1 files changed, 93 insertions, 0 deletions
diff --git a/vespajlib/src/main/java/com/yahoo/tensor/functions/CosineSimilarity.java b/vespajlib/src/main/java/com/yahoo/tensor/functions/CosineSimilarity.java
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+++ b/vespajlib/src/main/java/com/yahoo/tensor/functions/CosineSimilarity.java
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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.tensor.functions;
+
+import com.yahoo.tensor.evaluation.EvaluationContext;
+import com.yahoo.tensor.evaluation.Name;
+import com.yahoo.tensor.evaluation.TypeContext;
+import com.yahoo.tensor.Tensor;
+import com.yahoo.tensor.TensorType;
+import com.yahoo.tensor.TensorType.Dimension;
+
+import java.util.Collections;
+import java.util.List;
+import java.util.Objects;
+
+/**
+ * Convenience for cosine similarity between vectors.
+ * cosine_similarity(a, b, mydim) == sum(a*b, mydim) / sqrt(sum(a*a, mydim) * sum(b*b, mydim))
+ * @author arnej
+ */
+public class CosineSimilarity<NAMETYPE extends Name> extends TensorFunction<NAMETYPE> {
+
+    private final TensorFunction<NAMETYPE> arg1;
+    private final TensorFunction<NAMETYPE> arg2;
+    private final String dimension;
+
+    public CosineSimilarity(TensorFunction<NAMETYPE> argument1,
+                            TensorFunction<NAMETYPE> argument2,
+                            String dimension)
+    {
+        this.arg1 = argument1;
+        this.arg2 = argument2;
+        this.dimension = dimension;
+    }
+
+    @Override
+    public List<TensorFunction<NAMETYPE>> arguments() { return List.of(arg1, arg2); }
+
+    @Override
+    public TensorFunction<NAMETYPE> withArguments(List<TensorFunction<NAMETYPE>> arguments) {
+        if ( arguments.size() != 2)
+            throw new IllegalArgumentException("CosineSimilarity must have 2 arguments, got " + arguments.size());
+        return new CosineSimilarity<>(arguments.get(0), arguments.get(1), dimension);
+    }
+
+    @Override
+    public TensorType type(TypeContext<NAMETYPE> context) {
+        TensorType t1 = arg1.toPrimitive().type(context);
+        TensorType t2 = arg2.toPrimitive().type(context);
+        var d1 = t1.dimension(dimension);
+        var d2 = t2.dimension(dimension);
+        if (d1.isEmpty() || d2.isEmpty()
+            || d1.get().type() != Dimension.Type.indexedBound
+            || d2.get().type() != Dimension.Type.indexedBound
+            || d1.get().size().get() != d2.get().size().get())
+        {
+            throw new IllegalArgumentException("cosine_similarity expects both arguments to have the '"
+                                               + dimension + "' dimension with same size, but input types were "
+                                               + t1 + " and " + t2);
+        }
+        // Finds the type this produces by first converting it to a primitive function
+        return toPrimitive().type(context);
+    }
+
+    /** Evaluates this by first converting it to a primitive function */
+    @Override
+    public Tensor evaluate(EvaluationContext<NAMETYPE> context) {
+        return toPrimitive().evaluate(context);
+    }
+
+    @Override
+    public PrimitiveTensorFunction<NAMETYPE> toPrimitive() {
+        TensorFunction<NAMETYPE> a = arg1.toPrimitive();
+        TensorFunction<NAMETYPE> b = arg2.toPrimitive();
+        var aa = new Join<>(a, a, ScalarFunctions.multiply());
+        var ab = new Join<>(a, b, ScalarFunctions.multiply());
+        var bb = new Join<>(b, b, ScalarFunctions.multiply());
+        var dot_aa = new Reduce<>(aa, Reduce.Aggregator.sum, dimension);
+        var dot_ab = new Reduce<>(ab, Reduce.Aggregator.sum, dimension);
+        var dot_bb = new Reduce<>(bb, Reduce.Aggregator.sum, dimension);
+        var aabb = new Join<>(dot_aa, dot_bb, ScalarFunctions.multiply());
+        var sqrt_aabb = new Map<>(aabb, ScalarFunctions.sqrt());
+        return new Join<>(dot_ab, sqrt_aabb, ScalarFunctions.divide());
+    }
+
+    @Override
+    public String toString(ToStringContext<NAMETYPE> context) {
+        return "cosine_similarity(" + arg1.toString(context) + ", " + arg2.toString(context) + ", " + dimension + ")";
+    }
+
+    @Override
+    public int hashCode() { return Objects.hash("cosine_similarity", arg1, arg2, dimension); }
+
+}