}

    @Override
    public NavigableSet<E> subSet(
        @ParametricNullness E fromElement,
        boolean fromInclusive,
        @ParametricNullness E toElement,
        boolean toInclusive) {
      return forward.subSet(toElement, toInclusive, fromElement, fromInclusive).descendingSet();
    }

    @Override
    public SortedSet<E> subSet(@ParametricNullness E fromElement, @ParametricNullness E toElement) {

    assertNoExpectedFailures();
    super.tearDown();
  }

  public void testFrom() throws Exception {
    ClosingFuture<String> closingFuture =
        ClosingFuture.from(executor.submit(Callables.returning(closeable1)))
            .transform(
                new ClosingFunction<TestCloseable, String>() {
                  @Override

            }
        }
    }

    private static byte[] createToken(final SSPContext ctx, final byte[] token, Subject s) throws CIFSException {
        if (s != null) {
            try {
                return Subject.doAs(s,
                        (PrivilegedExceptionAction<byte[]>) () -> ctx.initSecContext(token, 0, token == null ? 0 : token.length));

```
KEY:
notify_nats[:name]  publish bucket notifications to NATS endpoints

ARGS:
address*                          (address)   NATS server address e.g. '0.0.0.0:4222'
subject*                          (string)    NATS subscription subject
username                          (string)    NATS username
password                          (string)    NATS password
token                             (string)    NATS token

// `max_func`. In usual usage, max_func should be set to the result of
// TF_GraphNumFunctions(g). In this case, all the functions registered in
// `g` will be returned. Else, an unspecified subset.
//
// If successful, returns the number of TF_Function* successfully set in
// `funcs` and sets status to OK. The caller takes ownership of
// all the returned TF_Functions. They must be deleted with TF_DeleteFunction.

  TF_Operation* func_feed = Placeholder(host_graph_, s_);
  TF_Operation* func_op = Use({func_feed, five});
  Run({{func_feed, Int32Tensor(2)}}, func_op, 2 /*+=*/ + 5 + 1);

  // Verify input, output, and subset of edges in fdef.
  // The subset of edges we verify is a chain between feed1 and output to
  // make sure that the correct output is picked.
  tensorflow::FunctionDef fdef;
  ASSERT_TRUE(GetFunctionDef(func_, &fdef));

   *
   * @throws RejectedExecutionException if the task cannot be scheduled for execution
   * @since 28.2
   */
  public static <O extends @Nullable Object> ListenableFuture<O> submit(
      Callable<O> callable, Executor executor) {
    TrustedListenableFutureTask<O> task = TrustedListenableFutureTask.create(callable);
    executor.execute(task);
    return task;
  }

  /**

# causing library conflicts (e.g., those reported in github issue 1924).
# On Linux, tell the linker (-Wl,<option>) to use a version script that
# excludes all but a subset of function names.
# On MacOS, the linker does not support version_script, but has an
# an "-exported_symbols_list" command.  -z defs disallows undefined
# symbols in object files.

pywrap_aware_tf_cc_shared_object(

        input.equals("%2e%2e", ignoreCase = true)

    /**
     * Cuts this string up into alternating parameter names and values. This divides a query string
     * like `subject=math&easy&problem=5-2=3` into the list `["subject", "math", "easy", null,
     * "problem", "5-2=3"]`. Note that values may be null and may contain '=' characters.
     */
    private fun String.toQueryNamesAndValues(): MutableList<String?> {

e}),lt:X(function(e,t,n){var r;for(r=n<0?n+t:t<n?t:n;0<=--r;)e.push(r);return e}),gt:X(function(e,t,n){for(var r=n<0?n+t:n;++r<t;)e.push(r);return e})}}).pseudos.nth=b.pseudos.eq,{radio:!0,checkbox:!0,file:!0,password:!0,image:!0})b.pseudos[e]=B(e);for(e in{submit:!0,reset:!0})b.pseudos[e]=_(e);function G(){}function Y(e,t){var n,r,i,o,a,s,u,l=c[e+" "];if(l)return t?0:l.slice(0);a=e,s=[],u=b.preFilter;while(a){for(o in n&&!(r=y.exec(a))||(r&&(a=a.slice(r[0].length)||a),s.push(i=[])),n=!1,(r=m.exec(a))&&(n=...