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// Copyright Vespa.ai. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root.
package com.yahoo.document.update;
import com.yahoo.document.DataType;
import com.yahoo.document.TensorDataType;
import com.yahoo.document.datatypes.FieldValue;
import com.yahoo.document.datatypes.TensorFieldValue;
import com.yahoo.document.serialization.DocumentUpdateWriter;
import com.yahoo.tensor.Tensor;
import com.yahoo.tensor.TensorType;
import java.util.Objects;
/**
* An update used to remove cells from a sparse tensor or dense sub-spaces from a mixed tensor.
*
* The specification of which cells to remove contains addresses using a subset or all of the sparse dimensions of the tensor type.
* This is represented as a sparse tensor where cell values are set to 1.0.
*/
public class TensorRemoveUpdate extends ValueUpdate<TensorFieldValue> {
private TensorFieldValue tensor;
public TensorRemoveUpdate(TensorFieldValue value) {
super(ValueUpdateClassID.TENSORREMOVE);
this.tensor = value;
if (!tensor.getTensor().isPresent()) {
throw new IllegalArgumentException("Tensor must be present in remove update");
}
verifyCompatibleType(tensor.getTensorType().get());
}
public void verifyCompatibleType(TensorType originalType) {
TensorType sparseType = extractSparseDimensions(originalType);
TensorType thisType = tensor.getTensorType().get();
for (var dim : thisType.dimensions()) {
if (sparseType.dimension(dim.name()).isEmpty()) {
throw new IllegalArgumentException("Unexpected type '" + thisType + "' in remove update. "
+ "Expected dimensions to be a subset of '" + sparseType + "'");
}
}
}
@Override
protected void checkCompatibility(DataType fieldType) {
if (!(fieldType instanceof TensorDataType)) {
throw new UnsupportedOperationException("Expected tensor type, got " + fieldType.getName() + ".");
}
}
@Override
public void serialize(DocumentUpdateWriter data, DataType superType) {
data.write(this);
}
@Override
public FieldValue applyTo(FieldValue oldValue) {
if ( ! (oldValue instanceof TensorFieldValue)) {
throw new IllegalStateException("Cannot use tensor remove update on non-tensor datatype " + oldValue.getClass().getName());
}
if ( ! ((TensorFieldValue) oldValue).getTensor().isPresent()) {
throw new IllegalArgumentException("No existing tensor to apply update to");
}
if ( ! tensor.getTensor().isPresent()) {
return oldValue;
}
Tensor old = ((TensorFieldValue) oldValue).getTensor().get();
Tensor update = tensor.getTensor().get();
// TODO: handle the case where this tensor only contains a subset of the sparse dimensions of the input tensor.
Tensor result = old.remove(update.cells().keySet());
return new TensorFieldValue(result);
}
@Override
public TensorFieldValue getValue() {
return tensor;
}
@Override
public void setValue(TensorFieldValue value) {
tensor = value;
}
@Override
public boolean equals(Object o) {
if (this == o) return true;
if (o == null || getClass() != o.getClass()) return false;
if (!super.equals(o)) return false;
TensorRemoveUpdate that = (TensorRemoveUpdate) o;
return tensor.equals(that.tensor);
}
@Override
public int hashCode() {
return Objects.hash(super.hashCode(), tensor);
}
@Override
public String toString() {
return super.toString() + " " + tensor;
}
public static TensorType extractSparseDimensions(TensorType type) {
TensorType.Builder builder = new TensorType.Builder(type.valueType());
type.dimensions().stream().filter(dim -> ! dim.isIndexed()).forEach(dim -> builder.mapped(dim.name()));
return builder.build();
}
}
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