Release 18.02
Change-Id: Id3c11dc5ee94ef664374a988fcc6901e9a232fa6
diff --git a/src/armnnUtils/ParserPrototxtFixture.hpp b/src/armnnUtils/ParserPrototxtFixture.hpp
new file mode 100644
index 0000000..0e34477
--- /dev/null
+++ b/src/armnnUtils/ParserPrototxtFixture.hpp
@@ -0,0 +1,134 @@
+//
+// Copyright © 2017 Arm Ltd. All rights reserved.
+// See LICENSE file in the project root for full license information.
+//
+
+#pragma once
+
+#include "armnn/IRuntime.hpp"
+#include "test/TensorHelpers.hpp"
+#include <string>
+
+template<typename TParser>
+struct ParserPrototxtFixture
+{
+ ParserPrototxtFixture()
+ : m_Parser(TParser::Create())
+ , m_Runtime(armnn::IRuntime::Create(armnn::Compute::CpuRef))
+ , m_NetworkIdentifier(-1)
+ {}
+
+ /// Parses and loads the network defined by the m_Prototext string.
+ /// @{
+ void SetupSingleInputSingleOutput(const std::string& inputName, const std::string& outputName);
+ void SetupSingleInputSingleOutput(const armnn::TensorShape& inputTensorShape,
+ const std::string& inputName,
+ const std::string& outputName);
+ void Setup(const std::map<std::string, armnn::TensorShape>& inputShapes,
+ const std::vector<std::string>& requestedOutputs);
+ /// @}
+
+ /// Executes the network with the given input tensor and checks the result against the given output tensor.
+ /// This overload assumes the network has a single input and a single output.
+ template <std::size_t NumOutputDimensions>
+ void RunTest(const std::vector<float>& inputData, const std::vector<float>& expectedOutputData);
+
+ /// Executes the network with the given input tensors and checks the results against the given output tensors.
+ /// This overload supports multiple inputs and multiple outputs, identified by name.
+ template <std::size_t NumOutputDimensions>
+ void RunTest(const std::map<std::string, std::vector<float>>& inputData,
+ const std::map<std::string, std::vector<float>>& expectedOutputData);
+
+ std::string m_Prototext;
+ std::unique_ptr<TParser, void(*)(TParser* parser)> m_Parser;
+ armnn::IRuntimePtr m_Runtime;
+ armnn::NetworkId m_NetworkIdentifier;
+
+ /// If the single-input-single-output overload of Setup() is called, these will store the input and output name
+ /// so they don't need to be passed to the single-input-single-output overload of RunTest().
+ /// @{
+ std::string m_SingleInputName;
+ std::string m_SingleOutputName;
+ /// @}
+};
+
+template<typename TParser>
+void ParserPrototxtFixture<TParser>::SetupSingleInputSingleOutput(const std::string& inputName,
+ const std::string& outputName)
+{
+ // Store the input and output name so they don't need to be passed to the single-input-single-output RunTest().
+ m_SingleInputName = inputName;
+ m_SingleOutputName = outputName;
+ Setup({ }, { outputName });
+}
+
+template<typename TParser>
+void ParserPrototxtFixture<TParser>::SetupSingleInputSingleOutput(const armnn::TensorShape& inputTensorShape,
+ const std::string& inputName,
+ const std::string& outputName)
+{
+ // Store the input and output name so they don't need to be passed to the single-input-single-output RunTest().
+ m_SingleInputName = inputName;
+ m_SingleOutputName = outputName;
+ Setup({ { inputName, inputTensorShape } }, { outputName });
+}
+
+template<typename TParser>
+void ParserPrototxtFixture<TParser>::Setup(const std::map<std::string, armnn::TensorShape>& inputShapes,
+ const std::vector<std::string>& requestedOutputs)
+{
+ armnn::INetworkPtr network =
+ m_Parser->CreateNetworkFromString(m_Prototext.c_str(), inputShapes, requestedOutputs);
+
+ auto optimized = Optimize(*network, m_Runtime->GetDeviceSpec());
+ armnn::Status ret = m_Runtime->LoadNetwork(m_NetworkIdentifier, move(optimized));
+ if (ret != armnn::Status::Success)
+ {
+ throw armnn::Exception("LoadNetwork failed");
+ }
+}
+
+template<typename TParser>
+template <std::size_t NumOutputDimensions>
+void ParserPrototxtFixture<TParser>::RunTest(const std::vector<float>& inputData,
+ const std::vector<float>& expectedOutputData)
+{
+ RunTest<NumOutputDimensions>({ { m_SingleInputName, inputData } }, { { m_SingleOutputName, expectedOutputData } });
+}
+
+template<typename TParser>
+template <std::size_t NumOutputDimensions>
+void ParserPrototxtFixture<TParser>::RunTest(const std::map<std::string, std::vector<float>>& inputData,
+ const std::map<std::string, std::vector<float>>& expectedOutputData)
+{
+ using BindingPointInfo = std::pair<armnn::LayerBindingId, armnn::TensorInfo>;
+
+ // Setup the armnn input tensors from the given vectors.
+ armnn::InputTensors inputTensors;
+ for (auto&& it : inputData)
+ {
+ BindingPointInfo bindingInfo = m_Parser->GetNetworkInputBindingInfo(it.first);
+ inputTensors.push_back({ bindingInfo.first, armnn::ConstTensor(bindingInfo.second, it.second.data()) });
+ }
+
+ // Allocate storage for the output tensors to be written to and setup the armnn output tensors.
+ std::map<std::string, boost::multi_array<float, NumOutputDimensions>> outputStorage;
+ armnn::OutputTensors outputTensors;
+ for (auto&& it : expectedOutputData)
+ {
+ BindingPointInfo bindingInfo = m_Parser->GetNetworkOutputBindingInfo(it.first);
+ outputStorage.emplace(it.first, MakeTensor<float, NumOutputDimensions>(bindingInfo.second));
+ outputTensors.push_back(
+ { bindingInfo.first, armnn::Tensor(bindingInfo.second, outputStorage.at(it.first).data()) });
+ }
+
+ m_Runtime->EnqueueWorkload(m_NetworkIdentifier, inputTensors, outputTensors);
+
+ // Compare each output tensor to the expected values
+ for (auto&& it : expectedOutputData)
+ {
+ BindingPointInfo bindingInfo = m_Parser->GetNetworkOutputBindingInfo(it.first);
+ auto outputExpected = MakeTensor<float, NumOutputDimensions>(bindingInfo.second, it.second);
+ BOOST_TEST(CompareTensors(outputExpected, outputStorage[it.first]));
+ }
+}