/*
 * Copyright (c) 2012, 2019, Oracle and/or its affiliates. All rights reserved.
 * DO NOT ALTER OR REMOVE COPYRIGHT NOTICES OR THIS FILE HEADER.
 *
 * This code is free software; you can redistribute it and/or modify it
 * under the terms of the GNU General Public License version 2 only, as
 * published by the Free Software Foundation.
 *
 * This code is distributed in the hope that it will be useful, but WITHOUT
 * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or
 * FITNESS FOR A PARTICULAR PURPOSE.  See the GNU General Public License
 * version 2 for more details (a copy is included in the LICENSE file that
 * accompanied this code).
 *
 * You should have received a copy of the GNU General Public License version
 * 2 along with this work; if not, write to the Free Software Foundation,
 * Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA.
 *
 * Please contact Oracle, 500 Oracle Parkway, Redwood Shores, CA 94065 USA
 * or visit www.oracle.com if you need additional information or have any
 * questions.
 */


package org.graalvm.compiler.nodes.extended;

import static org.graalvm.compiler.nodeinfo.NodeCycles.CYCLES_0;
import static org.graalvm.compiler.nodeinfo.NodeSize.SIZE_0;

import jdk.vm.ci.meta.JavaKind;
import org.graalvm.compiler.core.common.calc.CanonicalCondition;
import org.graalvm.compiler.core.common.type.IntegerStamp;
import org.graalvm.compiler.core.common.type.StampFactory;
import org.graalvm.compiler.debug.GraalError;
import org.graalvm.compiler.graph.Node;
import org.graalvm.compiler.graph.NodeClass;
import org.graalvm.compiler.graph.iterators.NodePredicates;
import org.graalvm.compiler.graph.spi.Canonicalizable;
import org.graalvm.compiler.graph.spi.CanonicalizerTool;
import org.graalvm.compiler.graph.spi.Simplifiable;
import org.graalvm.compiler.graph.spi.SimplifierTool;
import org.graalvm.compiler.nodeinfo.NodeInfo;
import org.graalvm.compiler.nodes.FixedGuardNode;
import org.graalvm.compiler.nodes.IfNode;
import org.graalvm.compiler.nodes.NodeView;
import org.graalvm.compiler.nodes.ReturnNode;
import org.graalvm.compiler.nodes.ValueNode;
import org.graalvm.compiler.nodes.calc.ConditionalNode;
import org.graalvm.compiler.nodes.calc.FloatingNode;
import org.graalvm.compiler.nodes.calc.IntegerEqualsNode;
import org.graalvm.compiler.nodes.calc.NarrowNode;
import org.graalvm.compiler.nodes.calc.ZeroExtendNode;
import org.graalvm.compiler.nodes.spi.Lowerable;
import org.graalvm.compiler.nodes.spi.LoweringTool;

Instances of this node class will look for a preceding if node and put the given probability into
the if node's taken probability. Then the branch probability node will be removed. This node is
intended primarily for snippets, so that they can define their fast and slow paths.
/**
 * Instances of this node class will look for a preceding if node and put the given probability into
 * the if node's taken probability. Then the branch probability node will be removed. This node is
 * intended primarily for snippets, so that they can define their fast and slow paths.
 */
@NodeInfo(cycles = CYCLES_0, cyclesRationale = "Artificial Node", size = SIZE_0)
public final class BranchProbabilityNode extends FloatingNode implements Simplifiable, Lowerable, Canonicalizable {

    public static final NodeClass<BranchProbabilityNode> TYPE = NodeClass.create(BranchProbabilityNode.class);
    public static final double LIKELY_PROBABILITY = 0.6;
    public static final double NOT_LIKELY_PROBABILITY = 1 - LIKELY_PROBABILITY;

    public static final double FREQUENT_PROBABILITY = 0.9;
    public static final double NOT_FREQUENT_PROBABILITY = 1 - FREQUENT_PROBABILITY;

    public static final double FAST_PATH_PROBABILITY = 0.99;
    public static final double SLOW_PATH_PROBABILITY = 1 - FAST_PATH_PROBABILITY;

    public static final double VERY_FAST_PATH_PROBABILITY = 0.999;
    public static final double VERY_SLOW_PATH_PROBABILITY = 1 - VERY_FAST_PATH_PROBABILITY;

    public static final double DEOPT_PROBABILITY = 0.0;

    /*
     * This probability may seem excessive, but it makes a difference in long running loops. Lets
     * say a loop is executed 100k times and it has a few null checks with probability 0.999. As
     * these probabilities multiply for every loop iteration, the overall loop frequency will be
     * calculated as approximately 30 while it should be 100k.
     */
    public static final double LUDICROUSLY_FAST_PATH_PROBABILITY = 0.999999;
    public static final double LUDICROUSLY_SLOW_PATH_PROBABILITY = 1 - LUDICROUSLY_FAST_PATH_PROBABILITY;

    @Input ValueNode probability;
    @Input ValueNode condition;

    public BranchProbabilityNode(ValueNode probability, ValueNode condition) {
        super(TYPE, StampFactory.forKind(JavaKind.Boolean));
        this.probability = probability;
        this.condition = condition;
    }

    public ValueNode getProbability() {
        return probability;
    }

    public ValueNode getCondition() {
        return condition;
    }

    @Override
    public Node canonical(CanonicalizerTool tool) {
        if (condition.isConstant()) {
            // fold constant conditions early during PE
            return condition;
        }
        return this;
    }

    @Override
    public void simplify(SimplifierTool tool) {
        if (!hasUsages()) {
            return;
        }
        if (probability.isConstant()) {
            double probabilityValue = probability.asJavaConstant().asDouble();
            if (probabilityValue < 0.0) {
                throw new GraalError("A negative probability of " + probabilityValue + " is not allowed!");
            } else if (probabilityValue > 1.0) {
                throw new GraalError("A probability of more than 1.0 (" + probabilityValue + ") is not allowed!");
            } else if (Double.isNaN(probabilityValue)) {
                /*
                 * We allow NaN if the node is in unreachable code that will eventually fall away,
                 * or else an error will be thrown during lowering since we keep the node around.
                 */
                return;
            }
            boolean usageFound = false;
            for (IntegerEqualsNode node : this.usages().filter(IntegerEqualsNode.class)) {
                assert node.condition() == CanonicalCondition.EQ;
                ValueNode other = node.getX();
                if (node.getX() == this) {
                    other = node.getY();
                }
                if (other.isConstant()) {
                    double probabilityToSet = probabilityValue;
                    if (other.asJavaConstant().asInt() == 0) {
                        probabilityToSet = 1.0 - probabilityToSet;
                    }
                    for (IfNode ifNodeUsages : node.usages().filter(IfNode.class)) {
                        usageFound = true;
                        ifNodeUsages.setTrueSuccessorProbability(probabilityToSet);
                    }
                    if (!usageFound) {
                        usageFound = node.usages().filter(NodePredicates.isA(FixedGuardNode.class).or(ConditionalNode.class)).isNotEmpty();
                    }
                }
            }
            if (usageFound) {
                ValueNode currentCondition = condition;
                IntegerStamp currentStamp = (IntegerStamp) currentCondition.stamp(NodeView.DEFAULT);
                if (currentStamp.lowerBound() < 0 || 1 < currentStamp.upperBound()) {
                    ValueNode narrow = graph().maybeAddOrUnique(NarrowNode.create(currentCondition, 1, NodeView.DEFAULT));
                    currentCondition = graph().maybeAddOrUnique(ZeroExtendNode.create(narrow, 32, NodeView.DEFAULT));
                }
                replaceAndDelete(currentCondition);
                if (tool != null) {
                    tool.addToWorkList(currentCondition.usages());
                }
            } else {
                if (!isSubstitutionGraph()) {
                    throw new GraalError("Wrong usage of branch probability injection!");
                }
            }
        }
    }

    private boolean isSubstitutionGraph() {
        return hasExactlyOneUsage() && usages().first() instanceof ReturnNode;
    }

    
This intrinsic should only be used for the condition of an if statement. The parameter
condition should also only denote a simple condition and not a combined condition involving
&& or || operators. It injects the probability of the condition into the if
statement.
Params:
probability – the probability that the given condition is true as a double value between
           0.0 and 1.0.
condition – the simple condition without any && or || operators
Returns:
the condition/**
     * This intrinsic should only be used for the condition of an if statement. The parameter
     * condition should also only denote a simple condition and not a combined condition involving
     * &amp;&amp; or || operators. It injects the probability of the condition into the if
     * statement.
     *
     * @param probability the probability that the given condition is true as a double value between
     *            0.0 and 1.0.
     * @param condition the simple condition without any &amp;&amp; or || operators
     * @return the condition
     */
    @NodeIntrinsic
    public static native boolean probability(double probability, boolean condition);

    @Override
    public void lower(LoweringTool tool) {
        throw new GraalError("Branch probability could not be injected, because the probability value did not reduce to a constant value.");
    }
}