super.tearDown();
  }

  public void testListenerDoesNotRunUntilTaskCompletes() throws Exception {

    // Test default state of not started.
    assertEquals(1, listenerLatch.getCount());
    assertFalse(task.isDone());
    assertFalse(task.isCancelled());

    // Start the task to put it in the RUNNING state.  Have to use a separate
    // thread because the task will block on the task latch after unblocking
    // the run latch.

    }

    /**
     * Returns the state of the "add default entities" flag.
     *
     * @return boolean a field value
     */
    public boolean getAddDefaultEntities() {
        return delegate.getAddDefaultEntities();
    }

    /**
     * Sets the state of the "add default entities" flag.
     *
     * @param addDefaultEntities a addDefaultEntities object.

from starlette.datastructures import Headers as Headers  # noqa: F401
from starlette.datastructures import QueryParams as QueryParams  # noqa: F401
from starlette.datastructures import State as State  # noqa: F401
from starlette.datastructures import UploadFile as StarletteUploadFile


class UploadFile(StarletteUploadFile):
    """
    A file uploaded in a request.

func (r *lockedRandSource) Int63() (n int64) {
	r.lk.Lock()
	n = r.src.Int63()
	r.lk.Unlock()
	return n
}

// Seed uses the provided seed value to initialize the generator to a
// deterministic state.
func (r *lockedRandSource) Seed(seed int64) {
	r.lk.Lock()
	r.src.Seed(seed)
	r.lk.Unlock()

    RateLimiter limiter = RateLimiter.create(2.0, 4000, MILLISECONDS, 3.0, stopwatch);
    for (int i = 0; i < 8; i++) {
      limiter.acquire(); // // #1
    }
    stopwatch.sleepMillis(4500); // #2: back to cold state (warmup period + repay last acquire)
    for (int i = 0; i < 3; i++) { // only three steps, we're somewhere in the warmup period
      limiter.acquire(); // #3
    }

    limiter.setRate(4.0); // double the rate!

    RateLimiter limiter = RateLimiter.create(2.0, 4000, MILLISECONDS, 3.0, stopwatch);
    for (int i = 0; i < 8; i++) {
      limiter.acquire(); // // #1
    }
    stopwatch.sleepMillis(4500); // #2: back to cold state (warmup period + repay last acquire)
    for (int i = 0; i < 3; i++) { // only three steps, we're somewhere in the warmup period
      limiter.acquire(); // #3
    }

    limiter.setRate(4.0); // double the rate!

 *
 * Duration duration = stopwatch.elapsed();
 *
 * log.info("time: " + stopwatch); // formatted string like "12.3 ms"
 * }
 *
 * <p>The state-changing methods are not idempotent; it is an error to start or stop a stopwatch
 * that is already in the desired state.
 *
 * <p>When testing code that uses this class, use {@link #createUnstarted(Ticker)} or {@link

#!/usr/bin/env bash

echo "script failed" >resiliency-verify-failure.log # assume initial state

ALIAS_NAME=myminio
BUCKET="test-bucket"
DEST_DIR="/tmp/dest"

OUT=$(./mc cp --quiet --recursive "${ALIAS_NAME}"/"${BUCKET}"/initial-data/ "${DEST_DIR}"/)
RET=${?}
if [ ${RET} -ne 0 ]; then
	# It is a success scenario as get objects should fail
	echo "GET objects failed as expected"
	echo "script passed" >resiliency-verify-failure.log
	exit 0

  BasicComponentConfigurator.

* Other

  We may need to define a new lifecycle/phase to contextualize a mojo right
  before it's used, and reset it's state afterward. Up to now, the approach
  of most plexus components has been to avoid instance state like the plague.
  With the current parameter passing model of mojos, this will not be possible,
  particularly when we move mojos to a singleton instantiation model, and then

{
    "description": "TensorFlow is an end-to-end open source platform for machine learning. It has a comprehensive, flexible ecosystem of tools, libraries, and community resources that lets researchers push the state-of-the-art in ML and developers easily build and deploy ML-powered applications.",
    "license": "Apache-2.0",
    "title": "TensorFlow",
    "upload_type": "software",
    "creators": [
        {
            "name": "TensorFlow Developers"
        }