ways to detect malicious models/graphs/checkpoints, so the recommended way to
mitigate the risk in this scenario is to sandbox the model execution.

### Hardware attacks

Physical GPUs or TPUs can also be the target of attacks. [Published
research](https://scholar.google.com/scholar?q=gpu+side+channel) shows that it
might be possible to use side channel attacks on the GPU to leak data from other

     * on most other types: In cases in which we "should" receive both an interrupt and a
     * notification nearly simultaneously, we sometimes receive only an interrupt. Thus, when we're
     * interrupted, we can't just poll whether it's time to end the wait because our "end the wait"
     * notification has been lost. (This is in contrast to how we can poll with, say, a

   * necessary. No observable state associated with this cache is modified until loading completes.
   * Unlike {@link #get}, this method does not throw a checked exception, and thus should only be
   * used in situations where checked exceptions are not thrown by the cache loader.
   *
   * <p>If another call to {@link #get} or {@link #getUnchecked} is currently loading the value for

     * proto:\\server[key1=val1,key2=val2]
     * or
     * proto:server[key1=val1,key2=val2]
     * or
     * proto:[key1=val1,key2=val2]
     *
     * If a key is absent it is assumed to be 'endpoint'. Thus the
     * following are equivalent:
     * proto:\\ts0.win.net[endpoint=\pipe\srvsvc]
     * proto:ts0.win.net[\pipe\srvsvc]
     *
     * If the server is absent it is set to "127.0.0.1"
     */
    /**

* Sécurité - HTTPS
* Exécution au démarrage
* Redémarrages
* **Réplication (le nombre de processus en cours d'exécution)**
* Mémoire
* Étapes préalables avant le démarrage

Jusqu'à présent, avec tous les tutoriels dans les documents, vous avez probablement exécuté un programme serveur, par exemple avec la commande `fastapi`, qui lance Uvicorn en exécutant un seul processus.

 * of the <i>next</i> request. I.e., if an expensive task arrives at an idle RateLimiter, it will be
 * granted immediately, but it is the <i>next</i> request that will experience extra throttling,
 * thus paying for the cost of the expensive task.
 *
 * @author Dimitris Andreou
 * @since 13.0
 */
// TODO(user): switch to nano precision. A natural unit of cost is "bytes", and a micro precision

         *
         * We *would* just check such functions redundantly, but kotlinc emits its nullness
         * annotations in the form of JetBrains annotations, which have only class retention and
         * thus are invisible at runtime. Thus, we conclude that the parameter types are
         * *non*-nullable, even when they are declared as `Foo?`.
         */
        || hasAutomaticNullChecksFromKotlin(member);
  }

   *       take each of the servers offline, {@code consistentHash} will be a poor fit: It provides
   *       no way for you to specify which of the three buckets is disappearing. Thus, if your
   *       buckets change from {@code [alpha, bravo, charlie]} to {@code [bravo, charlie]}, it will
   *       assign all the old {@code alpha} traffic to {@code bravo} and all the old {@code bravo}

   * this address.
   *
   * If [planToReplace] is non-null, this will swap it for a pooled connection if that pooled
   * connection uses HTTP/2. That results in fewer sockets overall and thus fewer TCP slow starts.
   */
  internal fun planReusePooledConnection(
    planToReplace: ConnectPlan? = null,
    routes: List<Route>? = null,
  ): ReusePlan? {
    val result =

 */
internal class DerReader(
  source: Source,
) {
  private val countingSource: CountingSource = CountingSource(source)
  private val source: BufferedSource = countingSource.buffer()

  /** Total bytes read thus far. */
  private val byteCount: Long
    get() = countingSource.bytesRead - source.buffer.size

  /** How many bytes to read before [peekHeader] should return false, or -1L for no limit. */
  private var limit = -1L