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, 473 insertions, 0 deletions

diff --git a/src/backends/backendsCommon/test/layerTests/BatchToSpaceNdTestImpl.hpp b/src/backends/backendsCommon/test/layerTests/BatchToSpaceNdTestImpl.hpp
new file mode 100644
index 0000000000..67e7cc5f6e
--- /dev/null
+++ b/src/backends/backendsCommon/test/layerTests/BatchToSpaceNdTestImpl.hpp
@@ -0,0 +1,473 @@
+//
+// Copyright © 2017 Arm Ltd. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+
+#pragma once
+
+#include "LayerTestResult.hpp"
+
+#include <ResolveType.hpp>
+
+#include <armnn/ArmNN.hpp>
+
+#include <backendsCommon/IBackendInternal.hpp>
+#include <backendsCommon/WorkloadFactory.hpp>
+
+#include <backendsCommon/test/DataTypeUtils.hpp>
+#include <backendsCommon/test/TensorCopyUtils.hpp>
+#include <backendsCommon/test/WorkloadTestUtils.hpp>
+
+#include <test/TensorHelpers.hpp>
+
+namespace
+{
+
+template<armnn::DataType ArmnnType,
+        std::size_t InputDim,
+        std::size_t OutputDim,
+        typename T = armnn::ResolveType<ArmnnType>>
+LayerTestResult<T, OutputDim> BatchToSpaceNdHelper(
+        armnn::IWorkloadFactory &workloadFactory,
+        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
+        const armnn::DataLayout& dataLayout,
+        const unsigned int *inputShape,
+        const std::vector<float> &inputData,
+        const std::vector<unsigned int> &blockShape,
+        const std::vector<std::pair<unsigned int, unsigned int>> &crops,
+        const unsigned int *outputShape,
+        const std::vector<float> &outputData,
+        float scale = 1.0f,
+        int32_t offset = 0)
+{
+    armnn::TensorInfo inputTensorInfo(InputDim, inputShape, ArmnnType);
+    armnn::TensorInfo outputTensorInfo(OutputDim, outputShape, ArmnnType);
+
+    inputTensorInfo.SetQuantizationScale(scale);
+    inputTensorInfo.SetQuantizationOffset(offset);
+
+    outputTensorInfo.SetQuantizationScale(scale);
+    outputTensorInfo.SetQuantizationOffset(offset);
+
+    auto input = MakeTensor<T, InputDim>(inputTensorInfo, ConvertToDataType<ArmnnType>(inputData, inputTensorInfo));
+
+    LayerTestResult<T, OutputDim> result(outputTensorInfo);
+    result.outputExpected = MakeTensor<T, OutputDim>(outputTensorInfo,
+                                                     ConvertToDataType<ArmnnType>(outputData, outputTensorInfo));
+
+    std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo);
+    std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo);
+
+    armnn::BatchToSpaceNdQueueDescriptor data;
+    data.m_Parameters.m_DataLayout = dataLayout;
+    data.m_Parameters.m_BlockShape = blockShape;
+    data.m_Parameters.m_Crops = crops;
+    armnn::WorkloadInfo info;
+    AddInputToWorkload(data, info, inputTensorInfo, inputHandle.get());
+    AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get());
+
+    std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateBatchToSpaceNd(data, info);
+
+    inputHandle->Allocate();
+    outputHandle->Allocate();
+
+    CopyDataToITensorHandle(inputHandle.get(), input.origin());
+
+    workload->PostAllocationConfigure();
+    workload->Execute();
+
+    CopyDataFromITensorHandle(&result.output[0][0][0][0], outputHandle.get());
+
+    return result;
+}
+
+} // anonymous namespace
+
+template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
+LayerTestResult<T, 4> BatchToSpaceNdNhwcTest1(
+        armnn::IWorkloadFactory& workloadFactory,
+        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
+{
+    const unsigned int inputShape[] = {4, 2, 2, 1};
+    const unsigned int outputShape[] = {1, 4, 4, 1};
+
+    std::vector<float> input({
+                                     // Batch 0, Height 0, Width (2) x Channel (1)
+                                     1.0f, 3.0f,
+                                     // Batch 0, Height 1, Width (2) x Channel (1)
+                                     9.0f, 11.0f,
+
+
+                                     // Batch 1, Height 0, Width (2) x Channel (1)
+                                     2.0f, 4.0f,
+                                     // Batch 1, Height 1, Width (2) x Channel (1)
+                                     10.0f, 12.0f,
+
+
+                                     // Batch 2, Height 0, Width (2) x Channel (1)
+                                     5.0f, 7.0f,
+                                     // Batch 2, Height 1, Width (2) x Channel (1)
+                                     13.0f, 15.0f,
+
+                                     // Batch 3, Height 0, Width (2) x Channel (3)
+                                     6.0f, 8.0f,
+                                     // Batch 3, Height 1, Width (2) x Channel (1)
+                                     14.0f, 16.0f
+                             });
+
+    std::vector<float> expectedOutput({
+                                              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
+                                      });
+
+    std::vector<unsigned int> blockShape {2, 2};
+    std::vector<std::pair<unsigned int, unsigned int>> crops = {{0, 0}, {0, 0}};
+
+    return BatchToSpaceNdHelper<ArmnnType, 4, 4>(workloadFactory, memoryManager,
+                                                                armnn::DataLayout::NHWC, inputShape, input, blockShape,
+                                                                crops, outputShape, expectedOutput);
+}
+
+template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
+LayerTestResult<T, 4> BatchToSpaceNdNhwcTest2(
+        armnn::IWorkloadFactory& workloadFactory,
+        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
+{
+    const unsigned int inputShape[] = {4, 1, 1, 1};
+    const unsigned int outputShape[] = {1, 2, 2, 1};
+
+    std::vector<float> input({
+                                     // Batch 0, Height 0, Width (2) x Channel (1)
+                                     1.0f, 2.0f, 3.0f, 4.0f
+                             });
+
+    std::vector<float> expectedOutput({1.0f, 2.0f, 3.0f, 4.0f});
+
+    std::vector<unsigned int> blockShape({2, 2});
+    std::vector<std::pair<unsigned int, unsigned int>> crops = {{0, 0}, {0, 0}};
+
+    return BatchToSpaceNdHelper<ArmnnType, 4, 4>(workloadFactory, memoryManager,
+                                                                armnn::DataLayout::NHWC, inputShape, input, blockShape,
+                                                                crops, outputShape, expectedOutput);
+}
+
+template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
+LayerTestResult<T, 4> BatchToSpaceNdNhwcTest3(
+        armnn::IWorkloadFactory& workloadFactory,
+        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
+{
+    const unsigned int inputShape[] = {4, 1, 1, 3};
+    const unsigned int outputShape[] = {1, 2, 2, 3};
+
+    std::vector<float> input({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<float> expectedOutput({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<unsigned int> blockShape({2, 2});
+    std::vector<std::pair<unsigned int, unsigned int>> crops = {{0, 0}, {0, 0}};
+
+    return BatchToSpaceNdHelper<ArmnnType, 4, 4>(workloadFactory, memoryManager,
+                                                                armnn::DataLayout::NHWC, inputShape, input, blockShape,
+                                                                crops, outputShape, expectedOutput);
+}
+
+template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
+LayerTestResult<T, 4> BatchToSpaceNdNhwcTest4(
+        armnn::IWorkloadFactory& workloadFactory,
+        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
+{
+    const unsigned int inputShape[] = {8, 1, 3, 1};
+    const unsigned int outputShape[] = {2, 2, 4, 1};
+
+    std::vector<float> input({
+                                     0.0f, 1.0f, 3.0f,
+                                     0.0f, 9.0f, 11.0f,
+                                     0.0f, 2.0f, 4.0f,
+                                     0.0f, 10.0f, 12.0f,
+                                     0.0f, 5.0f, 7.0f,
+                                     0.0f, 13.0f, 15.0f,
+                                     0.0f, 6.0f, 8.0f,
+                                     0.0f, 14.0f, 16.0f
+                             });
+
+    std::vector<float> expectedOutput({
+                                              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
+                                      });
+
+    std::vector<unsigned int> blockShape({2, 2});
+    std::vector<std::pair<unsigned int, unsigned int>> crops = {{0, 0}, {2, 0}};
+
+    return BatchToSpaceNdHelper<ArmnnType, 4, 4>(workloadFactory, memoryManager,
+                                                                armnn::DataLayout::NHWC, inputShape, input, blockShape,
+                                                                crops, outputShape, expectedOutput);
+}
+
+template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
+LayerTestResult<T, 4> BatchToSpaceNdNhwcTest5(
+        armnn::IWorkloadFactory& workloadFactory,
+        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
+{
+    const unsigned int inputShape[] = {4, 2, 2, 1};
+    const unsigned int outputShape[] = {1, 4, 4, 1};
+
+    std::vector<float> input({1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16});
+    std::vector<float> expectedOutput({1, 5, 2, 6, 9, 13, 10, 14, 3, 7, 4, 8, 11, 15, 12, 16});
+
+    std::vector<unsigned int> blockShape({2, 2});
+    std::vector<std::pair<unsigned int, unsigned int>> crops = {{0, 0}, {0, 0}};
+
+    return BatchToSpaceNdHelper<ArmnnType, 4, 4>(workloadFactory, memoryManager, armnn::DataLayout::NHWC, inputShape,
+                                                 input, blockShape, crops, outputShape, expectedOutput);
+}
+
+template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
+LayerTestResult<T, 4> BatchToSpaceNdNhwcTest6(
+        armnn::IWorkloadFactory& workloadFactory,
+        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
+{
+    const unsigned int inputShape[] = {4, 1, 1, 1};
+    const unsigned int outputShape[] = {1, 2, 2, 1};
+
+    std::vector<float> input({
+                                     // Batch 0, Height 0, Width (2) x Channel (1)
+                                     1, 2, 3, 4
+                             });
+
+    std::vector<float> expectedOutput({1, 2, 3, 4});
+
+    std::vector<unsigned int> blockShape({2, 2});
+    std::vector<std::pair<unsigned int, unsigned int>> crops = {{0, 0}, {0, 0}};
+
+    return BatchToSpaceNdHelper<ArmnnType, 4, 4>(workloadFactory, memoryManager,
+                                                 armnn::DataLayout::NHWC, inputShape, input, blockShape,
+                                                 crops, outputShape, expectedOutput);
+}
+
+template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
+LayerTestResult<T, 4> BatchToSpaceNdNhwcTest7(
+        armnn::IWorkloadFactory& workloadFactory,
+        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
+{
+    const unsigned int inputShape[] = {4, 1, 1, 3};
+    const unsigned int outputShape[] = {1, 2, 2, 3};
+
+    std::vector<float> input({1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12});
+
+    std::vector<float> expectedOutput({1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12});
+
+    std::vector<unsigned int> blockShape({2, 2});
+    std::vector<std::pair<unsigned int, unsigned int>> crops = {{0, 0}, {0, 0}};
+
+    return BatchToSpaceNdHelper<ArmnnType, 4, 4>(workloadFactory, memoryManager,
+                                                 armnn::DataLayout::NHWC, inputShape, input, blockShape,
+                                                 crops, outputShape, expectedOutput);
+}
+
+template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
+LayerTestResult<T, 4> BatchToSpaceNdNchwTest1(
+        armnn::IWorkloadFactory &workloadFactory,
+        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
+{
+    const unsigned int inputShape[] = {4, 3, 1, 1};
+    const unsigned int outputShape[] = {1, 3, 2, 2};
+
+    std::vector<float> input({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<float> expectedOutput({
+                                              // Batch 0, Channel 0, Height (2) x Width (2)
+                                              1.0f,  4.0f,
+                                              7.0f, 10.0f,
+
+                                              // Batch 0, Channel 1, Height (2) x Width (2)
+                                              2.0f,  5.0f,
+                                              8.0f, 11.0f,
+
+                                              // Batch 0, Channel 2, Height (2) x Width (2)
+                                              3.0f,  6.0f,
+                                              9.0f, 12.0f,
+                                      });
+
+    std::vector<unsigned int> blockShape({2, 2});
+    std::vector<std::pair<unsigned int, unsigned int>> crops = {{0, 0}, {0, 0}};
+
+    return BatchToSpaceNdHelper<ArmnnType, 4, 4>(workloadFactory, memoryManager,
+                                                                armnn::DataLayout::NCHW, inputShape, input, blockShape,
+                                                                crops, outputShape, expectedOutput);
+}
+
+template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
+LayerTestResult<T, 4> BatchToSpaceNdNchwTest2(
+        armnn::IWorkloadFactory& workloadFactory,
+        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
+{
+    const unsigned int inputShape[] = {4, 1, 1, 1};
+    const unsigned int outputShape[] = {1, 1, 2, 2};
+
+    std::vector<float> input({
+                                     // Batch 0, Height 0, Width (2) x Channel (1)
+                                     1.0f, 2.0f, 3.0f, 4.0f
+                             });
+
+    std::vector<float> expectedOutput({1.0f, 2.0f, 3.0f, 4.0f});
+
+    std::vector<unsigned int> blockShape({2, 2});
+    std::vector<std::pair<unsigned int, unsigned int>> crops = {{0, 0}, {0, 0}};
+
+    return BatchToSpaceNdHelper<ArmnnType, 4, 4>(workloadFactory, memoryManager,
+                                                                armnn::DataLayout::NCHW, inputShape, input, blockShape,
+                                                                crops, outputShape, expectedOutput);
+}
+
+template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
+LayerTestResult<T, 4> BatchToSpaceNdNchwTest3(
+        armnn::IWorkloadFactory& workloadFactory,
+        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
+{
+    const unsigned int inputShape[] = {4, 3, 1, 1};
+    const unsigned int outputShape[] = {1, 3, 2, 2};
+
+    std::vector<float> input({1.0f, 3.0f, 5.0f, 7.0f, 9.0f, 11.0f, 2.0f, 4.0f, 6.0f, 8.0f, 10.0f, 12.0f});
+
+    std::vector<float> expectedOutput({
+                                              // Batch 0, Channel 0, Height (2) x Width (2)
+                                              1.0f,  7.0f,
+                                              2.0f,  8.0f,
+
+                                              // Batch 0, Channel 1, Height (2) x Width (2)
+                                              3.0f,  9.0f,
+                                              4.0f, 10.0f,
+
+                                              // Batch 0, Channel 2, Height (2) x Width (2)
+                                              5.0f, 11.0f,
+                                              6.0f, 12.0f,
+                                      });
+
+    std::vector<unsigned int> blockShape({2, 2});
+    std::vector<std::pair<unsigned int, unsigned int>> crops = {{0, 0}, {0, 0}};
+
+    return BatchToSpaceNdHelper<ArmnnType, 4, 4>(workloadFactory, memoryManager,
+                                                                armnn::DataLayout::NCHW, inputShape, input, blockShape,
+                                                                crops, outputShape, expectedOutput);
+}
+
+template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
+LayerTestResult<T, 4> BatchToSpaceNdNchwTest4(
+        armnn::IWorkloadFactory &workloadFactory,
+        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
+{
+    const unsigned int inputShape[] = {4, 3, 1, 1};
+    const unsigned int outputShape[] = {1, 3, 2, 2};
+
+    std::vector<float> input({1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12});
+
+    std::vector<float> expectedOutput({
+                                              // Batch 0, Channel 0, Height (2) x Width (2)
+                                              1,  4,
+                                              7, 10,
+
+                                              // Batch 0, Channel 1, Height (2) x Width (2)
+                                              2,  5,
+                                              8, 11,
+
+                                              // Batch 0, Channel 2, Height (2) x Width (2)
+                                              3,  6,
+                                              9, 12,
+                                      });
+
+    std::vector<unsigned int> blockShape({2, 2});
+    std::vector<std::pair<unsigned int, unsigned int>> crops = {{0, 0}, {0, 0}};
+
+    return BatchToSpaceNdHelper<ArmnnType, 4, 4>(workloadFactory, memoryManager,
+                                                 armnn::DataLayout::NCHW, inputShape, input, blockShape,
+                                                 crops, outputShape, expectedOutput);
+}
+
+template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
+LayerTestResult<T, 4> BatchToSpaceNdNchwTest5(
+        armnn::IWorkloadFactory& workloadFactory,
+        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
+{
+    const unsigned int inputShape[] = {4, 1, 1, 1};
+    const unsigned int outputShape[] = {1, 1, 2, 2};
+
+    std::vector<float> input({
+                                     // Batch 0, Height 0, Width (2) x Channel (1)
+                                     1, 2, 3, 4
+                             });
+
+    std::vector<float> expectedOutput({1, 2, 3, 4});
+
+    std::vector<unsigned int> blockShape({2, 2});
+    std::vector<std::pair<unsigned int, unsigned int>> crops = {{0, 0}, {0, 0}};
+
+    return BatchToSpaceNdHelper<ArmnnType, 4, 4>(workloadFactory, memoryManager,
+                                                 armnn::DataLayout::NCHW, inputShape, input, blockShape,
+                                                 crops, outputShape, expectedOutput);
+}
+
+template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
+LayerTestResult<T, 4> BatchToSpaceNdNchwTest6(
+        armnn::IWorkloadFactory& workloadFactory,
+        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
+{
+    const unsigned int inputShape[] = {4, 3, 1, 1};
+    const unsigned int outputShape[] = {1, 3, 2, 2};
+
+    std::vector<float> input({1, 3, 5, 7, 9, 11, 2, 4, 6, 8, 10, 12});
+
+    std::vector<float> expectedOutput({
+                                              // Batch 0, Channel 0, Height (2) x Width (2)
+                                              1,  7,
+                                              2,  8,
+
+                                              // Batch 0, Channel 1, Height (2) x Width (2)
+                                              3,  9,
+                                              4, 10,
+
+                                              // Batch 0, Channel 2, Height (2) x Width (2)
+                                              5, 11,
+                                              6, 12,
+                                      });
+
+    std::vector<unsigned int> blockShape({2, 2});
+    std::vector<std::pair<unsigned int, unsigned int>> crops = {{0, 0}, {0, 0}};
+
+    return BatchToSpaceNdHelper<ArmnnType, 4, 4>(workloadFactory, memoryManager,
+                                                 armnn::DataLayout::NCHW, inputShape, input, blockShape,
+                                                 crops, outputShape, expectedOutput);
+}
+
+template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
+LayerTestResult<T, 4> BatchToSpaceNdNchwTest7(
+        armnn::IWorkloadFactory& workloadFactory,
+        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
+{
+    const unsigned int inputShape[] = {8, 1, 1, 3};
+    const unsigned int outputShape[] = {2, 1, 2, 4};
+
+    std::vector<float> input({
+                                     0, 1, 3, 0,  9, 11,
+                                     0, 2, 4, 0, 10, 12,
+                                     0, 5, 7, 0, 13, 15,
+                                     0, 6, 8, 0, 14, 16
+                             });
+
+    std::vector<float> expectedOutput({
+                                              1,  2,  3,  4,
+                                              5,  6,  7,  8,
+                                              9, 10, 11, 12,
+                                              13, 14, 15, 16
+                                      });
+
+    std::vector<unsigned int> blockShape({2, 2});
+    std::vector<std::pair<unsigned int, unsigned int>> crops = {{0, 0}, {2, 0}};
+
+    return BatchToSpaceNdHelper<ArmnnType, 4, 4>(workloadFactory, memoryManager,
+                                                 armnn::DataLayout::NCHW, inputShape, input, blockShape,
+                                                 crops, outputShape, expectedOutput);
+}