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// Copyright Yahoo. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root.
package ai.vespa.rankingexpression.importer.operations;
import ai.vespa.rankingexpression.importer.DimensionRenamer;
import ai.vespa.rankingexpression.importer.OrderedTensorType;
import com.yahoo.searchlib.rankingexpression.Reference;
import com.yahoo.searchlib.rankingexpression.evaluation.Value;
import com.yahoo.tensor.TensorType;
import com.yahoo.tensor.functions.Reduce;
import com.yahoo.tensor.functions.TensorFunction;
import java.util.ArrayList;
import java.util.List;
import java.util.Optional;
import java.util.stream.Collectors;
public class Squeeze extends IntermediateOperation {
private final AttributeMap attributeMap;
private List<String> squeezeDimensions;
public Squeeze(String modelName, String nodeName, List<IntermediateOperation> inputs, AttributeMap attributeMap) {
super(modelName, nodeName, inputs);
this.attributeMap = attributeMap;
}
@Override
protected OrderedTensorType lazyGetType() {
if ( ! allInputTypesPresent(1)) return null;
OrderedTensorType inputType = inputs.get(0).type().get();
squeezeDimensions = new ArrayList<>();
Optional<List<Value>> squeezeDimsAttr = attributeMap.getList("squeeze_dims");
if (squeezeDimsAttr.isEmpty()) {
squeezeDimsAttr = attributeMap.getList("axes"); // ONNX
}
if (squeezeDimsAttr.isEmpty()) {
squeezeDimensions = inputType.type().dimensions().stream().
filter(dim -> OrderedTensorType.dimensionSize(dim) == 1).
map(TensorType.Dimension::name).
toList();
} else {
squeezeDimensions = squeezeDimsAttr.get().stream().map(Value::asDouble).map(Double::intValue).
map(i -> i < 0 ? inputType.type().dimensions().size() - i : i).
map(i -> inputType.type().dimensions().get(i)).
filter(dim -> OrderedTensorType.dimensionSize(dim) == 1).
map(TensorType.Dimension::name).
toList();
}
return squeezeDimensions.isEmpty() ? inputType : reducedType(inputType);
}
@Override
protected TensorFunction<Reference> lazyGetFunction() {
if ( ! allInputFunctionsPresent(1)) return null;
TensorFunction<Reference> inputFunction = inputs.get(0).function().get();
return new Reduce<>(inputFunction, Reduce.Aggregator.sum, squeezeDimensions);
}
@Override
public void renameDimensions(DimensionRenamer renamer) {
super.renameDimensions(renamer);
List<String> renamedDimensions = new ArrayList<>(squeezeDimensions.size());
for (String name : squeezeDimensions) {
Optional<String> newName = renamer.dimensionNameOf(name);
if (newName.isEmpty()) {
return; // presumably, already renamed
}
renamedDimensions.add(newName.get());
}
squeezeDimensions = renamedDimensions;
}
@Override
public Squeeze withInputs(List<IntermediateOperation> inputs) {
return new Squeeze(modelName(), name(), inputs, attributeMap);
}
private OrderedTensorType reducedType(OrderedTensorType inputType) {
OrderedTensorType.Builder builder = new OrderedTensorType.Builder(resultValueType());
for (TensorType.Dimension dimension: inputType.dimensions()) {
if ( ! squeezeDimensions.contains(dimension.name())) {
builder.add(dimension);
}
}
return builder.build();
}
@Override
public String operationName() { return "Squeeze"; }
}
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