diff options
Diffstat (limited to 'tests/ExecuteNetwork/ExecuteNetworkParams.cpp')
| -rw-r--r-- | tests/ExecuteNetwork/ExecuteNetworkParams.cpp | 179 |
1 files changed, 93 insertions, 86 deletions
diff --git a/tests/ExecuteNetwork/ExecuteNetworkParams.cpp b/tests/ExecuteNetwork/ExecuteNetworkParams.cpp index 4002e89eba..dcdd423246 100644 --- a/tests/ExecuteNetwork/ExecuteNetworkParams.cpp +++ b/tests/ExecuteNetwork/ExecuteNetworkParams.cpp @@ -110,115 +110,122 @@ void CheckClTuningParameter(const int& tuningLevel, void ExecuteNetworkParams::ValidateParams() { - // Set to true if it is preferred to throw an exception rather than use ARMNN_LOG - bool throwExc = false; - - try + if (m_DynamicBackendsPath == "") { - if (m_DynamicBackendsPath == "") + // Check compute devices are valid unless they are dynamically loaded at runtime + std::string invalidBackends; + if (!CheckRequestedBackendsAreValid(m_ComputeDevices, armnn::Optional<std::string&>(invalidBackends))) { - // Check compute devices are valid unless they are dynamically loaded at runtime - std::string invalidBackends; - if (!CheckRequestedBackendsAreValid(m_ComputeDevices, armnn::Optional<std::string&>(invalidBackends))) - { - ARMNN_LOG(fatal) << "The list of preferred devices contains invalid backend IDs: " - << invalidBackends; - } + ARMNN_LOG(fatal) << "The list of preferred devices contains invalid backend IDs: " + << invalidBackends; } + } - CheckClTuningParameter(m_TuningLevel, m_TuningPath, m_ComputeDevices); + CheckClTuningParameter(m_TuningLevel, m_TuningPath, m_ComputeDevices); - if (m_EnableBf16TurboMode && m_EnableFp16TurboMode) - { - ARMNN_LOG(fatal) << "BFloat16 and Float16 turbo mode cannot be enabled at the same time."; - } + if (m_EnableBf16TurboMode && m_EnableFp16TurboMode) + { + throw armnn::InvalidArgumentException("BFloat16 and Float16 turbo mode cannot be " + "enabled at the same time."); + } - m_IsModelBinary = IsModelBinary(m_ModelFormat); + m_IsModelBinary = IsModelBinary(m_ModelFormat); - CheckModelFormat(m_ModelFormat); + CheckModelFormat(m_ModelFormat); - // Check input tensor shapes - if ((m_InputTensorShapes.size() != 0) && - (m_InputTensorShapes.size() != m_InputNames.size())) - { - ARMNN_LOG(fatal) << "input-name and input-tensor-shape must have the same amount of elements. "; - } + // Check input tensor shapes + if ((m_InputTensorShapes.size() != 0) && + (m_InputTensorShapes.size() != m_InputNames.size())) + { + throw armnn::InvalidArgumentException("input-name and input-tensor-shape must have " + "the same amount of elements. "); + } - if (m_InputTensorDataFilePaths.size() != 0) + if (m_InputTensorDataFilePaths.size() != 0) + { + if (!ValidatePaths(m_InputTensorDataFilePaths, true)) { - if (!ValidatePaths(m_InputTensorDataFilePaths, true)) - { - ARMNN_LOG(fatal) << "One or more input data file paths are not valid. "; - } - - if (!m_Concurrent && m_InputTensorDataFilePaths.size() != m_InputNames.size()) - { - ARMNN_LOG(fatal) << "input-name and input-tensor-data must have the same amount of elements. "; - } - - if (m_InputTensorDataFilePaths.size() < m_SimultaneousIterations * m_InputNames.size()) - { - ARMNN_LOG(fatal) << "There is not enough input data for " << m_SimultaneousIterations << " execution."; - } - if (m_InputTensorDataFilePaths.size() > m_SimultaneousIterations * m_InputNames.size()) - { - ARMNN_LOG(fatal) << "There is more input data for " << m_SimultaneousIterations << " execution."; - } + throw armnn::InvalidArgumentException("One or more input data file paths are not valid."); } - if ((m_OutputTensorFiles.size() != 0) && - (m_OutputTensorFiles.size() != m_OutputNames.size())) + if (m_InputTensorDataFilePaths.size() < m_InputNames.size()) { - ARMNN_LOG(fatal) << "output-name and write-outputs-to-file must have the same amount of elements. "; + throw armnn::InvalidArgumentException( + fmt::format("According to the number of input names the user provided the network has {} " + "inputs. But only {} input-tensor-data file paths were provided. Each input of the " + "model is expected to be stored in it's own file.", + m_InputNames.size(), + m_InputTensorDataFilePaths.size())); } - - if ((m_OutputTensorFiles.size() != 0) - && m_OutputTensorFiles.size() != m_SimultaneousIterations * m_OutputNames.size()) + else if (m_InputTensorDataFilePaths.size() % m_InputNames.size() != 0) { - ARMNN_LOG(fatal) << "There is not enough output data for " << m_SimultaneousIterations << " execution."; + throw armnn::InvalidArgumentException( + fmt::format("According to the number of input names the user provided the network has {} " + "inputs. The user specified {} input-tensor-data file paths which is not " + "divisible by the number of inputs.", + m_InputNames.size(), + m_InputTensorDataFilePaths.size())); } + } - if (m_InputTypes.size() == 0) - { - //Defaults the value of all inputs to "float" - m_InputTypes.assign(m_InputNames.size(), "float"); - } - else if ((m_InputTypes.size() != 0) && - (m_InputTypes.size() != m_InputNames.size())) - { - ARMNN_LOG(fatal) << "input-name and input-type must have the same amount of elements."; - } + if (m_InputTypes.size() == 0) + { + //Defaults the value of all inputs to "float" + m_InputTypes.assign(m_InputNames.size(), "float"); + } + else if ((m_InputTypes.size() != 0) && + (m_InputTypes.size() != m_InputNames.size())) + { + throw armnn::InvalidArgumentException("input-name and input-type must have the same amount of elements."); + } - if (m_OutputTypes.size() == 0) - { - //Defaults the value of all outputs to "float" - m_OutputTypes.assign(m_OutputNames.size(), "float"); - } - else if ((m_OutputTypes.size() != 0) && - (m_OutputTypes.size() != m_OutputNames.size())) - { - ARMNN_LOG(fatal) << "output-name and output-type must have the same amount of elements."; - } + // Make sure that the number of input files given is divisible by the number of inputs of the model + if (!(m_InputTensorDataFilePaths.size() % m_InputNames.size() == 0)) + { + throw armnn::InvalidArgumentException( + fmt::format("The number of input-tensor-data files ({0}) is not divisible by the " + "number of inputs ({1} according to the number of input names).", + m_InputTensorDataFilePaths.size(), + m_InputNames.size())); + } - // Check that threshold time is not less than zero - if (m_ThresholdTime < 0) - { - ARMNN_LOG(fatal) << "Threshold time supplied as a command line argument is less than zero."; - } + if (m_OutputTypes.size() == 0) + { + //Defaults the value of all outputs to "float" + m_OutputTypes.assign(m_OutputNames.size(), "float"); } - catch (std::string& exc) + else if ((m_OutputTypes.size() != 0) && + (m_OutputTypes.size() != m_OutputNames.size())) { - if (throwExc) - { - throw armnn::InvalidArgumentException(exc); - } - else - { - std::cout << exc; - exit(EXIT_FAILURE); + throw armnn::InvalidArgumentException("output-name and output-type must have the same amount of elements."); + } + + // Make sure that the number of output files given is equal to the number of outputs of the model + // or equal to the number of outputs of the model multiplied with the number of iterations + if (!m_OutputTensorFiles.empty()) + { + if ((m_OutputTensorFiles.size() != m_OutputNames.size()) && + (m_OutputTensorFiles.size() != m_OutputNames.size() * m_Iterations)) + { + std::stringstream errmsg; + auto numOutputs = m_OutputNames.size(); + throw armnn::InvalidArgumentException( + fmt::format("The user provided {0} output-tensor files. The only allowed number of output-tensor " + "files is the number of outputs of the network ({1} according to the number of " + "output names) or the number of outputs multiplied with the number of times the " + "network should be executed (NumOutputs * NumIterations = {1} * {2} = {3}).", + m_OutputTensorFiles.size(), + numOutputs, + m_Iterations, + numOutputs*m_Iterations)); } } - // Check turbo modes + + // Check that threshold time is not less than zero + if (m_ThresholdTime < 0) + { + throw armnn::InvalidArgumentException("Threshold time supplied as a command line argument is less than zero."); + } // Warn if ExecuteNetwork will generate dummy input data if (m_GenerateTensorData) |