IVGCVSW-3263 - Add End to End tests for SpaceToDepth on Ref
Change-Id: I35d1c06b34ca160895f902255a69b87b711275b7
Signed-off-by: Keith Davis <keith.davis@arm.com>
diff --git a/src/backends/backendsCommon/test/CMakeLists.txt b/src/backends/backendsCommon/test/CMakeLists.txt
index 7819cfe..caf2dd3 100644
--- a/src/backends/backendsCommon/test/CMakeLists.txt
+++ b/src/backends/backendsCommon/test/CMakeLists.txt
@@ -45,6 +45,7 @@
RuntimeTestImpl.hpp
SoftmaxTestImpl.hpp
SpaceToDepthTestImpl.hpp
+ SpaceToDepthEndToEndTestImpl.hpp
SplitterEndToEndTestImpl.hpp
SplitterTestImpl.hpp
StridedSliceTestImpl.hpp
diff --git a/src/backends/backendsCommon/test/SpaceToDepthEndToEndTestImpl.hpp b/src/backends/backendsCommon/test/SpaceToDepthEndToEndTestImpl.hpp
new file mode 100644
index 0000000..456af4c
--- /dev/null
+++ b/src/backends/backendsCommon/test/SpaceToDepthEndToEndTestImpl.hpp
@@ -0,0 +1,106 @@
+//
+// Copyright © 2017 Arm Ltd. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+#pragma once
+
+#include "ResolveType.hpp"
+#include "DataLayoutIndexed.hpp"
+#include "EndToEndTestImpl.hpp"
+
+#include "armnn/INetwork.hpp"
+
+#include "backendsCommon/test/CommonTestUtils.hpp"
+
+#include <Permute.hpp>
+#include <boost/test/unit_test.hpp>
+
+#include <vector>
+
+namespace
+{
+template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
+void PermuteDataToNCHW(const std::vector<armnn::BackendId>& backends,
+ const armnn::DataLayout& dataLayout,
+ TensorInfo& tensorInfo,
+ std::vector<T>& data)
+{
+ const armnn::PermutationVector NHWCToNCHW = {0, 2, 3, 1};
+
+ tensorInfo = armnnUtils::Permuted(tensorInfo, NHWCToNCHW);
+
+ std::vector<T> tmp(data.size());
+ armnnUtils::Permute(tensorInfo.GetShape(), NHWCToNCHW, data.data(), tmp.data(), sizeof(T));
+
+ data = tmp;
+}
+
+template<typename armnn::DataType DataType>
+armnn::INetworkPtr CreateSpaceToDepthNetwork(const armnn::TensorShape& inputShape,
+ const armnn::TensorShape& outputShape,
+ const armnn::DataLayout dataLayout,
+ unsigned int blockSize,
+ const float qScale = 1.0f,
+ const int32_t qOffset = 0)
+{
+ using namespace armnn;
+ // Builds up the structure of the network.
+ INetworkPtr net(INetwork::Create());
+
+ TensorInfo inputTensorInfo(inputShape, DataType, qScale, qOffset);
+
+ armnnUtils::DataLayoutIndexed dimensionIndices(dataLayout);
+ if (inputShape[dimensionIndices.GetHeightIndex()] % blockSize!=0
+ || inputShape[dimensionIndices.GetWidthIndex()] % blockSize!=0)
+ {
+ throw InvalidArgumentException("Input shape must be divisible by block size in all spatial dimensions");
+ }
+
+ SpaceToDepthDescriptor spaceToDepthDesc;
+ spaceToDepthDesc.m_BlockSize = blockSize;
+ spaceToDepthDesc.m_DataLayout = dataLayout;
+
+ IConnectableLayer* SpaceToDepth = net->AddSpaceToDepthLayer(spaceToDepthDesc, "SpaceToDepth");
+ IConnectableLayer* input = net->AddInputLayer(0, "input");
+ Connect(input, SpaceToDepth, inputTensorInfo, 0, 0);
+
+ TensorInfo outputTensorInfo(outputShape, DataType, qScale, qOffset);
+ IConnectableLayer* output = net->AddOutputLayer(0, "output");
+ Connect(SpaceToDepth, output, outputTensorInfo, 0, 0);
+
+ return net;
+}
+
+void SpaceToDepthEndToEnd(const std::vector<armnn::BackendId>& backends,
+ const armnn::DataLayout& dataLayout,
+ TensorInfo& inputTensorInfo,
+ TensorInfo& outputTensorInfo,
+ std::vector<float>& inputData,
+ std::vector<float>& expectedOutputData,
+ const unsigned int blockSize)
+{
+ using namespace armnn;
+
+ if (dataLayout == armnn::DataLayout::NCHW){
+ PermuteDataToNCHW<armnn::DataType::Float32>(backends, dataLayout, inputTensorInfo, inputData);
+ PermuteDataToNCHW<armnn::DataType::Float32>(backends, dataLayout, outputTensorInfo, expectedOutputData);
+ }
+
+ // Builds up the structure of the network
+ INetworkPtr net = CreateSpaceToDepthNetwork<armnn::DataType::Float32>(inputTensorInfo.GetShape(),
+ outputTensorInfo.GetShape(),
+ dataLayout,
+ blockSize);
+
+ BOOST_TEST_CHECKPOINT("Create a network");
+
+ std::map<int, std::vector<float>> inputTensorData = { { 0, inputData } };
+ std::map<int, std::vector<float>> expectedOutputTensorData = { { 0, expectedOutputData } };
+
+ EndToEndLayerTestImpl<armnn::DataType::Float32, armnn::DataType::Float32>(move(net),
+ inputTensorData,
+ expectedOutputTensorData,
+ backends);
+}
+
+} // anonymous namespace
diff --git a/src/backends/reference/test/RefEndToEndTests.cpp b/src/backends/reference/test/RefEndToEndTests.cpp
index 885773d..be73116 100644
--- a/src/backends/reference/test/RefEndToEndTests.cpp
+++ b/src/backends/reference/test/RefEndToEndTests.cpp
@@ -10,6 +10,7 @@
#include <backendsCommon/test/GatherEndToEndTestImpl.hpp>
#include <backendsCommon/test/ConcatTestImpl.hpp>
#include <backendsCommon/test/ArithmeticTestImpl.hpp>
+#include <backendsCommon/test/SpaceToDepthEndToEndTestImpl.hpp>
#include <backendsCommon/test/SplitterEndToEndTestImpl.hpp>
#include <boost/test/unit_test.hpp>
@@ -641,6 +642,123 @@
1.0f, 1, 0.01f, 0, 0.5f, 0);
}
+BOOST_AUTO_TEST_CASE(RefSpaceToDepthNHWCEndToEndTest1)
+{
+ const unsigned int blockSize = 2;
+
+ armnn::TensorShape inputShape{1, 2, 2, 1};
+ armnn::TensorInfo inputTensorInfo(inputShape, armnn::DataType::Float32);
+
+ armnn::TensorShape outputShape{1, 1, 1, 4};
+ armnn::TensorInfo outputTensorInfo(outputShape, armnn::DataType::Float32);
+
+ std::vector<float> inputData = std::vector<float>(
+ {
+ 1.0f, 2.0f, 3.0f, 4.0f
+ });
+
+ std::vector<float> expectedOutputData = std::vector<float>(
+ {
+ 1.0f, 2.0f, 3.0f, 4.0f
+ });
+
+ SpaceToDepthEndToEnd(defaultBackends,
+ armnn::DataLayout::NHWC,
+ inputTensorInfo,
+ outputTensorInfo,
+ inputData,
+ expectedOutputData,
+ blockSize);
+}
+
+BOOST_AUTO_TEST_CASE(RefSpaceToDepthNCHWEndToEndTest1)
+{
+ const unsigned int blockSize = 2;
+
+ armnn::TensorShape inputShape{1, 2, 2, 1};
+ armnn::TensorInfo inputTensorInfo(inputShape, armnn::DataType::Float32);
+
+ armnn::TensorShape outputShape{1, 1, 1, 4};
+ armnn::TensorInfo outputTensorInfo(outputShape, armnn::DataType::Float32);
+
+ std::vector<float> inputData = std::vector<float>(
+ {
+ 1.0f, 2.0f, 3.0f, 4.0f
+ });
+
+ std::vector<float> expectedOutputData = std::vector<float>(
+ {
+ 1.0f, 2.0f, 3.0f, 4.0f
+ });
+
+ SpaceToDepthEndToEnd(defaultBackends,
+ armnn::DataLayout::NCHW,
+ inputTensorInfo,
+ outputTensorInfo,
+ inputData,
+ expectedOutputData,
+ blockSize);
+}
+
+BOOST_AUTO_TEST_CASE(RefSpaceToDepthNHWCEndToEndTest2)
+{
+ const unsigned int blockSize = 2;
+
+ armnn::TensorShape inputShape{1, 2, 2, 2};
+ armnn::TensorShape outputShape{1, 1, 1, 8};
+
+ armnn::TensorInfo outputTensorInfo(outputShape, armnn::DataType::Float32);
+ armnn::TensorInfo inputTensorInfo(inputShape, armnn::DataType::Float32);
+
+ std::vector<float> inputData = std::vector<float>(
+ {
+ 1.4f, 2.3f, 3.2f, 4.1f, 5.4f, 6.3f, 7.2f, 8.1f
+ });
+
+ std::vector<float> expectedOutputData = std::vector<float>(
+ {
+ 1.4f, 2.3f, 3.2f, 4.1f, 5.4f, 6.3f, 7.2f, 8.1f
+ });
+
+ SpaceToDepthEndToEnd(defaultBackends,
+ armnn::DataLayout::NHWC,
+ inputTensorInfo,
+ outputTensorInfo,
+ inputData,
+ expectedOutputData,
+ blockSize);
+}
+
+BOOST_AUTO_TEST_CASE(RefSpaceToDepthNCHWEndToEndTest2)
+{
+ const unsigned int blockSize = 2;
+
+ armnn::TensorShape inputShape{1, 2, 2, 2};
+ armnn::TensorShape outputShape{1, 1, 1, 8};
+
+ armnn::TensorInfo inputTensorInfo(inputShape, armnn::DataType::Float32);
+ armnn::TensorInfo outputTensorInfo(outputShape, armnn::DataType::Float32);
+
+
+ std::vector<float> inputData = std::vector<float>(
+ {
+ 1.4f, 2.3f, 3.2f, 4.1f, 5.4f, 6.3f, 7.2f, 8.1f
+ });
+
+ std::vector<float> expectedOutputData = std::vector<float>(
+ {
+ 1.4f, 2.3f, 3.2f, 4.1f, 5.4f, 6.3f, 7.2f, 8.1f
+ });
+
+ SpaceToDepthEndToEnd(defaultBackends,
+ armnn::DataLayout::NCHW,
+ inputTensorInfo,
+ outputTensorInfo,
+ inputData,
+ expectedOutputData,
+ blockSize);
+}
+
BOOST_AUTO_TEST_CASE(RefSplitter1dEndToEndTest)
{
Splitter1dEndToEnd<armnn::DataType::Float32>(defaultBackends);