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-rw-r--r--src/backends/backendsCommon/test/SplitterEndToEndTestImpl.hpp380
1 files changed, 380 insertions, 0 deletions
diff --git a/src/backends/backendsCommon/test/SplitterEndToEndTestImpl.hpp b/src/backends/backendsCommon/test/SplitterEndToEndTestImpl.hpp
new file mode 100644
index 0000000000..f9fbcf55cb
--- /dev/null
+++ b/src/backends/backendsCommon/test/SplitterEndToEndTestImpl.hpp
@@ -0,0 +1,380 @@
+//
+// Copyright © 2017 Arm Ltd. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+#pragma once
+
+#include <ResolveType.hpp>
+
+#include <armnn/INetwork.hpp>
+
+#include <backendsCommon/test/CommonTestUtils.hpp>
+
+#include <boost/test/unit_test.hpp>
+
+#include <vector>
+
+namespace
+{
+
+template<typename armnn::DataType DataType>
+INetworkPtr CreateSplitterNetwork(const TensorShape& inputShape,
+ const std::vector<TensorShape>& outputShapes,
+ unsigned int splitAxis,
+ unsigned int numSplit,
+ 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);
+
+ std::vector<unsigned int> splitterDimSizes(inputShape.GetNumDimensions());
+
+ // Add current input shape to splitterDimSizes
+ for (unsigned int i = 0; i < inputShape.GetNumDimensions(); ++i)
+ {
+ splitterDimSizes[i] = inputTensorInfo.GetShape()[i];
+ }
+
+ if (splitterDimSizes[splitAxis] % numSplit != 0)
+ {
+ throw ParseException("Number of splits must evenly divide the dimension");
+ }
+ splitterDimSizes[splitAxis] /= numSplit;
+
+ SplitterDescriptor splitDesc(numSplit);
+ for (unsigned int g = 0; g < numSplit; ++g)
+ {
+ // Set the size of the views.
+ for (unsigned int dimIdx = 0; dimIdx < splitterDimSizes.size(); ++dimIdx)
+ {
+ splitDesc.SetViewSize(g, dimIdx, splitterDimSizes[dimIdx]);
+ }
+ splitDesc.SetViewOriginCoord(g, splitAxis, splitterDimSizes[splitAxis] * g);
+ }
+
+ IConnectableLayer* splitter = net->AddSplitterLayer(splitDesc, "splitter");
+ IConnectableLayer* input = net->AddInputLayer(0, "input");
+ Connect(input, splitter, inputTensorInfo, 0, 0);
+
+ for (unsigned int i = 0; i < outputShapes.size(); ++i)
+ {
+ TensorInfo outputTensorInfo(outputShapes[i], DataType, qScale, qOffset);
+ IConnectableLayer* output = net->AddOutputLayer(boost::numeric_cast<LayerBindingId>(i));
+ Connect(splitter, output, outputTensorInfo, i, 0);
+ }
+
+ return net;
+}
+
+template<armnn::DataType ArmnnType>
+void SplitterDim0EndToEnd(const std::vector<BackendId>& backends)
+{
+ using namespace armnn;
+ using T = ResolveType<ArmnnType>;
+
+ unsigned int splitAxis = 0;
+ unsigned int numSplit = 2;
+ const TensorShape& inputShape = { 4, 3, 2, 2 };
+ const std::vector<TensorShape> outputShapes{{ 2, 3, 2, 2 }, { 2, 3, 2, 2 }};
+
+ // Builds up the structure of the network
+ INetworkPtr net = CreateSplitterNetwork<ArmnnType>(inputShape, outputShapes, splitAxis, numSplit);
+
+ BOOST_TEST_CHECKPOINT("create a network");
+
+ // Creates structures for input & output.
+ std::vector<T> inputData{
+ 1, 2,
+ 3, 4,
+ 5, 6,
+ 7, 8,
+ 9, 10,
+ 11, 12,
+ 13, 14,
+ 15, 16,
+ 17, 18,
+ 19, 20,
+ 21, 22,
+ 23, 24,
+ 25, 26,
+ 27, 28,
+ 29, 30,
+ 31, 32,
+ 33, 34,
+ 35, 36,
+ 37, 38,
+ 39, 40,
+ 41, 42,
+ 43, 44,
+ 45, 46,
+ 47, 48
+ };
+
+ std::vector<T> expectedOutput0{
+ 1, 2,
+ 3, 4,
+ 5, 6,
+ 7, 8,
+ 9, 10,
+ 11, 12,
+ 13, 14,
+ 15, 16,
+ 17, 18,
+ 19, 20,
+ 21, 22,
+ 23, 24
+ };
+
+ std::vector<T> expectedOutput1{
+ 25, 26,
+ 27, 28,
+ 29, 30,
+ 31, 32,
+ 33, 34,
+ 35, 36,
+ 37, 38,
+ 39, 40,
+ 41, 42,
+ 43, 44,
+ 45, 46,
+ 47, 48
+ };
+
+ std::map<int, std::vector<T>> inputTensorData = {{ 0,inputData }};
+ std::map<int, std::vector<T>> expectedOutputData = {{ 0, expectedOutput0 }, { 1, expectedOutput1 }};
+
+ EndToEndLayerTestImpl<ArmnnType, ArmnnType>(move(net), inputTensorData, expectedOutputData, backends);
+}
+
+template<armnn::DataType ArmnnType>
+void SplitterDim1EndToEnd(const std::vector<BackendId>& backends)
+{
+ using namespace armnn;
+ using T = ResolveType<ArmnnType>;
+
+ unsigned int splitAxis = 1;
+ unsigned int numSplit = 2;
+ const TensorShape& inputShape = { 2, 6, 2, 2 };
+ const std::vector<TensorShape> outputShapes{{ 2, 3, 2, 2 }, { 2, 3, 2, 2 }};
+
+ // Builds up the structure of the network
+ INetworkPtr net = CreateSplitterNetwork<ArmnnType>(inputShape, outputShapes, splitAxis, numSplit);
+
+ BOOST_TEST_CHECKPOINT("create a network");
+
+ // Creates structures for input & output.
+ std::vector<T> inputData{
+ 1, 2,
+ 3, 4,
+ 5, 6,
+ 7, 8,
+ 9, 10,
+ 11, 12,
+ 13, 14,
+ 15, 16,
+ 17, 18,
+ 19, 20,
+ 21, 22,
+ 23, 24,
+ 25, 26,
+ 27, 28,
+ 29, 30,
+ 31, 32,
+ 33, 34,
+ 35, 36,
+ 37, 38,
+ 39, 40,
+ 41, 42,
+ 43, 44,
+ 45, 46,
+ 47, 48
+ };
+
+ std::vector<T> expectedOutput0{
+ 1, 2,
+ 3, 4,
+ 5, 6,
+ 7, 8,
+ 9, 10,
+ 11, 12,
+ 25, 26,
+ 27, 28,
+ 29, 30,
+ 31, 32,
+ 33, 34,
+ 35, 36
+ };
+
+ std::vector<T> expectedOutput1{
+ 13, 14,
+ 15, 16,
+ 17, 18,
+ 19, 20,
+ 21, 22,
+ 23, 24,
+ 37, 38,
+ 39, 40,
+ 41, 42,
+ 43, 44,
+ 45, 46,
+ 47, 48
+ };
+
+ std::map<int, std::vector<T>> inputTensorData = {{ 0,inputData }};
+ std::map<int, std::vector<T>> expectedOutputData = {{ 0, expectedOutput0 }, { 1, expectedOutput1 }};
+
+ EndToEndLayerTestImpl<ArmnnType, ArmnnType>(move(net), inputTensorData, expectedOutputData, backends);
+}
+
+template<armnn::DataType ArmnnType>
+void SplitterDim2EndToEnd(const std::vector<BackendId>& backends)
+{
+ using namespace armnn;
+ using T = ResolveType<ArmnnType>;
+
+ unsigned int splitAxis = 2;
+ unsigned int numSplit = 2;
+ const TensorShape& inputShape = { 2, 3, 4, 2 };
+ const std::vector<TensorShape> outputShapes{{ 2, 3, 2, 2 }, { 2, 3, 2, 2 }};
+
+ // Builds up the structure of the network
+ INetworkPtr net = CreateSplitterNetwork<ArmnnType>(inputShape, outputShapes, splitAxis, numSplit);
+
+ BOOST_TEST_CHECKPOINT("create a network");
+
+ // Creates structures for input & output.
+ std::vector<T> inputData{
+ 1, 2,
+ 3, 4,
+ 5, 6,
+ 7, 8,
+ 9, 10,
+ 11, 12,
+ 13, 14,
+ 15, 16,
+ 17, 18,
+ 19, 20,
+ 21, 22,
+ 23, 24,
+ 25, 26,
+ 27, 28,
+ 29, 30,
+ 31, 32,
+ 33, 34,
+ 35, 36,
+ 37, 38,
+ 39, 40,
+ 41, 42,
+ 43, 44,
+ 45, 46,
+ 47, 48
+ };
+
+ std::vector<T> expectedOutput0{
+ 1, 2,
+ 3, 4,
+ 9, 10,
+ 11, 12,
+ 17, 18,
+ 19, 20,
+ 25, 26,
+ 27, 28,
+ 33, 34,
+ 35, 36,
+ 41, 42,
+ 43, 44
+ };
+
+ std::vector<T> expectedOutput1{
+ 5, 6,
+ 7, 8,
+ 13, 14,
+ 15, 16,
+ 21, 22,
+ 23, 24,
+ 29, 30,
+ 31, 32,
+ 37, 38,
+ 39, 40,
+ 45, 46,
+ 47, 48
+ };
+
+ std::map<int, std::vector<T>> inputTensorData = {{ 0,inputData }};
+ std::map<int, std::vector<T>> expectedOutputData = {{ 0, expectedOutput0 }, { 1, expectedOutput1 }};
+
+ EndToEndLayerTestImpl<ArmnnType, ArmnnType>(move(net), inputTensorData, expectedOutputData, backends);
+}
+
+template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
+void SplitterDim3EndToEnd(const std::vector<BackendId>& backends)
+{
+ using namespace armnn;
+
+ unsigned int splitAxis = 3;
+ unsigned int numSplit = 2;
+ const TensorShape& inputShape = { 2, 3, 4, 2 };
+ const std::vector<TensorShape> outputShapes{{ 2, 3, 4, 1 }, { 2, 3, 4, 1 }};
+
+ // Builds up the structure of the network
+ INetworkPtr net = CreateSplitterNetwork<ArmnnType>(inputShape, outputShapes, splitAxis, numSplit);
+
+ BOOST_TEST_CHECKPOINT("create a network");
+
+ // Creates structures for input & output.
+ std::vector<T> inputData{
+ 1, 2,
+ 3, 4,
+ 5, 6,
+ 7, 8,
+ 9, 10,
+ 11, 12,
+ 13, 14,
+ 15, 16,
+ 17, 18,
+ 19, 20,
+ 21, 22,
+ 23, 24,
+ 25, 26,
+ 27, 28,
+ 29, 30,
+ 31, 32,
+ 33, 34,
+ 35, 36,
+ 37, 38,
+ 39, 40,
+ 41, 42,
+ 43, 44,
+ 45, 46,
+ 47, 48
+ };
+
+ std::vector<T> expectedOutput0{
+ 1, 3, 5, 7,
+ 9, 11, 13, 15,
+ 17, 19, 21, 23,
+ 25, 27, 29, 31,
+ 33, 35, 37, 39,
+ 41, 43, 45, 47
+ };
+
+ std::vector<T> expectedOutput1{
+ 2, 4, 6, 8,
+ 10, 12, 14, 16,
+ 18, 20, 22, 24,
+ 26, 28, 30, 32,
+ 34, 36, 38, 40,
+ 42, 44, 46, 48
+ };
+
+ std::map<int, std::vector<T>> inputTensorData = {{ 0,inputData }};
+ std::map<int, std::vector<T>> expectedOutputData = {{ 0, expectedOutput0 }, { 1, expectedOutput1 }};
+
+ EndToEndLayerTestImpl<ArmnnType, ArmnnType>(move(net), inputTensorData, expectedOutputData, backends);
+}
+
+} // anonymous namespace
generated by cgit v1.2.1 (git 2.23.0) at 2024-06-06 21:48:17 +0000