTestImpl<T, 3, 3>(
+        workloadFactory, memoryManager, inputTensorInfo, outputTensorInfo, input, outputExpected, desc);
+}
+
+template <typename T>
+LayerTestResult<T, 2> StridedSlice2DTest(
+    armnn::IWorkloadFactory& workloadFactory,
+    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
+{
+    armnn::TensorInfo inputTensorInfo;
+    armnn::TensorInfo outputTensorInfo;
+
+    unsigned int inputShape[]  = {3, 3};
+    unsigned int outputShape[] = {2, 2};
+
+    armnn::StridedSliceQueueDescriptor desc;
+    desc.m_Parameters.m_Begin   = {0, 0};
+    desc.m_Parameters.m_End     = {1, 1};
+    desc.m_Parameters.m_Stride  = {2, 2};
+    desc.m_Parameters.m_EndMask = (1 << 2) - 1;
+
+    inputTensorInfo = armnn::TensorInfo(2, inputShape, armnn::GetDataType<T>());
+    outputTensorInfo = armnn::TensorInfo(2, outputShape, armnn::GetDataType<T>());
+
+    std::vector<float> input = std::vector<float>(
+    {
+        1.0f, 2.0f, 3.0f,
+
+        4.0f, 5.0f, 6.0f,
+
+        7.0f, 8.0f, 9.0f
+    });
+
+    std::vector<float> outputExpected = std::vector<float>(
+    {
+        1.0f, 3.0f,
+
+        7.0f, 9.0f
+    });
+
+    return StridedSliceTestImpl<T, 2, 2>(
+        workloadFactory, memoryManager, inputTensorInfo, outputTensorInfo, input, outputExpected, desc);
+}
+
+template <typename T>
+LayerTestResult<T, 2> StridedSlice2DReverseTest(
+    armnn::IWorkloadFactory& workloadFactory,
+    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
+{
+    armnn::TensorInfo inputTensorInfo;
+    armnn::TensorInfo outputTensorInfo;
+
+    unsigned int inputShape[]  = {3, 3};
+    unsigned int outputShape[] = {2, 2};
+
+    armnn::StridedSliceQueueDescriptor desc;
+    desc.m_Parameters.m_Begin     = {0, 0};
+    desc.m_Parameters.m_End       = {1, 1};
+    desc.m_Parameters.m_Stride    = {-2, -2};
+    desc.m_Parameters.m_BeginMask = (1 << 2) - 1;
+    desc.m_Parameters.m_EndMask   = (1 << 2) - 1;
+
+    inputTensorInfo = armnn::TensorInfo(2, inputShape, armnn::GetDataType<T>());
+    outputTensorInfo = armnn::TensorInfo(2, outputShape, armnn::GetDataType<T>());
+
+    std::vector<float> input = std::vector<float>(
+    {
+        1.0f, 2.0f, 3.0f,
+
+        4.0f, 5.0f, 6.0f,
+
+        7.0f, 8.0f, 9.0f
+    });
+
+    std::vector<float> outputExpected = std::vector<float>(
+    {
+        9.0f, 7.0f,
+
+        3.0f, 1.0f
+    });
+
+    return StridedSliceTestImpl<T, 2, 2>(
+        workloadFactory, memoryManager, inputTensorInfo, outputTensorInfo, input, outputExpected, desc);
+}
+
+} // anonymous namespace