Function ExtractTrainedParameters

software/xtract/caffe_network_parser.cpp:315–361

Function that extract all the trained parameters from CaffeModel file

// Function that extract all the trained parameters from CaffeModel file
void ExtractTrainedParameters(const caffe::NetParameter* Net, XGraph* graph)
{
    // Create a map of layer_names -> index in caffemodel file for faster lookup
    map<string, int>* modelLayerIndex = new map<string, int>();
    for(int i=0; i<Net->layer_size(); i++)
    {
        const caffe::LayerParameter& cLayer = Net->layer(i);
        (*modelLayerIndex)[cLayer.name()] = i;
    }

    // Now iterate through each layer searching for layers with params
    for(map<string, XLayer*>::iterator xlayer_it = graph->layers.begin(); xlayer_it != graph->layers.end(); xlayer_it++)
    {
        if(xlayer_it->second->type == "Convolution")
        {
            extractConvolutionTrainedData(graph, xlayer_it->second->name, Net, modelLayerIndex);
        }
        else if(xlayer_it->second->type == "Deconvolution")
        {
            extractDeconvolutionTrainedData(graph, xlayer_it->second->name, Net, modelLayerIndex);
        }
        else if(xlayer_it->second->type == "InnerProduct")
        {
            extractFCTrainedData(graph, xlayer_it->second->name, Net, modelLayerIndex);
        }
        else if(xlayer_it->second->type == "L2Normalize")
        {
            extractL2NormalizeTrainedData(graph, xlayer_it->second->name, Net, modelLayerIndex);
        }
        else if(xlayer_it->second->type == "BatchNorm")
        {
            extractBatchNormTrainedData(graph, xlayer_it->second->name, Net, modelLayerIndex);
        }
        else if(xlayer_it->second->type == "Scale")
        {
            extractScaleTrainedData(graph, xlayer_it->second->name, Net, modelLayerIndex);
        }
        else if(xlayer_it->second->type == "XCustom")
        {
            extractXCustomTrainedData(graph, xlayer_it->second->name, Net, modelLayerIndex);
        }
        
    }

    // Free the map memory
    delete modelLayerIndex;
}

void extractConvolutionTrainedData(XGraph* graph, const string& layerName, const caffe::NetParameter* Net,
                                    const map<string, int>* layerIndex)