IVGCVSW-3381 Break up LayerTests.hpp into more manageable files

Signed-off-by: Aron Virginas-Tar <Aron.Virginas-Tar@arm.com>
Change-Id: Icf39434f09fd340ad664cb3b97b8bee6d9da4838

1 files changed, 0 insertions, 312 deletions

diff --git a/src/backends/backendsCommon/test/SplitterTestImpl.hpp b/src/backends/backendsCommon/test/SplitterTestImpl.hpp
deleted file mode 100644
index de677ef45d..0000000000
--- a/src/backends/backendsCommon/test/SplitterTestImpl.hpp
+++ /dev/null
@@ -1,312 +0,0 @@
-//
-// 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 <backendsCommon/CpuTensorHandle.hpp>
-#include <backendsCommon/IBackendInternal.hpp>
-#include <backendsCommon/WorkloadFactory.hpp>
-#include <backendsCommon/test/QuantizeHelper.hpp>
-
-#include <test/TensorHelpers.hpp>
-
-template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
-std::vector<LayerTestResult<T,3>> SplitterTestCommon(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-    float qScale = 0.0f,
-    int32_t qOffset = 0)
-{
-    unsigned int inputWidth = 5;
-    unsigned int inputHeight = 6;
-    unsigned int inputChannels = 3;
-
-    // NOTE: Compute Library imposes a restriction that the x and y dimension (input height and width)
-    //       cannot be split.
-    //       For the reasons for this, see first comment on https://jira.arm.com/browse/IVGCVSW-1239
-    //
-    // This test has therefore been recast to split the channels, then split the resulting subtensor.
-
-    // To take channel 0 of original output
-    // and channel 0 and channel 1 of the split subtensor.
-    unsigned int outputWidth1 = inputWidth;
-    unsigned int outputHeight1 = inputHeight;
-    unsigned int outputChannels1 = 1;
-
-    // To take channel 1 and 2 of the original output.
-    unsigned int outputWidth2 = inputWidth;
-    unsigned int outputHeight2 = inputHeight;
-    unsigned int outputChannels2 = 2;
-
-
-    // Define the tensor descriptors.
-    armnn::TensorInfo inputTensorInfo({ inputChannels, inputHeight, inputWidth }, ArmnnType, qScale, qOffset);
-
-    // Outputs of the original split.
-    armnn::TensorInfo outputTensorInfo1({ outputChannels1, outputHeight1, outputWidth1 }, ArmnnType, qScale, qOffset);
-    armnn::TensorInfo outputTensorInfo2({ outputChannels2, outputHeight2, outputWidth2 }, ArmnnType, qScale, qOffset);
-
-    // Outputs of the subsequent subtensor split.
-    armnn::TensorInfo outputTensorInfo3({ outputChannels1, outputHeight1, outputWidth1 }, ArmnnType, qScale, qOffset);
-    armnn::TensorInfo outputTensorInfo4({ outputChannels1, outputHeight1, outputWidth1 }, ArmnnType, qScale, qOffset);
-
-    // Set quantization parameters if the requested type is a quantized type.
-    // The quantization doesn't really matter as the splitter operator doesn't dequantize/quantize.
-    if(armnn::IsQuantizedType<T>())
-    {
-        inputTensorInfo.SetQuantizationScale(qScale);
-        inputTensorInfo.SetQuantizationOffset(qOffset);
-        outputTensorInfo1.SetQuantizationScale(qScale);
-        outputTensorInfo1.SetQuantizationOffset(qOffset);
-        outputTensorInfo2.SetQuantizationScale(qScale);
-        outputTensorInfo2.SetQuantizationOffset(qOffset);
-        outputTensorInfo3.SetQuantizationScale(qScale);
-        outputTensorInfo3.SetQuantizationOffset(qOffset);
-        outputTensorInfo4.SetQuantizationScale(qScale);
-        outputTensorInfo4.SetQuantizationOffset(qOffset);
-    }
-
-    LayerTestResult<T,3> ret1(outputTensorInfo1);
-    LayerTestResult<T,3> ret2(outputTensorInfo2);
-    LayerTestResult<T,3> ret3(outputTensorInfo3);
-    LayerTestResult<T,3> ret4(outputTensorInfo4);
-
-    auto input = MakeTensor<T, 3>(inputTensorInfo, std::vector<T>(
-        QuantizedVector<T>(qScale, qOffset, {
-            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, 28.0f, 29.0f, 30.0f,
-
-            31.0f, 32.0f, 33.0f, 34.0f, 35.0f,
-            36.0f, 37.0f, 38.0f, 39.0f, 40.0f,
-            41.0f, 42.0f, 43.0f, 44.0f, 45.0f,
-            46.0f, 47.0f, 48.0f, 49.0f, 50.0f,
-            51.0f, 52.0f, 53.0f, 54.0f, 55.0f,
-            56.0f, 57.0f, 58.0f, 59.0f, 60.0f,
-
-            61.0f, 62.0f, 63.0f, 64.0f, 65.0f,
-            66.0f, 67.0f, 68.0f, 69.0f, 70.0f,
-            71.0f, 72.0f, 73.0f, 74.0f, 75.0f,
-            76.0f, 77.0f, 78.0f, 79.0f, 80.0f,
-            81.0f, 82.0f, 83.0f, 84.0f, 85.0f,
-            86.0f, 87.0f, 88.0f, 89.0f, 90.0f,
-        })
-    ));
-
-    // Channel 0 of the original input.
-    ret1.outputExpected = MakeTensor<T, 3>(outputTensorInfo1, std::vector<T>(
-        QuantizedVector<T>(qScale, qOffset, {
-            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, 28.0f, 29.0f, 30.0f,
-        })
-    ));
-
-    // Channel 1 & 2 of the original input.
-    ret2.outputExpected = MakeTensor<T, 3>(outputTensorInfo2, std::vector<T>(
-        QuantizedVector<T>(qScale, qOffset, {
-            31.0f, 32.0f, 33.0f, 34.0f, 35.0f,
-            36.0f, 37.0f, 38.0f, 39.0f, 40.0f,
-            41.0f, 42.0f, 43.0f, 44.0f, 45.0f,
-            46.0f, 47.0f, 48.0f, 49.0f, 50.0f,
-            51.0f, 52.0f, 53.0f, 54.0f, 55.0f,
-            56.0f, 57.0f, 58.0f, 59.0f, 60.0f,
-
-            61.0f, 62.0f, 63.0f, 64.0f, 65.0f,
-            66.0f, 67.0f, 68.0f, 69.0f, 70.0f,
-            71.0f, 72.0f, 73.0f, 74.0f, 75.0f,
-            76.0f, 77.0f, 78.0f, 79.0f, 80.0f,
-            81.0f, 82.0f, 83.0f, 84.0f, 85.0f,
-            86.0f, 87.0f, 88.0f, 89.0f, 90.0f,
-        })
-    ));
-
-    // Channel 0 of return 2 (i.e. channels 1 and 2 of the original input).
-    ret3.outputExpected = MakeTensor<T, 3>(outputTensorInfo3, std::vector<T>(
-        QuantizedVector<T>(qScale, qOffset, {
-            31.0f, 32.0f, 33.0f, 34.0f, 35.0f,
-            36.0f, 37.0f, 38.0f, 39.0f, 40.0f,
-            41.0f, 42.0f, 43.0f, 44.0f, 45.0f,
-            46.0f, 47.0f, 48.0f, 49.0f, 50.0f,
-            51.0f, 52.0f, 53.0f, 54.0f, 55.0f,
-            56.0f, 57.0f, 58.0f, 59.0f, 60.0f,
-        })
-    ));
-
-    // Channel 1 of return 2.
-    ret4.outputExpected = MakeTensor<T, 3>(outputTensorInfo4, std::vector<T>(
-        QuantizedVector<T>(qScale, qOffset, {
-            61.0f, 62.0f, 63.0f, 64.0f, 65.0f,
-            66.0f, 67.0f, 68.0f, 69.0f, 70.0f,
-            71.0f, 72.0f, 73.0f, 74.0f, 75.0f,
-            76.0f, 77.0f, 78.0f, 79.0f, 80.0f,
-            81.0f, 82.0f, 83.0f, 84.0f, 85.0f,
-            86.0f, 87.0f, 88.0f, 89.0f, 90.0f,
-        })
-    ));
-
-    // NOTE: as a corollary of the splitting of x and y restriction the x and y values of the view origins
-    //       have to be zero, the co-ordinates are as per the tensor info above channels, height/y, width/x
-    //       note that under the hood the compute engine reverses these i.e. its coordinate system is x, y, channels.
-    std::vector<unsigned int> wOrigin1 = {0, 0, 0}; //Extent of the window is defined by size of output[0].
-    armnn::SplitterQueueDescriptor::ViewOrigin window1(wOrigin1);
-
-    std::vector<unsigned int> wOrigin2 = {1, 0, 0}; //Extent of the window is defined by size of output[1].
-    armnn::SplitterQueueDescriptor::ViewOrigin window2(wOrigin2);
-
-    std::vector<unsigned int> wOrigin3 = {0, 0, 0}; //Extent of the window is defined by size of output[2].
-    armnn::SplitterQueueDescriptor::ViewOrigin window3(wOrigin3);
-
-    std::vector<unsigned int> wOrigin4 = {1, 0, 0}; //Extent of the window is defined by size of output[3].
-    armnn::SplitterQueueDescriptor::ViewOrigin window4(wOrigin4);
-
-    bool subTensorsSupported = workloadFactory.SupportsSubTensors();
-
-    std::unique_ptr<armnn::ITensorHandle> inputHandle  = workloadFactory.CreateTensorHandle(inputTensorInfo);
-
-    std::unique_ptr<armnn::ITensorHandle> outputHandle1 =
-        subTensorsSupported ?
-            workloadFactory.CreateSubTensorHandle(*inputHandle, outputTensorInfo1.GetShape(), wOrigin1.data()) :
-            workloadFactory.CreateTensorHandle(outputTensorInfo1);
-
-    std::unique_ptr<armnn::ITensorHandle> outputHandle2 =
-        subTensorsSupported ?
-            workloadFactory.CreateSubTensorHandle(*inputHandle, outputTensorInfo2.GetShape(), wOrigin2.data()) :
-            workloadFactory.CreateTensorHandle(outputTensorInfo2);
-
-    std::unique_ptr<armnn::ITensorHandle> outputHandle3 =
-        subTensorsSupported ?
-            workloadFactory.CreateSubTensorHandle(*outputHandle2, outputTensorInfo3.GetShape(), wOrigin3.data()) :
-            workloadFactory.CreateTensorHandle(outputTensorInfo3);
-
-    std::unique_ptr<armnn::ITensorHandle> outputHandle4 =
-        subTensorsSupported ?
-            workloadFactory.CreateSubTensorHandle(*outputHandle2, outputTensorInfo4.GetShape(), wOrigin4.data()) :
-            workloadFactory.CreateTensorHandle(outputTensorInfo4);
-
-    // Do the first split
-    armnn::SplitterQueueDescriptor data;
-    armnn::WorkloadInfo info;
-    AddInputToWorkload(data, info, inputTensorInfo, inputHandle.get());
-    AddOutputToWorkload(data, info, outputTensorInfo1, outputHandle1.get());
-    AddOutputToWorkload(data, info, outputTensorInfo2, outputHandle2.get());
-
-    data.m_ViewOrigins.push_back(window1);
-    data.m_ViewOrigins.push_back(window2);
-
-    std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateSplitter(data, info);
-
-    inputHandle->Allocate();
-    outputHandle1->Allocate();
-    outputHandle2->Allocate();
-
-    CopyDataToITensorHandle(inputHandle.get(), &input[0][0][0]);
-
-    workload->Execute();
-
-    CopyDataFromITensorHandle(&ret1.output[0][0][0], outputHandle1.get());
-    CopyDataFromITensorHandle(&ret2.output[0][0][0], outputHandle2.get());
-
-    // Do the second split.
-    armnn::SplitterQueueDescriptor data2;
-    armnn::WorkloadInfo info2;
-    AddInputToWorkload(data2, info2, outputTensorInfo2, outputHandle2.get());
-    AddOutputToWorkload(data2, info2, outputTensorInfo3, outputHandle3.get());
-    AddOutputToWorkload(data2, info2, outputTensorInfo4, outputHandle4.get());
-
-    data2.m_ViewOrigins.push_back(window3);
-    data2.m_ViewOrigins.push_back(window4);
-
-    std::unique_ptr<armnn::IWorkload> workload2 = workloadFactory.CreateSplitter(data2, info2);
-
-    outputHandle3->Allocate();
-    outputHandle4->Allocate();
-
-    ExecuteWorkload(*workload2, memoryManager);
-
-    CopyDataFromITensorHandle(&ret3.output[0][0][0], outputHandle3.get());
-    CopyDataFromITensorHandle(&ret4.output[0][0][0], outputHandle4.get());
-
-    std::vector<LayerTestResult<T,3>> ret = {ret1, ret2, ret3, ret4,};
-
-    return ret;
-}
-
-
-template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
-LayerTestResult<T, 3> CopyViaSplitterTestImpl(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-    float qScale, int32_t qOffset)
-{
-    const armnn::TensorInfo tensorInfo({ 3, 6, 5 }, ArmnnType, qScale, qOffset);
-    auto input = MakeTensor<T, 3>(tensorInfo, QuantizedVector<T>(qScale, qOffset,
-                                                                 {
-                                                                     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, 28.0f, 29.0f, 30.0f,
-
-                                                                     31.0f, 32.0f, 33.0f, 34.0f, 35.0f,
-                                                                     36.0f, 37.0f, 38.0f, 39.0f, 40.0f,
-                                                                     41.0f, 42.0f, 43.0f, 44.0f, 45.0f,
-                                                                     46.0f, 47.0f, 48.0f, 49.0f, 50.0f,
-                                                                     51.0f, 52.0f, 53.0f, 54.0f, 55.0f,
-                                                                     56.0f, 57.0f, 58.0f, 59.0f, 60.0f,
-
-                                                                     61.0f, 62.0f, 63.0f, 64.0f, 65.0f,
-                                                                     66.0f, 67.0f, 68.0f, 69.0f, 70.0f,
-                                                                     71.0f, 72.0f, 73.0f, 74.0f, 75.0f,
-                                                                     76.0f, 77.0f, 78.0f, 79.0f, 80.0f,
-                                                                     81.0f, 82.0f, 83.0f, 84.0f, 85.0f,
-                                                                     86.0f, 87.0f, 88.0f, 89.0f, 90.0f,
-                                                                 }));
-
-    std::vector<unsigned int> origin = { 0, 0, 0 };
-    armnn::SplitterQueueDescriptor::ViewOrigin window(origin);
-
-    const bool subTensorsSupported = workloadFactory.SupportsSubTensors();
-
-    std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(tensorInfo);
-
-    std::unique_ptr<armnn::ITensorHandle> outputHandle =
-        subTensorsSupported ?
-            workloadFactory.CreateSubTensorHandle(*inputHandle, tensorInfo.GetShape(), origin.data()) :
-            workloadFactory.CreateTensorHandle(tensorInfo);
-
-    armnn::SplitterQueueDescriptor data;
-    armnn::WorkloadInfo info;
-    AddInputToWorkload(data, info, tensorInfo, inputHandle.get());
-    AddOutputToWorkload(data, info, tensorInfo, outputHandle.get());
-
-    data.m_ViewOrigins.push_back(window);
-
-    std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateSplitter(data, info);
-
-    inputHandle->Allocate();
-    outputHandle->Allocate();
-
-    CopyDataToITensorHandle(inputHandle.get(), &input[0][0][0]);
-
-    workload->Execute();
-
-    LayerTestResult<T, 3> ret(tensorInfo);
-    CopyDataFromITensorHandle(&ret.output[0][0][0], outputHandle.get());
-    ret.outputExpected = input;
-
-    return ret;
-}