public void testIsPresent_yes() {
    assertTrue(Optional.of("training").isPresent());
  }

  public void testGet_absent() {
    Optional<String> optional = Optional.absent();
    assertThrows(IllegalStateException.class, optional::get);
  }

  public void testGet_present() {
    assertThat(Optional.of("training").get()).isEqualTo("training");
  }

  virtual void ClearCachesAndThreadExecutors() = 0;

  // Initialize the step resource container for a training step. This is used
  // in current TF runtime. For tfrt, it is used by fallback op handler.
  virtual void StartStep() = 0;
  // Destroy the step resource container for a training step.
  virtual void EndStep() = 0;

  // Return the Eager Executor for current thread. Please note that Eager

# Using TensorFlow Securely

This document discusses the TensorFlow security model. It describes the security
risks to consider when using models, checkpoints or input data for training or
serving. We also provide guidelines on what constitutes a vulnerability in
TensorFlow and how to report them.

This document applies to other repositories in the TensorFlow organization,
covering security practices for the entirety of the TensorFlow ecosystem.

    [`tf.distribute.Strategy`](https://www.tensorflow.org/beta/guide/distribute_strategy)
    API to distribute training with minimal code changes, yielding great
    out-of-the-box performance. It supports distributed training with Keras
    model.fit, as well as with custom training loops. Multi-GPU support is
    available, along with experimental support for multi worker and Cloud TPUs.
    Check out the

- **[Community Resources](https://gradle.org/resources/)** - Find more community-contributed materials to expand your knowledge.

> 🌟 **Stay connected with the Gradle Community and access the latest news, training, and updates via [Slack](https://gradle.org/slack-invite), [Forum](https://discuss.gradle.org/), and our [Newsletter](https://newsletter.gradle.org)**.

<br><br>
<div align="center" style="margin-top: 20px;">

 [CertificatePinningKotlin]: https://github.com/square/okhttp/blob/master/samples/guide/src/main/java/okhttp3/recipes/kt/CertificatePinning.kt
 [provider_installer]: https://developer.android.com/training/articles/security-gms-provider

   *     not support creating temporary directories securely
   * @deprecated For Android users, see the <a
   *     href="https://developer.android.com/training/data-storage" target="_blank">Data and File
   *     Storage overview</a> to select an appropriate temporary directory (perhaps {@code
   *     context.getCacheDir()}), and create your own directory under that. (For example, you might

    bool clear_existing_contexts);

// Set server def with retries and timeout. This is helpful for fault-tolerant
// initial connection in high-preemption environments, such as
// ParameterServerStrategy training.
// This API is for experimental usage and may be subject to change.
TF_CAPI_EXPORT extern void TFE_ContextSetServerDefWithTimeoutAndRetries(
    TFE_Context* ctx, int keep_alive_secs, const void* proto, size_t proto_len,

// --------------------------------------------------------------------------
// In-process TensorFlow server functionality, for use in distributed training.
// A Server instance encapsulates a set of devices and a Session target that
// can participate in distributed training. A server belongs to a cluster
// (specified by a ClusterSpec), and corresponds to a particular task in a

toys

// trade : Elite Registry Limited
// https://www.iana.org/domains/root/db/trade.html
trade

// trading : Dog Beach, LLC
// https://www.iana.org/domains/root/db/trading.html
trading

// training : Binky Moon, LLC
// https://www.iana.org/domains/root/db/training.html
training

// travel : Dog Beach, LLC
// https://www.iana.org/domains/root/db/travel.html
travel