aboutsummaryrefslogtreecommitdiff
path: root/src/backends/backendsCommon/test/layerTests/PermuteTestImpl.hpp
diff options
context:
space:
mode:
authorAron Virginas-Tar <Aron.Virginas-Tar@arm.com>2019-08-28 18:08:46 +0100
committermike.kelly <mike.kelly@arm.com>2019-08-30 10:58:54 +0000
commit00d306e4db5153a4f4d280de4d4cf3e03788fefb (patch)
tree329c15f71c662e199a24dc0812bf95cb389ddbd8 /src/backends/backendsCommon/test/layerTests/PermuteTestImpl.hpp
parent08b518687d2bf2683a2c5f571d3e76d71d67d048 (diff)
downloadarmnn-00d306e4db5153a4f4d280de4d4cf3e03788fefb.tar.gz
IVGCVSW-3381 Break up LayerTests.hpp into more manageable files
Signed-off-by: Aron Virginas-Tar <Aron.Virginas-Tar@arm.com> Change-Id: Icf39434f09fd340ad664cb3b97b8bee6d9da4838
Diffstat (limited to 'src/backends/backendsCommon/test/layerTests/PermuteTestImpl.hpp')
-rw-r--r--src/backends/backendsCommon/test/layerTests/PermuteTestImpl.hpp241
1 files changed, 241 insertions, 0 deletions
diff --git a/src/backends/backendsCommon/test/layerTests/PermuteTestImpl.hpp b/src/backends/backendsCommon/test/layerTests/PermuteTestImpl.hpp
new file mode 100644
index 0000000000..ef48c9726f
--- /dev/null
+++ b/src/backends/backendsCommon/test/layerTests/PermuteTestImpl.hpp
@@ -0,0 +1,241 @@
+//
+// Copyright © 2017 Arm Ltd. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+
+#pragma once
+
+#include <ResolveType.hpp>
+
+#include <armnn/ArmNN.hpp>
+
+#include <backendsCommon/IBackendInternal.hpp>
+#include <backendsCommon/WorkloadFactory.hpp>
+
+#include <backendsCommon/test/QuantizeHelper.hpp>
+#include <backendsCommon/test/WorkloadTestUtils.hpp>
+
+#include <test/TensorHelpers.hpp>
+
+template<typename T>
+LayerTestResult<T, 4> SimplePermuteTestImpl(
+ armnn::IWorkloadFactory& workloadFactory,
+ const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
+ armnn::PermuteDescriptor descriptor,
+ armnn::TensorInfo inputTensorInfo,
+ armnn::TensorInfo outputTensorInfo,
+ const std::vector<T>& inputData,
+ const std::vector<T>& outputExpectedData)
+{
+ 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::PermuteQueueDescriptor 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.CreatePermute(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> SimplePermuteTest(
+ 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::PermuteDescriptor 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, 4,
+ 5, 6,
+ 7, 8
+ });
+
+ std::vector<T> outputExpected = std::vector<T>(
+ {
+ 1, 5, 2, 6,
+ 3, 7, 4, 8
+ });
+
+ return SimplePermuteTestImpl<T>(workloadFactory, memoryManager,
+ descriptor, inputTensorInfo,
+ outputTensorInfo, input, outputExpected);
+}
+
+template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
+LayerTestResult<T, 4> PermuteValueSet1Test(
+ 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::PermuteDescriptor 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,
+ 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 SimplePermuteTestImpl<T>(workloadFactory, memoryManager,
+ descriptor, inputTensorInfo,
+ outputTensorInfo, input, outputExpected);
+}
+
+template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
+LayerTestResult<T, 4> PermuteValueSet2Test(
+ 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::PermuteDescriptor 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, 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 SimplePermuteTestImpl<T>(workloadFactory, memoryManager,
+ descriptor, inputTensorInfo,
+ outputTensorInfo, input, outputExpected);
+}
+
+template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
+LayerTestResult<T, 4> PermuteValueSet3Test(
+ 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::PermuteDescriptor 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,
+ 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 SimplePermuteTestImpl<T>(workloadFactory, memoryManager,
+ descriptor, inputTensorInfo,
+ outputTensorInfo, input, outputExpected);
+}