// 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 com.yahoo.searchlib.rankingexpression.evaluation.DoubleValue;
import ai.vespa.rankingexpression.importer.DimensionRenamer;
import ai.vespa.rankingexpression.importer.OrderedTensorType;
import com.yahoo.searchlib.rankingexpression.Reference;
import com.yahoo.searchlib.rankingexpression.rule.ConstantNode;
import com.yahoo.searchlib.rankingexpression.rule.ExpressionNode;
import com.yahoo.searchlib.rankingexpression.rule.GeneratorLambdaFunctionNode;
import com.yahoo.tensor.Tensor;
import com.yahoo.tensor.TensorType;
import com.yahoo.tensor.functions.Generate;
import com.yahoo.tensor.functions.ScalarFunctions;
import com.yahoo.tensor.functions.TensorFunction;

import java.util.ArrayList;
import java.util.List;
import java.util.Optional;

public class ExpandDims extends IntermediateOperation {

    private List<String> expandDimensions;

    public ExpandDims(String modelName, String nodeName, List<IntermediateOperation> inputs) {
        super(modelName, nodeName, inputs);
    }

    @Override
    protected OrderedTensorType lazyGetType() {
        if ( ! allInputTypesPresent(2)) return null;

        IntermediateOperation axisOperation = inputs().get(1);
        if ( ! axisOperation.getConstantValue().isPresent()) {
            throw new IllegalArgumentException("ExpandDims in " + name + ": Axis must be a constant.");
        }
        Tensor axis = axisOperation.getConstantValue().get().asTensor();
        if (axis.type().rank() != 0)
            throw new IllegalArgumentException("ExpandDims in " + name + ": Axis argument must be a scalar.");

        OrderedTensorType inputType = inputs.get(0).type().get();
        int dimensionToInsert = (int)axis.asDouble();
        if (dimensionToInsert < 0) {
            dimensionToInsert = inputType.dimensions().size() + dimensionToInsert;
        }

        OrderedTensorType.Builder typeBuilder = new OrderedTensorType.Builder(resultValueType());
        expandDimensions = new ArrayList<>();
        int dimensionIndex = 0;
        for (TensorType.Dimension dimension : inputType.dimensions()) {
            if (dimensionIndex == dimensionToInsert)
                addDimension(dimensionIndex, typeBuilder);
            typeBuilder.add(dimension);
            dimensionIndex++;
        }
        if (dimensionToInsert == inputType.dimensions().size()) { // Insert last dimension
            addDimension(dimensionIndex, typeBuilder);
        }
        return typeBuilder.build();
    }

    private void addDimension(int dimensionIndex, OrderedTensorType.Builder typeBuilder) {
        String name = String.format("%s_%d", vespaName(), dimensionIndex);
        expandDimensions.add(name);
        typeBuilder.add(TensorType.Dimension.indexed(name, 1L));
    }

    @Override
    protected TensorFunction<Reference> lazyGetFunction() {
        if ( ! allInputFunctionsPresent(2)) return null;

        // multiply with a generated tensor created from the reduced dimensions
        TensorType.Builder typeBuilder = new TensorType.Builder(resultValueType());
        for (String name : expandDimensions) {
            typeBuilder.indexed(name, 1);
        }
        TensorType generatedType = typeBuilder.build();
        ExpressionNode generatedExpression = new ConstantNode(new DoubleValue(1));
        Generate<Reference> generatedFunction = new Generate<>(generatedType,
                new GeneratorLambdaFunctionNode(generatedType, generatedExpression).asLongListToDoubleOperator());
        return new com.yahoo.tensor.functions.Join<>(inputs().get(0).function().get(), generatedFunction, ScalarFunctions.multiply());
    }

    @Override
    public void addDimensionNameConstraints(DimensionRenamer renamer) {
        addConstraintsFrom(type, renamer);
    }

    @Override
    public void renameDimensions(DimensionRenamer renamer) {
        super.renameDimensions(renamer);
        List<String> renamedDimensions = new ArrayList<>(expandDimensions.size());
        for (String name : expandDimensions) {
            Optional<String> newName = renamer.dimensionNameOf(name);
            if ( ! newName.isPresent()) {
                return;  // presumably, already renamed
            }
            renamedDimensions.add(newName.get());
        }
        expandDimensions = renamedDimensions;
    }

    @Override
    public ExpandDims withInputs(List<IntermediateOperation> inputs) {
        return new ExpandDims(modelName(), name(), inputs);
    }

    @Override
    public String operationName() { return "ExpandDims"; }

}