ExecuteNetworkParams.cpp File Reference

#include "ExecuteNetworkParams.hpp"
#include "NetworkExecutionUtils/NetworkExecutionUtils.hpp"
#include <InferenceModel.hpp>
#include <armnn/Logging.hpp>
#include <fmt/format.h>

Go to the source code of this file.

Functions
bool	IsModelBinary (const std::string &modelFormat)
void	CheckModelFormat (const std::string &modelFormat)
void	CheckClTuningParameter (const int &tuningLevel, const std::string &tuningPath, const std::vector< armnn::BackendId > computeDevices)

Function Documentation

CheckClTuningParameter()

void CheckClTuningParameter	(	const int &	tuningLevel,
		const std::string &	tuningPath,
		const std::vector< armnn::BackendId >	computeDevices
	)

Definition at line 91 of file ExecuteNetworkParams.cpp.

References ARMNN_LOG, and ValidatePath().

Referenced by ExecuteNetworkParams::ValidateParams().

{
    if (!tuningPath.empty())
    {
        if (tuningLevel == 0)
        {
            ARMNN_LOG(info) << "Using cl tuning file: " << tuningPath << "\n";
            if (!ValidatePath(tuningPath, true))
            {
                throw armnn::InvalidArgumentException("The tuning path is not valid");
            }
        }
        else if ((1 <= tuningLevel) && (tuningLevel <= 3))
        {
            ARMNN_LOG(info) << "Starting execution to generate a cl tuning file: " << tuningPath << "\n"
                            << "Tuning level in use: " << tuningLevel << "\n";
        }
        else if ((0 < tuningLevel) || (tuningLevel > 3))
        {
            throw armnn::InvalidArgumentException(fmt::format("The tuning level {} is not valid.",
                                                              tuningLevel));
        }

        // Ensure that a GpuAcc is enabled. Otherwise no tuning data are used or genereted
        // Only warn if it's not enabled
        auto it = std::find(computeDevices.begin(), computeDevices.end(), "GpuAcc");
        if (it == computeDevices.end())
        {
            ARMNN_LOG(warning) << "To use Cl Tuning the compute device GpuAcc needs to be active.";
        }
    }

}

CheckModelFormat()

void CheckModelFormat

(

const std::string &

modelFormat

)

Definition at line 33 of file ExecuteNetworkParams.cpp.

References IsModelBinary().

Referenced by ExecuteNetworkParams::ValidateParams().

{
    // Forward to implementation based on the parser type
    if (modelFormat.find("armnn") != std::string::npos)
    {
#if defined(ARMNN_SERIALIZER)
#else
        throw armnn::InvalidArgumentException("Can't run model in armnn format without a "
                                              "built with serialization support.");
#endif
    }
    else if (modelFormat.find("caffe") != std::string::npos)
    {
#if defined(ARMNN_CAFFE_PARSER)
#else
        throw armnn::InvalidArgumentException("Can't run model in caffe format without a "
                                              "built with Caffe parser support.");
#endif
    }
    else if (modelFormat.find("onnx") != std::string::npos)
    {
#if defined(ARMNN_ONNX_PARSER)
#else
        throw armnn::InvalidArgumentException("Can't run model in onnx format without a "
                                              "built with Onnx parser support.");
#endif
    }
    else if (modelFormat.find("tensorflow") != std::string::npos)
    {
#if defined(ARMNN_TF_PARSER)
#else
        throw armnn::InvalidArgumentException("Can't run model in onnx format without a "
                                              "built with Tensorflow parser support.");
#endif
    }
    else if (modelFormat.find("tflite") != std::string::npos)
    {
#if defined(ARMNN_TF_LITE_PARSER)
        if (!IsModelBinary(modelFormat))
        {
            throw armnn::InvalidArgumentException(fmt::format("Unknown model format: '{}'. Only 'binary' "
                                                              "format supported for tflite files",
                                                              modelFormat));
        }
#elif defined(ARMNN_TFLITE_DELEGATE)
#else
        throw armnn::InvalidArgumentException("Can't run model in tflite format without a "
                                              "built with Tensorflow Lite parser support.");
#endif
    }
    else
    {
        throw armnn::InvalidArgumentException(fmt::format("Unknown model format: '{}'. "
                                                          "Please include 'caffe', 'tensorflow', 'tflite' or 'onnx'",
                                                          modelFormat));
    }
}

IsModelBinary()

bool IsModelBinary

(

const std::string &

modelFormat

)

Definition at line 14 of file ExecuteNetworkParams.cpp.

Referenced by CheckModelFormat(), and ExecuteNetworkParams::ValidateParams().

{
    // Parse model binary flag from the model-format string we got from the command-line
    if (modelFormat.find("binary") != std::string::npos)
    {
        return true;
    }
    else if (modelFormat.find("txt") != std::string::npos || modelFormat.find("text") != std::string::npos)
    {
        return false;
    }
    else
    {
        throw armnn::InvalidArgumentException(fmt::format("Unknown model format: '{}'. "
                                                          "Please include 'binary' or 'text'",
                                                          modelFormat));
    }
}