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// Copyright Yahoo. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root.
package com.yahoo.searchlib.rankingexpression.evaluation;
import com.yahoo.api.annotations.Beta;
import com.yahoo.searchlib.rankingexpression.rule.Function;
import com.yahoo.searchlib.rankingexpression.rule.TruthOperator;
import com.yahoo.tensor.Tensor;
import com.yahoo.tensor.TensorAddress;
import com.yahoo.tensor.TensorType;
/**
* A Value containing a tensor.
* See {@link com.yahoo.tensor.Tensor} for definition of a tensor
* and the operations supported.
*
* @author bratseth
*/
@Beta
public class TensorValue extends Value {
/** The tensor value of this */
private final Tensor value;
public TensorValue(Tensor value) {
this.value = value;
}
@Override
public TensorType type() { return value.type(); }
@Override
public double asDouble() {
if (hasDouble())
return value.get(TensorAddress.of());
throw new UnsupportedOperationException("Requires a double value, but " + this.value + " cannot be " +
"used as a double");
}
@Override
public boolean hasDouble() { return value.type().dimensions().isEmpty() && ! value.isEmpty(); }
@Override
public boolean asBoolean() {
if (hasDouble())
return asDouble() != 0.0;
throw new UnsupportedOperationException("Tensor does not have a value that can be converted to a boolean");
}
@Override
public Value negate() {
return new TensorValue(value.map((value) -> -value));
}
@Override
public Value add(Value argument) {
if (argument instanceof TensorValue)
return new TensorValue(value.add(((TensorValue)argument).value));
else
return new TensorValue(value.map((value) -> value + argument.asDouble()));
}
@Override
public Value subtract(Value argument) {
if (argument instanceof TensorValue)
return new TensorValue(value.subtract(((TensorValue) argument).value));
else
return new TensorValue(value.map((value) -> value - argument.asDouble()));
}
@Override
public Value multiply(Value argument) {
if (argument instanceof TensorValue)
return new TensorValue(value.multiply(((TensorValue) argument).value));
else
return new TensorValue(value.map((value) -> value * argument.asDouble()));
}
@Override
public Value divide(Value argument) {
if (argument instanceof TensorValue)
return new TensorValue(value.divide(((TensorValue) argument).value));
else
return new TensorValue(value.map((value) -> value / argument.asDouble()));
}
@Override
public Value modulo(Value argument) {
if (argument instanceof TensorValue)
return new TensorValue(value.fmod(((TensorValue) argument).value));
else
return new TensorValue(value.map((value) -> value % argument.asDouble()));
}
@Override
public Value and(Value argument) {
if (argument instanceof TensorValue)
return new TensorValue(value.join(((TensorValue)argument).value, (a, b) -> ((a!=0.0) && (b!=0.0)) ? 1.0 : 0.0 ));
else
return new TensorValue(value.map((value) -> ((value!=0.0) && argument.asBoolean()) ? 1 : 0));
}
@Override
public Value or(Value argument) {
if (argument instanceof TensorValue)
return new TensorValue(value.join(((TensorValue)argument).value, (a, b) -> ((a!=0.0) || (b!=0.0)) ? 1.0 : 0.0 ));
else
return new TensorValue(value.map((value) -> ((value!=0.0) || argument.asBoolean()) ? 1 : 0));
}
@Override
public Value not() {
return new TensorValue(value.map((value) -> (value==0.0) ? 1.0 : 0.0));
}
@Override
public Value power(Value argument) {
if (argument instanceof TensorValue)
return new TensorValue(value.pow(((TensorValue)argument).value));
else
return new TensorValue(value.map((value) -> Math.pow(value, argument.asDouble())));
}
public Tensor asTensor() { return value; }
@Override
public Value compare(TruthOperator operator, Value argument) {
return new TensorValue(compareTensor(operator, argument.asTensor()));
}
private Tensor compareTensor(TruthOperator operator, Tensor argument) {
switch (operator) {
case LARGER: return value.larger(argument);
case LARGEREQUAL: return value.largerOrEqual(argument);
case SMALLER: return value.smaller(argument);
case SMALLEREQUAL: return value.smallerOrEqual(argument);
case EQUAL: return value.equal(argument);
case NOTEQUAL: return value.notEqual(argument);
case APPROX_EQUAL: return value.approxEqual(argument);
default: throw new UnsupportedOperationException("Tensors cannot be compared with " + operator);
}
}
@Override
public Value function(Function function, Value arg) {
if (arg instanceof TensorValue)
return new TensorValue(functionOnTensor(function, arg.asTensor()));
else
return new TensorValue(value.map((value) -> function.evaluate(value, arg.asDouble())));
}
private Tensor functionOnTensor(Function function, Tensor argument) {
switch (function) {
case min: return value.min(argument);
case max: return value.max(argument);
case atan2: return value.atan2(argument);
case pow: return value.pow(argument);
case fmod: return value.fmod(argument);
case ldexp: return value.ldexp(argument);
case bit: return value.bit(argument);
case hamming: return value.hamming(argument);
default: throw new UnsupportedOperationException("Cannot combine two tensors using " + function);
}
}
@Override
public Value asMutable() {
throw new UnsupportedOperationException();
}
@Override
public String toString() {
return value.toString();
}
@Override
public boolean equals(Object o) {
if (this == o) return true;
if (o == null || getClass() != o.getClass()) return false;
TensorValue other = (TensorValue) o;
return value.equals(other.value);
}
@Override
public int hashCode() {
return value.hashCode();
}
}
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