IVGCVSW-2765 Modify ParserFlatBuffersSerilizeFixture to accept different output type
Change-Id: Ia61e25e7375f7c58db6b0cf6389af151ac004f4c
Signed-off-by: Nattapat Chaimanowong <nattapat.chaimanowong@arm.com>
diff --git a/src/armnnDeserializer/test/ParserFlatbuffersSerializeFixture.hpp b/src/armnnDeserializer/test/ParserFlatbuffersSerializeFixture.hpp
index 8db9d56..7baa010 100644
--- a/src/armnnDeserializer/test/ParserFlatbuffersSerializeFixture.hpp
+++ b/src/armnnDeserializer/test/ParserFlatbuffersSerializeFixture.hpp
@@ -116,22 +116,40 @@
/// 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,
- armnn::DataType ArmnnType,
- typename DataType = armnn::ResolveType<ArmnnType>>
+ template<std::size_t NumOutputDimensions,
+ armnn::DataType ArmnnType,
+ typename DataType = armnn::ResolveType<ArmnnType>>
void RunTest(unsigned int layersId,
const std::vector<DataType>& inputData,
const std::vector<DataType>& expectedOutputData);
+ template<std::size_t NumOutputDimensions,
+ armnn::DataType ArmnnInputType,
+ armnn::DataType ArmnnOutputType,
+ typename InputDataType = armnn::ResolveType<ArmnnInputType>,
+ typename OutputDataType = armnn::ResolveType<ArmnnOutputType>>
+ void RunTest(unsigned int layersId,
+ const std::vector<InputDataType>& inputData,
+ const std::vector<OutputDataType>& 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,
- armnn::DataType ArmnnType,
- typename DataType = armnn::ResolveType<ArmnnType>>
+ template<std::size_t NumOutputDimensions,
+ armnn::DataType ArmnnType,
+ typename DataType = armnn::ResolveType<ArmnnType>>
void RunTest(unsigned int layersId,
const std::map<std::string, std::vector<DataType>>& inputData,
const std::map<std::string, std::vector<DataType>>& expectedOutputData);
+ template<std::size_t NumOutputDimensions,
+ armnn::DataType ArmnnInputType,
+ armnn::DataType ArmnnOutputType,
+ typename InputDataType = armnn::ResolveType<ArmnnInputType>,
+ typename OutputDataType = armnn::ResolveType<ArmnnOutputType>>
+ void RunTest(unsigned int layersId,
+ const std::map<std::string, std::vector<InputDataType>>& inputData,
+ const std::map<std::string, std::vector<OutputDataType>>& expectedOutputData);
+
void CheckTensors(const TensorRawPtr& tensors, size_t shapeSize, const std::vector<int32_t>& shape,
armnnSerializer::TensorInfo tensorType, const std::string& name,
const float scale, const int64_t zeroPoint)
@@ -145,25 +163,46 @@
}
};
-template <std::size_t NumOutputDimensions,
- armnn::DataType ArmnnType,
- typename DataType>
+template<std::size_t NumOutputDimensions, armnn::DataType ArmnnType, typename DataType>
void ParserFlatbuffersSerializeFixture::RunTest(unsigned int layersId,
const std::vector<DataType>& inputData,
const std::vector<DataType>& expectedOutputData)
{
- RunTest<NumOutputDimensions, ArmnnType>(layersId,
- { { m_SingleInputName, inputData } },
- { { m_SingleOutputName, expectedOutputData } });
+ RunTest<NumOutputDimensions, ArmnnType, ArmnnType, DataType, DataType>(layersId, inputData, expectedOutputData);
}
-template <std::size_t NumOutputDimensions,
- armnn::DataType ArmnnType,
- typename DataType>
+template<std::size_t NumOutputDimensions,
+ armnn::DataType ArmnnInputType,
+ armnn::DataType ArmnnOutputType,
+ typename InputDataType,
+ typename OutputDataType>
+void ParserFlatbuffersSerializeFixture::RunTest(unsigned int layersId,
+ const std::vector<InputDataType>& inputData,
+ const std::vector<OutputDataType>& expectedOutputData)
+{
+ RunTest<NumOutputDimensions, ArmnnInputType, ArmnnOutputType>(layersId,
+ { { m_SingleInputName, inputData } },
+ { { m_SingleOutputName, expectedOutputData } });
+}
+
+template<std::size_t NumOutputDimensions, armnn::DataType ArmnnType, typename DataType>
void ParserFlatbuffersSerializeFixture::RunTest(unsigned int layersId,
const std::map<std::string, std::vector<DataType>>& inputData,
const std::map<std::string, std::vector<DataType>>& expectedOutputData)
{
+ RunTest<NumOutputDimensions, ArmnnType, ArmnnType, DataType, DataType>(layersId, inputData, expectedOutputData);
+}
+
+template<std::size_t NumOutputDimensions,
+ armnn::DataType ArmnnInputType,
+ armnn::DataType ArmnnOutputType,
+ typename InputDataType,
+ typename OutputDataType>
+void ParserFlatbuffersSerializeFixture::RunTest(
+ unsigned int layersId,
+ const std::map<std::string, std::vector<InputDataType>>& inputData,
+ const std::map<std::string, std::vector<OutputDataType>>& expectedOutputData)
+{
using BindingPointInfo = std::pair<armnn::LayerBindingId, armnn::TensorInfo>;
auto ConvertBindingInfo = [](const armnnDeserializer::BindingPointInfo& bindingInfo)
@@ -176,18 +215,18 @@
for (auto&& it : inputData)
{
BindingPointInfo bindingInfo = ConvertBindingInfo(m_Parser->GetNetworkInputBindingInfo(layersId, it.first));
- armnn::VerifyTensorInfoDataType(bindingInfo.second, ArmnnType);
+ armnn::VerifyTensorInfoDataType(bindingInfo.second, ArmnnInputType);
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<DataType, NumOutputDimensions>> outputStorage;
+ std::map<std::string, boost::multi_array<OutputDataType, NumOutputDimensions>> outputStorage;
armnn::OutputTensors outputTensors;
for (auto&& it : expectedOutputData)
{
BindingPointInfo bindingInfo = ConvertBindingInfo(m_Parser->GetNetworkOutputBindingInfo(layersId, it.first));
- armnn::VerifyTensorInfoDataType(bindingInfo.second, ArmnnType);
- outputStorage.emplace(it.first, MakeTensor<DataType, NumOutputDimensions>(bindingInfo.second));
+ armnn::VerifyTensorInfoDataType(bindingInfo.second, ArmnnOutputType);
+ outputStorage.emplace(it.first, MakeTensor<OutputDataType, NumOutputDimensions>(bindingInfo.second));
outputTensors.push_back(
{ bindingInfo.first, armnn::Tensor(bindingInfo.second, outputStorage.at(it.first).data()) });
}
@@ -198,7 +237,7 @@
for (auto&& it : expectedOutputData)
{
BindingPointInfo bindingInfo = ConvertBindingInfo(m_Parser->GetNetworkOutputBindingInfo(layersId, it.first));
- auto outputExpected = MakeTensor<DataType, NumOutputDimensions>(bindingInfo.second, it.second);
+ auto outputExpected = MakeTensor<OutputDataType, NumOutputDimensions>(bindingInfo.second, it.second);
BOOST_TEST(CompareTensors(outputExpected, outputStorage[it.first]));
}
}