/*
 * Licensed to the Apache Software Foundation (ASF) under one
 * or more contributor license agreements.  See the NOTICE file
 * distributed with this work for additional information
 * regarding copyright ownership.  The ASF licenses this file
 * to you under the Apache License, Version 2.0 (the
 * "License"); you may not use this file except in compliance
 * with the License.  You may obtain a copy of the License at
 *
 *   http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing,
 * software distributed under the License is distributed on an
 * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
 * KIND, either express or implied.  See the License for the
 * specific language governing permissions and limitations
 * under the License.
 */

package org.apache.sysds.hops.ipa;

import org.apache.commons.logging.Log;
import org.apache.commons.logging.LogFactory;
import org.apache.sysds.common.Types.DataType;
import org.apache.sysds.common.Types.ValueType;
import org.apache.sysds.conf.ConfigurationManager;
import org.apache.sysds.hops.DataOp;
import org.apache.sysds.hops.FunctionOp;
import org.apache.sysds.hops.FunctionOp.FunctionType;
import org.apache.sysds.hops.Hop;
import org.apache.sysds.hops.HopsException;
import org.apache.sysds.hops.LiteralOp;
import org.apache.sysds.hops.OptimizerUtils;
import org.apache.sysds.hops.recompile.Recompiler;
import org.apache.sysds.parser.DMLProgram;
import org.apache.sysds.parser.DMLTranslator;
import org.apache.sysds.parser.DataIdentifier;
import org.apache.sysds.parser.ForStatement;
import org.apache.sysds.parser.ForStatementBlock;
import org.apache.sysds.parser.FunctionStatement;
import org.apache.sysds.parser.FunctionStatementBlock;
import org.apache.sysds.parser.IfStatement;
import org.apache.sysds.parser.IfStatementBlock;
import org.apache.sysds.parser.StatementBlock;
import org.apache.sysds.parser.WhileStatement;
import org.apache.sysds.parser.WhileStatementBlock;
import org.apache.sysds.runtime.controlprogram.LocalVariableMap;
import org.apache.sysds.runtime.controlprogram.caching.MatrixObject;
import org.apache.sysds.runtime.instructions.cp.Data;
import org.apache.sysds.runtime.instructions.cp.ScalarObject;
import org.apache.sysds.runtime.instructions.cp.ScalarObjectFactory;
import org.apache.sysds.runtime.meta.DataCharacteristics;
import org.apache.sysds.runtime.meta.MatrixCharacteristics;
import org.apache.sysds.runtime.meta.MetaDataFormat;

import java.util.ArrayList;
import java.util.HashSet;
import java.util.Set;

/**
 * This Inter Procedural Analysis (IPA) serves two major purposes:
 *   1) Inter-Procedure Analysis: propagate statistics from calling program into 
 *      functions and back into main program. This is done recursively for nested 
 *      function invocations.
 *   2) Intra-Procedural Analysis: propagate statistics across hop dags of subsequent 
 *      statement blocks in order to allow chained function calls and reasoning about
 *      changing sparsity etc (that requires the rewritten hops dag as input). This 
 *      also includes control-flow aware propagation of size and sparsity. Furthermore,
 *      it also serves as a second constant propagation pass.
 *   
 *  Additionally, IPA also covers the removal of unused functions, the decision on
 *  recompile once functions, the removal of unnecessary checkpoints, and the 
 *  global removal of constant binary operations such as X * ones.
 */
public class InterProceduralAnalysis 
{
	private static final Log LOG = LogFactory.getLog(InterProceduralAnalysis.class.getName());

	//internal configuration parameters
	protected static final boolean INTRA_PROCEDURAL_ANALYSIS      = true; //propagate statistics across statement blocks (main/functions)	
	protected static final boolean PROPAGATE_KNOWN_UDF_STATISTICS = true; //propagate statistics for known external functions 
	protected static final boolean ALLOW_MULTIPLE_FUNCTION_CALLS  = true; //propagate consistent statistics from multiple calls 
	protected static final boolean REMOVE_UNUSED_FUNCTIONS        = true; //remove unused functions (inlined or never called)
	protected static final boolean FLAG_FUNCTION_RECOMPILE_ONCE   = true; //flag functions which require recompilation inside a loop for full function recompile
	protected static final boolean REMOVE_UNNECESSARY_CHECKPOINTS = true; //remove unnecessary checkpoints (unconditionally overwritten intermediates) 
	protected static final boolean REMOVE_CONSTANT_BINARY_OPS     = true; //remove constant binary operations (e.g., X*ones, where ones=matrix(1,...)) 
	protected static final boolean PROPAGATE_SCALAR_VARS_INTO_FUN = true; //propagate scalar variables into functions that are called once
	protected static final boolean PROPAGATE_SCALAR_LITERALS      = true; //propagate and replace scalar literals into functions
	protected static final boolean APPLY_STATIC_REWRITES          = true; //apply static hop dag and statement block rewrites
	protected static final boolean APPLY_DYNAMIC_REWRITES         = true; //apply dynamic hop dag and statement block rewrites
	protected static final int     INLINING_MAX_NUM_OPS           = 10;   //inline single-statement functions w/ #ops <= threshold, other than dataops and literals
	protected static final boolean ELIMINATE_DEAD_CODE            = true; //remove dead code (e.g., assigments) not used later on
	protected static final boolean FORWARD_SIMPLE_FUN_CALLS       = true; //replace a call to a simple forwarding function with the function itself
	protected static final boolean FLAG_NONDETERMINISM            = true; //flag functions which directly or transitively contain non-deterministic calls
	
	private final DMLProgram _prog;
	private final StatementBlock _sb;
	
	//function call graph for functions reachable from main
	private FunctionCallGraph _fgraph;
	
	//set IPA passes to apply in order 
	private final ArrayList<IPAPass> _passes;
	
	/**
	 * Creates a handle for performing inter-procedural analysis
	 * for a given DML program and its associated HOP DAGs. This
	 * call initializes various internal information such as the
	 * function call graph  which can be reused across multiple IPA 
	 * calls (e.g., for second chance analysis).
	 *
	 * @param dmlp The DML program to analyze
	 */
	public InterProceduralAnalysis(DMLProgram dmlp) {
		//analyzes the function call graph 
		_prog = dmlp;
		_sb = null;
		_fgraph = new FunctionCallGraph(dmlp);
		
		//create order list of IPA passes
		_passes = new ArrayList<>();
		_passes.add(new IPAPassRemoveUnusedFunctions());
		_passes.add(new IPAPassFlagFunctionsRecompileOnce());
		_passes.add(new IPAPassRemoveUnnecessaryCheckpoints());
		_passes.add(new IPAPassRemoveConstantBinaryOps());
		_passes.add(new IPAPassPropagateReplaceLiterals());
		_passes.add(new IPAPassInlineFunctions());
		_passes.add(new IPAPassEliminateDeadCode());
		_passes.add(new IPAPassFlagNonDeterminism());
		//note: apply rewrites last because statement block rewrites
		//might merge relevant statement blocks in special cases, which 
		//would require an update of the function call graph
		_passes.add(new IPAPassForwardFunctionCalls());
		_passes.add(new IPAPassApplyStaticAndDynamicHopRewrites());
	}
	
	public InterProceduralAnalysis(StatementBlock sb) {
		//analyzes the function call graph 
		_prog = sb.getDMLProg();
		_sb = sb;
		_fgraph = new FunctionCallGraph(sb);
		
		//create order list of IPA passes
		_passes = new ArrayList<>();
	}
	
	/**
	 * Main interface to perform IPA over a given DML program.
	 * 
	 */
	public void analyzeProgram() {
		analyzeProgram(1); //single run
	}
	
	/**
	 * Main interface to perform IPA over a given DML program.
	 * 
	 * @param repetitions number of IPA rounds 
	 */
	@SuppressWarnings("null")
	public void analyzeProgram(int repetitions) {
		//sanity check for valid number of repetitions
		if( repetitions <= 0 )
			throw new HopsException("Invalid number of IPA repetitions: " + repetitions);
		
		//perform number of requested IPA iterations
		FunctionCallSizeInfo lastSizes = null;
		for( int i=0; i<repetitions; i++ ) {
			if( LOG.isDebugEnabled() )
				LOG.debug("IPA: start IPA iteration " + (i+1) + "/" + repetitions +".");
			
			//get function call size infos to obtain candidates for statistics propagation
			FunctionCallSizeInfo fcallSizes = new FunctionCallSizeInfo(_fgraph);
			if( LOG.isDebugEnabled() )
				LOG.debug("IPA: Initial FunctionCallSummary: \n" + fcallSizes);
			
			//step 0: retain original unoptimized functions for eval()
			if( _fgraph.containsSecondOrderCall() && i==0 ) //on first call
				_prog.copyOriginalFunctions();
			
			//step 1: intra- and inter-procedural 
			if( INTRA_PROCEDURAL_ANALYSIS ) {
				//get unary dimension-preserving non-candidate functions
				//note: we have to guard against recursive functions because these might
				//be seen at top-level as a unary size-preserving function but internally
				//called with different sizes (e.g., common block-recursive cholesky)
				for( String tmp : fcallSizes.getInvalidFunctions() ) {
					if( !_fgraph.isRecursiveFunction(tmp)
						&& isUnarySizePreservingFunction(_prog.getFunctionStatementBlock(tmp)))
						fcallSizes.addDimsPreservingFunction(tmp);
				}
				if( LOG.isDebugEnabled() )
					LOG.debug("IPA: Extended FunctionCallSummary: \n" + fcallSizes);
				
				//propagate statistics and scalars into functions and across DAGs
				//(callVars used to chain outputs/inputs of multiple functions calls)
				LocalVariableMap callVars = new LocalVariableMap();
				for ( StatementBlock sb : _prog.getStatementBlocks() ) //propagate stats into candidates
					propagateStatisticsAcrossBlock( sb, callVars, fcallSizes, new HashSet<String>(), true );
			}
			
			//step 2: apply additional IPA passes
			boolean rebuildFGraph = false;
			for( IPAPass pass : _passes )
				if( pass.isApplicable(_fgraph) )
					rebuildFGraph |= pass.rewriteProgram(_prog, _fgraph, fcallSizes);
			
			//early abort without functions or on reached fixpoint
			if( _fgraph.getReachableFunctions().isEmpty() 
				|| (lastSizes != null && lastSizes.equals(fcallSizes)) ) {
				if( LOG.isDebugEnabled() )
					LOG.debug("IPA: Early abort after " + (i+1) + "/" + repetitions
						+ " repetitions due to reached fixpoint.");
				break;
			}
			
			//step 3: rebuild function call graph if necessary
			if( rebuildFGraph && i < repetitions-1 )
				_fgraph = new FunctionCallGraph(_prog);
		}
		
		//cleanup pass: remove unused functions
		FunctionCallGraph graph2 = new FunctionCallGraph(_prog);
		IPAPass rmFuns = new IPAPassRemoveUnusedFunctions();
		if( rmFuns.isApplicable(graph2) )
			rmFuns.rewriteProgram(_prog, graph2, null);
	}
	
	public Set<String> analyzeSubProgram() {
		DMLTranslator.resetHopsDAGVisitStatus(_sb);
		
		//get function call size infos to obtain candidates for statistics propagation
		FunctionCallSizeInfo fcallSizes = new FunctionCallSizeInfo(_fgraph);
		
		//propagate statistics and scalars into functions and across DAGs
		//(callVars used to chain outputs/inputs of multiple functions calls) 
		if( !fcallSizes.getValidFunctions().isEmpty() ) {
			LocalVariableMap callVars = new LocalVariableMap();
			propagateStatisticsAcrossBlock(_sb, callVars, fcallSizes, new HashSet<String>(), true);
		}
		
		return fcallSizes.getValidFunctions();
	}
	
	private boolean isUnarySizePreservingFunction(FunctionStatementBlock fsb) {
		FunctionStatement fstmt = (FunctionStatement) fsb.getStatement(0);
		
		//check unary functions over matrices
		boolean ret = (fstmt.getInputParams().size() == 1 
			&& fstmt.getInputParams().get(0).getDataType()==DataType.MATRIX
			&& fstmt.getOutputParams().size() == 1
			&& fstmt.getOutputParams().get(0).getDataType()==DataType.MATRIX);
		
		//check size-preserving characteristic
		if( ret ) {
			FunctionCallSizeInfo fcallSizes = new FunctionCallSizeInfo(_fgraph, false);
			HashSet<String> fnStack = new HashSet<>();
			LocalVariableMap callVars = new LocalVariableMap();
			
			//populate input (recognizable numbers, later reset)
			MatrixObject mo = createOutputMatrix(7777, 3333, -1);
			callVars.put(fstmt.getInputParams().get(0).getName(), mo);
			
			//propagate statistics
			for (StatementBlock sbi : fstmt.getBody())
				propagateStatisticsAcrossBlock(sbi, callVars, fcallSizes, fnStack, false);
		
			//compare output
			MatrixObject mo2 = (MatrixObject)callVars.get(fstmt.getOutputParams().get(0).getName());
			ret &= mo.getNumRows() == mo2.getNumRows() && mo.getNumColumns() == mo2.getNumColumns();
		
			//reset function (note: mo might have been replaced)
			mo.getDataCharacteristics().setDimension(-1, -1);
			callVars.put(fstmt.getInputParams().get(0).getName(), mo);
			for (StatementBlock sbi : fstmt.getBody())
				propagateStatisticsAcrossBlock(sbi, callVars, fcallSizes, fnStack, false);
		}
		
		return ret;
	}
	
	/////////////////////////////
	// INTRA-PROCEDURE ANALYSIS
	//////	

	private void propagateStatisticsAcrossBlock( StatementBlock sb, LocalVariableMap callVars, FunctionCallSizeInfo fcallSizes, Set<String> fnStack, boolean replaceScalars )
	{
		if (sb instanceof FunctionStatementBlock)
		{
			FunctionStatementBlock fsb = (FunctionStatementBlock)sb;
			FunctionStatement fstmt = (FunctionStatement)fsb.getStatement(0);
			for (StatementBlock sbi : fstmt.getBody())
				propagateStatisticsAcrossBlock(sbi, callVars, fcallSizes, fnStack, replaceScalars);
		}
		else if (sb instanceof WhileStatementBlock)
		{
			WhileStatementBlock wsb = (WhileStatementBlock) sb;
			WhileStatement wstmt = (WhileStatement)wsb.getStatement(0);
			//old stats into predicate
			propagateStatisticsAcrossPredicateDAG(wsb.getPredicateHops(), callVars);
			//remove updated constant scalars
			Recompiler.removeUpdatedScalars(callVars, wsb);
			//check and propagate stats into body
			LocalVariableMap oldCallVars = (LocalVariableMap) callVars.clone();
			for (StatementBlock sbi : wstmt.getBody())
				propagateStatisticsAcrossBlock(sbi, callVars, fcallSizes, fnStack, replaceScalars);
			if( Recompiler.reconcileUpdatedCallVarsLoops(oldCallVars, callVars, wsb) ){ //second pass if required
				propagateStatisticsAcrossPredicateDAG(wsb.getPredicateHops(), callVars);
				for (StatementBlock sbi : wstmt.getBody())
					propagateStatisticsAcrossBlock(sbi, callVars, fcallSizes, fnStack, replaceScalars);
			}
			//remove updated constant scalars
			Recompiler.removeUpdatedScalars(callVars, sb);
		}	
		else if (sb instanceof IfStatementBlock) 
		{
			IfStatementBlock isb = (IfStatementBlock) sb;
			IfStatement istmt = (IfStatement)isb.getStatement(0);
			//old stats into predicate
			propagateStatisticsAcrossPredicateDAG(isb.getPredicateHops(), callVars);
			//check and propagate stats into body
			LocalVariableMap oldCallVars = (LocalVariableMap) callVars.clone();
			LocalVariableMap callVarsElse = (LocalVariableMap) callVars.clone();
			for (StatementBlock sbi : istmt.getIfBody())
				propagateStatisticsAcrossBlock(sbi, callVars, fcallSizes, fnStack, replaceScalars);
			for (StatementBlock sbi : istmt.getElseBody())
				propagateStatisticsAcrossBlock(sbi, callVarsElse, fcallSizes, fnStack, replaceScalars);
			callVars = Recompiler.reconcileUpdatedCallVarsIf(oldCallVars, callVars, callVarsElse, isb);
			//remove updated constant scalars
			Recompiler.removeUpdatedScalars(callVars, sb);
		}
		else if (sb instanceof ForStatementBlock) //incl parfor
		{
			ForStatementBlock fsb = (ForStatementBlock) sb;
			ForStatement fstmt = (ForStatement)fsb.getStatement(0);
			//old stats into predicate
			propagateStatisticsAcrossPredicateDAG(fsb.getFromHops(), callVars);
			propagateStatisticsAcrossPredicateDAG(fsb.getToHops(), callVars);
			propagateStatisticsAcrossPredicateDAG(fsb.getIncrementHops(), callVars);
			//remove updated constant scalars
			Recompiler.removeUpdatedScalars(callVars, fsb);
			//check and propagate stats into body
			LocalVariableMap oldCallVars = (LocalVariableMap) callVars.clone();
			for (StatementBlock sbi : fstmt.getBody())
				propagateStatisticsAcrossBlock(sbi, callVars, fcallSizes, fnStack, replaceScalars);
			if( Recompiler.reconcileUpdatedCallVarsLoops(oldCallVars, callVars, fsb) )
				for (StatementBlock sbi : fstmt.getBody())
					propagateStatisticsAcrossBlock(sbi, callVars, fcallSizes, fnStack, replaceScalars);
			//remove updated constant scalars
			Recompiler.removeUpdatedScalars(callVars, sb);
		}
		else //generic (last-level)
		{	
			//remove updated constant scalars
			Recompiler.removeUpdatedScalars(callVars, sb);
			//old stats in, new stats out if updated
			ArrayList<Hop> roots = sb.getHops();
			DMLProgram prog = sb.getDMLProg();
			//replace scalar reads with literals
			if( replaceScalars ) {
				Hop.resetVisitStatus(roots);
				propagateScalarsAcrossDAG(roots, callVars);
			}
			//refresh stats across dag
			Hop.resetVisitStatus(roots);
			propagateStatisticsAcrossDAG(roots, callVars);
			//propagate stats into function calls
			Hop.resetVisitStatus(roots);
			propagateStatisticsIntoFunctions(prog, roots, callVars, fcallSizes, fnStack, replaceScalars);
		}
	}

	/**
	 * Propagate scalar values across DAGs.
	 *
	 * This replaces scalar reads and typecasts thereof with literals.
	 *
	 * Ultimately, this leads to improvements because the size
	 * expression evaluation over DAGs with scalar symbol table entries
	 * (which is also applied during IPA) is limited to supported
	 * operations, whereas literal replacement is a brute force method
	 * that applies to all (including future) operations.
	 *
	 * @param roots  List of HOPs.
	 * @param vars  Map of variables eligible for propagation.
	 */
	private static void propagateScalarsAcrossDAG(ArrayList<Hop> roots, LocalVariableMap vars) {
		for (Hop hop : roots) {
			try {
				Recompiler.rReplaceLiterals(hop, vars, true);
			} catch (Exception ex) {
				throw new HopsException("Failed to perform scalar literal replacement.", ex);
			}
		}
	}

	private static void propagateStatisticsAcrossPredicateDAG( Hop root, LocalVariableMap vars ) {
		if( root == null )
			return;
		
		//reset visit status because potentially called multiple times
		root.resetVisitStatus();
		
		try {
			//note: for predicates no output statistics
			Recompiler.rUpdateStatistics( root, vars );
		}
		catch(Exception ex) {
			throw new HopsException("Failed to update Hop DAG statistics.", ex);
		}
	}

	/**
	 * Propagate matrix sizes across DAGs.
	 *
	 * @param roots  List of HOP DAG root nodes.
	 * @param vars  Map of variables eligible for propagation.
	 */
	private static void propagateStatisticsAcrossDAG( ArrayList<Hop> roots, LocalVariableMap vars ) {
		if( roots == null )
			return;
		
		try {
			//update DAG statistics from leafs to roots
			for( Hop hop : roots )
				Recompiler.rUpdateStatistics( hop, vars );

			//extract statistics from roots
			Recompiler.extractDAGOutputStatistics(roots, vars, true);
		}
		catch( Exception ex ) {
			throw new HopsException("Failed to update Hop DAG statistics.", ex);
		}
	}
	
	
	/////////////////////////////
	// INTER-PROCEDURE ANALYIS
	//////

	/**
	 * Propagate statistics from the calling program into a function
	 * block.
	 *
	 * @param prog  The DML program.
	 * @param roots List of HOP DAG root notes for propagation.
	 * @param callVars  Calling program's map of variables eligible for propagation.
	 * @param fcallSizes function call summary
	 * @param fnStack  Function stack to determine current scope.
	 */
	private void propagateStatisticsIntoFunctions(DMLProgram prog, ArrayList<Hop> roots, LocalVariableMap callVars, FunctionCallSizeInfo fcallSizes, Set<String> fnStack, boolean replaceScalars) {
		for( Hop root : roots )
			propagateStatisticsIntoFunctions(prog, root, callVars, fcallSizes, fnStack, replaceScalars);
	}

	/**
	 * Propagate statistics from the calling program into a function
	 * block.
	 *
	 * @param prog  The DML program.
	 * @param hop HOP to propagate statistics into.
	 * @param callVars  Calling program's map of variables eligible for propagation.
	 * @param fcallSizes function call summary
	 * @param fnStack  Function stack to determine current scope.
	 */
	private void propagateStatisticsIntoFunctions(DMLProgram prog, Hop hop, LocalVariableMap callVars, FunctionCallSizeInfo fcallSizes, Set<String> fnStack, boolean replaceScalars ) 
	{
		if( hop.isVisited() )
			return;
		
		for( Hop c : hop.getInput() )
			propagateStatisticsIntoFunctions(prog, c, callVars, fcallSizes, fnStack, replaceScalars);
		
		if( hop instanceof FunctionOp )
		{
			//maintain counters and investigate functions if not seen so far
			FunctionOp fop = (FunctionOp) hop;
			String fkey = fop.getFunctionKey();
			
			if( fop.getFunctionType() == FunctionType.DML )
			{
				FunctionStatementBlock fsb = prog.getFunctionStatementBlock(fop.getFunctionNamespace(), fop.getFunctionName());
				FunctionStatement fstmt = (FunctionStatement)fsb.getStatement(0);
				
				if( fcallSizes.isValidFunction(fkey) && 
					!fnStack.contains(fkey)  ) //prevent recursion
				{
					//maintain function call stack
					fnStack.add(fkey);
					
					//create mapping and populate symbol table for refresh
					LocalVariableMap tmpVars = new LocalVariableMap();
					populateLocalVariableMapForFunctionCall( fstmt, fop, callVars, tmpVars, fcallSizes);
	
					//recursively propagate statistics
					propagateStatisticsAcrossBlock(fsb, tmpVars, fcallSizes, fnStack, replaceScalars);
					
					//extract vars from symbol table, re-map and refresh main program
					extractFunctionCallReturnStatistics(fstmt, fop, tmpVars, callVars, true);
					
					//maintain function call stack
					fnStack.remove(fkey);
				}
				else if( fcallSizes.isDimsPreservingFunction(fkey) ) {
					extractFunctionCallEquivalentReturnStatistics(fstmt, fop, callVars);
				}
				else {
					extractFunctionCallUnknownReturnStatistics(fstmt, fop, callVars);
				}
			}
		}
		
		hop.setVisited();
	}
	
	private static void populateLocalVariableMapForFunctionCall( FunctionStatement fstmt, FunctionOp fop, LocalVariableMap callvars, LocalVariableMap vars, FunctionCallSizeInfo fcallSizes ) 
	{
		//note: due to arbitrary binding sequences of named function arguments,
		//we cannot use the sequence as defined in the function signature
		String[] funArgNames = fop.getInputVariableNames();
		ArrayList<Hop> inputOps = fop.getInput();
		String fkey = fop.getFunctionKey();
		
		for( int i=0; i<funArgNames.length; i++ )
		{
			//create mapping between input hops and vars
			DataIdentifier dat = fstmt.getInputParam(funArgNames[i]);
			Hop input = inputOps.get(i);
			
			if( input.getDataType()==DataType.MATRIX )
			{
				//propagate matrix characteristics
				MatrixObject mo = new MatrixObject(ValueType.FP64, null);
				DataCharacteristics mc = new MatrixCharacteristics( input.getDim1(), input.getDim2(),
					ConfigurationManager.getBlocksize(),
					fcallSizes.isSafeNnz(fkey, i)?input.getNnz():-1 );
				MetaDataFormat meta = new MetaDataFormat(mc,null);
				mo.setMetaData(meta);
				vars.put(dat.getName(), mo);
			}
			else if( input.getDataType()==DataType.SCALAR )
			{
				//always propagate scalar literals into functions
				//(for multiple calls, literal equivalence already checked)
				if( input instanceof LiteralOp ) {
					vars.put(dat.getName(), ScalarObjectFactory
						.createScalarObject(input.getValueType(), (LiteralOp)input));
				}
				//propagate scalar variables into functions if called once
				//and input scalar is existing variable in symbol table
				else if( PROPAGATE_SCALAR_VARS_INTO_FUN 
					&& fcallSizes.getFunctionCallCount(fkey) == 1
					&& input instanceof DataOp )
				{
					Data scalar = callvars.get(input.getName()); 
					if( scalar != null && scalar instanceof ScalarObject ) {
						vars.put(dat.getName(), scalar);
					}
				}
			}
		}
	}

	/**
	 * Extract return variable statistics from this function into the
	 * calling program.
	 *
	 * @param fstmt  The function statement.
	 * @param fop  The function op.
	 * @param tmpVars  Function's map of variables eligible for
	 *                    extraction.
	 * @param callVars  Calling program's map of variables.
	 * @param overwrite  Whether or not to overwrite variables in the
	 *                      calling program's variable map.
	 */
	private static void extractFunctionCallReturnStatistics( FunctionStatement fstmt, FunctionOp fop, LocalVariableMap tmpVars, LocalVariableMap callVars, boolean overwrite ) {
		ArrayList<DataIdentifier> foutputOps = fstmt.getOutputParams();
		String[] outputVars = fop.getOutputVariableNames();
		String fkey = fop.getFunctionKey();
		
		try
		{
			for( int i=0; i<foutputOps.size(); i++ ) {
				//robustness for unbound outputs
				if( outputVars.length <= i )
					break;
				
				DataIdentifier di = foutputOps.get(i);
				String fvarname = di.getName(); //name in function signature
				String pvarname = outputVars[i]; //name in calling program

				// If the calling program is reassigning a variable with the output of this
				// function, and the datatype differs between that variable and this function
				// output, remove that variable from the calling program's variable map.
				if( callVars.keySet().contains(pvarname) ) {
					DataType fdataType = di.getDataType();
					DataType pdataType = callVars.get(pvarname).getDataType();
					if( fdataType != pdataType ) {
						// datatype has changed, and the calling program is reassigning the
						// the variable, so remove it from the calling variable map
						callVars.remove(pvarname);
					}
				}
				// Update or add to the calling program's variable map.
				if( di.getDataType()==DataType.MATRIX && tmpVars.keySet().contains(fvarname) ) {
					MatrixObject moIn = (MatrixObject) tmpVars.get(fvarname);
					if( !callVars.keySet().contains(pvarname) || overwrite ) { //not existing so far
						MatrixObject moOut = createOutputMatrix(moIn.getNumRows(), moIn.getNumColumns(), moIn.getNnz());
						callVars.put(pvarname, moOut);
					}
					else { //already existing: take largest
						Data dat = callVars.get(pvarname);
						if( !(dat instanceof MatrixObject) )
							continue;
						MatrixObject moOut = (MatrixObject)dat;
						DataCharacteristics dc = moOut.getDataCharacteristics();
						if( OptimizerUtils.estimateSizeExactSparsity(dc.getRows(), dc.getCols(), (dc.getNonZeros()>0)?
							OptimizerUtils.getSparsity(dc):1.0)
							< OptimizerUtils.estimateSize(moIn.getNumRows(), moIn.getNumColumns()) )
						{
							//update statistics if necessary
							dc.setDimension(moIn.getNumRows(), moIn.getNumColumns());
							dc.setNonZeros(moIn.getNnz());
						}
					}
				}
			}
		}
		catch( Exception ex ) {
			throw new HopsException( "Failed to extract output statistics of function "+fkey+".", ex);
		}
	}
	
	private static void extractFunctionCallUnknownReturnStatistics(FunctionStatement fstmt, FunctionOp fop, LocalVariableMap callVars) {
		ArrayList<DataIdentifier> foutputOps = fstmt.getOutputParams();
		String[] outputVars = fop.getOutputVariableNames();
		String fkey = fop.getFunctionKey();
		try {
			//robustness for subset of bound output variables
			int olen = Math.min(foutputOps.size(), outputVars.length);
			for( int i=0; i<olen; i++ ) {
				DataIdentifier di = foutputOps.get(i);
				String pvarname = outputVars[i]; //name in calling program
				if( di.getDataType()==DataType.MATRIX )
					callVars.put(pvarname, createOutputMatrix(-1, -1, -1));
			}
		}
		catch( Exception ex ) {
			throw new HopsException( "Failed to extract output statistics of function "+fkey+".", ex);
		}
	}
	
	private static void extractFunctionCallEquivalentReturnStatistics( FunctionStatement fstmt, FunctionOp fop, LocalVariableMap callVars ) 
	{
		try {
			Hop input = fop.getInput().get(0);
			MatrixObject moOut = createOutputMatrix(input.getDim1(), input.getDim2(), -1);	
			callVars.put(fop.getOutputVariableNames()[0], moOut);
		}
		catch( Exception ex ) {
			throw new HopsException( "Failed to extract output statistics "
				+ "for unary function "+fop.getFunctionKey()+".", ex);
		}
	}
	
	private static MatrixObject createOutputMatrix( long dim1, long dim2, long nnz ) {
		MatrixObject moOut = new MatrixObject(ValueType.FP64, null);
		DataCharacteristics mc = new MatrixCharacteristics(
			dim1, dim2, ConfigurationManager.getBlocksize(), nnz);
		MetaDataFormat meta = new MetaDataFormat(mc,null);
		moOut.setMetaData(meta);
		return moOut;
	}
}