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Declarative Machine Learning
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/*
 * 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.sysml.hops;

import java.util.ArrayList;
import java.util.HashMap;

import org.apache.sysml.hops.Hop.DataOpTypes;
import org.apache.sysml.hops.Hop.VisitStatus;
import org.apache.sysml.hops.recompile.RecompileStatus;
import org.apache.sysml.parser.Expression.DataType;
import org.apache.sysml.runtime.matrix.MatrixCharacteristics;

/**
 * Memoization Table (hop id, worst-case matrix characteristics).
 * 
 */
public class MemoTable 
{
	
	private HashMap _memo = null;
	
	public MemoTable()
	{
		_memo = new HashMap();
	}
	
	/**
	 * 
	 * @param hops
	 * @param status
	 */
	public void init( ArrayList hops, RecompileStatus status)
	{
		//check existing status
		if(    hops == null ||  hops.isEmpty() || status == null 
			|| status.getTWriteStats().isEmpty() )
		{
			return; //nothing to do
		}
		
		//population via recursive search for treads
		Hop.resetVisitStatus(hops);
		for( Hop hop : hops )
			rinit(hop, status);
	}
	
	/**
	 * 
	 * @param hop
	 * @param status
	 */
	public void init( Hop hop, RecompileStatus status)
	{
		//check existing status
		if(    hop == null || status == null 
			|| status.getTWriteStats().isEmpty() )
		{
			return; //nothing to do
		}
		
		//population via recursive search for treads
		hop.resetVisitStatus();
		rinit(hop, status);
	}
	
	/**
	 * 
	 * @param hops
	 * @param status
	 */
	public void extract( ArrayList hops, RecompileStatus status)
	{
		//check existing status
		if( status == null )
			return; //nothing to do
		
		//extract all transient writes (must be dag root)
		for( Hop hop : hops ) {
			if(    hop instanceof DataOp 
				&& ((DataOp)hop).getDataOpType()==DataOpTypes.TRANSIENTWRITE )
			{
				String varname = hop.getName();
				Hop input = hop.getInput().get(0); //child
				MatrixCharacteristics mc = getAllInputStats(input);
				if( mc != null )
					status.getTWriteStats().put(varname, mc);
				else
					status.getTWriteStats().remove(varname);
			}
		}
	}

	/**
	 * 
	 * @param hopID
	 * @param dim1
	 * @param dim2
	 * @param nnz
	 */
	public void memoizeStatistics( long hopID, long dim1, long dim2, long nnz )
	{
		_memo.put(hopID, new MatrixCharacteristics(dim1, dim2, -1, -1, nnz));
	}
		
	/**
	 * 
	 * @param inputs
	 * @return
	 */
	public MatrixCharacteristics[] getAllInputStats( ArrayList inputs )
	{
		MatrixCharacteristics[] ret = new MatrixCharacteristics[inputs.size()];
		for( int i=0; i