// This loads a graph in the format of PIC 2011.
int LoadGraphUAI(ifstream &file_graph,
FactorGraph *factor_graph) {
string line = "";
// Read header.
while (line == "") {
getline(file_graph, line);
if (file_graph.eof()) return -1;
TrimComments("#", &line);
Trim("\t ", &line);
}
if (line != "MARKOV") {
cout << "Wrong header: " << line << endl;
return -1;
}
int num_factor_log_potentials = 0;
// Read number of multi-variables.
getline(file_graph, line);
TrimComments("#", &line);
int num_multi_variables = atoi(line.c_str());
vector<MultiVariable*> multi_variables(num_multi_variables);
// Read cardinality of each multi-variable.
getline(file_graph, line);
TrimComments("#", &line);
vector<string> fields;
StringSplit(line, "\t ", &fields);
assert(fields.size() == num_multi_variables);
for (int i = 0; i < num_multi_variables; ++i) {
int num_states = atoi(fields[i].c_str());
MultiVariable* multi_variable =
factor_graph->CreateMultiVariable(num_states);
multi_variables[i] = multi_variable;
}
// Read number of factors (includes unary factors).
getline(file_graph, line);
TrimComments("#", &line);
int num_factors = atoi(line.c_str());
// Read factors (just the structure).
vector<Factor*> factors(num_factors);
vector<MultiVariable*> unary_factors(num_factors);
for (int i = 0; i < num_factors; ++i) {
getline(file_graph, line);
TrimComments("#", &line);
fields.clear();
StringSplit(line, "\t ", &fields);
// Read linked multi-variables.
int num_links = atoi(fields[0].c_str());
int offset = 1;
assert(num_links == fields.size() - offset);
if (num_links == 1) {
// Unary factor; in our formalism this is just a multi-variable.
int k = atoi(fields[offset].c_str());
unary_factors[i] = multi_variables[k];
} else {
vector<MultiVariable*> multi_variables_local(num_links);
for (int j = 0; j < num_links; ++j) {
int k = atoi(fields[offset + j].c_str());
multi_variables_local[j] = multi_variables[k];
}
// For now, set an empty vector of additional log potentials.
vector<double> additional_log_potentials;
Factor *factor =
factor_graph->CreateFactorDense(multi_variables_local,
additional_log_potentials);
factors[i] = factor;
}
}
// Read factors (the log-potentials).
// IMPORTANT: the scores in the UAI files are potentials (not log-potentials!)
for (int i = 0; i < num_factors; ++i) {
Factor *factor = factors[i];
line = "";
while (line == "") {
getline(file_graph, line);
TrimComments("#", &line);
Trim(" \t", &line);
}
int num_configurations = atoi(line.c_str());
if (factor == NULL) {
// Unary factor; in our formalism this is just a multi-variable.
assert(unary_factors[i] != NULL);
MultiVariable *multi_variable = unary_factors[i];
int index = 0;
assert(num_configurations == multi_variable->GetNumStates());
while (index < num_configurations) {
getline(file_graph, line);
TrimComments("#", &line);
Trim(" \t", &line);
fields.clear();
StringSplit(line, "\t ", &fields);
for (int j = 0; j < fields.size(); ++j) {
double log_potential = LOG_STABLE(atof(fields[j].c_str()));
multi_variable->SetLogPotential(index, log_potential);
assert(index < num_configurations);
++index;
}
}
} else {
int num_links = static_cast<FactorDense*>(factor)->
GetNumMultiVariables();
int index = 0;
assert(num_configurations ==
static_cast<FactorDense*>(factor)->GetNumConfigurations());
//int r = factor_graph->GetNumVariables() + num_factor_log_potentials;
num_factor_log_potentials += num_configurations;
//static_cast<FactorMultiDense*>(factor)->SetFirstGlobalIndex(r);
vector<double> additional_log_potentials(num_configurations);
while (index < num_configurations) {
getline(file_graph, line);
TrimComments("#", &line);
Trim(" \t", &line);
fields.clear();
StringSplit(line, "\t ", &fields);
for (int j = 0; j < fields.size(); ++j) {
double log_potential = LOG_STABLE(atof(fields[j].c_str()));
additional_log_potentials[index] = log_potential;
assert(index < num_configurations);
++index;
}
}
factor->SetAdditionalLogPotentials(additional_log_potentials);
}
}
cout << "Read " << num_multi_variables << " multi-variables and "
<< num_factors << " factors." << endl;
return 0;
}
int LoadGraph(ifstream &file_graph,
FactorGraph *factor_graph) {
string line;
// Read number of variables.
getline(file_graph, line);
//cout << line << endl;
if (file_graph.eof()) return -1;
TrimComments("#", &line);
int num_variables = atoi(line.c_str());
// Read number of factors.
getline(file_graph, line);
//cout << line << endl;
TrimComments("#", &line);
int num_factors = atoi(line.c_str());
// Read variable log-potentials.
vector<BinaryVariable*> variables(num_variables);
for (int i = 0; i < num_variables; ++i) {
getline(file_graph, line);
TrimComments("#", &line);
double log_potential = atof(line.c_str());
BinaryVariable* variable = factor_graph->CreateBinaryVariable();
variable->SetLogPotential(log_potential);
variables[i] = variable;
}
// Read factors.
int num_messages = 0;
int num_factor_log_potentials = 0;
for (int i = 0; i < num_factors; ++i) {
getline(file_graph, line);
TrimComments("#", &line);
vector<string> fields;
StringSplit(line, "\t ", &fields);
// Read linked variables.
int offset = 1;
int num_links = atoi(fields[1].c_str());
vector<BinaryVariable*> binary_variables(num_links);
vector<bool> negated(num_links, false);
++offset;
if (fields[0] == "PAIR" && num_links != 2) {
cout << "Error: PAIR factor must be attached to 2 variables." << endl;
return -1;
}
for (int j = 0; j < num_links; ++j) {
int k = atoi(fields[offset+j].c_str());
if (k < 0) {
negated[j] = true;
k = -k;
}
--k;
binary_variables[j] = variables[k];
}
// Read factor type.
Factor *factor;
if (fields[0] == "XOR") {
factor = factor_graph->CreateFactorXOR(binary_variables, negated);
} else if (fields[0] == "XOROUT") {
factor = factor_graph->CreateFactorXOROUT(binary_variables, negated);
} else if (fields[0] == "ATMOSTONE") {
factor = factor_graph->CreateFactorAtMostOne(binary_variables,
negated);
} else if (fields[0] == "OR") {
factor = factor_graph->CreateFactorOR(binary_variables, negated);
} else if (fields[0] == "OROUT") {
factor = factor_graph->CreateFactorOROUT(binary_variables, negated);
} else if (fields[0] == "ANDOUT") {
factor = factor_graph->CreateFactorANDOUT(binary_variables, negated);
} else if (fields[0] == "BUDGET") {
// Read the budget value.
int budget = atoi(fields[offset+num_links].c_str());
factor = factor_graph->CreateFactorBUDGET(binary_variables, negated, budget);
} else if (fields[0] == "PAIR") {
// If it is a soft factor, read the factor log-potential.
double log_potential = atof(fields[offset+num_links].c_str());
//int r = num_variables + num_factor_log_potentials;
++num_factor_log_potentials;
//static_cast<FactorPAIR*>(factor)->SetGlobalIndex(r);
//static_cast<FactorPAIR*>(factor)->SetFactorLogPotential(log_potential);
factor = factor_graph->CreateFactorPAIR(binary_variables, log_potential);
} else if (fields[0] == "DENSE") {
// Read the number of multi-variables.
int num_multi_variables = atoi(fields[offset+num_links].c_str());
// Read the number of states for each multi-variable.
vector<MultiVariable*> multi_variables(num_multi_variables);
int num_configurations = 1;
int total_states = 0;
for (int k = 0; k < num_multi_variables; ++k) {
int num_states = atoi(fields[offset+num_links+1+k].c_str());
num_configurations *= num_states;
vector<BinaryVariable*> states(binary_variables.begin() + total_states,
binary_variables.begin() + total_states +
num_states);
total_states += num_states;
multi_variables[k] = factor_graph->CreateMultiVariable(states);
}
// Read the additional log-potentials.
vector<double> additional_scores;
for (int index = 0; index < num_configurations; ++index) {
// Read the factor log-potential for this configuration.
double log_potential = atof(fields[offset+num_links+1+num_multi_variables+index].c_str());
additional_scores.push_back(log_potential);
}
// Create the factor and declare it.
factor = new FactorDense;
factor_graph->DeclareFactor(factor, binary_variables, true);
static_cast<FactorDense*>(factor)->Initialize(multi_variables);
factor->SetAdditionalLogPotentials(additional_scores);
num_factor_log_potentials += additional_scores.size();
cout << "Read dense factor." << endl;
} else if (fields[0] == "SEQUENCE" ||
fields[0] == "SEQUENCE_BUDGET") {
bool has_budget = false;
if (fields[0] == "SEQUENCE_BUDGET") has_budget = true;
// Read the sequence length.
int length = atoi(fields[offset+num_links].c_str());
// If budget, read the budget.
int budget = -1;
if (has_budget) {
++offset; // TODO: Make sure this is fine.
budget = atoi(fields[offset+num_links].c_str());
}
// Read the number of states for each position in the sequence.
vector<int> num_states(length);
int total_states = 0;
for (int k = 0; k < length; ++k) {
num_states[k] = atoi(fields[offset+num_links+1+k].c_str());
total_states += num_states[k];
}
// Read the additional log-potentials.
vector<double> additional_scores;
int index = 0;
for (int i = 0; i <= length; ++i) {
// If i == 0, the previous state is the start symbol.
int num_previous_states = (i > 0)? num_states[i - 1] : 1;
// If i == length-1, the previous state is the final symbol.
int num_current_states = (i < length)? num_states[i] : 1;
for (int j = 0; j < num_previous_states; ++j) {
for (int k = 0; k < num_current_states; ++k) {
double log_potential = atof(fields[offset+num_links+1+length+index].c_str());
additional_scores.push_back(log_potential);
++index;
}
}
}
if (fields.size() != offset+num_links+1+length+index) {
cout << fields.size() << " "
<< offset+num_links+1+length+index;
assert(false);
}
// Create the factor and declare it.
if (has_budget) {
factor = new FactorSequenceBudget;
factor_graph->DeclareFactor(factor, binary_variables, true);
static_cast<FactorSequenceBudget*>(factor)->
Initialize(num_states, budget);
factor->SetAdditionalLogPotentials(additional_scores);
num_factor_log_potentials += additional_scores.size();
cout << "Read sequence budget factor." << endl;
} else {
factor = new FactorSequence;
factor_graph->DeclareFactor(factor, binary_variables, true);
static_cast<FactorSequence*>(factor)->Initialize(num_states);
factor->SetAdditionalLogPotentials(additional_scores);
num_factor_log_potentials += additional_scores.size();
cout << "Read sequence factor." << endl;
}
} else if (fields[0] == "GENERAL_TREE" ||
fields[0] == "GENERAL_TREE_COUNTS") {
// Read the number of nodes in the tree.
int length = atoi(fields[offset+num_links].c_str());
// Read the number of states for each node in the tree.
vector<int> num_states(length);
int total_states = 0;
for (int k = 0; k < length; ++k) {
num_states[k] = atoi(fields[offset+num_links+1+k].c_str());
total_states += num_states[k];
}
// Read the parent node for each node in the tree.
vector<int> parents(length);
for (int k = 0; k < length; ++k) {
parents[k] = atoi(fields[offset+num_links+1+length+k].c_str());
}
// Read the additional log-potentials.
vector<double> additional_scores;
int index = 0;
for (int i = 1; i < length; ++i) {
int p = parents[i];
int num_previous_states = num_states[p];
int num_current_states = num_states[i];
for (int k = 0; k < num_previous_states; ++k) {
for (int j = 0; j < num_current_states; ++j) {
double log_potential = atof(fields[offset+num_links+1+length+length+index].c_str());
additional_scores.push_back(log_potential);
++index;
}
}
}
if (fields.size() != offset+num_links+1+length+length+index) {
cout << fields.size() << " "
<< offset+num_links+1+length+length+index << endl;
assert(false);
}
// Create the factor and declare it.
if (fields[0] == "GENERAL_TREE") {
factor = new FactorGeneralTree;
factor_graph->DeclareFactor(factor, binary_variables, true);
static_cast<FactorGeneralTree*>(factor)->Initialize(parents, num_states);
} else {
factor = new FactorGeneralTreeCounts;
factor_graph->DeclareFactor(factor, binary_variables, true);
static_cast<FactorGeneralTreeCounts*>(factor)->Initialize(parents, num_states);
}
factor->SetAdditionalLogPotentials(additional_scores);
num_factor_log_potentials += additional_scores.size();
if (fields[0] == "GENERAL_TREE") {
cout << "Read general tree factor." << endl;
} else {
cout << "Read general tree counts factor." << endl;
}
} else if (fields[0] == "ARBORESCENCE") {
// Read the sentence length.
int sentence_length = atoi(fields[offset+num_links].c_str());
// Read the arcs.
vector<Arc*> arcs(binary_variables.size());
for (int r = 0; r < binary_variables.size(); ++r) {
//cout << fields.size() << " " << offset+num_links+2*r+1 << endl;
int h = atoi(fields[offset+num_links+1+2*r].c_str());
int m = atoi(fields[offset+num_links+1+2*r+1].c_str());
Arc *arc = new Arc(h, m);
arcs[r] = arc;
}
factor = new FactorTree;
factor_graph->DeclareFactor(factor, binary_variables, true);
static_cast<FactorTree*>(factor)->Initialize(sentence_length, arcs);
for (int r = 0; r < arcs.size(); ++r) {
delete arcs[r];
}
cout << "Read tree factor." << endl;
} else if (fields[0] == "HEAD_AUTOMATON") {
// Read the length of the automaton.
int length = binary_variables.size() + 1;
vector<vector<int> > index_siblings(length, vector<int>(length+1, -1));
int total = 0;
vector<Sibling*> siblings;
vector<double> additional_scores;
for (int m = 0; m < length; ++m) {
for (int s = m+1; s <= length; ++s) {
// Create a fake sibling.
Sibling *sibling = new Sibling(0, m, s);
siblings.push_back(sibling);
// Read the sibling log-potential.
double log_potential = atof(fields[offset+num_links+total].c_str());
additional_scores.push_back(log_potential);
++total;
}
}
factor = new FactorHeadAutomaton;
factor_graph->DeclareFactor(factor, binary_variables, true);
static_cast<FactorHeadAutomaton*>(factor)->Initialize(length, siblings);
for (int r = 0; r < siblings.size(); ++r) {
delete siblings[r];
}
factor->SetAdditionalLogPotentials(additional_scores);
num_factor_log_potentials += additional_scores.size();
cout << "Read head automaton factor." << endl;
} else if (fields[0] == "SEQUENCE_COMPRESSOR") {
// Read the length of the automaton.
int length = binary_variables.size();
vector<vector<int> > index_siblings(length, vector<int>(length+1, -1));
int total = 0;
vector<Sibling*> siblings;
vector<double> additional_scores;
for (int m = 0; m < length; ++m) {
for (int s = m+1; s <= length; ++s) {
// Create a fake sibling.
Sibling *sibling = new Sibling(0, m, s);
siblings.push_back(sibling);
// Read the sibling log-potential.
double log_potential = atof(fields[offset+num_links+total].c_str());
additional_scores.push_back(log_potential);
++total;
}
}
factor = new FactorSequenceCompressor;
factor_graph->DeclareFactor(factor, binary_variables, true);
static_cast<FactorSequenceCompressor*>(factor)->Initialize(length, siblings);
for (int r = 0; r < siblings.size(); ++r) {
delete siblings[r];
}
factor->SetAdditionalLogPotentials(additional_scores);
num_factor_log_potentials += additional_scores.size();
cout << "Read sequence compressor factor." << endl;
} else if (fields[0] == "GRANDPARENT_HEAD_AUTOMATON") {
// Read the number of grandparents.
int num_grandparents = atoi(fields[offset+num_links].c_str());
// Read the length of the automaton.
int length = binary_variables.size() + 1 - num_grandparents;
vector<vector<int> > index_siblings(length, vector<int>(length+1, -1));
int total = 0;
vector<Grandparent*> grandparents;
vector<double> additional_scores;
for (int g = 0; g < num_grandparents; ++g) {
for (int m = 1; m < length; ++m) {
// Create a fake grandparent.
Grandparent *grandparent = new Grandparent(g, 0, m);
grandparents.push_back(grandparent);
// Read the sibling log-potential.
double log_potential = atof(fields[offset+num_links+1+total].c_str());
additional_scores.push_back(log_potential);
++total;
}
}
vector<Sibling*> siblings;
for (int m = 0; m < length; ++m) {
for (int s = m+1; s <= length; ++s) {
// Create a fake sibling.
Sibling *sibling = new Sibling(0, m, s);
siblings.push_back(sibling);
// Read the sibling log-potential.
double log_potential = atof(fields[offset+num_links+1+total].c_str());
additional_scores.push_back(log_potential);
++total;
}
}
factor = new FactorGrandparentHeadAutomaton;
factor_graph->DeclareFactor(factor, binary_variables, true);
static_cast<FactorGrandparentHeadAutomaton*>(factor)->
Initialize(length, num_grandparents, siblings, grandparents);
for (int r = 0; r < grandparents.size(); ++r) {
delete grandparents[r];
}
for (int r = 0; r < siblings.size(); ++r) {
delete siblings[r];
}
factor->SetAdditionalLogPotentials(additional_scores);
num_factor_log_potentials += additional_scores.size();
cout << "Read grandparent head automaton factor." << endl;
} else {
cout << "Unknown factor type: " << fields[0] << endl;
return -1;
}
}
// Read blank line.
getline(file_graph, line);
cout << "Read " << num_variables << " variables and "
<< num_factors << " factors." << endl;
//ofstream file_out("test.fg", ios_base::out);
//factor_graph->Print(file_out);
//file_out.flush();
//file_out.clear();
//file_out.close();
//factor_graph->Initialize(variables, factors, num_messages);
return 0;
}
