Revert "Require constant() for large constants and fix a type resolving bug (#9769)"

This reverts commit cee1c3a3804d5d3c25407b3c4ac64228e9d194e3.

1 files changed, 0 insertions, 93 deletions

diff --git a/searchlib/src/main/java/com/yahoo/searchlib/rankingexpression/transform/TensorMaxMinTransformer.java b/searchlib/src/main/java/com/yahoo/searchlib/rankingexpression/transform/TensorMaxMinTransformer.java
deleted file mode 100644
index 979c5b0f88c..00000000000
--- a/searchlib/src/main/java/com/yahoo/searchlib/rankingexpression/transform/TensorMaxMinTransformer.java
+++ /dev/null
@@ -1,93 +0,0 @@
-// Copyright 2017 Yahoo Holdings. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root.
-package com.yahoo.searchlib.rankingexpression.transform;
-
-import com.yahoo.searchlib.rankingexpression.Reference;
-import com.yahoo.searchlib.rankingexpression.rule.CompositeNode;
-import com.yahoo.searchlib.rankingexpression.rule.ExpressionNode;
-import com.yahoo.searchlib.rankingexpression.rule.FunctionNode;
-import com.yahoo.searchlib.rankingexpression.rule.NameNode;
-import com.yahoo.searchlib.rankingexpression.rule.ReferenceNode;
-import com.yahoo.searchlib.rankingexpression.rule.TensorFunctionNode;
-import com.yahoo.tensor.TensorType;
-import com.yahoo.tensor.evaluation.TypeContext;
-import com.yahoo.tensor.functions.Reduce;
-
-import java.util.Optional;
-
-/**
- * Transforms min(tensor,dim) and max(tensor,dim) to
- * reduce(tensor,min/max,dim). This is necessary as the backend does
- * not recognize these forms of min and max.
- *
- * @author lesters
- */
-public class TensorMaxMinTransformer<CONTEXT extends TransformContext> extends ExpressionTransformer<CONTEXT> {
-
-    @Override
-    public ExpressionNode transform(ExpressionNode node, CONTEXT context) {
-        if (node instanceof CompositeNode) {
-            node = transformChildren((CompositeNode) node, context);
-        }
-        if (node instanceof FunctionNode) {
-            node = transformFunctionNode((FunctionNode) node, context.types());
-        }
-        return node;
-    }
-
-    public static ExpressionNode transformFunctionNode(FunctionNode node, TypeContext<Reference> context) {
-        switch (node.getFunction()) {
-            case min:
-            case max:
-                return transformMaxAndMinFunctionNode(node, context);
-        }
-        return node;
-    }
-
-    /**
-     * Transforms max and min functions if the first
-     * argument returns a tensor type and the second argument is a valid
-     * dimension in the tensor.
-     */
-    private static ExpressionNode transformMaxAndMinFunctionNode(FunctionNode node, TypeContext<Reference> context) {
-        if (node.children().size() != 2) {
-            return node;
-        }
-        ExpressionNode arg1 = node.children().get(0);
-        Optional<String> dimension = dimensionName(node.children().get(1));
-        if (dimension.isPresent()) {
-            TensorType type = arg1.type(context);
-            if (type.dimension(dimension.get()).isPresent()) {
-                return replaceMaxAndMinFunction(node);
-            }
-        }
-        return node;
-    }
-
-    private static Optional<String> dimensionName(ExpressionNode node) {
-        if (node instanceof ReferenceNode) {
-            Reference reference = ((ReferenceNode)node).reference();
-            if (reference.isIdentifier())
-                return Optional.of(reference.name());
-            else
-                return Optional.empty();
-        }
-        else if (node instanceof NameNode) {
-            return Optional.of(((NameNode)node).getValue());
-        }
-        else {
-            return Optional.empty();
-        }
-    }
-
-    private static ExpressionNode replaceMaxAndMinFunction(FunctionNode node) {
-        ExpressionNode arg1 = node.children().get(0);
-        ExpressionNode arg2 = node.children().get(1);
-
-        TensorFunctionNode.TensorFunctionExpressionNode expression = TensorFunctionNode.wrapArgument(arg1);
-        Reduce.Aggregator aggregator = Reduce.Aggregator.valueOf(node.getFunction().name());
-        String dimension = ((ReferenceNode) arg2).getName();
-
-        return new TensorFunctionNode(new Reduce(expression, aggregator, dimension));
-    }
-
-}