IVGCVSW-2629 Adding support for uint8 in ExecuteNetwork to fix issues with output tensor being all zero
Change-Id: I4da1ffd684672fff0853fb053c3340d06a3bc165
Signed-off-by: Éanna Ó Catháin <eanna.ocathain@arm.com>
diff --git a/tests/ExecuteNetwork/ExecuteNetwork.cpp b/tests/ExecuteNetwork/ExecuteNetwork.cpp
index c040c9b..8904d13 100644
--- a/tests/ExecuteNetwork/ExecuteNetwork.cpp
+++ b/tests/ExecuteNetwork/ExecuteNetwork.cpp
@@ -125,33 +125,51 @@
CheckOptionDependency(vm, "input-tensor-shape", "model-path");
}
-template<typename T>
-std::vector<T> ParseArray(std::istream& stream);
+template<armnn::DataType NonQuantizedType>
+auto ParseDataArray(std::istream & stream);
+
+template<armnn::DataType QuantizedType>
+auto ParseDataArray(std::istream& stream,
+ const float& quantizationScale,
+ const int32_t& quantizationOffset);
template<>
-std::vector<float> ParseArray(std::istream& stream)
+auto ParseDataArray<armnn::DataType::Float32>(std::istream & stream)
{
return ParseArrayImpl<float>(stream, [](const std::string& s) { return std::stof(s); });
}
template<>
+auto ParseDataArray<armnn::DataType::Signed32>(std::istream & stream)
+{
+ return ParseArrayImpl<int>(stream, [](const std::string & s) { return std::stoi(s); });
+}
+
+template<>
+auto ParseDataArray<armnn::DataType::QuantisedAsymm8>(std::istream& stream,
+ const float& quantizationScale,
+ const int32_t& quantizationOffset)
+{
+ return ParseArrayImpl<uint8_t>(stream,
+ [&quantizationScale, &quantizationOffset](const std::string & s)
+ {
+ return boost::numeric_cast<uint8_t>(
+ armnn::Quantize<u_int8_t>(std::stof(s),
+ quantizationScale,
+ quantizationOffset));
+ });
+}
+
std::vector<unsigned int> ParseArray(std::istream& stream)
{
return ParseArrayImpl<unsigned int>(stream,
[](const std::string& s) { return boost::numeric_cast<unsigned int>(std::stoi(s)); });
}
-template<>
-std::vector<int> ParseArray(std::istream& stream)
-{
- return ParseArrayImpl<int>(stream, [](const std::string& s) { return std::stoi(s); });
-}
-
-std::vector<std::string> ParseInputString(const std::string& inputString, const char * chars)
+std::vector<std::string> ParseStringList(const std::string & inputString, const char * delimiter)
{
std::stringstream stream(inputString);
-
- return ParseArrayImpl<std::string>(stream, [](const std::string& s) { return boost::trim_copy(s); }, chars);
+ return ParseArrayImpl<std::string>(stream, [](const std::string& s) { return boost::trim_copy(s); }, delimiter);
}
void RemoveDuplicateDevices(std::vector<armnn::BackendId>& computeDevices)
@@ -183,6 +201,7 @@
const std::vector<std::unique_ptr<armnn::TensorShape>>& inputTensorShapes,
const std::vector<string>& inputTensorDataFilePaths,
const std::vector<string>& inputTypes,
+ const std::vector<string>& outputTypes,
const std::vector<string>& outputNames,
bool enableProfiling,
const size_t subgraphId,
@@ -192,27 +211,6 @@
std::vector<TContainer> inputDataContainers;
- for(unsigned int i = 0; i < inputTensorDataFilePaths.size(); ++i)
- {
- std::ifstream inputTensorFile(inputTensorDataFilePaths[i]);
-
- if (inputTypes[i].compare("float") == 0)
- {
- inputDataContainers.push_back(ParseArray<float>(inputTensorFile));
- }
- else if (inputTypes[i].compare("int") == 0)
- {
- inputDataContainers.push_back(ParseArray<int>(inputTensorFile));;
- }
- else
- {
- BOOST_LOG_TRIVIAL(fatal) << "Unsupported tensor data type \"" << inputTypes[i] << "\". ";
- return EXIT_FAILURE;
- }
-
- inputTensorFile.close();
- }
-
try
{
// Creates an InferenceModel, which will parse the model and load it into an IRuntime.
@@ -240,12 +238,59 @@
params.m_SubgraphId = subgraphId;
InferenceModel<TParser, TDataType> model(params, runtime);
+ for(unsigned int i = 0; i < inputTensorDataFilePaths.size(); ++i)
+ {
+ std::ifstream inputTensorFile(inputTensorDataFilePaths[i]);
+
+ if (inputTypes[i].compare("float") == 0)
+ {
+ inputDataContainers.push_back(
+ ParseDataArray<armnn::DataType::Float32>(inputTensorFile));
+ }
+ else if (inputTypes[i].compare("int") == 0)
+ {
+ inputDataContainers.push_back(
+ ParseDataArray<armnn::DataType::Signed32>(inputTensorFile));
+ }
+ else if (inputTypes[i].compare("qasymm8") == 0)
+ {
+ auto inputBinding = model.GetInputBindingInfo();
+ inputDataContainers.push_back(
+ ParseDataArray<armnn::DataType::QuantisedAsymm8>(inputTensorFile,
+ inputBinding.second.GetQuantizationScale(),
+ inputBinding.second.GetQuantizationOffset()));
+ }
+ else
+ {
+ BOOST_LOG_TRIVIAL(fatal) << "Unsupported tensor data type \"" << inputTypes[i] << "\". ";
+ return EXIT_FAILURE;
+ }
+
+ inputTensorFile.close();
+ }
+
const size_t numOutputs = params.m_OutputBindings.size();
std::vector<TContainer> outputDataContainers;
for (unsigned int i = 0; i < numOutputs; ++i)
{
- outputDataContainers.push_back(std::vector<float>(model.GetOutputSize(i)));
+ if (outputTypes[i].compare("float") == 0)
+ {
+ outputDataContainers.push_back(std::vector<float>(model.GetOutputSize(i)));
+ }
+ else if (outputTypes[i].compare("int") == 0)
+ {
+ outputDataContainers.push_back(std::vector<int>(model.GetOutputSize(i)));
+ }
+ else if (outputTypes[i].compare("qasymm8") == 0)
+ {
+ outputDataContainers.push_back(std::vector<uint8_t>(model.GetOutputSize(i)));
+ }
+ else
+ {
+ BOOST_LOG_TRIVIAL(fatal) << "Unsupported tensor data type \"" << outputTypes[i] << "\". ";
+ return EXIT_FAILURE;
+ }
}
model.Run(inputDataContainers, outputDataContainers);
@@ -282,6 +327,7 @@
const std::string& inputNames,
const std::string& inputTensorDataFilePaths,
const std::string& inputTypes,
+ const std::string& outputTypes,
const std::string& outputNames,
bool enableProfiling,
const size_t subgraphId,
@@ -289,11 +335,13 @@
{
std::string modelFormat = boost::trim_copy(format);
std::string modelPath = boost::trim_copy(path);
- std::vector<std::string> inputNamesVector = ParseInputString(inputNames, ",");
- std::vector<std::string> inputTensorShapesVector = ParseInputString(inputTensorShapesStr, ";");
- std::vector<std::string> inputTensorDataFilePathsVector = ParseInputString(inputTensorDataFilePaths, ",");
- std::vector<std::string> outputNamesVector = ParseInputString(outputNames, ",");
- std::vector<std::string> inputTypesVector = ParseInputString(inputTypes, ",");
+ std::vector<std::string> inputNamesVector = ParseStringList(inputNames, ",");
+ std::vector<std::string> inputTensorShapesVector = ParseStringList(inputTensorShapesStr, ";");
+ std::vector<std::string> inputTensorDataFilePathsVector = ParseStringList(
+ inputTensorDataFilePaths, ",");
+ std::vector<std::string> outputNamesVector = ParseStringList(outputNames, ",");
+ std::vector<std::string> inputTypesVector = ParseStringList(inputTypes, ",");
+ std::vector<std::string> outputTypesVector = ParseStringList(outputTypes, ",");
// Parse model binary flag from the model-format string we got from the command-line
bool isModelBinary;
@@ -327,10 +375,12 @@
if (inputTypesVector.size() == 0)
{
//Defaults the value of all inputs to "float"
- for(unsigned int i = 0; i < inputNamesVector.size(); ++i)
- {
- inputTypesVector.push_back("float");
- }
+ inputTypesVector.assign(inputNamesVector.size(), "float");
+ }
+ if (outputTypesVector.size() == 0)
+ {
+ //Defaults the value of all outputs to "float"
+ outputTypesVector.assign(outputNamesVector.size(), "float");
}
else if ((inputTypesVector.size() != 0) && (inputTypesVector.size() != inputNamesVector.size()))
{
@@ -348,7 +398,7 @@
for(const std::string& shape : inputTensorShapesVector)
{
std::stringstream ss(shape);
- std::vector<unsigned int> dims = ParseArray<unsigned int>(ss);
+ std::vector<unsigned int> dims = ParseArray(ss);
try
{
@@ -370,7 +420,7 @@
return MainImpl<armnnDeserializer::IDeserializer, float>(
modelPath.c_str(), isModelBinary, computeDevice,
inputNamesVector, inputTensorShapes,
- inputTensorDataFilePathsVector, inputTypesVector,
+ inputTensorDataFilePathsVector, inputTypesVector, outputTypesVector,
outputNamesVector, enableProfiling, subgraphId, runtime);
#else
BOOST_LOG_TRIVIAL(fatal) << "Not built with serialization support.";
@@ -383,7 +433,8 @@
return MainImpl<armnnCaffeParser::ICaffeParser, float>(modelPath.c_str(), isModelBinary, computeDevice,
inputNamesVector, inputTensorShapes,
inputTensorDataFilePathsVector, inputTypesVector,
- outputNamesVector, enableProfiling, subgraphId, runtime);
+ outputTypesVector, outputNamesVector, enableProfiling,
+ subgraphId, runtime);
#else
BOOST_LOG_TRIVIAL(fatal) << "Not built with Caffe parser support.";
return EXIT_FAILURE;
@@ -395,7 +446,8 @@
return MainImpl<armnnOnnxParser::IOnnxParser, float>(modelPath.c_str(), isModelBinary, computeDevice,
inputNamesVector, inputTensorShapes,
inputTensorDataFilePathsVector, inputTypesVector,
- outputNamesVector, enableProfiling, subgraphId, runtime);
+ outputTypesVector, outputNamesVector, enableProfiling,
+ subgraphId, runtime);
#else
BOOST_LOG_TRIVIAL(fatal) << "Not built with Onnx parser support.";
return EXIT_FAILURE;
@@ -407,7 +459,8 @@
return MainImpl<armnnTfParser::ITfParser, float>(modelPath.c_str(), isModelBinary, computeDevice,
inputNamesVector, inputTensorShapes,
inputTensorDataFilePathsVector, inputTypesVector,
- outputNamesVector, enableProfiling, subgraphId, runtime);
+ outputTypesVector, outputNamesVector, enableProfiling,
+ subgraphId, runtime);
#else
BOOST_LOG_TRIVIAL(fatal) << "Not built with Tensorflow parser support.";
return EXIT_FAILURE;
@@ -425,8 +478,8 @@
return MainImpl<armnnTfLiteParser::ITfLiteParser, float>(modelPath.c_str(), isModelBinary, computeDevice,
inputNamesVector, inputTensorShapes,
inputTensorDataFilePathsVector, inputTypesVector,
- outputNamesVector, enableProfiling, subgraphId,
- runtime);
+ outputTypesVector, outputNamesVector, enableProfiling,
+ subgraphId, runtime);
#else
BOOST_LOG_TRIVIAL(fatal) << "Unknown model format: '" << modelFormat <<
"'. Please include 'caffe', 'tensorflow', 'tflite' or 'onnx'";
@@ -451,6 +504,7 @@
std::string inputTensorDataFilePaths;
std::string outputNames;
std::string inputTypes;
+ std::string outputTypes;
size_t subgraphId = 0;
@@ -481,7 +535,10 @@
"Several paths can be passed separating them by comma.")
("input-type,y",po::value(&inputTypes), "The type of the input tensors in the network separated by comma. "
"If unset, defaults to \"float\" for all defined inputs. "
- "Accepted values (float or int).")
+ "Accepted values (float, int or qasymm8).")
+ ("output-type,z",po::value(&outputTypes), "The type of the output tensors in the network separated by comma. "
+ "If unset, defaults to \"float\" for all defined outputs. "
+ "Accepted values (float, int or qasymm8).")
("output-name,o", po::value(&outputNames),
"Identifier of the output tensors in the network separated by comma.");
}
@@ -534,7 +591,7 @@
}
return RunTest(modelFormat, inputTensorShapes, computeDevices, modelPath, inputNames, inputTensorDataFilePaths,
- inputTypes, outputNames, enableProfiling, subgraphId);
+ inputTypes, outputTypes, outputNames, enableProfiling, subgraphId);
}
int main(int argc, const char* argv[])
@@ -557,6 +614,7 @@
std::string inputTensorDataFilePaths;
std::string outputNames;
std::string inputTypes;
+ std::string outputTypes;
size_t subgraphId = 0;
@@ -593,7 +651,11 @@
"Several paths can be passed separating them by comma. ")
("input-type,y",po::value(&inputTypes), "The type of the input tensors in the network separated by comma. "
"If unset, defaults to \"float\" for all defined inputs. "
- "Accepted values (float or int)")
+ "Accepted values (float, int or qasymm8)")
+ ("output-type,z",po::value(&outputTypes),
+ "The type of the output tensors in the network separated by comma. "
+ "If unset, defaults to \"float\" for all defined outputs. "
+ "Accepted values (float, int or qasymm8).")
("output-name,o", po::value(&outputNames),
"Identifier of the output tensors in the network separated by comma.")
("event-based-profiling,e", po::bool_switch()->default_value(false),
@@ -737,6 +799,6 @@
}
return RunTest(modelFormat, inputTensorShapes, computeDevices, modelPath, inputNames, inputTensorDataFilePaths,
- inputTypes, outputNames, enableProfiling, subgraphId);
+ inputTypes, outputTypes, outputNames, enableProfiling, subgraphId);
}
}