text:
/*
 * This file is available under and governed by the GNU General Public
 * License version 2 only, as published by the Free Software Foundation.
 * However, the following notice accompanied the original version of this
 * file:
 *
 * Written by Doug Lea with assistance from members of JCP JSR-166
 * Expert Group and released to the public domain, as explained at
 * http://creativecommons.org/publicdomain/zero/1.0/
 */

package java.util.concurrent;

import java.util.AbstractQueue;
import java.util.Collection;
import java.util.Iterator;
import java.util.NoSuchElementException;
import java.util.Queue;
import java.util.concurrent.TimeUnit;
import java.util.concurrent.locks.LockSupport;

/**
 * An unbounded {@link TransferQueue} based on linked nodes.
 * This queue orders elements FIFO (first-in-first-out) with respect
 * to any given producer.  The head of the queue is that
 * element that has been on the queue the longest time for some
 * producer.  The tail of the queue is that element that has
 * been on the queue the shortest time for some producer.
 *
 *
Beware that, unlike in most collections, the {@code size} method
 * is NOT a constant-time operation. Because of the
 * asynchronous nature of these queues, determining the current number
 * of elements requires a traversal of the elements, and so may report
 * inaccurate results if this collection is modified during traversal.
 * Additionally, the bulk operations {@code addAll},
 * {@code removeAll}, {@code retainAll}, {@code containsAll},
 * {@code equals}, and {@code toArray} are not guaranteed
 * to be performed atomically. For example, an iterator operating
 * concurrently with an {@code addAll} operation might view only some
 * of the added elements.
 *
 *
This class and its iterator implement all of the
 * optional methods of the {@link Collection} and {@link
 * Iterator} interfaces.
 *
 *
Memory consistency effects: As with other concurrent
 * collections, actions in a thread prior to placing an object into a
 * {@code LinkedTransferQueue}
 * happen-before
 * actions subsequent to the access or removal of that element from
 * the {@code LinkedTransferQueue} in another thread.
 *
 *
This class is a member of the
 *
 * Java Collections Framework.
 *
 * @since 1.7
 * @author Doug Lea
 * @param <E> the type of elements held in this collection
 */
public class LinkedTransferQueue<E> extends AbstractQueue<E>
    implements TransferQueue<E>, java.io.Serializable {
    private static final long serialVersionUID = -3223113410248163686L;

    /*
     * *** Overview of Dual Queues with Slack ***
     *
     * Dual Queues, introduced by Scherer and Scott
     * (http://www.cs.rice.edu/~wns1/papers/2004-DISC-DDS.pdf) are
     * (linked) queues in which nodes may represent either data or
     * requests.  When a thread tries to enqueue a data node, but
     * encounters a request node, it instead "matches" and removes it;
     * and vice versa for enqueuing requests. Blocking Dual Queues
     * arrange that threads enqueuing unmatched requests block until
     * other threads provide the match. Dual Synchronous Queues (see
     * Scherer, Lea, & Scott
     * http://www.cs.rochester.edu/u/scott/papers/2009_Scherer_CACM_SSQ.pdf)
     * additionally arrange that threads enqueuing unmatched data also
     * block.  Dual Transfer Queues support all of these modes, as
     * dictated by callers.
     *
     * A FIFO dual queue may be implemented using a variation of the
     * Michael & Scott (M&S) lock-free queue algorithm
     * (http://www.cs.rochester.edu/u/scott/papers/1996_PODC_queues.pdf).
     * It maintains two pointer fields, "head", pointing to a
     * (matched) node that in turn points to the first actual
     * (unmatched) queue node (or null if empty); and "tail" that
     * points to the last node on the queue (or again null if
     * empty). For example, here is a possible queue with four data
     * elements:
     *
     *  head                tail
     *    |                   |
     *    v                   v
     *    M -> U -> U -> U -> U
     *
     * The M&S queue algorithm is known to be prone to scalability and
     * overhead limitations when maintaining (via CAS) these head and
     * tail pointers. This has led to the development of
     * contention-reducing variants such as elimination arrays (see
     * Moir et al http://portal.acm.org/citation.cfm?id=1074013) and
     * optimistic back pointers (see Ladan-Mozes & Shavit
     * http://people.csail.mit.edu/edya/publications/OptimisticFIFOQueue-journal.pdf).
     * However, the nature of dual queues enables a simpler tactic for
     * improving M&S-style implementations when dual-ness is needed.
     *
     * In a dual queue, each node must atomically maintain its match
     * status. While there are other possible variants, we implement
     * this here as: for a data-mode node, matching entails CASing an
     * "item" field from a non-null data value to null upon match, and
     * vice-versa for request nodes, CASing from null to a data
     * value. (Note that the linearization properties of this style of
     * queue are easy to verify -- elements are made available by
     * linking, and unavailable by matching.) Compared to plain M&S
     * queues, this property of dual queues requires one additional
     * successful atomic operation per enq/deq pair. But it also
     * enables lower cost variants of queue maintenance mechanics. (A
     * variation of this idea applies even for non-dual queues that
     * support deletion of interior elements, such as
     * j.u.c.ConcurrentLinkedQueue.)
     *
     * Once a node is matched, its match status can never again
     * change.  We may thus arrange that the linked list of them
     * contain a prefix of zero or more matched nodes, followed by a
     * suffix of zero or more unmatched nodes. (Note that we allow
     * both the prefix and suffix to be zero length, which in turn
     * means that we do not use a dummy header.)  If we were not
     * concerned with either time or space efficiency, we could
     * correctly perform enqueue and dequeue operations by traversing
     * from a pointer to the initial node; CASing the item of the
     * first unmatched node on match and CASing the next field of the
     * trailing node on appends. (Plus some special-casing when
     * initially empty).  While this would be a terrible idea in
     * itself, it does have the benefit of not requiring ANY atomic
     * updates on head/tail fields.
     *
     * We introduce here an approach that lies between the extremes of
     * never versus always updating queue (head and tail) pointers.
     * This offers a tradeoff between sometimes requiring extra
     * traversal steps to locate the first and/or last unmatched
     * nodes, versus the reduced overhead and contention of fewer
     * updates to queue pointers. For example, a possible snapshot of
     * a queue is:
     *
     *  head           tail
     *    |              |
     *    v              v
     *    M -> M -> U -> U -> U -> U
     *
     * The best value for this "slack" (the targeted maximum distance
     * between the value of "head" and the first unmatched node, and
     * similarly for "tail") is an empirical matter. We have found
     * that using very small constants in the range of 1-3 work best
     * over a range of platforms. Larger values introduce increasing
     * costs of cache misses and risks of long traversal chains, while
     * smaller values increase CAS contention and overhead.
     *
     * Dual queues with slack differ from plain M&S dual queues by
     * virtue of only sometimes updating head or tail pointers when
     * matching, appending, or even traversing nodes; in order to
     * maintain a targeted slack.  The idea of "sometimes" may be
     * operationalized in several ways. The simplest is to use a
     * per-operation counter incremented on each traversal step, and
     * to try (via CAS) to update the associated queue pointer
     * whenever the count exceeds a threshold. Another, that requires
     * more overhead, is to use random number generators to update
     * with a given probability per traversal step.
     *
     * In any strategy along these lines, because CASes updating
     * fields may fail, the actual slack may exceed targeted
     * slack. However, they may be retried at any time to maintain
     * targets.  Even when using very small slack values, this
     * approach works well for dual queues because it allows all
     * operations up to the point of matching or appending an item
     * (hence potentially allowing progress by another thread) to be
     * read-only, thus not introducing any further contention. As
     * described below, we implement this by performing slack
     * maintenance retries only after these points.
     *
     * As an accompaniment to such techniques, traversal overhead can
     * be further reduced without increasing contention of head
     * pointer updates: Threads may sometimes shortcut the "next" link
     * path from the current "head" node to be closer to the currently
     * known first unmatched node, and similarly for tail. Again, this
     * may be triggered with using thresholds or randomization.
     *
     * These ideas must be further extended to avoid unbounded amounts
     * of costly-to-reclaim garbage caused by the sequential "next"
     * links of nodes starting at old forgotten head nodes: As first
     * described in detail by Boehm
     * (http://portal.acm.org/citation.cfm?doid=503272.503282) if a GC
     * delays noticing that any arbitrarily old node has become
     * garbage, all newer dead nodes will also be unreclaimed.
     * (Similar issues arise in non-GC environments.)  To cope with
     * this in our implementation, upon CASing to advance the head
     * pointer, we set the "next" link of the previous head to point
     * only to itself; thus limiting the length of connected dead lists.
     * (We also take similar care to wipe out possibly garbage
     * retaining values held in other Node fields.)  However, doing so
     * adds some further complexity to traversal: If any "next"
     * pointer links to itself, it indicates that the current thread
     * has lagged behind a head-update, and so the traversal must
     * continue from the "head".  Traversals trying to find the
     * current tail starting from "tail" may also encounter
     * self-links, in which case they also continue at "head".
     *
     * It is tempting in slack-based scheme to not even use CAS for
     * updates (similarly to Ladan-Mozes & Shavit). However, this
     * cannot be done for head updates under the above link-forgetting
     * mechanics because an update may leave head at a detached node.
     * And while direct writes are possible for tail updates, they
     * increase the risk of long retraversals, and hence long garbage
     * chains, which can be much more costly than is worthwhile
     * considering that the cost difference of performing a CAS vs
     * write is smaller when they are not triggered on each operation
     * (especially considering that writes and CASes equally require
     * additional GC bookkeeping ("write barriers") that are sometimes
     * more costly than the writes themselves because of contention).
     *
     * *** Overview of implementation ***
     *
     * We use a threshold-based approach to updates, with a slack
     * threshold of two -- that is, we update head/tail when the
     * current pointer appears to be two or more steps away from the
     * first/last node. The slack value is hard-wired: a path greater
     * than one is naturally implemented by checking equality of
     * traversal pointers except when the list has only one element,
     * in which case we keep slack threshold at one. Avoiding tracking
     * explicit counts across method calls slightly simplifies an
     * already-messy implementation. Using randomization would
     * probably work better if there were a low-quality dirt-cheap
     * per-thread one available, but even ThreadLocalRandom is too
     * heavy for these purposes.
     *
     * With such a small slack threshold value, it is not worthwhile
     * to augment this with path short-circuiting (i.e., unsplicing
     * interior nodes) except in the case of cancellation/removal (see
     * below).
     *
     * We allow both the head and tail fields to be null before any
     * nodes are enqueued; initializing upon first append.  This
     * simplifies some other logic, as well as providing more
     * efficient explicit control paths instead of letting JVMs insert
     * implicit NullPointerExceptions when they are null.  While not
     * currently fully implemented, we also leave open the possibility
     * of re-nulling these fields when empty (which is complicated to
     * arrange, for little benefit.)
     *
     * All enqueue/dequeue operations are handled by the single method
     * "xfer" with parameters indicating whether to act as some form
     * of offer, put, poll, take, or transfer (each possibly with
     * timeout). The relative complexity of using one monolithic
     * method outweighs the code bulk and maintenance problems of
     * using separate methods for each case.
     *
     * Operation consists of up to three phases. The first is
     * implemented within method xfer, the second in tryAppend, and
     * the third in method awaitMatch.
     *
     * 1. Try to match an existing node
     *
     *    Starting at head, skip already-matched nodes until finding
     *    an unmatched node of opposite mode, if one exists, in which
     *    case matching it and returning, also if necessary updating
     *    head to one past the matched node (or the node itself if the
     *    list has no other unmatched nodes). If the CAS misses, then
     *    a loop retries advancing head by two steps until either
     *    success or the slack is at most two. By requiring that each
     *    attempt advances head by two (if applicable), we ensure that
     *    the slack does not grow without bound. Traversals also check
     *    if the initial head is now off-list, in which case they
     *    start at the new head.
     *
     *    If no candidates are found and the call was untimed
     *    poll/offer, (argument "how" is NOW) return.
     *
     * 2. Try to append a new node (method tryAppend)
     *
     *    Starting at current tail pointer, find the actual last node
     *    and try to append a new node (or if head was null, establish
     *    the first node). Nodes can be appended only if their
     *    predecessors are either already matched or are of the same
     *    mode. If we detect otherwise, then a new node with opposite
     *    mode must have been appended during traversal, so we must
     *    restart at phase 1. The traversal and update steps are
     *    otherwise similar to phase 1: Retrying upon CAS misses and
     *    checking for staleness.  In particular, if a self-link is
     *    encountered, then we can safely jump to a node on the list
     *    by continuing the traversal at current head.
     *
     *    On successful append, if the call was ASYNC, return.
     *
     * 3. Await match or cancellation (method awaitMatch)
     *
     *    Wait for another thread to match node; instead cancelling if
     *    the current thread was interrupted or the wait timed out. On
     *    multiprocessors, we use front-of-queue spinning: If a node
     *    appears to be the first unmatched node in the queue, it
     *    spins a bit before blocking. In either case, before blocking
     *    it tries to unsplice any nodes between the current "head"
     *    and the first unmatched node.
     *
     *    Front-of-queue spinning vastly improves performance of
     *    heavily contended queues. And so long as it is relatively
     *    brief and "quiet", spinning does not much impact performance
     *    of less-contended queues.  During spins threads check their
     *    interrupt status and generate a thread-local random number
     *    to decide to occasionally perform a Thread.yield. While
     *    yield has underdefined specs, we assume that might it help,
     *    and will not hurt in limiting impact of spinning on busy
     *    systems.  We also use smaller (1/2) spins for nodes that are
     *    not known to be front but whose predecessors have not
     *    blocked -- these "chained" spins avoid artifacts of
     *    front-of-queue rules which otherwise lead to alternating
     *    nodes spinning vs blocking. Further, front threads that
     *    represent phase changes (from data to request node or vice
     *    versa) compared to their predecessors receive additional
     *    chained spins, reflecting longer paths typically required to
     *    unblock threads during phase changes.
     *
     *
     * ** Unlinking removed interior nodes **
     *
     * In addition to minimizing garbage retention via self-linking
     * described above, we also unlink removed interior nodes. These
     * may arise due to timed out or interrupted waits, or calls to
     * remove(x) or Iterator.remove.  Normally, given a node that was
     * at one time known to be the predecessor of some node s that is
     * to be removed, we can unsplice s by CASing the next field of
     * its predecessor if it still points to s (otherwise s must
     * already have been removed or is now offlist). But there are two
     * situations in which we cannot guarantee to make node s
     * unreachable in this way: (1) If s is the trailing node of list
     * (i.e., with null next), then it is pinned as the target node
     * for appends, so can only be removed later after other nodes are
     * appended. (2) We cannot necessarily unlink s given a
     * predecessor node that is matched (including the case of being
     * cancelled): the predecessor may already be unspliced, in which
     * case some previous reachable node may still point to s.
     * (For further explanation see Herlihy & Shavit "The Art of
     * Multiprocessor Programming" chapter 9).  Although, in both
     * cases, we can rule out the need for further action if either s
     * or its predecessor are (or can be made to be) at, or fall off
     * from, the head of list.
     *
     * Without taking these into account, it would be possible for an
     * unbounded number of supposedly removed nodes to remain
     * reachable.  Situations leading to such buildup are uncommon but
     * can occur in practice; for example when a series of short timed
     * calls to poll repeatedly time out but never otherwise fall off
     * the list because of an untimed call to take at the front of the
     * queue.
     *
     * When these cases arise, rather than always retraversing the
     * entire list to find an actual predecessor to unlink (which
     * won't help for case (1) anyway), we record a conservative
     * estimate of possible unsplice failures (in "sweepVotes").
     * We trigger a full sweep when the estimate exceeds a threshold
     * ("SWEEP_THRESHOLD") indicating the maximum number of estimated
     * removal failures to tolerate before sweeping through, unlinking
     * cancelled nodes that were not unlinked upon initial removal.
     * We perform sweeps by the thread hitting threshold (rather than
     * background threads or by spreading work to other threads)
     * because in the main contexts in which removal occurs, the
     * caller is already timed-out, cancelled, or performing a
     * potentially O(n) operation (e.g. remove(x)), none of which are
     * time-critical enough to warrant the overhead that alternatives
     * would impose on other threads.
     *
     * Because the sweepVotes estimate is conservative, and because
     * nodes become unlinked "naturally" as they fall off the head of
     * the queue, and because we allow votes to accumulate even while
     * sweeps are in progress, there are typically significantly fewer
     * such nodes than estimated.  Choice of a threshold value
     * balances the likelihood of wasted effort and contention, versus
     * providing a worst-case bound on retention of interior nodes in
     * quiescent queues. The value defined below was chosen
     * empirically to balance these under various timeout scenarios.
     *
     * Note that we cannot self-link unlinked interior nodes during
     * sweeps. However, the associated garbage chains terminate when
     * some successor ultimately falls off the head of the list and is
     * self-linked.
     */

    /** True if on multiprocessor */
    private static final boolean MP =
        Runtime.getRuntime().availableProcessors() > 1;

    /**
     * The number of times to spin (with randomly interspersed calls
     * to Thread.yield) on multiprocessor before blocking when a node
     * is apparently the first waiter in the queue.  See above for
     * explanation. Must be a power of two. The value is empirically
     * derived -- it works pretty well across a variety of processors,
     * numbers of CPUs, and OSes.
     */
    private static final int FRONT_SPINS   = 1 << 7;

    /**
     * The number of times to spin before blocking when a node is
     * preceded by another node that is apparently spinning.  Also
     * serves as an increment to FRONT_SPINS on phase changes, and as
     * base average frequency for yielding during spins. Must be a
     * power of two.
     */
    private static final int CHAINED_SPINS = FRONT_SPINS >>> 1;

    /**
     * The maximum number of estimated removal failures (sweepVotes)
     * to tolerate before sweeping through the queue unlinking
     * cancelled nodes that were not unlinked upon initial
     * removal. See above for explanation. The value must be at least
     * two to avoid useless sweeps when removing trailing nodes.
     */
    static final int SWEEP_THRESHOLD = 32;

    /**
     * Queue nodes. Uses Object, not E, for items to allow forgetting
     * them after use.  Relies heavily on Unsafe mechanics to minimize
     * unnecessary ordering constraints: Writes that are intrinsically
     * ordered wrt other accesses or CASes use simple relaxed forms.
     */
    static final class Node {
        final boolean isData;   // false if this is a request node
        volatile Object item;   // initially non-null if isData; CASed to match
        volatile Node next;
        volatile Thread waiter; // null until waiting

        // CAS methods for fields
        final boolean casNext(Node cmp, Node val) {
            return UNSAFE.compareAndSwapObject(this, nextOffset, cmp, val);
        }

        final boolean casItem(Object cmp, Object val) {
            // assert cmp == null || cmp.getClass() != Node.class;
            return UNSAFE.compareAndSwapObject(this, itemOffset, cmp, val);
        }

        /**
         * Constructs a new node.  Uses relaxed write because item can
         * only be seen after publication via casNext.
         */
        Node(Object item, boolean isData) {
            UNSAFE.putObject(this, itemOffset, item); // relaxed write
            this.isData = isData;
        }

        /**
         * Links node to itself to avoid garbage retention.  Called
         * only after CASing head field, so uses relaxed write.
         */
        final void forgetNext() {
            UNSAFE.putObject(this, nextOffset, this);
        }

        /**
         * Sets item to self and waiter to null, to avoid garbage
         * retention after matching or cancelling. Uses relaxed writes
         * because order is already constrained in the only calling
         * contexts: item is forgotten only after volatile/atomic
         * mechanics that extract items.  Similarly, clearing waiter
         * follows either CAS or return from park (if ever parked;
         * else we don't care).
         */
        final void forgetContents() {
            UNSAFE.putObject(this, itemOffset, this);
            UNSAFE.putObject(this, waiterOffset, null);
        }

        /**
         * Returns true if this node has been matched, including the
         * case of artificial matches due to cancellation.
         */
        final boolean isMatched() {
            Object x = item;
            return (x == this) || ((x == null) == isData);
        }

        /**
         * Returns true if this is an unmatched request node.
         */
        final boolean isUnmatchedRequest() {
            return !isData && item == null;
        }

        /**
         * Returns true if a node with the given mode cannot be
         * appended to this node because this node is unmatched and
         * has opposite data mode.
         */
        final boolean cannotPrecede(boolean haveData) {
            boolean d = isData;
            Object x;
            return d != haveData && (x = item) != this && (x != null) == d;
        }

        /**
         * Tries to artificially match a data node -- used by remove.
         */
        final boolean tryMatchData() {
            // assert isData;
            Object x = item;
            if (x != null && x != this && casItem(x, null)) {
                LockSupport.unpark(waiter);
                return true;
            }
            return false;
        }

        private static final long serialVersionUID = -3375979862319811754L;

        // Unsafe mechanics
        private static final sun.misc.Unsafe UNSAFE;
        private static final long itemOffset;
        private static final long nextOffset;
        private static final long waiterOffset;
        static {
            try {
                UNSAFE = sun.misc.Unsafe.getUnsafe();
                Class k = Node.class;
                itemOffset = UNSAFE.objectFieldOffset
                    (k.getDeclaredField("item"));
                nextOffset = UNSAFE.objectFieldOffset
                    (k.getDeclaredField("next"));
                waiterOffset = UNSAFE.objectFieldOffset
                    (k.getDeclaredField("waiter"));
            } catch (Exception e) {
                throw new Error(e);
            }
        }
    }

    /** head of the queue; null until first enqueue */
    transient volatile Node head;

    /** tail of the queue; null until first append */
    private transient volatile Node tail;

    /** The number of apparent failures to unsplice removed nodes */
    private transient volatile int sweepVotes;

    // CAS methods for fields
    private boolean casTail(Node cmp, Node val) {
        return UNSAFE.compareAndSwapObject(this, tailOffset, cmp, val);
    }

    private boolean casHead(Node cmp, Node val) {
        return UNSAFE.compareAndSwapObject(this, headOffset, cmp, val);
    }

    private boolean casSweepVotes(int cmp, int val) {
        return UNSAFE.compareAndSwapInt(this, sweepVotesOffset, cmp, val);
    }

    /*
     * Possible values for "how" argument in xfer method.
     */
    private static final int NOW   = 0; // for untimed poll, tryTransfer
    private static final int ASYNC = 1; // for offer, put, add
    private static final int SYNC  = 2; // for transfer, take
    private static final int TIMED = 3; // for timed poll, tryTransfer

    @SuppressWarnings("unchecked")
    static <E> E cast(Object item) {
        // assert item == null || item.getClass() != Node.class;
        return (E) item;
    }

    /**
     * Implements all queuing methods. See above for explanation.
     *
     * @param e the item or null for take
     * @param haveData true if this is a put, else a take
     * @param how NOW, ASYNC, SYNC, or TIMED
     * @param nanos timeout in nanosecs, used only if mode is TIMED
     * @return an item if matched, else e
     * @throws NullPointerException if haveData mode but e is null
     */
    private E xfer(E e, boolean haveData, int how, long nanos) {
        if (haveData && (e == null))
            throw new NullPointerException();
        Node s = null;                        // the node to append, if needed

        retry:
        for (;;) {                            // restart on append race

            for (Node h = head, p = h; p != null;) { // find & match first node
                boolean isData = p.isData;
                Object item = p.item;
                if (item != p && (item != null) == isData) { // unmatched
                    if (isData == haveData)   // can't match
                        break;
                    if (p.casItem(item, e)) { // match
                        for (Node q = p; q != h;) {
                            Node n = q.next;  // update by 2 unless singleton
                            if (head == h && casHead(h, n == null ? q : n)) {
                                h.forgetNext();
                                break;
                            }                 // advance and retry
                            if ((h = head)   == null ||
                                (q = h.next) == null || !q.isMatched())
                                break;        // unless slack < 2
                        }
                        LockSupport.unpark(p.waiter);
                        return this.<E>cast(item);
                    }
                }
                Node n = p.next;
                p = (p != n) ? n : (h = head); // Use head if p offlist
            }

            if (how != NOW) {                 // No matches available
                if (s == null)
                    s = new Node(e, haveData);
                Node pred = tryAppend(s, haveData);
                if (pred == null)
                    continue retry;           // lost race vs opposite mode
                if (how != ASYNC)
                    return awaitMatch(s, pred, e, (how == TIMED), nanos);
            }
            return e; // not waiting
        }
    }

    /**
     * Tries to append node s as tail.
     *
     * @param s the node to append
     * @param haveData true if appending in data mode
     * @return null on failure due to losing race with append in
     * different mode, else s's predecessor, or s itself if no
     * predecessor
     */
    private Node tryAppend(Node s, boolean haveData) {
        for (Node t = tail, p = t;;) {        // move p to last node and append
            Node n, u;                        // temps for reads of next & tail
            if (p == null && (p = head) == null) {
                if (casHead(null, s))
                    return s;                 // initialize
            }
            else if (p.cannotPrecede(haveData))
                return null;                  // lost race vs opposite mode
            else if ((n = p.next) != null)    // not last; keep traversing
                p = p != t && t != (u = tail) ? (t = u) : // stale tail
                    (p != n) ? n : null;      // restart if off list
            else if (!p.casNext(null, s))
                p = p.next;                   // re-read on CAS failure
            else {
                if (p != t) {                 // update if slack now >= 2
                    while ((tail != t || !casTail(t, s)) &&
                           (t = tail)   != null &&
                           (s = t.next) != null && // advance and retry
                           (s = s.next) != null && s != t);
                }
                return p;
            }
        }
    }

    /**
     * Spins/yields/blocks until node s is matched or caller gives up.
     *
     * @param s the waiting node
     * @param pred the predecessor of s, or s itself if it has no
     * predecessor, or null if unknown (the null case does not occur
     * in any current calls but may in possible future extensions)
     * @param e the comparison value for checking match
     * @param timed if true, wait only until timeout elapses
     * @param nanos timeout in nanosecs, used only if timed is true
     * @return matched item, or e if unmatched on interrupt or timeout
     */
    private E awaitMatch(Node s, Node pred, E e, boolean timed, long nanos) {
        long lastTime = timed ? System.nanoTime() : 0L;
        Thread w = Thread.currentThread();
        int spins = -1; // initialized after first item and cancel checks
        ThreadLocalRandom randomYields = null; // bound if needed

        for (;;) {
            Object item = s.item;
            if (item != e) {                  // matched
                // assert item != s;
                s.forgetContents();           // avoid garbage
                return this.<E>cast(item);
            }
            if ((w.isInterrupted() || (timed && nanos <= 0)) &&
                    s.casItem(e, s)) {        // cancel
                unsplice(pred, s);
                return e;
            }

            if (spins < 0) {                  // establish spins at/near front
                if ((spins = spinsFor(pred, s.isData)) > 0)
                    randomYields = ThreadLocalRandom.current();
            }
            else if (spins > 0) {             // spin
                --spins;
                if (randomYields.nextInt(CHAINED_SPINS) == 0)
                    Thread.yield();           // occasionally yield
            }
            else if (s.waiter == null) {
                s.waiter = w;                 // request unpark then recheck
            }
            else if (timed) {
                long now = System.nanoTime();
                if ((nanos -= now - lastTime) > 0)
                    LockSupport.parkNanos(this, nanos);
                lastTime = now;
            }
            else {
                LockSupport.park(this);
            }
        }
    }

    /**
     * Returns spin/yield value for a node with given predecessor and
     * data mode. See above for explanation.
     */
    private static int spinsFor(Node pred, boolean haveData) {
        if (MP && pred != null) {
            if (pred.isData != haveData)      // phase change
                return FRONT_SPINS + CHAINED_SPINS;
            if (pred.isMatched())             // probably at front
                return FRONT_SPINS;
            if (pred.waiter == null)          // pred apparently spinning
                return CHAINED_SPINS;
        }
        return 0;
    }

    /* -------------- Traversal methods -------------- */

    /**
     * Returns the successor of p, or the head node if p.next has been
     * linked to self, which will only be true if traversing with a
     * stale pointer that is now off the list.
     */
    final Node succ(Node p) {
        Node next = p.next;
        return (p == next) ? head : next;
    }

    /**
     * Returns the first unmatched node of the given mode, or null if
     * none.  Used by methods isEmpty, hasWaitingConsumer.
     */
    private Node firstOfMode(boolean isData) {
        for (Node p = head; p != null; p = succ(p)) {
            if (!p.isMatched())
                return (p.isData == isData) ? p : null;
        }
        return null;
    }

    /**
     * Returns the item in the first unmatched node with isData; or
     * null if none.  Used by peek.
     */
    private E firstDataItem() {
        for (Node p = head; p != null; p = succ(p)) {
            Object item = p.item;
            if (p.isData) {
                if (item != null && item != p)
                    return this.<E>cast(item);
            }
            else if (item == null)
                return null;
        }
        return null;
    }

    /**
     * Traverses and counts unmatched nodes of the given mode.
     * Used by methods size and getWaitingConsumerCount.
     */
    private int countOfMode(boolean data) {
        int count = 0;
        for (Node p = head; p != null; ) {
            if (!p.isMatched()) {
                if (p.isData != data)
                    return 0;
                if (++count == Integer.MAX_VALUE) // saturated
                    break;
            }
            Node n = p.next;
            if (n != p)
                p = n;
            else {
                count = 0;
                p = head;
            }
        }
        return count;
    }

    final class Itr implements Iterator<E> {
        private Node nextNode;   // next node to return item for
        private E nextItem;      // the corresponding item
        private Node lastRet;    // last returned node, to support remove
        private Node lastPred;   // predecessor to unlink lastRet

        /**
         * Moves to next node after prev, or first node if prev null.
         */
        private void advance(Node prev) {
            /*
             * To track and avoid buildup of deleted nodes in the face
             * of calls to both Queue.remove and Itr.remove, we must
             * include variants of unsplice and sweep upon each
             * advance: Upon Itr.remove, we may need to catch up links
             * from lastPred, and upon other removes, we might need to
             * skip ahead from stale nodes and unsplice deleted ones
             * found while advancing.
             */

            Node r, b; // reset lastPred upon possible deletion of lastRet
            if ((r = lastRet) != null && !r.isMatched())
                lastPred = r;    // next lastPred is old lastRet
            else if ((b = lastPred) == null || b.isMatched())
                lastPred = null; // at start of list
            else {
                Node s, n;       // help with removal of lastPred.next
                while ((s = b.next) != null &&
                       s != b && s.isMatched() &&
                       (n = s.next) != null && n != s)
                    b.casNext(s, n);
            }

            this.lastRet = prev;

            for (Node p = prev, s, n;;) {
                s = (p == null) ? head : p.next;
                if (s == null)
                    break;
                else if (s == p) {
                    p = null;
                    continue;
                }
                Object item = s.item;
                if (s.isData) {
                    if (item != null && item != s) {
                        nextItem = LinkedTransferQueue.<E>cast(item);
                        nextNode = s;
                        return;
                    }
                }
                else if (item == null)
                    break;
                // assert s.isMatched();
                if (p == null)
                    p = s;
                else if ((n = s.next) == null)
                    break;
                else if (s == n)
                    p = null;
                else
                    p.casNext(s, n);
            }
            nextNode = null;
            nextItem = null;
        }

        Itr() {
            advance(null);
        }

        public final boolean hasNext() {
            return nextNode != null;
        }

        public final E next() {
            Node p = nextNode;
            if (p == null) throw new NoSuchElementException();
            E e = nextItem;
            advance(p);
            return e;
        }

        public final void remove() {
            final Node lastRet = this.lastRet;
            if (lastRet == null)
                throw new IllegalStateException();
            this.lastRet = null;
            if (lastRet.tryMatchData())
                unsplice(lastPred, lastRet);
        }
    }

    /* -------------- Removal methods -------------- */

    /**
     * Unsplices (now or later) the given deleted/cancelled node with
     * the given predecessor.
     *
     * @param pred a node that was at one time known to be the
     * predecessor of s, or null or s itself if s is/was at head
     * @param s the node to be unspliced
     */
    final void unsplice(Node pred, Node s) {
        s.forgetContents(); // forget unneeded fields
        /*
         * See above for rationale. Briefly: if pred still points to
         * s, try to unlink s.  If s cannot be unlinked, because it is
         * trailing node or pred might be unlinked, and neither pred
         * nor s are head or offlist, add to sweepVotes, and if enough
         * votes have accumulated, sweep.
         */
        if (pred != null && pred != s && pred.next == s) {
            Node n = s.next;
            if (n == null ||
                (n != s && pred.casNext(s, n) && pred.isMatched())) {
                for (;;) {               // check if at, or could be, head
                    Node h = head;
                    if (h == pred || h == s || h == null)
                        return;          // at head or list empty
                    if (!h.isMatched())
                        break;
                    Node hn = h.next;
                    if (hn == null)
                        return;          // now empty
                    if (hn != h && casHead(h, hn))
                        h.forgetNext();  // advance head
                }
                if (pred.next != pred && s.next != s) { // recheck if offlist
                    for (;;) {           // sweep now if enough votes
                        int v = sweepVotes;
                        if (v < SWEEP_THRESHOLD) {
                            if (casSweepVotes(v, v + 1))
                                break;
                        }
                        else if (casSweepVotes(v, 0)) {
                            sweep();
                            break;
                        }
                    }
                }
            }
        }
    }

    /**
     * Unlinks matched (typically cancelled) nodes encountered in a
     * traversal from head.
     */
    private void sweep() {
        for (Node p = head, s, n; p != null && (s = p.next) != null; ) {
            if (!s.isMatched())
                // Unmatched nodes are never self-linked
                p = s;
            else if ((n = s.next) == null) // trailing node is pinned
                break;
            else if (s == n)    // stale
                // No need to also check for p == s, since that implies s == n
                p = head;
            else
                p.casNext(s, n);
        }
    }

    /**
     * Main implementation of remove(Object)
     */
    private boolean findAndRemove(Object e) {
        if (e != null) {
            for (Node pred = null, p = head; p != null; ) {
                Object item = p.item;
                if (p.isData) {
                    if (item != null && item != p && e.equals(item) &&
                        p.tryMatchData()) {
                        unsplice(pred, p);
                        return true;
                    }
                }
                else if (item == null)
                    break;
                pred = p;
                if ((p = p.next) == pred) { // stale
                    pred = null;
                    p = head;
                }
            }
        }
        return false;
    }

    /**
     * Creates an initially empty {@code LinkedTransferQueue}.
     */
    public LinkedTransferQueue() {
    }

    /**
     * Creates a {@code LinkedTransferQueue}
     * initially containing the elements of the given collection,
     * added in traversal order of the collection's iterator.
     *
     * @param c the collection of elements to initially contain
     * @throws NullPointerException if the specified collection or any
     *         of its elements are null
     */
    public LinkedTransferQueue(Collection<? extends E> c) {
        this();
        addAll(c);
    }

    /**
     * Inserts the specified element at the tail of this queue.
     * As the queue is unbounded, this method will never block.
     *
     * @throws NullPointerException if the specified element is null
     */
    public void put(E e) {
        xfer(e, true, ASYNC, 0);
    }

    /**
     * Inserts the specified element at the tail of this queue.
     * As the queue is unbounded, this method will never block or
     * return {@code false}.
     *
     * @return {@code true} (as specified by
     *  {@link BlockingQueue#offer(Object,long,TimeUnit) BlockingQueue.offer})
     * @throws NullPointerException if the specified element is null
     */
    public boolean offer(E e, long timeout, TimeUnit unit) {
        xfer(e, true, ASYNC, 0);
        return true;
    }

    /**
     * Inserts the specified element at the tail of this queue.
     * As the queue is unbounded, this method will never return {@code false}.
     *
     * @return {@code true} (as specified by {@link Queue#offer})
     * @throws NullPointerException if the specified element is null
     */
    public boolean offer(E e) {
        xfer(e, true, ASYNC, 0);
        return true;
    }

    /**
     * Inserts the specified element at the tail of this queue.
     * As the queue is unbounded, this method will never throw
     * {@link IllegalStateException} or return {@code false}.
     *
     * @return {@code true} (as specified by {@link Collection#add})
     * @throws NullPointerException if the specified element is null
     */
    public boolean add(E e) {
        xfer(e, true, ASYNC, 0);
        return true;
    }

    /**
     * Transfers the element to a waiting consumer immediately, if possible.
     *
     *
More precisely, transfers the specified element immediately
     * if there exists a consumer already waiting to receive it (in
     * {@link #take} or timed {@link #poll(long,TimeUnit) poll}),
     * otherwise returning {@code false} without enqueuing the element.
     *
     * @throws NullPointerException if the specified element is null
     */
    public boolean tryTransfer(E e) {
        return xfer(e, true, NOW, 0) == null;
    }

    /**
     * Transfers the element to a consumer, waiting if necessary to do so.
     *
     *
More precisely, transfers the specified element immediately
     * if there exists a consumer already waiting to receive it (in
     * {@link #take} or timed {@link #poll(long,TimeUnit) poll}),
     * else inserts the specified element at the tail of this queue
     * and waits until the element is received by a consumer.
     *
     * @throws NullPointerException if the specified element is null
     */
    public void transfer(E e) throws InterruptedException {
        if (xfer(e, true, SYNC, 0) != null) {
            Thread.interrupted(); // failure possible only due to interrupt
            throw new InterruptedException();
        }
    }

    /**
     * Transfers the element to a consumer if it is possible to do so
     * before the timeout elapses.
     *
     *
More precisely, transfers the specified element immediately
     * if there exists a consumer already waiting to receive it (in
     * {@link #take} or timed {@link #poll(long,TimeUnit) poll}),
     * else inserts the specified element at the tail of this queue
     * and waits until the element is received by a consumer,
     * returning {@code false} if the specified wait time elapses
     * before the element can be transferred.
     *
     * @throws NullPointerException if the specified element is null
     */
    public boolean tryTransfer(E e, long timeout, TimeUnit unit)
        throws InterruptedException {
        if (xfer(e, true, TIMED, unit.toNanos(timeout)) == null)
            return true;
        if (!Thread.interrupted())
            return false;
        throw new InterruptedException();
    }

    public E take() throws InterruptedException {
        E e = xfer(null, false, SYNC, 0);
        if (e != null)
            return e;
        Thread.interrupted();
        throw new InterruptedException();
    }

    public E poll(long timeout, TimeUnit unit) throws InterruptedException {
        E e = xfer(null, false, TIMED, unit.toNanos(timeout));
        if (e != null || !Thread.interrupted())
            return e;
        throw new InterruptedException();
    }

    public E poll() {
        return xfer(null, false, NOW, 0);
    }

    /**
     * @throws NullPointerException     {@inheritDoc}
     * @throws IllegalArgumentException {@inheritDoc}
     */
    public int drainTo(Collection<? super E> c) {
        if (c == null)
            throw new NullPointerException();
        if (c == this)
            throw new IllegalArgumentException();
        int n = 0;
        E e;
        while ( (e = poll()) != null) {
            c.add(e);
            ++n;
        }
        return n;
    }

    /**
     * @throws NullPointerException     {@inheritDoc}
     * @throws IllegalArgumentException {@inheritDoc}
     */
    public int drainTo(Collection<? super E> c, int maxElements) {
        if (c == null)
            throw new NullPointerException();
        if (c == this)
            throw new IllegalArgumentException();
        int n = 0;
        E e;
        while (n < maxElements && (e = poll()) != null) {
            c.add(e);
            ++n;
        }
        return n;
    }

    /**
     * Returns an iterator over the elements in this queue in proper sequence.
     * The elements will be returned in order from first (head) to last (tail).
     *
     *
The returned iterator is a "weakly consistent" iterator that
     * will never throw {@link java.util.ConcurrentModificationException
     * ConcurrentModificationException}, and guarantees to traverse
     * elements as they existed upon construction of the iterator, and
     * may (but is not guaranteed to) reflect any modifications
     * subsequent to construction.
     *
     * @return an iterator over the elements in this queue in proper sequence
     */
    public Iterator<E> iterator() {
        return new Itr();
    }

    public E peek() {
        return firstDataItem();
    }

    /**
     * Returns {@code true} if this queue contains no elements.
     *
     * @return {@code true} if this queue contains no elements
     */
    public boolean isEmpty() {
        for (Node p = head; p != null; p = succ(p)) {
            if (!p.isMatched())
                return !p.isData;
        }
        return true;
    }

    public boolean hasWaitingConsumer() {
        return firstOfMode(false) != null;
    }

    /**
     * Returns the number of elements in this queue.  If this queue
     * contains more than {@code Integer.MAX_VALUE} elements, returns
     * {@code Integer.MAX_VALUE}.
     *
     *
Beware that, unlike in most collections, this method is
     * NOT a constant-time operation. Because of the
     * asynchronous nature of these queues, determining the current
     * number of elements requires an O(n) traversal.
     *
     * @return the number of elements in this queue
     */
    public int size() {
        return countOfMode(true);
    }

    public int getWaitingConsumerCount() {
        return countOfMode(false);
    }

    /**
     * Removes a single instance of the specified element from this queue,
     * if it is present.  More formally, removes an element {@code e} such
     * that {@code o.equals(e)}, if this queue contains one or more such
     * elements.
     * Returns {@code true} if this queue contained the specified element
     * (or equivalently, if this queue changed as a result of the call).
     *
     * @param o element to be removed from this queue, if present
     * @return {@code true} if this queue changed as a result of the call
     */
    public boolean remove(Object o) {
        return findAndRemove(o);
    }

    /**
     * Returns {@code true} if this queue contains the specified element.
     * More formally, returns {@code true} if and only if this queue contains
     * at least one element {@code e} such that {@code o.equals(e)}.
     *
     * @param o object to be checked for containment in this queue
     * @return {@code true} if this queue contains the specified element
     */
    public boolean contains(Object o) {
        if (o == null) return false;
        for (Node p = head; p != null; p = succ(p)) {
            Object item = p.item;
            if (p.isData) {
                if (item != null && item != p && o.equals(item))
                    return true;
            }
            else if (item == null)
                break;
        }
        return false;
    }

    /**
     * Always returns {@code Integer.MAX_VALUE} because a
     * {@code LinkedTransferQueue} is not capacity constrained.
     *
     * @return {@code Integer.MAX_VALUE} (as specified by
     *         {@link BlockingQueue#remainingCapacity()})
     */
    public int remainingCapacity() {
        return Integer.MAX_VALUE;
    }

    /**
     * Saves the state to a stream (that is, serializes it).
     *
     * @serialData All of the elements (each an {@code E}) in
     * the proper order, followed by a null
     * @param s the stream
     */
    private void writeObject(java.io.ObjectOutputStream s)
        throws java.io.IOException {
        s.defaultWriteObject();
        for (E e : this)
            s.writeObject(e);
        // Use trailing null as sentinel
        s.writeObject(null);
    }

    /**
     * Reconstitutes the Queue instance from a stream (that is,
     * deserializes it).
     *
     * @param s the stream
     */
    private void readObject(java.io.ObjectInputStream s)
        throws java.io.IOException, ClassNotFoundException {
        s.defaultReadObject();
        for (;;) {
            @SuppressWarnings("unchecked") E item = (E) s.readObject();
            if (item == null)
                break;
            else
                offer(item);
        }
    }

    // Unsafe mechanics

    private static final sun.misc.Unsafe UNSAFE;
    private static final long headOffset;
    private static final long tailOffset;
    private static final long sweepVotesOffset;
    static {
        try {
            UNSAFE = sun.misc.Unsafe.getUnsafe();
            Class k = LinkedTransferQueue.class;
            headOffset = UNSAFE.objectFieldOffset
                (k.getDeclaredField("head"));
            tailOffset = UNSAFE.objectFieldOffset
                (k.getDeclaredField("tail"));
            sweepVotesOffset = UNSAFE.objectFieldOffset
                (k.getDeclaredField("sweepVotes"));
        } catch (Exception e) {
            throw new Error(e);
        }
    }
}


text:
"""API renderers for accessing hunts."""

import operator

from grr.gui import api_object_renderers
from grr.gui import api_renderers

from grr.lib import aff4
from grr.lib import hunts
from grr.lib import rdfvalue

HUNTS_ROOT_PATH = rdfvalue.RDFURN("aff4:/hunts")

class ApiHuntsListRenderer(api_renderers.ApiRenderer):

  method = "GET"
  route = "/api/hunts"

  def Render(self, request):
    offset = int(request.get("offset", 0))
    count = int(request.get("count", 10000))

    fd = aff4.FACTORY.Open("aff4:/hunts", mode="r", token=request.token)

    children = list(fd.ListChildren())
    children.sort(key=operator.attrgetter("age"), reverse=True)
    children = children[offset:offset + count]

    hunt_list = []
    for hunt in fd.OpenChildren(children=children):
      if not isinstance(hunt, hunts.GRRHunt) or not hunt.state:
        continue

      hunt.create_time = hunt.GetRunner().context.create_time
      hunt_list.append(hunt)

    hunt_list.sort(key=lambda x: x.create_time, reverse=True)

    encoded_hunt_list = []
    for hunt in hunt_list:
      encoded_hunt = api_object_renderers.RenderObject(
          hunt, {"no_lists": True})
      encoded_hunt["create_time"] = api_object_renderers.RenderObject(
          hunt.create_time)
      encoded_hunt["description"] = hunt.state.context.args.description
      encoded_hunt_list.append(encoded_hunt)

    return encoded_hunt_list

class ApiHuntSummaryRenderer(api_renderers.ApiRenderer):
  """Renders hunt's summary."""

  method = "GET"
  route = "/api/hunts/<hunt_id>"

  def Render(self, request):
    hunt = aff4.FACTORY.Open(
        HUNTS_ROOT_PATH.Add(request.route_args["hunt_id"]),
        aff4_type="GRRHunt",
        token=request.token)
    return api_object_renderers.RenderObject(hunt, {})

class ApiHuntLogRenderer(api_renderers.ApiRenderer):
  """Renders hunt's log."""

  method = "GET"
  route = "/api/hunts/<hunt_id>/log"

  def Render(self, request):
    logs_collection = aff4.FACTORY.Create(
        HUNTS_ROOT_PATH.Add(request.route_args["hunt_id"]).Add("log"),
        aff4_type="RDFValueCollection", mode="r", token=request.token)
    return api_object_renderers.RenderObject(logs_collection, {})

class ApiHuntErrorsRenderer(api_renderers.ApiRenderer):
  """Renders hunt's errors."""

  method = "GET"
  route = "/api/hunts/<hunt_id>/errors"

  def Render(self, request):
    errors_collection = aff4.FACTORY.Create(
        HUNTS_ROOT_PATH.Add(request.route_args["hunt_id"]).Add("errors"),
        aff4_type="RDFValueCollection", mode="r", token=request.token)
    return api_object_renderers.RenderObject(errors_collection, {})

redpajama_set_name: RedPajamaGithub


text:
<?php

use yii\widgets\DetailView;
use app\models\Area;
use app\models\Category;

/* @var $this yii\web\View */
/* @var $model app\models\Category */
?>
<div class="category-view">

    <?= DetailView::widget([
        'model' => $model,
        'attributes' => [
            'id',
            [
                'label' => 'Father Category',
                'value' => isset($model->category) ? $model->category->name : "",
            ],
            [
                'label' => 'Area',
                'value' => $model->idArea->name,
            ],
            'name',
            'description',
            'service_level_agreement_asignment',
            'service_level_agreement_completion',
        ],
    ]) ?>

</div>


text:
<?php

// autoload_namespaces.php @generated by Composer

$vendorDir = dirname(dirname(__FILE__));
$baseDir = dirname($vendorDir);

return array(
    'phpDocumentor' => array($vendorDir . '/phpdocumentor/reflection-docblock/src'),
    'Psr\\Log\\' => array($vendorDir . '/psr/log'),
    'Prophecy\\' => array($vendorDir . '/phpspec/prophecy/src'),
    'JakubOnderka\\PhpConsoleHighlighter' => array($vendorDir . '/jakub-onderka/php-console-highlighter/src'),
    'JakubOnderka\\PhpConsoleColor' => array($vendorDir . '/jakub-onderka/php-console-color/src'),
    'Dotenv' => array($vendorDir . '/vlucas/phpdotenv/src'),
    'Doctrine\\Common\\Inflector\\' => array($vendorDir . '/doctrine/inflector/lib'),
    'Cron' => array($vendorDir . '/mtdowling/cron-expression/src'),
);


text:
#include "tensorflow/compiler/xla/service/hlo_memory_scheduler.h"

#include <algorithm>
#include <limits>
#include <map>
#include <queue>
#include <utility>
#include <vector>

#include "absl/container/flat_hash_map.h"
#include "absl/container/flat_hash_set.h"
#include "tensorflow/compiler/xla/service/dfs_hlo_visitor_with_default.h"
#include "tensorflow/compiler/xla/service/heap_simulator.h"
#include "tensorflow/compiler/xla/service/hlo_computation.h"
#include "tensorflow/compiler/xla/service/hlo_opcode.h"
#include "tensorflow/compiler/xla/service/hlo_schedule.h"
#include "tensorflow/compiler/xla/service/tuple_points_to_analysis.h"
#include "tensorflow/compiler/xla/shape_util.h"
#include "tensorflow/compiler/xla/status_macros.h"
#include "tensorflow/compiler/xla/statusor.h"
#include "tensorflow/compiler/xla/types.h"
#include "tensorflow/compiler/xla/util.h"
#include "tensorflow/core/lib/core/errors.h"
#include "tensorflow/core/lib/gtl/map_util.h"
#include "tensorflow/core/platform/logging.h"

namespace xla {
namespace {

using ::tensorflow::strings::HumanReadableNumBytes;

// Class implementing a list scheduler of HLO instructions which produces a
// sequence which minimizes memory usage by preferring to schedule the node that
// frees bigger buffer and defines smaller outputs.
//
// Note that list scheduler is a greedy algorithm which cannot guarantee a
// global optimal solution. As a counterexample, considering the following
// graph:
//
//      +--> B ===> C -------+
// A -> |                    |
//      |                    v
//      +--> D ---> F=======>G
//      |           ^
//      |           |
//      +--> E -----+
//
//  --> : Buffer with size 1
//  ==> : Buffer with size 2
//
// The list scheduler will always try to defer scheduling B in a greedy way
// since its output buffer is bigger than input. The sequence it creates will
// be:
//   A D E F B C G
// , which has a maximum memory usage of 6 (B is alive while F is executing).
//
// An optimal way to schedule the previous graph is:
//   A B C D E F G
// , which has a maximum memory usage of 5 (when F is executing).
//
class ListScheduler {
 public:
  // Construct and return a memory-minimizing sequence of HLO instructions
  // containing the given HLO computation.
  static StatusOr<HloInstructionSequence> Run(
      HloComputation* computation,
      const TuplePointsToAnalysis& points_to_analysis,
      const BufferValue::SizeFunction& size_function,
      const absl::flat_hash_map<const HloComputation*, int64_t>&
          memory_by_computation) {
    ListScheduler scheduler(computation, points_to_analysis, size_function,
                            memory_by_computation);
    return scheduler.CreateSchedule();
  }

  // Returns whether the memory used by the given HLO should be ignored by the
  // scheduling heuristic.
  static bool IgnoreInstruction(const HloInstruction& instruction) {
    return instruction.opcode() == HloOpcode::kParameter ||
           instruction.opcode() == HloOpcode::kConstant;
  }

 private:
  // The scheduling priority of an instruction is first the number of bytes
  // freed by scheduling the instruction, and second (tie-breaker) by the number
  // of users. This is represented as a std::pair containing these two values
  // (first element is the bytes freed). std::pair provides the necessary
  // comparison operators.
  using Priority = std::pair<int64_t, int64_t>;

  ListScheduler(HloComputation* computation,
                const TuplePointsToAnalysis& points_to_analysis,
                const BufferValue::SizeFunction& size_function,
                const absl::flat_hash_map<const HloComputation*, int64_t>&
                    memory_by_computation)
      : computation_(computation),
        points_to_analysis_(points_to_analysis),
        size_function_(size_function),
        memory_by_computation_(memory_by_computation) {
    // Create a map containing the LogicalBuffer uses for each HLO
    // instruction. An HLO instruction "uses" a LogicalBuffer if the
    // LogicalBuffer is in an operand of the instruction as indicated by
    // points-to analysis.
    for (auto* instruction : computation->instructions()) {
      absl::flat_hash_set<const LogicalBuffer*> instr_uses;
      for (auto* operand : instruction->operands()) {
        points_to_analysis.GetPointsToSet(operand).ForEachElement(
            [&](const ShapeIndex& /*index*/,
                const PointsToSet::BufferList& buffers) {
              instr_uses.insert(buffers.begin(), buffers.end());
            });
      }
      buffer_uses_[instruction] = std::vector<const LogicalBuffer*>(
          instr_uses.begin(), instr_uses.end());
    }

    // Create map containing the number of unscheduled uses (hlo instructions)
    // of each logical buffer.
    unscheduled_use_count_.reserve(points_to_analysis.num_logical_buffers());
    for (auto* instruction : computation->instructions()) {
      for (auto* buffer :
           points_to_analysis.GetBuffersDefinedByInstruction(instruction)) {
        unscheduled_use_count_[buffer] = 0;
      }
    }
    for (auto* instruction : computation->instructions()) {
      for (const LogicalBuffer* buffer : buffer_uses_.at(instruction)) {
        ++unscheduled_use_count_[buffer];
      }
    }

    // Buffers live out of the computation have an implicit use at the end of
    // the computation.
    for (const LogicalBuffer* live_out_buffer :
         points_to_analysis.GetPointsToSet(computation->root_instruction())
             .CreateFlattenedSet()) {
      ++unscheduled_use_count_[live_out_buffer];
    }
  }

  // Returns whether the memory used by the given buffer should be ignored by
  // the scheduling heuristic.
  static bool IgnoreBuffer(const LogicalBuffer& buffer) {
    return IgnoreInstruction(*buffer.instruction());
  }

  // An entry in the worklist used by CreateSchedule.  Corresponds to one
  // HloInstruction, plus some cached metadata, saved for the purposes of making
  // BytesFreedIfScheduled fast.
  struct ReadyListEntry {
    HloInstruction* instruction;

    // The total size of all buffers defined by this instruction.
    int64_t bytes_defined;

    // For each buffer B used by this instruction, we keep a pair (B, U), where
    // U is the number of uses of B that have not yet been scheduled. This pair
    // is a pointer into the unscheduled_use_count_ map, so it gets updated for
    // free when we update counts in the map.
    std::vector<const std::pair<const LogicalBuffer* const, int64_t>*>
        used_buffer_unscheduled_use_counts;
  };

  // Creates a ReadyListEntry for the given instruction.
  ReadyListEntry MakeReadyListEntry(HloInstruction* instruction) {
    ReadyListEntry entry;
    entry.instruction = instruction;

    entry.bytes_defined = 0;
    for (auto* buffer :
         points_to_analysis_.GetBuffersDefinedByInstruction(instruction)) {
      if (!IgnoreBuffer(*buffer)) {
        entry.bytes_defined += size_function_(*buffer);
      }
    }

    for (auto* buffer : buffer_uses_.at(instruction)) {
      if (IgnoreBuffer(*buffer)) {
        continue;
      }
      auto unscheduled_use_count_it = unscheduled_use_count_.find(buffer);
      CHECK(unscheduled_use_count_it != unscheduled_use_count_.end());
      entry.used_buffer_unscheduled_use_counts.push_back(
          &*unscheduled_use_count_it);
    }
    return entry;
  }

  // Returns the number of bytes freed *after* the HLO instruction finishes.
  // The current List algorithm only considers two states for an instruction:
  // right before it runs, and after it finishes. We don't represent memory
  // usage during the execution of an instruction. But if the instruction calls
  // subcomputations, they are only live during the instruction's execution.
  // We end up counting the memory used by subcomputations as memory "defined"
  // by the instruction. This is not entirely accurate, but it is more accurate
  // than not taking subcomputations into account at all. In the future, we may
  // improve accounting for subcomputation memory (b/65409243).
  int64_t BytesFreedIfScheduled(const ReadyListEntry& entry) {
    auto instruction = entry.instruction;
    auto opcode = instruction->opcode();

    // Scheduling the outfeed early and the infeed late gives more time to the
    // communicating processor to do its work.
    if (opcode == HloOpcode::kOutfeed &&
        !instruction->outfeed_config().empty()) {
      return INT_MAX;
    }
    if (opcode == HloOpcode::kInfeed && !instruction->infeed_config().empty()) {
      return INT_MIN;
    }

    int64_t freed_bytes = 0;
    for (const auto& kv : entry.used_buffer_unscheduled_use_counts) {
      auto buffer = kv->first;
      auto use_count = kv->second;
      if (use_count == 1) {
        freed_bytes += size_function_(*buffer);
      }
    }
    // We only count the memory usage of the largest subcomputation, instead of
    // adding them all, because subcomputations won't execute in parallel.
    int64_t max_subcomputation_bytes = 0;
    for (const auto* c : instruction->called_computations()) {
      auto it = memory_by_computation_.find(c);
      if (it != memory_by_computation_.end()) {
        int64_t subcomputation_bytes = it->second;
        if (subcomputation_bytes > max_subcomputation_bytes) {
          max_subcomputation_bytes = subcomputation_bytes;
        }
      }
    }
    int64_t bytes_defined;
    if (max_subcomputation_bytes > 0 &&
        (opcode == HloOpcode::kWhile || opcode == HloOpcode::kCall ||
         opcode == HloOpcode::kConditional)) {
      // The output buffer of while/call/conditional is always aliased with the
      // output buffer of the root instruction in the body. Don't double count.
      bytes_defined = max_subcomputation_bytes;
    } else {
      bytes_defined = entry.bytes_defined + max_subcomputation_bytes;
    }
    return freed_bytes - bytes_defined;
  }

  // Constructs the scheduling priority of the given instruction.
  Priority GetPriority(const ReadyListEntry& entry) {
    // Try to cluster scalars as close together as possible so that if they are
    // in unfused hlos, they can still live in machine registers without
    // excessive spilling.
    if (ShapeUtil::IsEffectiveScalar(entry.instruction->shape())) {
      return {std::numeric_limits<int64_t>::max(),
              std::numeric_limits<int64_t>::max()};
    }
    return {BytesFreedIfScheduled(entry), entry.instruction->user_count()};
  }

  HloInstructionSequence CreateSchedule() {
    HloInstructionSequence schedule;

    // Populate the ready list with instructions which have no operands or
    // control predecessors.
    absl::flat_hash_map<const HloInstruction*, int64_t> unscheduled_pred_count;
    for (auto* instruction : computation_->instructions()) {
      // TODO(b/34466113): Replace this and above with successors() or
      // predecessors() when these methods are added to HloInstruction.
      for (HloInstruction* user : instruction->users()) {
        unscheduled_pred_count[user]++;
      }
      for (HloInstruction* succ : instruction->control_successors()) {
        unscheduled_pred_count[succ]++;
      }
    }

    // Use a multimap to sort ReadyListEntry according to their priority.
    std::multimap<Priority, ReadyListEntry> ready_queue;

    // Map of ready instructions to their iterators in ready_queue.
    absl::flat_hash_map<const HloInstruction*,
                        std::multimap<Priority, ReadyListEntry>::iterator>
        ready_instructions;

    auto add_to_ready_queue = [&](HloInstruction* inst) {
      auto entry = MakeReadyListEntry(inst);
      auto it = ready_queue.emplace(GetPriority(entry), std::move(entry));
      ready_instructions[inst] = it;
    };

    for (auto* instruction : computation_->instructions()) {
      if (instruction->operands().empty() &&
          instruction->control_predecessors().empty()) {
        add_to_ready_queue(instruction);
      }
    }

    while (!ready_queue.empty()) {
      // Remove the selected instruction from the ready list and add it to the
      // schedule.
      auto best_it = ready_queue.end();
      --best_it;
      HloInstruction* best = best_it->second.instruction;
      VLOG(2) << "Schedule instruction: " << best->ToShortString()
              << " Bytes freed: " << best_it->first.first;
      ready_queue.erase(best_it);
      ready_instructions.erase(best);
      schedule.push_back(best);
      scheduled_instructions_.insert(best);

      bool adjust_ready_queue = false;
      // Update the unscheduled uses of the logical buffers.
      for (const LogicalBuffer* buffer : buffer_uses_.at(best)) {
        int64_t& count = unscheduled_use_count_[buffer];
        CHECK_GT(count, 0);
        --count;
        if (count == 1) {
          adjust_ready_queue = true;
        }
      }

      // Add new instructions to ready list.
      auto update_pred_count = [&](HloInstruction* inst) {
        int64_t pred_count = --unscheduled_pred_count.at(inst);
        CHECK_GE(pred_count, 0);
        if (pred_count == 0) {
          add_to_ready_queue(inst);
        }
      };
      // TODO(b/34466113): Replace this and above with successors() or
      // predecessors() when these methods are added to HloInstruction.
      for (HloInstruction* user : best->users()) {
        update_pred_count(user);
      }
      for (HloInstruction* succ : best->control_successors()) {
        update_pred_count(succ);
      }
      // The unscheduled use count for a buffer has changed to 1, so the
      // priorities of some ready instructions may go up. We update them in the
      // ready queue, so that they can appear earlier.
      if (adjust_ready_queue) {
        for (HloInstruction* operand : best->operands()) {
          for (HloInstruction* operand_user : operand->users()) {
            auto ready_instructions_it = ready_instructions.find(operand_user);
            if (ready_instructions_it == ready_instructions.end()) {
              continue;
            }
            auto ready_queue_it = ready_instructions_it->second;
            auto& entry = ready_queue_it->second;
            Priority new_priority = GetPriority(entry);
            if (new_priority == ready_queue_it->first) {
              continue;
            }
            // Create a new entry in ready_queue, then update
            // ready_instructions[operand_user] to refer to the new entry.
            ready_instructions_it->second =
                ready_queue.emplace(new_priority, std::move(entry));
            // Remove the old entry in ready_queue.
            ready_queue.erase(ready_queue_it);
          }
        }
      }
    }
    CHECK_EQ(schedule.size(), computation_->instruction_count());
    CHECK_EQ(scheduled_instructions_.size(), computation_->instruction_count());

    return schedule;
  }

  HloComputation* computation_;
  const TuplePointsToAnalysis& points_to_analysis_;
  const BufferValue::SizeFunction& size_function_;
  // Computations are analyzed in post-order. When scheduling an instruction
  // that includes subcomputations, such as a while loop, we use this map to
  // look up the memory needed by subcomputations.
  const absl::flat_hash_map<const HloComputation*, int64_t>&
      memory_by_computation_;

  // A map containing the LogicalBuffers that each instruction uses.
  absl::flat_hash_map<const HloInstruction*, std::vector<const LogicalBuffer*>>
      buffer_uses_;

  // A map containing the count of unscheduled HLOs which using a particular
  // LogicalBuffer.
  absl::flat_hash_map<const LogicalBuffer*, int64_t> unscheduled_use_count_;

  // Set of instructions which have been scheduled.
  absl::flat_hash_set<const HloInstruction*> scheduled_instructions_;
};

int64_t SumLogicalBufferSizes(
    const TuplePointsToAnalysis::BufferDefinitionVector& buffers,
    const BufferValue::SizeFunction& size_function) {
  int64_t size = 0;
  for (const LogicalBuffer* buffer : buffers) {
    size += size_function(*buffer);
  }
  return size;
}

StatusOr<HloInstructionSequence> ScheduleComputationHelper(
    HloComputation* computation,
    const TuplePointsToAnalysis& points_to_analysis,
    const HloAliasAnalysis& alias_analysis,
    const BufferValue::SizeFunction& size_function,
    const MemorySchedulerAlgorithm& algorithm,
    const absl::flat_hash_map<const HloComputation*, int64_t>&
        memory_by_computation,
    const MemorySchedulerPostprocessor& postprocessor, int64_t* peak_memory) {
  VLOG(2) << "Computation: " << computation->name();

  if (algorithm) {
    return algorithm(computation, points_to_analysis, alias_analysis,
                     size_function, memory_by_computation, postprocessor,
                     peak_memory);
  }
  return DefaultMemoryScheduler(computation, points_to_analysis, alias_analysis,
                                size_function, memory_by_computation,
                                postprocessor, peak_memory);
}

}  // namespace

StatusOr<HloInstructionSequence> DFSMemoryScheduler(
    HloComputation* computation,
    const TuplePointsToAnalysis& points_to_analysis,
    const HloAliasAnalysis& alias_analysis,
    const BufferValue::SizeFunction& size_function,
    const absl::flat_hash_map<const HloComputation*, int64_t>&
        memory_by_computation,
    const MemorySchedulerPostprocessor& postprocessor, int64_t* peak_memory) {
  // These variables are a hack to prevent overflows.
  int64_t cumulative_total_size = 0;
  int64_t total_hlos = computation->parent()->instruction_count();
  absl::flat_hash_map<const HloInstruction*, int64_t> extra_users;
  absl::flat_hash_map<const HloInstruction*, int64_t> total_sizes;
  for (const HloInstruction* hlo : computation->MakeInstructionPostOrder()) {
    if (ListScheduler::IgnoreInstruction(*hlo)) {
      extra_users[hlo] = 0;
      total_sizes[hlo] = 0;
      continue;
    }
    // This ordering is based on DFS post-order, with a heuristic to decide
    // which operand to visit first.  The heuristic is based on 'extra_users',
    // which is simply users-1 for each instruction.  By subtracting 1, we're
    // saying that instructions with no users or a single user don't count;
    // instructions with lots of fan-out will be visited earlier.
    extra_users[hlo] = hlo->users().empty() ? 0 : hlo->users().size() - 1;
    int64_t logical_buffer_size = SumLogicalBufferSizes(
        points_to_analysis.GetBuffersDefinedByInstruction(hlo), size_function);
    total_sizes[hlo] = logical_buffer_size;
    cumulative_total_size += logical_buffer_size;
    absl::flat_hash_set<const HloInstruction*> unique_operands(
        hlo->operands().begin(), hlo->operands().end());
    for (const HloInstruction* operand : unique_operands) {
      extra_users[hlo] += extra_users[operand];
      total_sizes[hlo] += total_sizes[operand];
    }
    // total_sizes[hlo] transitively includes the sizes of all nodes that
    // lead to it. But computation is a DAG, so we are double-counting nodes,
    // which can lead to overflows for large programs.
    // cumulative_total_size caps the size to prevent overflows.
    // Same for total_hlos: it prevents overflows on very large and branchy
    // models, where the number of paths is exponential to the number of nodes.
    // NOTE(dimvar): this is quite ugly and should be changed. It's unclear
    // why we care about transitive sizes; when scheduling a node, its input
    // and output buffers should be all that matters, not its "history".
    total_sizes[hlo] = std::min(total_sizes[hlo], cumulative_total_size);
    extra_users[hlo] = std::min(extra_users[hlo], total_hlos);
  }
  CHECK_EQ(extra_users.size(), computation->instruction_count());
  CHECK_EQ(total_sizes.size(), computation->instruction_count());

  // Construct a total order based on DFS post-order, visiting operands in
  // decreasing cumulative extra user order, and next by cumulative size, with a
  // tiebreaker by name for determinism.
  HloInstructionSequence sequence;
  FunctionVisitor visitor([&sequence](HloInstruction* hlo) {
    sequence.push_back(hlo);
    return Status::OK();
  });
  visitor.ReserveVisitStates(computation->instruction_count());
  TF_RETURN_IF_ERROR(computation->AcceptWithOperandOrder(
      &visitor, [&extra_users, &total_sizes](const HloInstruction* a,
                                             const HloInstruction* b) {
        if (extra_users[a] != extra_users[b]) {
          return extra_users[a] > extra_users[b];
        }
        if (total_sizes[a] != total_sizes[b]) {
          return total_sizes[a] > total_sizes[b];
        }
        return a->name() < b->name();
      }));
  if (postprocessor) {
    sequence = postprocessor(sequence);
  }
  CHECK_EQ(sequence.size(), computation->instruction_count());
  if (peak_memory) {
    TF_ASSIGN_OR_RETURN(
        *peak_memory, HeapSimulator::MinimumMemoryForComputation(
                          *computation, sequence, alias_analysis, size_function,
                          &memory_by_computation));
  }
  return sequence;
}  // namespace xla

ModuleSchedulerAlgorithm ComputationSchedulerToModuleScheduler(
    const MemorySchedulerAlgorithm& computation_scheduler,
    const MemorySchedulerPostprocessor& postprocessor) {
  return [computation_scheduler, postprocessor](
             HloModule* module, const TuplePointsToAnalysis& points_to_analysis,
             const HloAliasAnalysis& alias_analysis,
             const LogicalBuffer::SizeFunction& size_func,
             int64_t* peak_memory) -> StatusOr<HloSchedule> {
    HloSchedule schedule(module);
    absl::flat_hash_map<const HloComputation*, int64_t> memory_by_computation;
    for (auto* computation : module->MakeComputationPostOrder()) {
      if (!computation->IsFusionComputation()) {
        TF_ASSIGN_OR_RETURN(
            HloInstructionSequence computation_sequence,
            ScheduleComputationHelper(
                computation, points_to_analysis, alias_analysis, size_func,
                computation_scheduler, memory_by_computation, postprocessor,
                /*peak_memory=*/nullptr));
        schedule.set_sequence(computation, std::move(computation_sequence));
      }
    }
    if (peak_memory) {
      TF_ASSIGN_OR_RETURN(*peak_memory, HeapSimulator::MinimumMemoryForModule(
                                            schedule, size_func));
    }
    return std::move(schedule);
  };
}

StatusOr<HloInstructionSequence> ListMemoryScheduler(
    HloComputation* computation,
    const TuplePointsToAnalysis& points_to_analysis,
    const HloAliasAnalysis& alias_analysis,
    const BufferValue::SizeFunction& size_function,
    const absl::flat_hash_map<const HloComputation*, int64_t>&
        memory_by_computation,
    const MemorySchedulerPostprocessor& postprocessor, int64_t* peak_memory) {
  TF_ASSIGN_OR_RETURN(HloInstructionSequence sequence,
                      ListScheduler::Run(computation, points_to_analysis,
                                         size_function, memory_by_computation));
  if (postprocessor) {
    sequence = postprocessor(sequence);
  }
  if (peak_memory) {
    TF_ASSIGN_OR_RETURN(
        *peak_memory, HeapSimulator::MinimumMemoryForComputation(
                          *computation, sequence, alias_analysis, size_function,
                          &memory_by_computation));
  }
  return sequence;
}

StatusOr<HloInstructionSequence> PostOrderMemoryScheduler(
    HloComputation* computation,
    const TuplePointsToAnalysis& points_to_analysis,
    const HloAliasAnalysis& alias_analysis,
    const BufferValue::SizeFunction& size_function,
    const absl::flat_hash_map<const HloComputation*, int64_t>&
        memory_by_computation,
    const MemorySchedulerPostprocessor& postprocessor, int64_t* peak_memory) {
  HloInstructionSequence sequence(computation->MakeInstructionPostOrder());
  if (postprocessor) {
    sequence = postprocessor(sequence);
  }
  if (peak_memory) {
    TF_ASSIGN_OR_RETURN(
        *peak_memory, HeapSimulator::MinimumMemoryForComputation(
                          *computation, sequence, alias_analysis, size_function,
                          &memory_by_computation));
  }
  return sequence;
}

StatusOr<HloInstructionSequence> DefaultMemoryScheduler(
    HloComputation* computation,
    const TuplePointsToAnalysis& points_to_analysis,
    const HloAliasAnalysis& alias_analysis,
    const BufferValue::SizeFunction& size_function,
    const absl::flat_hash_map<const HloComputation*, int64_t>&
        memory_by_computation,
    const MemorySchedulerPostprocessor& postprocessor, int64_t* peak_memory) {
  // We try a few schedulers and choose whichever returns a lower min-memory,
  // not accounting for fragmentation.
  // - List is a scheduler that uses greedy heuristics.
  // - DFS visits HLOs in postorder, with a heuristic to decide the order of
  //   children.
  // - Postorder does not use any heuristics.
  // List wins for most of our benchmarks; postorder-based schedulers win for
  // some RNNs.
  int64_t list_memory;
  TF_ASSIGN_OR_RETURN(
      HloInstructionSequence list_sequence,
      ListMemoryScheduler(computation, points_to_analysis, alias_analysis,
                          size_function, memory_by_computation, postprocessor,
                          &list_memory));
  VLOG(2) << "Min-memory list sequence: " << HumanReadableNumBytes(list_memory);

  int64_t dfs_memory;
  TF_ASSIGN_OR_RETURN(
      HloInstructionSequence dfs_sequence,
      DFSMemoryScheduler(computation, points_to_analysis, alias_analysis,
                         size_function, memory_by_computation, postprocessor,
                         &dfs_memory));
  VLOG(2) << "Min-memory dfs sequence: " << HumanReadableNumBytes(dfs_memory);

  int64_t post_order_memory;
  TF_ASSIGN_OR_RETURN(
      HloInstructionSequence post_order_sequence,
      PostOrderMemoryScheduler(computation, points_to_analysis, alias_analysis,
                               size_function, memory_by_computation,
                               postprocessor, &post_order_memory));
  VLOG(2) << "Min-memory post order sequence: "
          << HumanReadableNumBytes(post_order_memory);

  auto min_memory = std::min({dfs_memory, post_order_memory, list_memory});
  if (peak_memory) {
    *peak_memory = min_memory;
  }

  if (min_memory == list_memory) {
    VLOG(2) << "Chose min-memory list sequence: "
            << HumanReadableNumBytes(list_memory);
    return list_sequence;
  } else if (min_memory == dfs_memory) {
    VLOG(2) << "Chose min-memory dfs sequence: "
            << HumanReadableNumBytes(dfs_memory);
    return dfs_sequence;
  } else {
    VLOG(2) << "Chose min-memory post_order sequence: "
            << HumanReadableNumBytes(post_order_memory);
    return post_order_sequence;
  }
}

StatusOr<HloSchedule> DefaultModuleScheduler(
    HloModule* module, const TuplePointsToAnalysis& points_to_analysis,
    const HloAliasAnalysis& alias_analysis,
    const BufferValue::SizeFunction& size_function, int64_t* peak_memory) {
  // We try a few schedulers and choose whichever returns a lower min-memory,
  // not accounting for fragmentation.
  // - List is a scheduler that uses greedy heuristics.
  // - DFS visits HLOs in postorder, with a heuristic to decide the order of
  //   children.
  // - Postorder does not use any heuristics.
  // List wins for most of our benchmarks; postorder-based schedulers win for
  // some RNNs.
  int64_t list_memory;
  TF_ASSIGN_OR_RETURN(
      HloSchedule list_sequence,
      ComputationSchedulerToModuleScheduler(ListMemoryScheduler, {})(
          module, points_to_analysis, alias_analysis, size_function,
          &list_memory));

  VLOG(2) << "Min-memory list sequence: " << HumanReadableNumBytes(list_memory);

  int64_t dfs_memory;
  TF_ASSIGN_OR_RETURN(
      HloSchedule dfs_sequence,
      ComputationSchedulerToModuleScheduler(DFSMemoryScheduler, {})(
          module, points_to_analysis, alias_analysis, size_function,
          &dfs_memory));
  VLOG(2) << "Min-memory dfs sequence: " << HumanReadableNumBytes(dfs_memory);

  int64_t post_order_memory;
  TF_ASSIGN_OR_RETURN(
      HloSchedule post_order_sequence,
      ComputationSchedulerToModuleScheduler(PostOrderMemoryScheduler, {})(
          module, points_to_analysis, alias_analysis, size_function,
          &post_order_memory));
  VLOG(2) << "Min-memory post order sequence: "
          << HumanReadableNumBytes(post_order_memory);

  auto min_memory = std::min({dfs_memory, post_order_memory, list_memory});
  if (peak_memory) {
    *peak_memory = min_memory;
  }

  if (min_memory == list_memory) {
    VLOG(2) << "Chose min-memory list sequence: "
            << HumanReadableNumBytes(list_memory);
    return list_sequence;
  } else if (min_memory == dfs_memory) {
    VLOG(2) << "Chose min-memory dfs sequence: "
            << HumanReadableNumBytes(dfs_memory);
    return dfs_sequence;
  } else {
    VLOG(2) << "Chose min-memory post_order sequence: "
            << HumanReadableNumBytes(post_order_memory);
    return post_order_sequence;
  }
}

StatusOr<HloSchedule> ScheduleModule(
    HloModule* module, const BufferValue::SizeFunction& size_function,
    const ModuleSchedulerAlgorithm& algorithm, int64_t* peak_memory) {
  TF_ASSIGN_OR_RETURN(std::unique_ptr<TuplePointsToAnalysis> points_to_analysis,
                      TuplePointsToAnalysis::Run(module));
  TF_ASSIGN_OR_RETURN(std::unique_ptr<HloAliasAnalysis> alias_analysis,
                      HloAliasAnalysis::Run(module));

  TF_ASSIGN_OR_RETURN(HloSchedule schedule,
                      (algorithm ? algorithm : DefaultModuleScheduler)(
                          module, *points_to_analysis, *alias_analysis,
                          size_function, peak_memory));

  TF_RETURN_IF_ERROR(schedule.Verify());

  return std::move(schedule);
}

StatusOr<HloInstructionSequence> ScheduleComputation(
    HloComputation* computation, const BufferValue::SizeFunction& size_function,
    const MemorySchedulerPostprocessor& postprocessor) {
  CHECK(!computation->IsFusionComputation());
  TF_ASSIGN_OR_RETURN(std::unique_ptr<TuplePointsToAnalysis> points_to_analysis,
                      TuplePointsToAnalysis::Run(computation->parent()));
  TF_ASSIGN_OR_RETURN(std::unique_ptr<HloAliasAnalysis> alias_analysis,
                      HloAliasAnalysis::Run(computation->parent()));
  absl::flat_hash_map<const HloComputation*, int64_t> empty_map;
  return ScheduleComputationHelper(
      computation, *points_to_analysis, *alias_analysis, size_function,
      /*algorithm=*/nullptr, empty_map, postprocessor,
      /*peak_memory=*/nullptr);
}

HloMemoryScheduler::HloMemoryScheduler(
    const BufferValue::SizeFunction& size_function,
    const ModuleSchedulerAlgorithm& algorithm)
    : size_function_(size_function), algorithm_(algorithm) {}

StatusOr<bool> HloMemoryScheduler::Run(HloModule* module) {
  TF_ASSIGN_OR_RETURN(HloSchedule schedule,
                      ScheduleModule(module, size_function_, algorithm_));
  TF_RETURN_IF_ERROR(module->set_schedule(std::move(schedule)));
  return true;
}

StatusOr<bool> HloTrivialScheduler::Run(HloModule* module) {
  HloSchedule schedule(module);
  for (HloComputation* computation : module->MakeComputationPostOrder()) {
    if (!computation->IsFusionComputation()) {
      HloInstructionSequence& computation_sequence =
          schedule.GetOrCreateSequence(computation);
      FunctionVisitor visitor(
          [&computation_sequence](HloInstruction* instruction) {
            computation_sequence.push_back(instruction);
            return Status::OK();
          });
      visitor.ReserveVisitStates(computation->instruction_count());
      TF_RETURN_IF_ERROR(computation->Accept(&visitor));
    }
  }
  TF_RETURN_IF_ERROR(module->set_schedule(std::move(schedule)));
  return true;
}

StatusOr<bool> HloDescheduler::Run(HloModule* module) {
  bool changed = module->has_schedule();
  module->clear_schedule();
  return changed;
}

}  // namespace xla


text:
<?xml version="1.0"?>
<!DOCTYPE hibernate-mapping PUBLIC "-//Hibernate/Hibernate Mapping DTD 3.0//EN"
"http://hibernate.sourceforge.net/hibernate-mapping-3.0.dtd">
<hibernate-mapping package="model">
	<class name="Group" table="groupe">
		<id name="group_ID" type="long" column="group_ID">
			<generator class="native" />
		</id>
		<version name="version" access="field" column="version"/>

		<property name="groupName">
			<column name="groupName"></column>
		</property>

		<!-- Un groupe possède 0, 1 ou n contact(s) -->
		<set name="contacts" table="contact_group" inverse="true" cascade="persist, save-update" lazy="true" optimistic-lock="false">
			<key column="group_ID" not-null="true"></key>
			<many-to-many column="contact_ID" class="Contact"></many-to-many>
		</set>

	</class>
</hibernate-mapping>


text:
package nl.xillio.xill.plugins.file.services.permissions;

import java.nio.file.Path;
import java.util.HashMap;
import java.util.Map;
import java.util.stream.Collectors;

/**
 * This class represents a summary of the declared permissions on a file.
 *
 * @author Thomas Biesaart
 */
public class FilePermissions {
    private final Path file;
    private final Map<String, FileOperations> users = new HashMap<>();
    private final Map<String, FileOperations> groups = new HashMap<>();

    public FilePermissions(Path file) {
        this.file = file;
    }

    public void setUser(String user, boolean readable, boolean writable, boolean executable) {
        setOn(users, user, new FileOperations(readable, writable, executable));
    }

    public void setGroup(String group, boolean readable, boolean writable, boolean executable) {
        setOn(groups, group, new FileOperations(readable, writable, executable));
    }

    /**
     * This method will set or combine file permissions on a map with a string index.
     *
     * @param map        the map
     * @param key        the key
     * @param operations the operations to add.
     */
    private void setOn(Map<String, FileOperations> map, String key, FileOperations operations) {
        FileOperations current = map.get(key);
        if (current == null) {
            map.put(key, operations);
        } else {
            FileOperations combined = new FileOperations(
                    current.isReadable() || operations.isReadable(),
                    current.isWritable() || operations.isWritable(),
                    current.isExecutable() || operations.isExecutable()
            );

            map.put(key, combined);
        }
    }

    public Path getFile() {
        return file;
    }

    public Map<String, Map<String, Map<String, Boolean>>> toMap() {
        Map<String, Map<String, Map<String, Boolean>>> result = new HashMap<>();
        result.put("users", toMap(this.users));
        result.put("groups", toMap(this.groups));

        return result;
    }

    private Map<String, Map<String, Boolean>> toMap(Map<String, FileOperations> input) {
        return input.entrySet()
                .stream()
                .collect(Collectors.toMap(
                        Map.Entry::getKey,
                        entry -> entry.getValue().toMap()
                ));
    }

}


text:
@interface PodsDummy_Charleene : NSObject
@end
@implementation PodsDummy_Charleene
@end


text:
package com.lenzhao.framework.protocol;

import java.io.Serializable;
import java.util.Date;

/**
 *协议请求实体
 */
public class RpcRequest implements Serializable {

	private static final long serialVersionUID = 1L;

	/**
	 * 请求唯一标示
	 */
	private String requestID;

	/**
	 * 接口名
	 * @eg: com.lenzhao.framework.IServer1
	 */
	private String interfaceName;

	/**
	 * 服务名,也就是@ServiceAnnotation的name
	 * @eg: MyServer1
	 */
	private String className;

	/**
	 * 方法名
	 */
	private String methodName;

	/**
	 * 请求参数类型
	 */
	private String[] parameterTypes;

	/**
	 * 请求参数值
	 */
	private Object[] parameters;

	/**
	 * 请求时间
	 */
	private Date addTime;

	public RpcRequest() {
		super();
	}

	public RpcRequest(String requestID, String interfaceName, String className,
			String methodName, String[] parameterTypes, Object[] parameters) {
		super();
		this.requestID = requestID;
		this.interfaceName = interfaceName;
		this.className = className;
		this.methodName = methodName;
		this.parameterTypes = parameterTypes;
		this.parameters = parameters;
		this.addTime = new Date();
	}

	public String getRequestID() {
		return requestID;
	}

	public void setRequestID(String requestID) {
		this.requestID = requestID;
	}

	public String getInterfaceName() {
		return interfaceName;
	}

	public void setInterfaceName(String interfaceName) {
		this.interfaceName = interfaceName;
	}

	public String getClassName() {
		return className;
	}

	public void setClassName(String className) {
		this.className = className;
	}

	public String getMethodName() {
		return methodName;
	}

	public void setMethodName(String methodName) {
		this.methodName = methodName;
	}

	public String[] getParameterTypes() {
		return parameterTypes;
	}

	public void setParameterTypes(String[] parameterTypes) {
		this.parameterTypes = parameterTypes;
	}

	public Object[] getParameters() {
		return parameters;
	}

	public void setParameters(Object[] parameters) {
		this.parameters = parameters;
	}

	public Date getAddTime() {
		return addTime;
	}

	public void setAddTime(Date addTime) {
		this.addTime = addTime;
	}

}


text:
module RemoteDuplicateSupport

  def self.included klass
    klass.class_eval do
      # Include PeerAccess module so authorize_peer! method is available.
      # It checks whether request is coming from trusted Portal instance.
      include PeerAccess
    end
  end

  def self.get_resource

  end

  # Action triggered by Portal. Duplicates an activity or sequence and returns its publication data.
  # It expects an author_url param or @activity or @sequence to be available.
  def remote_duplicate
    authorize_peer!

    if params[:author_url].present?
      resource_path = URI.parse(params[:author_url]).path
      resource_type = resource_path.split("/")[1]
      resource_id = resource_path.split("/")[2]
      if resource_type == 'sequences'
        resource = Sequence.find(resource_id)
      else
        resource = LightweightActivity.find(resource_id)
      end
    else
      resource = @activity || @sequence
    end

    # Make sure that user exists. It might not if the user never opened LARA before and it's just copying an activity using Portal.
    user = User.find_by_email params[:user_email]
    unless user
      user = User.create(
        email: params[:user_email],
        password: User.get_random_password,
        is_author: true
      )
    end

    new_resource = resource.duplicate(user)

    if new_resource.save(validations: false) # in case the old resource was invalid
      self_url = "#{request.protocol}#{request.host_with_port}"
      publication_data = new_resource.serialize_for_portal(self_url)
      # We need to manually create publication data. Since this path is a bit different than typical,
      # not all the field make so much sense. Also, we don't get response from Portal whether it has been
      # successful or not, so we have to assume it was.
      auth_portal = Concord::AuthPortal.portal_for_url(params[:add_to_portal])
      new_resource.add_portal_publication(auth_portal) do
        {
          publication_data: publication_data.to_json,
          response: "published during copy, we don't really know if it is succeeded",
          success: true
        }
      end
      render status: 200, json: { publication_data: publication_data }, content_type: 'text/json'
    else
      render status: 500, json: { error: "Remote duplicate failed" }, content_type: 'text/json'
    end
  end
end