Esempio n. 1
3
/////////////////////////////////////////////////////////////////////////
// Vertex Loader (used to read images and load the vertex data of the graph)
//bool vertex_loader(graph_type& graph, const std::string& fname,
//                   const std::string& line)
bool vertex_loader(graphlab::distributed_control& dc, graph_type& graph, string img_path)
{
    // force a "/" at the end of the path
    // make sure to check that the path is non-empty. (you do not
    // want to make the empty path "" the root path "/" )
    string path = img_path;
    if (path.length() > 0 && path[path.length() - 1] != '/') path = path + "/";
    
    vector<string> graph_files;
    string search_prefix;
    graphlab::fs_util::list_files_with_prefix(path, search_prefix, graph_files);
    
    if (graph_files.size() == 0)
        logstream(LOG_WARNING) << "No files found in " << path << std::endl;
    
    // vertex data & id
    graphlab::vertex_id_type vid(-1);
    
    ///////////////////////////////////////////////////////
    // Loop over files
    for(size_t i = 0; i < graph_files.size(); ++i)
    {
        // Each machine loads corresponding file
        if (i % dc.numprocs() == dc.procid())
        {
            if (opts.verbose > 0)
                logstream(LOG_EMPH)
                << "Process: " << dc.procid() << "/" << dc.numprocs() << " "
                << "picked image: " << graph_files[i] << "\n";
            
            
            vid = i;
            vertex_data vdata;
            vdata.empty = false;
            vdata.img_path = graph_files[i];
            vdata.features.img_idx = i;
            
            graph.add_vertex(vid, vdata);
            
        }
    }
    
    return true;
}
Esempio n. 2
0
/////////////////////////////////////////////////////////////////////////
// Load the UAI file. Each factor as a different vertex
void loadUAIfile(graphlab::distributed_control& dc, graph_type& graph, string graph_file) 
{
    // Not sure why this is needed
    dc.barrier();
    
    // Open file
    ifstream in(graph_file.c_str());
    
    //CHECK(in.good(),"Could not open file: "+graph_file);
    CHECK(in.good());
    
    // Read type of network
    string name; 
    
    in >> name; 
    //CHECK(name.compare("MARKOV")==0, "Only Markov networks are supported. Are you sure this is a typeUAI energy file?");
    CHECK(name.compare("MARKOV")==0);
    
    // Read size of graph
    int nnodes, nfactors;
    in >> nnodes;
    //CHECK(nnodes>0, "No. of nodes can't be negative. Are you sure this is a typeUAI energy file?");
    CHECK(nnodes>0);
        
    // Read node cardinalities
    vector<int> cardinalities(nnodes,0);
    int cardinality_i, sum_of_cardinalities = 0;
    for (int i = 0; i != nnodes; ++i) 
    {
        in >> cardinality_i;
        cardinalities[i] = cardinality_i;
        sum_of_cardinalities += cardinality_i;
        
        //cout << cardinalities[i] << " ";
        //CHECK(in.good(), "Could not finish reading cardinalities. Are you sure this is a typeUAI energy file?");
        CHECK(in.good());
    }
    
    // Read no. of factors
    in >> nfactors;
    
    //factor_size.resize(nfactors); factor_id.resize(nfactors);
    vector<int> factor_size(nfactors,0); //vector<int> factor_id(nfactors,0); 
    vector< vector<int> > factor_memb; factor_memb.resize(nfactors);
    int temp1, temp2;
    
    // Loop and read factor members
    for (int i=0; i!=nfactors; ++i) 
    {
        in >> temp1;
        factor_size[i] = temp1; 
        
        factor_memb[i].resize(temp1);
        for (int j=0; j!=temp1; ++j) 
        {
            in >> temp2;
            factor_memb[i][j] = temp2;
        }
        
        //CHECK(in.good(), "Could not finish reading cardinalities. Are you sure this is a typeUAI energy file?");
        CHECK(in.good());
    }
    
    if (opts.verbose > 0)
        cout 
        << "Finished Reading UAI-Preamble:"
        << " #Nodes = " << nnodes 
        << ", #Factors = "<< nfactors 
        << ", Average Cardinality = " << double(sum_of_cardinalities)/nfactors
        << "\n";
        
        
    // Now read factor potentials
    for (int i=0; i!=nfactors; ++i) 
    {
        int cardprod; double potential_value; //, energy;
        in >> cardprod;
        
        vertex_data vdata;        
        vdata.nvars = factor_size[i];
        if (vdata.nvars > 1) {
          vdata.degree = vdata.nvars; // Factor degree.
        }
        
        vdata.cards.resize(factor_size[i]);
        vdata.neighbors.resize(factor_size[i]);
        
        vector<edge_data> edata(factor_size[i]);
        
        int cardprod2 = 1;
        for (int j=0; j!=factor_size[i]; ++j) 
        {
            vdata.cards[j] = cardinalities[factor_memb[i][j]];
            vdata.neighbors[j] = factor_memb[i][j]; // afm (check if this was intended!)
            cardprod2 *= vdata.cards[j];
            
            // Also create edge structs here
            if (factor_size[i]>1)
            {
                edata[j].varid = factor_memb[i][j];
                edata[j].card = cardinalities[edata[j].varid];
                edata[j].multiplier_messages.setZero(edata[j].card);
                edata[j].local_messages.setZero(edata[j].card);
            }
        }
        
        //CHECK_EQ(cardprod, cardprod2, "Incorrectly sized factor");
        CHECK_EQ(cardprod, cardprod2);
        
        // Read factor potentials
        vdata.potentials.resize(cardprod);
        for (int k = 0; k != cardprod; ++k) 
        {
            in >> potential_value;
            //energy = Potential2Energy(potential_value);
            
            vdata.potentials[k] = log10(potential_value);
        }
        
        //CHECK(in.good(), "Could not finish reading factor tables. Are you sure this is a typeUAI energy file?");
        CHECK(in.good());
        
        // allocate factors evenly to different machines.
        if (i%dc.numprocs() != dc.procid()) 
            continue;
        
        // If all is well, add vertex and edges
        graph.add_vertex(i,vdata);
        if (factor_size[i] > 1) // if not a unary, add edges to unaries
            for (int j=0; j!=factor_size[i]; ++j) 
                graph.add_edge(i,edata[j].varid,edata[j]);
        
        if (opts.verbose > 1)
        {
            cout << "Machine #" << dc.procid() << ", Vertex Id = " << i
            << " with " << vdata.nvars << " variables."; 
            if (factor_size[i] > 1)
            {
                cout << ", Edges = ";
                for (int j=0; j!=factor_size[i]; ++j)             
                    cout << ", (" << i << "," << edata[j].varid << ")";
            }
            cout << "\n";
            cout << "potential: " << vdata.potentials << "\n";
        }
        
    } // End of reading factors   
    
    
    
    dc.barrier();
} // end of loading UAI file
Esempio n. 3
0
bool graph_loader(graphlab::distributed_control& dc, graph_type& graph, string img_dir)
{
    // force a "/" at the end of the path
    // make sure to check that the path is non-empty. (you do not
    // want to make the empty path "" the root path "/" )
    string path = img_dir;
    if (path.length() > 0 && path[path.length() - 1] != '/') path = path + "/";
    
    vector<string> graph_files;
    string search_prefix;
    graphlab::fs_util::list_files_with_prefix(path, search_prefix, graph_files);
    
    if (graph_files.size() == 0)
        logstream(LOG_WARNING) << "No files found in " << path << std::endl;
    
    
    if (opts.verbose > 2)
        logstream(LOG_EMPH)
        << "Total number of images: " << graph_files.size() << "\n";
    
    // vertex data & id
    graphlab::vertex_id_type vid(-1);
    graphlab::vertex_id_type other_vid;
    
    ///////////////////////////////////////////////////////
    // Loop over files
    for(size_t i = 0; i < graph_files.size(); ++i)
    {
        // Each machine loads corresponding file
        if (i % dc.numprocs() == dc.procid())
        {
            if (opts.verbose > 0)
                logstream(LOG_EMPH)
                << "Process: " << dc.procid() << "/" << dc.numprocs() << " "
                << "picked image: " << graph_files[i] << "\n";
            
            
            vid = i;
            vertex_data vdata;
            vdata.empty = false;
            vdata.img_path = graph_files[i];
            vdata.features.img_idx = i;
            
            graph.add_vertex(vid, vdata);
            
            if (opts.verbose > 2)
                logstream(LOG_EMPH)
                << "Vertex " << i << " Image: " << vdata.img_path << "\n"; 
            
        }
    }
    
    // Adding edges between every pair of vertices to create a fully connected graph
    // no duplicate edges are added
    for(size_t i = 0; i < graph_files.size()-1; ++i)
    {
        vid = i;
        for(size_t j = i+1; j < graph_files.size(); ++j)
        {
            other_vid = j;
            if (opts.verbose > 0)
                logstream(LOG_EMPH) << "Adding edge: (" << vid << "," << other_vid << ")\n";
            
            edge_data edata; edata.empty = false;
            graph.add_edge(vid,other_vid,edata);
        }
    }
    return true;
}
Esempio n. 4
0
/////////////////////////////////////////////////////////////////////////
// Load the UAI file. Each factor as a different vertex
void loadUAIfile(graphlab::distributed_control& dc, graph_type& graph, string graph_file, int& nodes) 
{  
    // Not sure why this is needed
    dc.barrier();
    // Open file
    ifstream in(graph_file.c_str());
     
    //CHECK(in.good(),"Could not open file: "+graph_file);
    CHECK(in.good());
    
    // Read type of network
    string name; 
    
    in >> name; 
    //CHECK(name.compare("MARKOV")==0, "Only Markov networks are supported. Are you sure this is a typeUAI energy file?");
    CHECK(name.compare("MARKOV")==0);
    
    // Read size of graph
    int nnodes, nfactors;
    in >> nnodes;
    nodes = nnodes;
    //CHECK(nnodes>0, "No. of nodes can't be negative. Are you sure this is a typeUAI energy file?");
    CHECK(nnodes>0);    
    // Read node cardinalities
    vector<int> cardinalities(nnodes,0);
    int cardinality_i, sum_of_cardinalities = 0;
    for (int i = 0; i != nnodes; ++i) 
    {
        in >> cardinality_i;
        cardinalities[i] = cardinality_i;
        sum_of_cardinalities += cardinality_i;
       
        //CHECK(in.good(), "Could not finish reading cardinalities. Are you sure this is a typeUAI energy file?");
        CHECK(in.good());
    }

    int vid = 0;
    if(opts.algorithm != 0){
       for(int i = 0; i < nnodes; i++){                      //temporary .. put condition
           vertex_data vdata;
           vdata.factor_type = VAR; 
           vdata.nvars = 1;
           vdata.cards.resize(1, cardinalities[i]);
           vdata.potentials.setZero(cardinalities[i]);
           vdata.beliefs.setConstant(cardinalities[i], 0.5);
           graph.add_vertex(vid, vdata);
           vid++;
       }
    }
    // Read no. of factors
    in >> nfactors;
    
    //factor_size.resize(nfactors); factor_id.resize(nfactors);
    vector<int> factor_size(nfactors,0); //vector<int> factor_id(nfactors,0); 
    vector< vector<int> > factor_memb; factor_memb.resize(nfactors);
    int temp1, temp2;
    
    // Loop and read factor members
    for (int i=0; i!=nfactors; ++i) 
    {
        in >> temp1;
        factor_size[i] = temp1; 
        
        factor_memb[i].resize(temp1);
        for (int j=0; j!=temp1; ++j) 
        {
            in >> temp2;
            factor_memb[i][j] = temp2;
        }
        
        //CHECK(in.good(), "Could not finish reading cardinalities. Are you sure this is a typeUAI energy file?");
        CHECK(in.good());
    }
    
    if (opts.verbose > 1)
        cout 
        << "Finished Reading UAI-Preamble:"
        << " #Nodes = " << nnodes 
        << ", #Factors = "<< nfactors 
        << ", Average Cardinality = " << double(sum_of_cardinalities)/nfactors
        << "\n";
        
        
    // Now read factor potentials
    for (int i=0; i!=nfactors; ++i) 
    {
        int cardprod; double potential_value; //, energy;
        in >> cardprod;
        
        vertex_data vdata;        
        vdata.nvars = factor_size[i];
        if (vdata.nvars > 1) {
          vdata.degree = vdata.nvars; // Factor degree.
          vdata.factor_type = DENSE;
        }
        else {
          vdata.degree = 1; // Factor degree.
          vdata.factor_type = XOR;
        }
        vdata.cards.resize(factor_size[i]);
        vdata.neighbors.resize(factor_size[i]);
        
        vector<edge_data> edata(factor_size[i]);
        vector<int> varid(factor_size[i]);
        vector<int> card(factor_size[i]);
        
        int cardprod2 = 1;
        for (int j=0; j!=factor_size[i]; ++j) 
        {
            vdata.cards[j] = cardinalities[factor_memb[i][j]];
            vdata.neighbors[j] = factor_memb[i][j]; // afm (check if this was intended!)
            cardprod2 *= vdata.cards[j];
                      
            // Also create edge structs here
            //if (factor_size[i]>1)
           // {
                varid[j] = factor_memb[i][j];
                card[j] = cardinalities[varid[j]];
                edata[j].multiplier_messages.setZero(card[j]);
                edata[j].local_messages.setZero(card[j]);
                edata[j].potentials.setZero(card[j]);
          //  }
        }
        
        //CHECK_EQ(cardprod, cardprod2, "Incorrectly sized factor");
        CHECK_EQ(cardprod, cardprod2);
        
        // Read factor potentials
        vdata.potentials.resize(cardprod);
        vdata.beliefs.resize(cardprod);
        int x_offset = 0;
        for(int x=0; x< vdata.nvars; x++){
            for(int y=0; y<vdata.cards[x]; y++){
               vdata.beliefs[x_offset+y] = 1.0/vdata.cards[x];
            }
            x_offset += vdata.cards[x];
        }         
            
        vdata.factor_beliefs.setConstant(cardprod, 1.0/cardprod);
        for (int k = 0; k != cardprod; ++k) 
        {
            in >> potential_value;
            //energy = Potential2Energy(potential_value);
            
            vdata.potentials[k] = log10(potential_value) ;
        }
        
        //CHECK(in.good(), "Could not finish reading factor tables. Are you sure this is a typeUAI energy file?");

        CHECK(in.good());
         

         vdata.potentials.maxCoeff(&vdata.best_configuration);
        // allocate factors evenly to different machines.
        if (i%dc.numprocs() != dc.procid()) 
            continue;
        
        // If all is well, add vertex and edge
        graph.add_vertex(vid ,vdata);

        if (factor_size[i] > 1 || opts.algorithm > 0) // if not a unary, add edges to unaries
        for (int j=0; j!=factor_size[i]; ++j) 
            graph.add_edge(vid,varid[j],edata[j]);
        
        //after adding everything increment vertex id
        vid++; 
        
        if (opts.verbose > 1)
        {
            cout << "Machine #" << dc.procid() << ", Vertex Id = " << i
            << " with " << vdata.nvars << " variables."; 
            if (factor_size[i] > 1)
            {
                cout << ", Edges = ";
                for (int j=0; j!=factor_size[i]; ++j)             
                    cout << ", (" << i << "," << varid[j] << ")";
            }
            cout << "\n";
            cout << "potential: " << vdata.potentials << "\n";
        }
        
    } // End of reading factors     
   
    dc.barrier();
} // end of loading UAI file