Holds and parses program options for the ExecuteNetwork application. More...

#include <ExecuteNetworkProgramOptions.hpp>

Public Member Functions
	ProgramOptions ()
	Initializes ProgramOptions by adding options to the underlying cxxopts::options object. More...

	ProgramOptions (int ac, const char *av[])
	Runs ParseOptions() on initialization. More...

void	ParseOptions (int ac, const char *av[])
	Parses program options from the command line or another source and stores the values in member variables. More...

void	ValidateExecuteNetworkParams ()
	Ensures that the parameters for ExecuteNetwork fit together. More...

void	ValidateRuntimeOptions ()
	Ensures that the runtime options are valid. More...

Public Attributes
cxxopts::Options	m_CxxOptions

cxxopts::ParseResult	m_CxxResult

ExecuteNetworkParams	m_ExNetParams

armnn::IRuntime::CreationOptions	m_RuntimeOptions

Detailed Description

Holds and parses program options for the ExecuteNetwork application.

Definition at line 21 of file ExecuteNetworkProgramOptions.hpp.

Constructor & Destructor Documentation

◆ ProgramOptions() [1/2]

ProgramOptions ( )

Initializes ProgramOptions by adding options to the underlying cxxopts::options object.

(Does not parse any options)

Definition at line 171 of file ExecuteNetworkProgramOptions.cpp.

                                : m_CxxOptions{"ExecuteNetwork",
                                                 "Executes a neural network model using the provided input "
                                                 "tensor. Prints the resulting output tensor."}
 {
     try
     {
         // cxxopts doesn't provide a mechanism to ensure required options are given. There is a
         // separate function CheckRequiredOptions() for that.
         m_CxxOptions.add_options("a) Required")
                 ("c,compute",
                  "Which device to run layers on by default. If a single device doesn't support all layers in the model "
                  "you can specify a second or third to fall back on. Possible choices: "
                  + armnn::BackendRegistryInstance().GetBackendIdsAsString()
                  + " NOTE: Multiple compute devices need to be passed as a comma separated list without whitespaces "
                    "e.g. GpuAcc,CpuAcc,CpuRef or by repeating the program option e.g. '-c Cpuacc -c CpuRef'. "
                    "Duplicates are ignored.",
                  cxxopts::value<std::vector<std::string>>())
 
                 ("f,model-format",
                  "armnn-binary, onnx-binary, onnx-text, tflite-binary",
                  cxxopts::value<std::string>())
 
                 ("m,model-path",
                  "Path to model file, e.g. .armnn, , .prototxt, .tflite, .onnx",
                  cxxopts::value<std::string>(m_ExNetParams.m_ModelPath))
 
                 ("i,input-name",
                  "Identifier of the input tensors in the network separated by comma.",
                  cxxopts::value<std::string>())
 
                 ("o,output-name",
                  "Identifier of the output tensors in the network separated by comma.",
                  cxxopts::value<std::string>());
 
         m_CxxOptions.add_options("b) General")
                 ("b,dynamic-backends-path",
                  "Path where to load any available dynamic backend from. "
                  "If left empty (the default), dynamic backends will not be used.",
                  cxxopts::value<std::string>(m_RuntimeOptions.m_DynamicBackendsPath))
 
                 ("n,concurrent",
                  "This option is for Arm NN internal asynchronous testing purposes. "
                  "False by default. If set to true will use std::launch::async or the Arm NN thread pool, "
                  "if 'thread-pool-size' is greater than 0, for asynchronous execution.",
                  cxxopts::value<bool>(m_ExNetParams.m_Concurrent)->default_value("false")->implicit_value("true"))
 
                 ("d,input-tensor-data",
                  "Path to files containing the input data as a flat array separated by whitespace. "
                  "Several paths can be passed by separating them with a comma if the network has multiple inputs "
                  "or you wish to run the model multiple times with different input data using the 'iterations' option. "
                  "If not specified, the network will be run with dummy data (useful for profiling).",
                  cxxopts::value<std::string>()->default_value(""))
 
                 ("h,help", "Display usage information")
 
                 ("infer-output-shape",
                  "Infers output tensor shape from input tensor shape and validate where applicable (where supported by "
                  "parser)",
                  cxxopts::value<bool>(m_ExNetParams.m_InferOutputShape)->default_value("false")->implicit_value("true"))
 
                 ("allow-expanded-dims",
                  "If true will disregard dimensions with a size of 1 when validating tensor shapes. Tensor sizes must "
                  "still match. This is an Experimental parameter that is incompatible with infer-output-shape. "
                  "This parameter may be removed in a later update. ",
                  cxxopts::value<bool>(m_ExNetParams.m_AllowExpandedDims)->default_value("false")
                  ->implicit_value("true"))
 
                 ("iterations",
                  "Number of iterations to run the network for, default is set to 1. "
                  "If you wish to run the model with different input data for every execution you can do so by "
                  "supplying more input file paths to the 'input-tensor-data' option. "
                  "Note: The number of input files provided must be divisible by the number of inputs of the model. "
                  "e.g. Your model has 2 inputs and you supply 4 input files. If you set 'iterations' to 6 the first "
                  "run will consume the first two inputs, the second the next two and the last will begin from the "
                  "start and use the first two inputs again. "
                  "Note: If the 'concurrent' option is enabled all iterations will be run asynchronously.",
                  cxxopts::value<size_t>(m_ExNetParams.m_Iterations)->default_value("1"))
 
                 ("l,dequantize-output",
                  "If this option is enabled, all quantized outputs will be dequantized to float. "
                  "If unset, default to not get dequantized. "
                  "Accepted values (true or false)"
                  " (Not available when executing ArmNNTfLiteDelegate or TfliteInterpreter)",
                  cxxopts::value<bool>(m_ExNetParams.m_DequantizeOutput)->default_value("false")->implicit_value("true"))
 
                 ("p,print-intermediate-layers",
                  "If this option is enabled, the output of every graph layer will be printed.",
                  cxxopts::value<bool>(m_ExNetParams.m_PrintIntermediate)->default_value("false")
                  ->implicit_value("true"))
 
                 ("parse-unsupported",
                  "Add unsupported operators as stand-in layers (where supported by parser)",
                  cxxopts::value<bool>(m_ExNetParams.m_ParseUnsupported)->default_value("false")->implicit_value("true"))
 
                 ("N,do-not-print-output",
                  "The default behaviour of ExecuteNetwork is to print the resulting outputs on the console. "
                  "This behaviour can be changed by adding this flag to your command.",
                  cxxopts::value<bool>(m_ExNetParams.m_DontPrintOutputs)->default_value("false")->implicit_value("true"))
 
                 ("q,quantize-input",
                  "If this option is enabled, all float inputs will be quantized as appropriate for the model's inputs. "
                  "If unset, default to not quantized. Accepted values (true or false)"
                  " (Not available when executing ArmNNTfLiteDelegate or TfliteInterpreter)",
                  cxxopts::value<bool>(m_ExNetParams.m_QuantizeInput)->default_value("false")->implicit_value("true"))
                 ("r,threshold-time",
                  "Threshold time is the maximum allowed time for inference measured in milliseconds. If the actual "
                  "inference time is greater than the threshold time, the test will fail. By default, no threshold "
                  "time is used.",
                  cxxopts::value<double>(m_ExNetParams.m_ThresholdTime)->default_value("0.0"))
 
                 ("s,input-tensor-shape",
                  "The shape of the input tensors in the network as a flat array of integers separated by comma."
                  "Several shapes can be passed by separating them with a colon (:).",
                  cxxopts::value<std::string>())
 
                 ("v,visualize-optimized-model",
                  "Enables built optimized model visualizer. If unset, defaults to off.",
                  cxxopts::value<bool>(m_ExNetParams.m_EnableLayerDetails)->default_value("false")
                  ->implicit_value("true"))
 
                 ("w,write-outputs-to-file",
                  "Comma-separated list of output file paths keyed with the binding-id of the output slot. "
                  "If left empty (the default), the output tensors will not be written to a file.",
                  cxxopts::value<std::string>())
 
                 ("x,subgraph-number",
                  "Id of the subgraph to be executed. Defaults to 0."
                  " (Not available when executing ArmNNTfLiteDelegate or TfliteInterpreter)",
                  cxxopts::value<size_t>(m_ExNetParams.m_SubgraphId)->default_value("0"))
 
                 ("y,input-type",
                  "The type of the input tensors in the network separated by comma. "
                  "If unset, defaults to \"float\" for all defined inputs. "
                  "Accepted values (float, int, qasymms8 or qasymmu8).",
                  cxxopts::value<std::string>())
 
                 ("z,output-type",
                  "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,  qasymms8 or qasymmu8).",
                  cxxopts::value<std::string>())
 
                 ("T,tflite-executor",
                  "Set the executor for the tflite model: parser, delegate, tflite"
                  "parser is the ArmNNTfLiteParser, "
                  "delegate is the ArmNNTfLiteDelegate, "
                  "tflite is the TfliteInterpreter",
                  cxxopts::value<std::string>()->default_value("parser"))
 
                 ("D,armnn-tflite-delegate",
                  "Enable Arm NN TfLite delegate. "
                  "DEPRECATED: This option is deprecated please use tflite-executor instead",
                  cxxopts::value<bool>(m_ExNetParams.m_EnableDelegate)->default_value("false")->implicit_value("true"))
 
                 ("simultaneous-iterations",
                  "Number of simultaneous iterations to async-run the network for, default is set to 1 (disabled). "
                  "When thread-pool-size is set the Arm NN thread pool is used. Otherwise std::launch::async is used."
                  "DEPRECATED: This option is deprecated and will be removed soon. "
                  "Please use the option 'iterations' combined with 'concurrent' instead.",
                  cxxopts::value<size_t>(m_ExNetParams.m_SimultaneousIterations)->default_value("1"))
 
                 ("thread-pool-size",
                  "Number of Arm NN threads to use when running the network asynchronously via the Arm NN thread pool. "
                  "The default is set to 0 which equals disabled. If 'thread-pool-size' is greater than 0 the "
                  "'concurrent' option is automatically set to true.",
                  cxxopts::value<size_t>(m_ExNetParams.m_ThreadPoolSize)->default_value("0"));
 
         m_CxxOptions.add_options("c) Optimization")
                 ("bf16-turbo-mode",
                  "If this option is enabled, FP32 layers, "
                  "weights and biases will be converted to BFloat16 where the backend supports it",
                  cxxopts::value<bool>(m_ExNetParams.m_EnableBf16TurboMode)
                  ->default_value("false")->implicit_value("true"))
 
                 ("enable-fast-math",
                  "Enables fast_math options in backends that support it. Using the fast_math flag can lead to "
                  "performance improvements but may result in reduced or different precision.",
                  cxxopts::value<bool>(m_ExNetParams.m_EnableFastMath)->default_value("false")->implicit_value("true"))
 
                 ("number-of-threads",
                  "Assign the number of threads used by the CpuAcc backend. "
                  "Input value must be between 1 and 64. "
                  "Default is set to 0 (Backend will decide number of threads to use).",
                  cxxopts::value<unsigned int>(m_ExNetParams.m_NumberOfThreads)->default_value("0"))
 
                 ("save-cached-network",
                  "Enables saving of the cached network to a file given with the cached-network-filepath option. "
                  "See also --cached-network-filepath",
                  cxxopts::value<bool>(m_ExNetParams.m_SaveCachedNetwork)
                  ->default_value("false")->implicit_value("true"))
 
                 ("cached-network-filepath",
                  "If non-empty, the given file will be used to load/save the cached network. "
                  "If save-cached-network is given then the cached network will be saved to the given file. "
                  "To save the cached network a file must already exist. "
                  "If save-cached-network is not given then the cached network will be loaded from the given file. "
                  "This will remove initial compilation time of kernels and speed up the first execution.",
                  cxxopts::value<std::string>(m_ExNetParams.m_CachedNetworkFilePath)->default_value(""))
 
                 ("fp16-turbo-mode",
                  "If this option is enabled, FP32 layers, "
                  "weights and biases will be converted to FP16 where the backend supports it",
                  cxxopts::value<bool>(m_ExNetParams.m_EnableFp16TurboMode)
                  ->default_value("false")->implicit_value("true"))
 
                 ("tuning-level",
                  "Sets the tuning level which enables a tuning run which will update/create a tuning file. "
                  "Available options are: 1 (Rapid), 2 (Normal), 3 (Exhaustive). "
                  "Requires tuning-path to be set, default is set to 0 (No tuning run)",
                  cxxopts::value<int>(m_ExNetParams.m_TuningLevel)->default_value("0"))
 
                 ("tuning-path",
                  "Path to tuning file. Enables use of CL tuning",
                  cxxopts::value<std::string>(m_ExNetParams.m_TuningPath))
 
                 ("MLGOTuningFilePath",
                 "Path to tuning file. Enables use of CL MLGO tuning",
                 cxxopts::value<std::string>(m_ExNetParams.m_MLGOTuningFilePath))
 
                 ("R, reuse-buffers",
                 "If enabled then the IO buffers will be reused for each inference",
                 cxxopts::value<bool>(m_ExNetParams.m_ReuseBuffers)->default_value("false")->implicit_value("true"));
 
         m_CxxOptions.add_options("d) Profiling")
                 ("a,enable-external-profiling",
                  "If enabled external profiling will be switched on",
                  cxxopts::value<bool>(m_RuntimeOptions.m_ProfilingOptions.m_EnableProfiling)
                          ->default_value("false")->implicit_value("true"))
 
                 ("e,event-based-profiling",
                  "Enables built in profiler. If unset, defaults to off.",
                  cxxopts::value<bool>(m_ExNetParams.m_EnableProfiling)->default_value("false")->implicit_value("true"))
 
                 ("g,file-only-external-profiling",
                  "If enabled then the 'file-only' test mode of external profiling will be enabled",
                  cxxopts::value<bool>(m_RuntimeOptions.m_ProfilingOptions.m_FileOnly)
                  ->default_value("false")->implicit_value("true"))
 
                 ("file-format",
                  "If profiling is enabled specifies the output file format",
                  cxxopts::value<std::string>(m_RuntimeOptions.m_ProfilingOptions.m_FileFormat)->default_value("binary"))
 
                 ("j,outgoing-capture-file",
                  "If specified the outgoing external profiling packets will be captured in this binary file",
                  cxxopts::value<std::string>(m_RuntimeOptions.m_ProfilingOptions.m_OutgoingCaptureFile))
 
                 ("k,incoming-capture-file",
                  "If specified the incoming external profiling packets will be captured in this binary file",
                  cxxopts::value<std::string>(m_RuntimeOptions.m_ProfilingOptions.m_IncomingCaptureFile))
 
                 ("timeline-profiling",
                  "If enabled timeline profiling will be switched on, requires external profiling",
                  cxxopts::value<bool>(m_RuntimeOptions.m_ProfilingOptions.m_TimelineEnabled)
                  ->default_value("false")->implicit_value("true"))
 
                 ("u,counter-capture-period",
                  "If profiling is enabled in 'file-only' mode this is the capture period that will be used in the test",
                  cxxopts::value<uint32_t>(m_RuntimeOptions.m_ProfilingOptions.m_CapturePeriod)->default_value("150"))
 
                 ("output-network-details",
                  "Outputs layer tensor infos and descriptors to std out along with profiling events. Defaults to off.",
                  cxxopts::value<bool>(m_ExNetParams.m_OutputDetailsToStdOut)->default_value("false")
                                                                             ->implicit_value("true"))
                 ("output-network-details-only",
                  "Outputs layer tensor infos and descriptors to std out without profiling events. Defaults to off.",
                  cxxopts::value<bool>(m_ExNetParams.m_OutputDetailsOnlyToStdOut)->default_value("false")
                                                                                 ->implicit_value("true"))
 
                 ("import-inputs-if-aligned",
                  "In & Out tensors will be imported per inference if the memory alignment allows. Defaults to false.",
                  cxxopts::value<bool>(m_ExNetParams.m_ImportInputsIfAligned)->default_value("false")
                          ->implicit_value("true"));
     }
     catch (const std::exception& e)
     {
         ARMNN_ASSERT_MSG(false, "Caught unexpected exception");
         ARMNN_LOG(fatal) << "Fatal internal error: " << e.what();
         exit(EXIT_FAILURE);
     }
 }

◆ ProgramOptions() [2/2]

ProgramOptions	(	int	ac,
		const char *	av[]
	)

Runs ParseOptions() on initialization.

Definition at line 452 of file ExecuteNetworkProgramOptions.cpp.

References ParseOptions().

                                                       : ProgramOptions()
 {
     ParseOptions(ac, av);
 }

Member Function Documentation

◆ ParseOptions()

void ParseOptions	(	int	ac,
		const char *	av[]
	)

Parses program options from the command line or another source and stores the values in member variables.

It also checks the validity of the parsed parameters. Throws a cxxopts exception if parsing fails or an armnn exception if parameters are not valid.

Definition at line 457 of file ExecuteNetworkProgramOptions.cpp.

Referenced by main(), and ProgramOptions().

 {
     // Parses the command-line.
     m_CxxResult = m_CxxOptions.parse(ac, av);
 
     if (m_CxxResult.count("help") || ac <= 1)
     {
         std::cout << m_CxxOptions.help() << std::endl;
         exit(EXIT_SUCCESS);
     }
 
     CheckRequiredOptions(m_CxxResult);
     CheckOptionDependencies(m_CxxResult);
     CheckForDeprecatedOptions(m_CxxResult);
 
     // Some options can't be assigned directly because they need some post-processing:
     auto computeDevices = GetOptionValue<std::vector<std::string>>("compute", m_CxxResult);
     m_ExNetParams.m_ComputeDevices = GetBackendIDs(computeDevices);
     m_ExNetParams.m_ModelFormat =
             armnn::stringUtils::StringTrimCopy(GetOptionValue<std::string>("model-format", m_CxxResult));
     m_ExNetParams.m_InputNames =
             ParseStringList(GetOptionValue<std::string>("input-name", m_CxxResult), ",");
     m_ExNetParams.m_InputTensorDataFilePaths =
             ParseStringList(GetOptionValue<std::string>("input-tensor-data", m_CxxResult), ",");
     m_ExNetParams.m_OutputNames =
             ParseStringList(GetOptionValue<std::string>("output-name", m_CxxResult), ",");
     m_ExNetParams.m_InputTypes =
             ParseStringList(GetOptionValue<std::string>("input-type", m_CxxResult), ",");
     m_ExNetParams.m_OutputTypes =
             ParseStringList(GetOptionValue<std::string>("output-type", m_CxxResult), ",");
     m_ExNetParams.m_OutputTensorFiles =
             ParseStringList(GetOptionValue<std::string>("write-outputs-to-file", m_CxxResult), ",");
     m_ExNetParams.m_GenerateTensorData =
             m_ExNetParams.m_InputTensorDataFilePaths.empty();
     m_ExNetParams.m_DynamicBackendsPath = m_RuntimeOptions.m_DynamicBackendsPath;
 
     m_RuntimeOptions.m_EnableGpuProfiling = m_ExNetParams.m_EnableProfiling;
 
     std::string tfliteExecutor = GetOptionValue<std::string>("tflite-executor", m_CxxResult);
 
     if (tfliteExecutor.size() == 0 || tfliteExecutor == "parser")
     {
         m_ExNetParams.m_TfLiteExecutor = ExecuteNetworkParams::TfLiteExecutor::ArmNNTfLiteParser;
     }
     else if (tfliteExecutor == "delegate")
     {
         m_ExNetParams.m_TfLiteExecutor = ExecuteNetworkParams::TfLiteExecutor::ArmNNTfLiteDelegate;
     }
     else if (tfliteExecutor == "tflite")
     {
         m_ExNetParams.m_TfLiteExecutor = ExecuteNetworkParams::TfLiteExecutor::TfliteInterpreter;
     }
     else
     {
         ARMNN_LOG(info) << fmt::format("Invalid tflite-executor option '{}'.", tfliteExecutor);
         throw armnn::InvalidArgumentException ("Invalid tflite-executor option");
     }
 
     // For backwards compatibility when deprecated options are used
     if (m_ExNetParams.m_EnableDelegate)
     {
         m_ExNetParams.m_TfLiteExecutor = ExecuteNetworkParams::TfLiteExecutor::ArmNNTfLiteDelegate;
     }
     if (m_ExNetParams.m_SimultaneousIterations > 1)
     {
         m_ExNetParams.m_Iterations = m_ExNetParams.m_SimultaneousIterations;
         m_ExNetParams.m_Concurrent = true;
     }
 
     // Set concurrent to true if the user expects to run inferences asynchronously
     if (m_ExNetParams.m_ThreadPoolSize > 0)
     {
         m_ExNetParams.m_Concurrent = true;
     }
 
     // Parse input tensor shape from the string we got from the command-line.
     std::vector<std::string> inputTensorShapesVector =
             ParseStringList(GetOptionValue<std::string>("input-tensor-shape", m_CxxResult), ":");
 
     if (!inputTensorShapesVector.empty())
     {
         m_ExNetParams.m_InputTensorShapes.reserve(inputTensorShapesVector.size());
 
         for(const std::string& shape : inputTensorShapesVector)
         {
             std::stringstream ss(shape);
             std::vector<unsigned int> dims = ParseArray(ss);
 
             m_ExNetParams.m_InputTensorShapes.push_back(
                     std::make_unique<armnn::TensorShape>(static_cast<unsigned int>(dims.size()), dims.data()));
         }
     }
 
     // We have to validate ExecuteNetworkParams first so that the tuning path and level is validated
     ValidateExecuteNetworkParams();
 
     // Parse CL tuning parameters to runtime options
     if (!m_ExNetParams.m_TuningPath.empty())
     {
         m_RuntimeOptions.m_BackendOptions.emplace_back(
             armnn::BackendOptions
             {
                 "GpuAcc",
                 {
                     {"TuningLevel", m_ExNetParams.m_TuningLevel},
                     {"TuningFile", m_ExNetParams.m_TuningPath.c_str()},
                     {"KernelProfilingEnabled", m_ExNetParams.m_EnableProfiling},
                     {"MLGOTuningFilePath", m_ExNetParams.m_MLGOTuningFilePath}
                 }
             }
         );
     }
 
     ValidateRuntimeOptions();
 }

◆ ValidateExecuteNetworkParams()

void ValidateExecuteNetworkParams ( )

Ensures that the parameters for ExecuteNetwork fit together.

Definition at line 156 of file ExecuteNetworkProgramOptions.cpp.

References m_ExNetParams, and ExecuteNetworkParams::ValidateParams().

Referenced by ParseOptions().

 {
     m_ExNetParams.ValidateParams();
 }

◆ ValidateRuntimeOptions()

void ValidateRuntimeOptions ( )

Ensures that the runtime options are valid.

Definition at line 161 of file ExecuteNetworkProgramOptions.cpp.

References LogAndThrowFatal(), IRuntime::CreationOptions::ExternalProfilingOptions::m_EnableProfiling, IRuntime::CreationOptions::m_ProfilingOptions, m_RuntimeOptions, and IRuntime::CreationOptions::ExternalProfilingOptions::m_TimelineEnabled.

Referenced by ParseOptions().

 {
     if (m_RuntimeOptions.m_ProfilingOptions.m_TimelineEnabled &&
         !m_RuntimeOptions.m_ProfilingOptions.m_EnableProfiling)
     {
         LogAndThrowFatal("Timeline profiling requires external profiling to be turned on");
     }
 }