From c9ea45adefdde2890e9aa191a5b31563a3dd35ea Mon Sep 17 00:00:00 2001
From: Mike Kelly <mike.kelly@arm.com>
Date: Fri, 28 Feb 2020 18:11:58 +0000
Subject: IVGCVSW-4375 Add support for Transpose

 * Added TransposeLayer
 * Added CL, Neon and Ref Workloads
 * Added Transpose utilities
 * Added Serializer and Deserializer support
 * Added Quantizer support

Signed-off-by: Mike Kelly <mike.kelly@arm.com>
Change-Id: I04c755ba7cb5b1edf72b3c9f3c0314878032e3c7
---
 .../test/layerTests/TransposeTestImpl.hpp          | 240 +++++++++++++++++++++
 1 file changed, 240 insertions(+)
 create mode 100644 src/backends/backendsCommon/test/layerTests/TransposeTestImpl.hpp

(limited to 'src/backends/backendsCommon/test/layerTests')

diff --git a/src/backends/backendsCommon/test/layerTests/TransposeTestImpl.hpp b/src/backends/backendsCommon/test/layerTests/TransposeTestImpl.hpp
new file mode 100644
index 0000000000..3949dcc142
--- /dev/null
+++ b/src/backends/backendsCommon/test/layerTests/TransposeTestImpl.hpp
@@ -0,0 +1,240 @@
+//
+// Copyright © 2020 Arm Ltd. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+
+#pragma once
+
+#include <ResolveType.hpp>
+
+
+#include <armnn/backends/IBackendInternal.hpp>
+#include <backendsCommon/WorkloadFactory.hpp>
+
+#include <backendsCommon/test/WorkloadTestUtils.hpp>
+
+#include <test/TensorHelpers.hpp>
+
+template<typename T>
+LayerTestResult<T, 4> SimpleTransposeTestImpl(
+        armnn::IWorkloadFactory& workloadFactory,
+        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
+        armnn::TransposeDescriptor descriptor,
+        armnn::TensorInfo inputTensorInfo,
+        armnn::TensorInfo outputTensorInfo,
+        const std::vector<T>& inputData,
+        const std::vector<T>& outputExpectedData)
+{
+    boost::ignore_unused(memoryManager);
+    auto input = MakeTensor<T, 4>(inputTensorInfo, inputData);
+
+    LayerTestResult<T, 4> ret(outputTensorInfo);
+    ret.outputExpected = MakeTensor<T, 4>(outputTensorInfo, outputExpectedData);
+
+    std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo);
+    std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo);
+
+    armnn::TransposeQueueDescriptor data;
+    data.m_Parameters = descriptor;
+    armnn::WorkloadInfo info;
+    AddInputToWorkload(data, info, inputTensorInfo, inputHandle.get());
+    AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get());
+
+    std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateTranspose(data, info);
+
+    inputHandle->Allocate();
+    outputHandle->Allocate();
+
+    CopyDataToITensorHandle(inputHandle.get(), &input[0][0][0][0]);
+
+    workload->Execute();
+
+    CopyDataFromITensorHandle(&ret.output[0][0][0][0], outputHandle.get());
+
+    return ret;
+}
+
+template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
+LayerTestResult<T, 4> SimpleTransposeTest(
+        armnn::IWorkloadFactory& workloadFactory,
+        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
+{
+    armnn::TensorInfo inputTensorInfo;
+    armnn::TensorInfo outputTensorInfo;
+
+    unsigned int inputShape[] = { 1, 2, 2, 2 };
+    unsigned int outputShape[] = { 1, 2, 2, 2 };
+
+    armnn::TransposeDescriptor descriptor;
+    descriptor.m_DimMappings = {0U, 2U, 3U, 1U};
+
+    inputTensorInfo = armnn::TensorInfo(4, inputShape, ArmnnType);
+    outputTensorInfo = armnn::TensorInfo(4, outputShape, ArmnnType);
+
+    // Set quantization parameters if the requested type is a quantized type.
+    if(armnn::IsQuantizedType<T>())
+    {
+        inputTensorInfo.SetQuantizationScale(0.5f);
+        inputTensorInfo.SetQuantizationOffset(5);
+        outputTensorInfo.SetQuantizationScale(0.5f);
+        outputTensorInfo.SetQuantizationOffset(5);
+    }
+
+    std::vector<T> input = std::vector<T>(
+    {
+        1, 2,
+        3, 4,
+        5, 6,
+        7, 8
+    });
+
+    std::vector<T> outputExpected = std::vector<T>(
+    {
+        1, 5, 2, 6,
+        3, 7, 4, 8
+    });
+
+    return SimpleTransposeTestImpl<T>(workloadFactory, memoryManager,
+                                    descriptor, inputTensorInfo,
+                                    outputTensorInfo, input, outputExpected);
+}
+
+template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
+LayerTestResult<T, 4> TransposeValueSet1Test(
+        armnn::IWorkloadFactory& workloadFactory,
+        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
+{
+    armnn::TensorInfo inputTensorInfo;
+    armnn::TensorInfo outputTensorInfo;
+
+    unsigned int inputShape[]  = { 1, 2, 2, 3 };
+    unsigned int outputShape[] = { 1, 3, 2, 2 };
+
+    armnn::TransposeDescriptor descriptor;
+    descriptor.m_DimMappings = {0U, 3U, 1U, 2U};
+
+    inputTensorInfo = armnn::TensorInfo(4, inputShape, ArmnnType);
+    outputTensorInfo = armnn::TensorInfo(4, outputShape, ArmnnType);
+
+    // Set quantization parameters if the requested type is a quantized type.
+    if(armnn::IsQuantizedType<T>())
+    {
+        inputTensorInfo.SetQuantizationScale(0.5f);
+        inputTensorInfo.SetQuantizationOffset(5);
+        outputTensorInfo.SetQuantizationScale(0.5f);
+        outputTensorInfo.SetQuantizationOffset(5);
+    }
+
+    std::vector<T> input = std::vector<T>(
+    {
+         1,  2,  3,
+        11, 12, 13,
+        21, 22, 23,
+        31, 32, 33
+    });
+
+    std::vector<T> outputExpected = std::vector<T>(
+    {
+        1, 11, 21, 31,
+        2, 12, 22, 32,
+        3, 13, 23, 33
+    });
+
+    return SimpleTransposeTestImpl<T>(workloadFactory, memoryManager,
+                                    descriptor, inputTensorInfo,
+                                    outputTensorInfo, input, outputExpected);
+}
+
+template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
+LayerTestResult<T, 4> TransposeValueSet2Test(
+        armnn::IWorkloadFactory& workloadFactory,
+        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
+{
+    armnn::TensorInfo inputTensorInfo;
+    armnn::TensorInfo outputTensorInfo;
+
+    unsigned int inputShape[]  = { 1, 3, 2, 2 };
+    unsigned int outputShape[] = { 1, 2, 2, 3 };
+
+    armnn::TransposeDescriptor descriptor;
+    descriptor.m_DimMappings = {0U, 2U, 3U, 1U};
+
+    inputTensorInfo = armnn::TensorInfo(4, inputShape, ArmnnType);
+    outputTensorInfo = armnn::TensorInfo(4, outputShape, ArmnnType);
+
+    // Set quantization parameters if the requested type is a quantized type.
+    if(armnn::IsQuantizedType<T>())
+    {
+        inputTensorInfo.SetQuantizationScale(0.5f);
+        inputTensorInfo.SetQuantizationOffset(5);
+        outputTensorInfo.SetQuantizationScale(0.5f);
+        outputTensorInfo.SetQuantizationOffset(5);
+    }
+
+    std::vector<T> input = std::vector<T>(
+    {
+        1, 11, 21, 31,
+        2, 12, 22, 32,
+        3, 13, 23, 33
+    });
+
+    std::vector<T> outputExpected = std::vector<T>(
+    {
+         1,  2,  3,
+        11, 12, 13,
+        21, 22, 23,
+        31, 32, 33,
+    });
+
+    return SimpleTransposeTestImpl<T>(workloadFactory, memoryManager,
+                                    descriptor, inputTensorInfo,
+                                    outputTensorInfo, input, outputExpected);
+}
+
+template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
+LayerTestResult<T, 4> TransposeValueSet3Test(
+        armnn::IWorkloadFactory& workloadFactory,
+        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
+{
+    armnn::TensorInfo inputTensorInfo;
+    armnn::TensorInfo outputTensorInfo;
+
+    unsigned int inputShape[]  = { 1, 2, 3, 3 };
+    unsigned int outputShape[] = { 1, 3, 2, 3 };
+
+    armnn::TransposeDescriptor descriptor;
+    descriptor.m_DimMappings = {0U, 3U, 1U, 2U};
+
+    inputTensorInfo = armnn::TensorInfo(4, inputShape, ArmnnType);
+    outputTensorInfo = armnn::TensorInfo(4, outputShape, ArmnnType);
+
+    // Set quantization parameters if the requested type is a quantized type.
+    if(armnn::IsQuantizedType<T>())
+    {
+        inputTensorInfo.SetQuantizationScale(0.5f);
+        inputTensorInfo.SetQuantizationOffset(5);
+        outputTensorInfo.SetQuantizationScale(0.5f);
+        outputTensorInfo.SetQuantizationOffset(5);
+    }
+
+    std::vector<T> input = std::vector<T>(
+    {
+         1,  2,  3,
+        11, 12, 13,
+        21, 22, 23,
+        31, 32, 33,
+        41, 42, 43,
+        51, 52, 53
+    });
+
+    std::vector<T> outputExpected = std::vector<T>(
+    {
+        1, 11, 21, 31, 41, 51,
+        2, 12, 22, 32, 42, 52,
+        3, 13, 23, 33, 43, 53
+    });
+
+    return SimpleTransposeTestImpl<T>(workloadFactory, memoryManager,
+                                      descriptor, inputTensorInfo,
+                                      outputTensorInfo, input, outputExpected);
+}
-- 
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