use of org.apache.sysml.hops.TernaryOp in project systemml by apache.
the class RewriteAlgebraicSimplificationDynamic method simplifyTableSeqExpand.
private static Hop simplifyTableSeqExpand(Hop parent, Hop hi, int pos) {
// note: this rewrite supports both left/right sequence
if (// table without weights
hi instanceof TernaryOp && hi.getInput().size() == 5 && // i.e., weight of 1
HopRewriteUtils.isLiteralOfValue(hi.getInput().get(2), 1)) {
Hop first = hi.getInput().get(0);
Hop second = hi.getInput().get(1);
// pattern a: table(seq(1,nrow(v)), v, nrow(v), m, 1)
if (HopRewriteUtils.isBasic1NSequence(first, second, true) && HopRewriteUtils.isSizeExpressionOf(hi.getInput().get(3), second, true)) {
// setup input parameter hops
HashMap<String, Hop> args = new HashMap<>();
args.put("target", second);
args.put("max", hi.getInput().get(4));
args.put("dir", new LiteralOp("cols"));
args.put("ignore", new LiteralOp(false));
args.put("cast", new LiteralOp(true));
// create new hop
ParameterizedBuiltinOp pbop = HopRewriteUtils.createParameterizedBuiltinOp(second, args, ParamBuiltinOp.REXPAND);
HopRewriteUtils.replaceChildReference(parent, hi, pbop, pos);
HopRewriteUtils.cleanupUnreferenced(hi);
hi = pbop;
LOG.debug("Applied simplifyTableSeqExpand1 (line " + hi.getBeginLine() + ")");
} else // pattern b: table(v, seq(1,nrow(v)), m, nrow(v))
if (HopRewriteUtils.isBasic1NSequence(second, first, true) && HopRewriteUtils.isSizeExpressionOf(hi.getInput().get(4), first, true)) {
// setup input parameter hops
HashMap<String, Hop> args = new HashMap<>();
args.put("target", first);
args.put("max", hi.getInput().get(3));
args.put("dir", new LiteralOp("rows"));
args.put("ignore", new LiteralOp(false));
args.put("cast", new LiteralOp(true));
// create new hop
ParameterizedBuiltinOp pbop = HopRewriteUtils.createParameterizedBuiltinOp(first, args, ParamBuiltinOp.REXPAND);
HopRewriteUtils.replaceChildReference(parent, hi, pbop, pos);
HopRewriteUtils.cleanupUnreferenced(hi);
hi = pbop;
LOG.debug("Applied simplifyTableSeqExpand2 (line " + hi.getBeginLine() + ")");
}
}
return hi;
}
use of org.apache.sysml.hops.TernaryOp in project systemml by apache.
the class PlanSelectionFuseCostBased method rGetComputeCosts.
private static void rGetComputeCosts(Hop current, HashSet<Long> partition, HashMap<Long, Double> computeCosts) {
if (computeCosts.containsKey(current.getHopID()))
return;
// recursively process children
for (Hop c : current.getInput()) rGetComputeCosts(c, partition, computeCosts);
// get costs for given hop
double costs = 1;
if (current instanceof UnaryOp) {
switch(((UnaryOp) current).getOp()) {
case ABS:
case ROUND:
case CEIL:
case FLOOR:
case SIGN:
costs = 1;
break;
case SPROP:
case SQRT:
costs = 2;
break;
case EXP:
costs = 18;
break;
case SIGMOID:
costs = 21;
break;
case LOG:
case LOG_NZ:
costs = 32;
break;
case NCOL:
case NROW:
case PRINT:
case ASSERT:
case CAST_AS_BOOLEAN:
case CAST_AS_DOUBLE:
case CAST_AS_INT:
case CAST_AS_MATRIX:
case CAST_AS_SCALAR:
costs = 1;
break;
case SIN:
costs = 18;
break;
case COS:
costs = 22;
break;
case TAN:
costs = 42;
break;
case ASIN:
costs = 93;
break;
case ACOS:
costs = 103;
break;
case ATAN:
costs = 40;
break;
// TODO:
case SINH:
costs = 93;
break;
case COSH:
costs = 103;
break;
case TANH:
costs = 40;
break;
case CUMSUM:
case CUMMIN:
case CUMMAX:
case CUMPROD:
costs = 1;
break;
default:
LOG.warn("Cost model not " + "implemented yet for: " + ((UnaryOp) current).getOp());
}
} else if (current instanceof BinaryOp) {
switch(((BinaryOp) current).getOp()) {
case MULT:
case PLUS:
case MINUS:
case MIN:
case MAX:
case AND:
case OR:
case EQUAL:
case NOTEQUAL:
case LESS:
case LESSEQUAL:
case GREATER:
case GREATEREQUAL:
case CBIND:
case RBIND:
costs = 1;
break;
case INTDIV:
costs = 6;
break;
case MODULUS:
costs = 8;
break;
case DIV:
costs = 22;
break;
case LOG:
case LOG_NZ:
costs = 32;
break;
case POW:
costs = (HopRewriteUtils.isLiteralOfValue(current.getInput().get(1), 2) ? 1 : 16);
break;
case MINUS_NZ:
case MINUS1_MULT:
costs = 2;
break;
case CENTRALMOMENT:
int type = (int) (current.getInput().get(1) instanceof LiteralOp ? HopRewriteUtils.getIntValueSafe((LiteralOp) current.getInput().get(1)) : 2);
switch(type) {
// count
case 0:
costs = 1;
break;
// mean
case 1:
costs = 8;
break;
// cm2
case 2:
costs = 16;
break;
// cm3
case 3:
costs = 31;
break;
// cm4
case 4:
costs = 51;
break;
// variance
case 5:
costs = 16;
break;
}
break;
case COVARIANCE:
costs = 23;
break;
default:
LOG.warn("Cost model not " + "implemented yet for: " + ((BinaryOp) current).getOp());
}
} else if (current instanceof TernaryOp) {
switch(((TernaryOp) current).getOp()) {
case PLUS_MULT:
case MINUS_MULT:
costs = 2;
break;
case CTABLE:
costs = 3;
break;
case CENTRALMOMENT:
int type = (int) (current.getInput().get(1) instanceof LiteralOp ? HopRewriteUtils.getIntValueSafe((LiteralOp) current.getInput().get(1)) : 2);
switch(type) {
// count
case 0:
costs = 2;
break;
// mean
case 1:
costs = 9;
break;
// cm2
case 2:
costs = 17;
break;
// cm3
case 3:
costs = 32;
break;
// cm4
case 4:
costs = 52;
break;
// variance
case 5:
costs = 17;
break;
}
break;
case COVARIANCE:
costs = 23;
break;
default:
LOG.warn("Cost model not " + "implemented yet for: " + ((TernaryOp) current).getOp());
}
} else if (current instanceof ParameterizedBuiltinOp) {
costs = 1;
} else if (current instanceof IndexingOp) {
costs = 1;
} else if (current instanceof ReorgOp) {
costs = 1;
} else if (current instanceof AggBinaryOp) {
// matrix vector
costs = 2;
} else if (current instanceof AggUnaryOp) {
switch(((AggUnaryOp) current).getOp()) {
case SUM:
costs = 4;
break;
case SUM_SQ:
costs = 5;
break;
case MIN:
case MAX:
costs = 1;
break;
default:
LOG.warn("Cost model not " + "implemented yet for: " + ((AggUnaryOp) current).getOp());
}
}
computeCosts.put(current.getHopID(), costs);
}
use of org.apache.sysml.hops.TernaryOp in project incubator-systemml by apache.
the class PlanSelectionFuseCostBased method rGetComputeCosts.
private static void rGetComputeCosts(Hop current, HashSet<Long> partition, HashMap<Long, Double> computeCosts) {
if (computeCosts.containsKey(current.getHopID()))
return;
//recursively process children
for (Hop c : current.getInput()) rGetComputeCosts(c, partition, computeCosts);
//get costs for given hop
double costs = 1;
if (current instanceof UnaryOp) {
switch(((UnaryOp) current).getOp()) {
case ABS:
case ROUND:
case CEIL:
case FLOOR:
case SIGN:
case SELP:
costs = 1;
break;
case SPROP:
case SQRT:
costs = 2;
break;
case EXP:
costs = 18;
break;
case SIGMOID:
costs = 21;
break;
case LOG:
case LOG_NZ:
costs = 32;
break;
case NCOL:
case NROW:
case PRINT:
case CAST_AS_BOOLEAN:
case CAST_AS_DOUBLE:
case CAST_AS_INT:
case CAST_AS_MATRIX:
case CAST_AS_SCALAR:
costs = 1;
break;
case SIN:
costs = 18;
break;
case COS:
costs = 22;
break;
case TAN:
costs = 42;
break;
case ASIN:
costs = 93;
break;
case ACOS:
costs = 103;
break;
case ATAN:
costs = 40;
break;
case CUMSUM:
case CUMMIN:
case CUMMAX:
case CUMPROD:
costs = 1;
break;
default:
LOG.warn("Cost model not " + "implemented yet for: " + ((UnaryOp) current).getOp());
}
} else if (current instanceof BinaryOp) {
switch(((BinaryOp) current).getOp()) {
case MULT:
case PLUS:
case MINUS:
case MIN:
case MAX:
case AND:
case OR:
case EQUAL:
case NOTEQUAL:
case LESS:
case LESSEQUAL:
case GREATER:
case GREATEREQUAL:
case CBIND:
case RBIND:
costs = 1;
break;
case INTDIV:
costs = 6;
break;
case MODULUS:
costs = 8;
break;
case DIV:
costs = 22;
break;
case LOG:
case LOG_NZ:
costs = 32;
break;
case POW:
costs = (HopRewriteUtils.isLiteralOfValue(current.getInput().get(1), 2) ? 1 : 16);
break;
case MINUS_NZ:
case MINUS1_MULT:
costs = 2;
break;
case CENTRALMOMENT:
int type = (int) (current.getInput().get(1) instanceof LiteralOp ? HopRewriteUtils.getIntValueSafe((LiteralOp) current.getInput().get(1)) : 2);
switch(type) {
//count
case 0:
costs = 1;
break;
//mean
case 1:
costs = 8;
break;
//cm2
case 2:
costs = 16;
break;
//cm3
case 3:
costs = 31;
break;
//cm4
case 4:
costs = 51;
break;
//variance
case 5:
costs = 16;
break;
}
break;
case COVARIANCE:
costs = 23;
break;
default:
LOG.warn("Cost model not " + "implemented yet for: " + ((BinaryOp) current).getOp());
}
} else if (current instanceof TernaryOp) {
switch(((TernaryOp) current).getOp()) {
case PLUS_MULT:
case MINUS_MULT:
costs = 2;
break;
case CTABLE:
costs = 3;
break;
case CENTRALMOMENT:
int type = (int) (current.getInput().get(1) instanceof LiteralOp ? HopRewriteUtils.getIntValueSafe((LiteralOp) current.getInput().get(1)) : 2);
switch(type) {
//count
case 0:
costs = 2;
break;
//mean
case 1:
costs = 9;
break;
//cm2
case 2:
costs = 17;
break;
//cm3
case 3:
costs = 32;
break;
//cm4
case 4:
costs = 52;
break;
//variance
case 5:
costs = 17;
break;
}
break;
case COVARIANCE:
costs = 23;
break;
default:
LOG.warn("Cost model not " + "implemented yet for: " + ((TernaryOp) current).getOp());
}
} else if (current instanceof ParameterizedBuiltinOp) {
costs = 1;
} else if (current instanceof IndexingOp) {
costs = 1;
} else if (current instanceof ReorgOp) {
costs = 1;
} else if (current instanceof AggBinaryOp) {
//matrix vector
costs = 2;
} else if (current instanceof AggUnaryOp) {
switch(((AggUnaryOp) current).getOp()) {
case SUM:
costs = 4;
break;
case SUM_SQ:
costs = 5;
break;
case MIN:
case MAX:
costs = 1;
break;
default:
LOG.warn("Cost model not " + "implemented yet for: " + ((AggUnaryOp) current).getOp());
}
}
computeCosts.put(current.getHopID(), costs);
}
use of org.apache.sysml.hops.TernaryOp in project incubator-systemml by apache.
the class PlanSelectionFuseCostBased method rGetComputeCosts.
private static void rGetComputeCosts(Hop current, HashSet<Long> partition, HashMap<Long, Double> computeCosts) {
if (computeCosts.containsKey(current.getHopID()))
return;
// recursively process children
for (Hop c : current.getInput()) rGetComputeCosts(c, partition, computeCosts);
// get costs for given hop
double costs = 1;
if (current instanceof UnaryOp) {
switch(((UnaryOp) current).getOp()) {
case ABS:
case ROUND:
case CEIL:
case FLOOR:
case SIGN:
costs = 1;
break;
case SPROP:
case SQRT:
costs = 2;
break;
case EXP:
costs = 18;
break;
case SIGMOID:
costs = 21;
break;
case LOG:
case LOG_NZ:
costs = 32;
break;
case NCOL:
case NROW:
case PRINT:
case ASSERT:
case CAST_AS_BOOLEAN:
case CAST_AS_DOUBLE:
case CAST_AS_INT:
case CAST_AS_MATRIX:
case CAST_AS_SCALAR:
costs = 1;
break;
case SIN:
costs = 18;
break;
case COS:
costs = 22;
break;
case TAN:
costs = 42;
break;
case ASIN:
costs = 93;
break;
case ACOS:
costs = 103;
break;
case ATAN:
costs = 40;
break;
// TODO:
case SINH:
costs = 93;
break;
case COSH:
costs = 103;
break;
case TANH:
costs = 40;
break;
case CUMSUM:
case CUMMIN:
case CUMMAX:
case CUMPROD:
costs = 1;
break;
default:
LOG.warn("Cost model not " + "implemented yet for: " + ((UnaryOp) current).getOp());
}
} else if (current instanceof BinaryOp) {
switch(((BinaryOp) current).getOp()) {
case MULT:
case PLUS:
case MINUS:
case MIN:
case MAX:
case AND:
case OR:
case EQUAL:
case NOTEQUAL:
case LESS:
case LESSEQUAL:
case GREATER:
case GREATEREQUAL:
case CBIND:
case RBIND:
costs = 1;
break;
case INTDIV:
costs = 6;
break;
case MODULUS:
costs = 8;
break;
case DIV:
costs = 22;
break;
case LOG:
case LOG_NZ:
costs = 32;
break;
case POW:
costs = (HopRewriteUtils.isLiteralOfValue(current.getInput().get(1), 2) ? 1 : 16);
break;
case MINUS_NZ:
case MINUS1_MULT:
costs = 2;
break;
case CENTRALMOMENT:
int type = (int) (current.getInput().get(1) instanceof LiteralOp ? HopRewriteUtils.getIntValueSafe((LiteralOp) current.getInput().get(1)) : 2);
switch(type) {
// count
case 0:
costs = 1;
break;
// mean
case 1:
costs = 8;
break;
// cm2
case 2:
costs = 16;
break;
// cm3
case 3:
costs = 31;
break;
// cm4
case 4:
costs = 51;
break;
// variance
case 5:
costs = 16;
break;
}
break;
case COVARIANCE:
costs = 23;
break;
default:
LOG.warn("Cost model not " + "implemented yet for: " + ((BinaryOp) current).getOp());
}
} else if (current instanceof TernaryOp) {
switch(((TernaryOp) current).getOp()) {
case PLUS_MULT:
case MINUS_MULT:
costs = 2;
break;
case CTABLE:
costs = 3;
break;
case CENTRALMOMENT:
int type = (int) (current.getInput().get(1) instanceof LiteralOp ? HopRewriteUtils.getIntValueSafe((LiteralOp) current.getInput().get(1)) : 2);
switch(type) {
// count
case 0:
costs = 2;
break;
// mean
case 1:
costs = 9;
break;
// cm2
case 2:
costs = 17;
break;
// cm3
case 3:
costs = 32;
break;
// cm4
case 4:
costs = 52;
break;
// variance
case 5:
costs = 17;
break;
}
break;
case COVARIANCE:
costs = 23;
break;
default:
LOG.warn("Cost model not " + "implemented yet for: " + ((TernaryOp) current).getOp());
}
} else if (current instanceof ParameterizedBuiltinOp) {
costs = 1;
} else if (current instanceof IndexingOp) {
costs = 1;
} else if (current instanceof ReorgOp) {
costs = 1;
} else if (current instanceof AggBinaryOp) {
// matrix vector
costs = 2;
} else if (current instanceof AggUnaryOp) {
switch(((AggUnaryOp) current).getOp()) {
case SUM:
costs = 4;
break;
case SUM_SQ:
costs = 5;
break;
case MIN:
case MAX:
costs = 1;
break;
default:
LOG.warn("Cost model not " + "implemented yet for: " + ((AggUnaryOp) current).getOp());
}
}
computeCosts.put(current.getHopID(), costs);
}
use of org.apache.sysml.hops.TernaryOp in project incubator-systemml by apache.
the class TemplateRow method rConstructCplan.
private void rConstructCplan(Hop hop, CPlanMemoTable memo, HashMap<Long, CNode> tmp, HashSet<Hop> inHops, HashMap<String, Hop> inHops2, boolean compileLiterals) {
// memoization for common subexpression elimination and to avoid redundant work
if (tmp.containsKey(hop.getHopID()))
return;
// recursively process required childs
MemoTableEntry me = memo.getBest(hop.getHopID(), TemplateType.ROW, TemplateType.CELL);
for (int i = 0; i < hop.getInput().size(); i++) {
Hop c = hop.getInput().get(i);
if (me != null && me.isPlanRef(i))
rConstructCplan(c, memo, tmp, inHops, inHops2, compileLiterals);
else {
CNodeData cdata = TemplateUtils.createCNodeData(c, compileLiterals);
tmp.put(c.getHopID(), cdata);
inHops.add(c);
}
}
// construct cnode for current hop
CNode out = null;
if (hop instanceof AggUnaryOp) {
CNode cdata1 = tmp.get(hop.getInput().get(0).getHopID());
if (((AggUnaryOp) hop).getDirection() == Direction.Row && HopRewriteUtils.isAggUnaryOp(hop, SUPPORTED_ROW_AGG)) {
if (hop.getInput().get(0).getDim2() == 1)
out = (cdata1.getDataType() == DataType.SCALAR) ? cdata1 : new CNodeUnary(cdata1, UnaryType.LOOKUP_R);
else {
String opcode = "ROW_" + ((AggUnaryOp) hop).getOp().name().toUpperCase() + "S";
out = new CNodeUnary(cdata1, UnaryType.valueOf(opcode));
if (cdata1 instanceof CNodeData && !inHops2.containsKey("X"))
inHops2.put("X", hop.getInput().get(0));
}
} else if (((AggUnaryOp) hop).getDirection() == Direction.Col && ((AggUnaryOp) hop).getOp() == AggOp.SUM) {
// vector add without temporary copy
if (cdata1 instanceof CNodeBinary && ((CNodeBinary) cdata1).getType().isVectorScalarPrimitive())
out = new CNodeBinary(cdata1.getInput().get(0), cdata1.getInput().get(1), ((CNodeBinary) cdata1).getType().getVectorAddPrimitive());
else
out = cdata1;
} else if (((AggUnaryOp) hop).getDirection() == Direction.RowCol && ((AggUnaryOp) hop).getOp() == AggOp.SUM) {
out = (cdata1.getDataType().isMatrix()) ? new CNodeUnary(cdata1, UnaryType.ROW_SUMS) : cdata1;
}
} else if (hop instanceof AggBinaryOp) {
CNode cdata1 = tmp.get(hop.getInput().get(0).getHopID());
CNode cdata2 = tmp.get(hop.getInput().get(1).getHopID());
if (HopRewriteUtils.isTransposeOperation(hop.getInput().get(0))) {
// correct input under transpose
cdata1 = TemplateUtils.skipTranspose(cdata1, hop.getInput().get(0), tmp, compileLiterals);
inHops.remove(hop.getInput().get(0));
if (cdata1 instanceof CNodeData)
inHops.add(hop.getInput().get(0).getInput().get(0));
// note: vectorMultAdd applicable to vector-scalar, and vector-vector
if (hop.getInput().get(1).getDim2() == 1)
out = new CNodeBinary(cdata1, cdata2, BinType.VECT_MULT_ADD);
else {
out = new CNodeBinary(cdata1, cdata2, BinType.VECT_OUTERMULT_ADD);
if (!inHops2.containsKey("B1")) {
// incl modification of X for consistency
if (cdata1 instanceof CNodeData)
inHops2.put("X", hop.getInput().get(0).getInput().get(0));
inHops2.put("B1", hop.getInput().get(1));
}
}
if (!inHops2.containsKey("X"))
inHops2.put("X", hop.getInput().get(0).getInput().get(0));
} else {
if (hop.getInput().get(0).getDim2() == 1 && hop.getInput().get(1).getDim2() == 1)
out = new CNodeBinary((cdata1.getDataType() == DataType.SCALAR) ? cdata1 : new CNodeUnary(cdata1, UnaryType.LOOKUP0), (cdata2.getDataType() == DataType.SCALAR) ? cdata2 : new CNodeUnary(cdata2, UnaryType.LOOKUP0), BinType.MULT);
else if (hop.getInput().get(1).getDim2() == 1) {
out = new CNodeBinary(cdata1, cdata2, BinType.DOT_PRODUCT);
inHops2.put("X", hop.getInput().get(0));
} else {
out = new CNodeBinary(cdata1, cdata2, BinType.VECT_MATRIXMULT);
inHops2.put("X", hop.getInput().get(0));
inHops2.put("B1", hop.getInput().get(1));
}
}
} else if (HopRewriteUtils.isTransposeOperation(hop)) {
out = TemplateUtils.skipTranspose(tmp.get(hop.getHopID()), hop, tmp, compileLiterals);
if (out instanceof CNodeData && !inHops.contains(hop.getInput().get(0)))
inHops.add(hop.getInput().get(0));
} else if (hop instanceof UnaryOp) {
CNode cdata1 = tmp.get(hop.getInput().get(0).getHopID());
// if one input is a matrix then we need to do vector by scalar operations
if (hop.getInput().get(0).getDim1() >= 1 && hop.getInput().get(0).getDim2() > 1 || (!hop.dimsKnown() && cdata1.getDataType() == DataType.MATRIX)) {
if (HopRewriteUtils.isUnary(hop, SUPPORTED_VECT_UNARY)) {
String opname = "VECT_" + ((UnaryOp) hop).getOp().name();
out = new CNodeUnary(cdata1, UnaryType.valueOf(opname));
if (cdata1 instanceof CNodeData && !inHops2.containsKey("X"))
inHops2.put("X", hop.getInput().get(0));
} else
throw new RuntimeException("Unsupported unary matrix " + "operation: " + ((UnaryOp) hop).getOp().name());
} else // general scalar case
{
cdata1 = TemplateUtils.wrapLookupIfNecessary(cdata1, hop.getInput().get(0));
String primitiveOpName = ((UnaryOp) hop).getOp().toString();
out = new CNodeUnary(cdata1, UnaryType.valueOf(primitiveOpName));
}
} else if (HopRewriteUtils.isBinary(hop, OpOp2.CBIND)) {
// special case for cbind with zeros
CNode cdata1 = tmp.get(hop.getInput().get(0).getHopID());
CNode cdata2 = null;
if (HopRewriteUtils.isDataGenOpWithConstantValue(hop.getInput().get(1))) {
cdata2 = TemplateUtils.createCNodeData(HopRewriteUtils.getDataGenOpConstantValue(hop.getInput().get(1)), true);
// rm 0-matrix
inHops.remove(hop.getInput().get(1));
} else {
cdata2 = tmp.get(hop.getInput().get(1).getHopID());
cdata2 = TemplateUtils.wrapLookupIfNecessary(cdata2, hop.getInput().get(1));
}
out = new CNodeBinary(cdata1, cdata2, BinType.VECT_CBIND);
if (cdata1 instanceof CNodeData && !inHops2.containsKey("X"))
inHops2.put("X", hop.getInput().get(0));
} else if (hop instanceof BinaryOp) {
CNode cdata1 = tmp.get(hop.getInput().get(0).getHopID());
CNode cdata2 = tmp.get(hop.getInput().get(1).getHopID());
// if one input is a matrix then we need to do vector by scalar operations
if ((hop.getInput().get(0).getDim1() >= 1 && hop.getInput().get(0).getDim2() > 1) || (hop.getInput().get(1).getDim1() >= 1 && hop.getInput().get(1).getDim2() > 1) || (!(hop.dimsKnown() && hop.getInput().get(0).dimsKnown() && hop.getInput().get(1).dimsKnown()) && // not a known vector output
(hop.getDim2() != 1) && (cdata1.getDataType().isMatrix() || cdata2.getDataType().isMatrix()))) {
if (HopRewriteUtils.isBinary(hop, SUPPORTED_VECT_BINARY)) {
if (TemplateUtils.isMatrix(cdata1) && (TemplateUtils.isMatrix(cdata2) || TemplateUtils.isRowVector(cdata2))) {
String opname = "VECT_" + ((BinaryOp) hop).getOp().name();
out = new CNodeBinary(cdata1, cdata2, BinType.valueOf(opname));
} else {
String opname = "VECT_" + ((BinaryOp) hop).getOp().name() + "_SCALAR";
if (TemplateUtils.isColVector(cdata1))
cdata1 = new CNodeUnary(cdata1, UnaryType.LOOKUP_R);
if (TemplateUtils.isColVector(cdata2))
cdata2 = new CNodeUnary(cdata2, UnaryType.LOOKUP_R);
out = new CNodeBinary(cdata1, cdata2, BinType.valueOf(opname));
}
if (cdata1 instanceof CNodeData && !inHops2.containsKey("X") && !(cdata1.getDataType() == DataType.SCALAR)) {
inHops2.put("X", hop.getInput().get(0));
}
} else
throw new RuntimeException("Unsupported binary matrix " + "operation: " + ((BinaryOp) hop).getOp().name());
} else // one input is a vector/scalar other is a scalar
{
String primitiveOpName = ((BinaryOp) hop).getOp().toString();
if (TemplateUtils.isColVector(cdata1))
cdata1 = new CNodeUnary(cdata1, UnaryType.LOOKUP_R);
if (// vector or vector can be inferred from lhs
TemplateUtils.isColVector(cdata2) || (TemplateUtils.isColVector(hop.getInput().get(0)) && cdata2 instanceof CNodeData && hop.getInput().get(1).getDataType().isMatrix()))
cdata2 = new CNodeUnary(cdata2, UnaryType.LOOKUP_R);
out = new CNodeBinary(cdata1, cdata2, BinType.valueOf(primitiveOpName));
}
} else if (hop instanceof TernaryOp) {
TernaryOp top = (TernaryOp) hop;
CNode cdata1 = tmp.get(hop.getInput().get(0).getHopID());
CNode cdata2 = tmp.get(hop.getInput().get(1).getHopID());
CNode cdata3 = tmp.get(hop.getInput().get(2).getHopID());
// add lookups if required
cdata1 = TemplateUtils.wrapLookupIfNecessary(cdata1, hop.getInput().get(0));
cdata3 = TemplateUtils.wrapLookupIfNecessary(cdata3, hop.getInput().get(2));
// construct ternary cnode, primitive operation derived from OpOp3
out = new CNodeTernary(cdata1, cdata2, cdata3, TernaryType.valueOf(top.getOp().toString()));
} else if (HopRewriteUtils.isNary(hop, OpOpN.CBIND)) {
CNode[] inputs = new CNode[hop.getInput().size()];
for (int i = 0; i < hop.getInput().size(); i++) {
Hop c = hop.getInput().get(i);
CNode cdata = tmp.get(c.getHopID());
if (TemplateUtils.isColVector(cdata) || TemplateUtils.isRowVector(cdata))
cdata = TemplateUtils.wrapLookupIfNecessary(cdata, c);
inputs[i] = cdata;
if (i == 0 && cdata instanceof CNodeData && !inHops2.containsKey("X"))
inHops2.put("X", c);
}
out = new CNodeNary(inputs, NaryType.VECT_CBIND);
} else if (hop instanceof ParameterizedBuiltinOp) {
CNode cdata1 = tmp.get(((ParameterizedBuiltinOp) hop).getTargetHop().getHopID());
cdata1 = TemplateUtils.wrapLookupIfNecessary(cdata1, hop.getInput().get(0));
CNode cdata2 = tmp.get(((ParameterizedBuiltinOp) hop).getParameterHop("pattern").getHopID());
CNode cdata3 = tmp.get(((ParameterizedBuiltinOp) hop).getParameterHop("replacement").getHopID());
TernaryType ttype = (cdata2.isLiteral() && cdata2.getVarname().equals("Double.NaN")) ? TernaryType.REPLACE_NAN : TernaryType.REPLACE;
out = new CNodeTernary(cdata1, cdata2, cdata3, ttype);
} else if (hop instanceof IndexingOp) {
CNode cdata1 = tmp.get(hop.getInput().get(0).getHopID());
out = new CNodeTernary(cdata1, TemplateUtils.createCNodeData(new LiteralOp(hop.getInput().get(0).getDim2()), true), TemplateUtils.createCNodeData(hop.getInput().get(4), true), (hop.getDim2() != 1) ? TernaryType.LOOKUP_RVECT1 : TernaryType.LOOKUP_RC1);
}
if (out == null) {
throw new RuntimeException(hop.getHopID() + " " + hop.getOpString());
}
if (out.getDataType().isMatrix()) {
out.setNumRows(hop.getDim1());
out.setNumCols(hop.getDim2());
}
tmp.put(hop.getHopID(), out);
}
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