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Declarative Machine Learning
/*
* 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.api.jmlc;
import java.util.ArrayList;
import java.util.Collection;
import java.util.HashMap;
import java.util.HashSet;
import java.util.Map.Entry;
import org.apache.sysml.api.DMLException;
import org.apache.sysml.conf.ConfigurationManager;
import org.apache.sysml.conf.DMLConfig;
import org.apache.sysml.parser.Expression.ValueType;
import org.apache.sysml.runtime.controlprogram.LocalVariableMap;
import org.apache.sysml.runtime.controlprogram.Program;
import org.apache.sysml.runtime.controlprogram.caching.MatrixObject;
import org.apache.sysml.runtime.controlprogram.context.ExecutionContext;
import org.apache.sysml.runtime.controlprogram.context.ExecutionContextFactory;
import org.apache.sysml.runtime.instructions.cp.BooleanObject;
import org.apache.sysml.runtime.instructions.cp.Data;
import org.apache.sysml.runtime.instructions.cp.DoubleObject;
import org.apache.sysml.runtime.instructions.cp.IntObject;
import org.apache.sysml.runtime.instructions.cp.ScalarObject;
import org.apache.sysml.runtime.instructions.cp.StringObject;
import org.apache.sysml.runtime.matrix.MatrixCharacteristics;
import org.apache.sysml.runtime.matrix.MatrixFormatMetaData;
import org.apache.sysml.runtime.matrix.data.InputInfo;
import org.apache.sysml.runtime.matrix.data.MatrixBlock;
import org.apache.sysml.runtime.matrix.data.OutputInfo;
import org.apache.sysml.runtime.util.DataConverter;
/**
* JMLC (Java Machine Learning Connector) API:
*
* NOTE: Currently fused API and implementation in order to reduce complexity.
*/
public class PreparedScript
{
//input/output specification
private HashSet _inVarnames = null;
private HashSet _outVarnames = null;
private HashMap _inVarReuse = null;
//internal state (reused)
private Program _prog = null;
private LocalVariableMap _vars = null;
/**
* Meant to be invoked only from Connection
*/
protected PreparedScript( Program prog, String[] inputs, String[] outputs )
{
_prog = prog;
_vars = new LocalVariableMap();
//populate input/output vars
_inVarnames = new HashSet();
for( String var : inputs )
_inVarnames.add( var );
_outVarnames = new HashSet();
for( String var : outputs )
_outVarnames.add( var );
_inVarReuse = new HashMap();
}
/** Binds a scalar boolean to a registered input variable. */
public void setScalar(String varname, boolean scalar) throws DMLException {
setScalar(varname, scalar, false);
}
/** Binds a scalar boolean to a registered input variable. */
public void setScalar(String varname, boolean scalar, boolean reuse) throws DMLException {
setScalar(varname, new BooleanObject(varname, scalar), reuse);
}
/** Binds a scalar long to a registered input variable. */
public void setScalar(String varname, long scalar) throws DMLException {
setScalar(varname, scalar, false);
}
/** Binds a scalar long to a registered input variable. */
public void setScalar(String varname, long scalar, boolean reuse) throws DMLException {
setScalar(varname, new IntObject(varname, scalar), reuse);
}
/** Binds a scalar double to a registered input variable. */
public void setScalar(String varname, double scalar) throws DMLException {
setScalar(varname, scalar, false);
}
/** Binds a scalar double to a registered input variable. */
public void setScalar(String varname, double scalar, boolean reuse) throws DMLException {
setScalar(varname, new DoubleObject(varname, scalar), reuse);
}
/** Binds a scalar string to a registered input variable. */
public void setScalar(String varname, String scalar) throws DMLException {
setScalar(varname, scalar, false);
}
/** Binds a scalar string to a registered input variable. */
public void setScalar(String varname, String scalar, boolean reuse) throws DMLException {
setScalar(varname, new StringObject(varname, scalar), reuse);
}
/**
* Binds a scalar object to a registered input variable.
* If reuse requested, then the input is guaranteed to be
* preserved over multiple executeScript calls.
*
* @param varname
* @param scalar
* @param reuse
* @throws DMLException
*/
public void setScalar(String varname, ScalarObject scalar, boolean reuse)
throws DMLException
{
if( !_inVarnames.contains(varname) )
throw new DMLException("Unspecified input variable: "+varname);
_vars.put(varname, scalar);
}
/**
*
* @param varname
* @param matrix
* @throws DMLException
*/
public void setMatrix(String varname, double[][] matrix)
throws DMLException
{
setMatrix(varname, matrix, false);
}
/**
*
* @param varname
* @param matrix
* @throws DMLException
*/
public void setMatrix(String varname, double[][] matrix, boolean reuse)
throws DMLException
{
setMatrix(varname, DataConverter.convertToMatrixBlock(matrix), reuse);
}
/**
* Binds a matrix object to a registered input variable.
* If reuse requested, then the input is guaranteed to be
* preserved over multiple executeScript calls.
*
* @param varname
* @param matrix
* @throws DMLException
*/
public void setMatrix(String varname, MatrixBlock matrix, boolean reuse)
throws DMLException
{
if( !_inVarnames.contains(varname) )
throw new DMLException("Unspecified input variable: "+varname);
DMLConfig conf = ConfigurationManager.getConfig();
String scratch_space = conf.getTextValue(DMLConfig.SCRATCH_SPACE);
int blocksize = conf.getIntValue(DMLConfig.DEFAULT_BLOCK_SIZE);
//create new matrix object
MatrixCharacteristics mc = new MatrixCharacteristics(matrix.getNumRows(), matrix.getNumColumns(), blocksize, blocksize);
MatrixFormatMetaData meta = new MatrixFormatMetaData(mc, OutputInfo.BinaryBlockOutputInfo, InputInfo.BinaryBlockInputInfo);
MatrixObject mo = new MatrixObject(ValueType.DOUBLE, scratch_space+"/"+varname, meta);
mo.acquireModify(matrix);
mo.release();
//put create matrix wrapper into symbol table
_vars.put(varname, mo);
if( reuse ) {
mo.enableCleanup(false); //prevent cleanup
_inVarReuse.put(varname, mo);
}
}
/**
* Remove all current values bound to input or output variables.
*
*/
public void clearParameters()
{
_vars.removeAll();
}
/**
* Executes the prepared script over the bound inputs, creating the
* result variables according to bound and registered outputs.
*
* @return
* @throws DMLException
*/
public ResultVariables executeScript()
throws DMLException
{
//add reused variables
for( Entry e : _inVarReuse.entrySet() )
_vars.put(e.getKey(), e.getValue());
//create and populate execution context
ExecutionContext ec = ExecutionContextFactory.createContext(_prog);
ec.setVariables(_vars);
//core execute runtime program
_prog.execute( ec );
//cleanup unnecessary outputs
Collection tmpVars = new ArrayList(_vars.keySet());
for( String var : tmpVars )
if( !_outVarnames.contains(var) )
_vars.remove(var);
//construct results
ResultVariables rvars = new ResultVariables();
for( String ovar : _outVarnames )
if( _vars.keySet().contains(ovar) )
rvars.addResult(ovar, _vars.get(ovar));
return rvars;
}
}