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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.sysds.hops.codegen.cplan;
import java.util.Arrays;
import org.apache.sysds.common.Types.DataType;
import org.apache.sysds.runtime.util.UtilFunctions;
import org.apache.sysds.hops.codegen.SpoofCompiler.GeneratorAPI;
public class CNodeTernary extends CNode
{
public enum TernaryType {
PLUS_MULT, MINUS_MULT,
BIASADD, BIASMULT,
REPLACE, REPLACE_NAN, IFELSE,
LOOKUP_RC1, LOOKUP_RVECT1;
public static boolean contains(String value) {
return Arrays.stream(values()).anyMatch(tt -> tt.name().equals(value));
}
public boolean isVectorPrimitive() {
return (this == LOOKUP_RVECT1);
}
}
private final TernaryType _type;
public CNodeTernary( CNode in1, CNode in2, CNode in3, TernaryType type ) {
_inputs.add(in1);
_inputs.add(in2);
_inputs.add(in3);
_type = type;
setOutputDims();
}
public TernaryType getType() {
return _type;
}
@Override
public String codegen(boolean sparse, GeneratorAPI api) {
if( isGenerated() )
return "";
StringBuilder sb = new StringBuilder();
//generate children
sb.append(_inputs.get(0).codegen(sparse, api));
sb.append(_inputs.get(1).codegen(sparse, api));
sb.append(_inputs.get(2).codegen(sparse, api));
//generate binary operation
boolean lsparse = sparse && (_inputs.get(0) instanceof CNodeData
&& _inputs.get(0).getVarname().startsWith("a")
&& !_inputs.get(0).isLiteral());
String var = createVarname();
// String tmp = _type.getTemplate(lsparse, api, lang);
String tmp = getLanguageTemplateClass(this, api).getTemplate(_type, lsparse);
tmp = tmp.replace("%TMP%", var);
for( int j=1; j<=3; j++ ) {
String varj = _inputs.get(j-1).getVarname();
//replace sparse and dense inputs
tmp = tmp.replace("%IN"+j+"v%",
varj+(varj.startsWith("a")?"vals":"") );
tmp = tmp.replace("%IN"+j+"i%",
varj+(varj.startsWith("a")?"ix":"") );
tmp = tmp.replace("%IN"+j+"%", varj );
}
sb.append(tmp);
//mark as generated
_generated = true;
return sb.toString();
}
@Override
public String toString() {
switch(_type) {
case PLUS_MULT: return "t(+*)";
case MINUS_MULT: return "t(-*)";
case BIASADD: return "t(bias+)";
case BIASMULT: return "t(bias*)";
case REPLACE:
case REPLACE_NAN: return "t(rplc)";
case IFELSE: return "t(ifelse)";
case LOOKUP_RC1: return "u(ixrc1)";
case LOOKUP_RVECT1: return "u(ixrv1)";
default: return super.toString();
}
}
@Override
public void setOutputDims() {
switch(_type) {
case PLUS_MULT:
case MINUS_MULT:
case BIASADD:
case BIASMULT:
case REPLACE:
case REPLACE_NAN:
case IFELSE:
case LOOKUP_RC1:
_rows = 0;
_cols = 0;
_dataType= DataType.SCALAR;
break;
case LOOKUP_RVECT1:
_rows = 1;
_cols = _inputs.get(0)._cols;
_dataType= DataType.MATRIX;
break;
}
}
@Override
public int hashCode() {
if( _hash == 0 ) {
_hash = UtilFunctions.intHashCode(
super.hashCode(), _type.hashCode());
}
return _hash;
}
@Override
public boolean equals(Object o) {
if( !(o instanceof CNodeTernary) )
return false;
CNodeTernary that = (CNodeTernary) o;
return super.equals(that)
&& _type == that._type;
}
@Override
public boolean isSupported(GeneratorAPI api) {
boolean is_supported = (api == GeneratorAPI.CUDA || api == GeneratorAPI.JAVA);
int i = 0;
while(is_supported && i < _inputs.size()) {
CNode in = _inputs.get(i++);
is_supported = in.isSupported(api);
}
return is_supported;
}
}