Method Print

src/armnn/Graph.cpp:68–144

}

Status Graph::Print(bool extended) const
{
    if (m_Layers.empty())
    {
        ARMNN_LOG(info) << "\n Graph is empty.\n";
        return Status::Success;
    }
    ARMNN_LOG(info) << "\n";
    ARMNN_LOG(info) << "Walking Pattern: \n";

    for (auto&& it : TopologicalSort())
    {
        auto numInputSlots = it->GetNumInputSlots();
        auto numOutputSlots = it->GetNumOutputSlots();

        std::string guid;
        if (extended)
        {
            guid += ":";
            guid += std::to_string(it->GetGuid());
        }
        ARMNN_LOG(info) << it->GetName() << ":" << GetLayerTypeAsCString(it->GetType())
                                << ":" << it->GetBackendId().Get()
                                << guid
                                << " has " << numInputSlots << " input slots"
                                << " and " << numOutputSlots << " output slots.";

        for (auto i : it->GetInputSlots())
        {
            std::ostringstream message;
            auto inputTensorShape = i.GetConnectedOutputSlot()->GetTensorInfo().GetShape();
            unsigned int numDims = inputTensorShape.GetNumDimensions();

            message << "The input slot has shape [ ";
            for (unsigned int dim=0; dim < numDims; dim++)
            {
                message << inputTensorShape[dim] << ",";
            }
            message << " ]";
            if (extended)
            {
                message << " Scale: " << i.GetConnectedOutputSlot()->GetTensorInfo().GetQuantizationScale();
                message << " Offset: " << i.GetConnectedOutputSlot()->GetTensorInfo().GetQuantizationOffset();
                message <<  " The input slot is connected to: ";
                message << i.GetConnectedOutputSlot()->GetOwningIConnectableLayer().GetGuid();
            }
            ARMNN_LOG(info) << message.str();
        }

        for (unsigned int i = 0; i < it->GetNumOutputSlots(); i++)
        {
            const armnn::Layer *layer = it;
            std::ostringstream message;
            auto outputTensorShape = layer->GetOutputSlots()[i].GetTensorInfo().GetShape();
            unsigned int numDims = outputTensorShape.GetNumDimensions();

            message << "The output slot has shape [ ";
            for (unsigned int dim=0; dim < numDims; dim++)