* canceled, even if this plan is canceled.
     */
    fun retry(): Plan?
  }

  /**
   * What to do once a plan has executed.
   *
   * If [nextPlan] is not-null, another attempt should be made by following it. If [throwable] is
   * non-null, it should be reported to the user should all further attempts fail.
   *

     */
    @Nonnull
    Map<String, String> systemProperties();

    /**
     * Returns the top-level directory of the Maven invocation.
     * This is typically the directory containing the POM file being executed.
     *
     * @return the top-level directory path
     */
    @Nonnull
    Path topDirectory();

    /**

    }
  }

  public void testVerifyGetsCalled() {
    TesterThatCountsCalls tester = new TesterThatCountsCalls();

    tester.test();

    assertEquals(
        "Should have verified once per stimulus executed",
        tester.numCallsToVerify,
        tester.numCallsToNewTargetIterator * STEPS);
  }

  public void testVerifyCanThrowAssertionThatFailsTest() {

struct LoggingDevice {
  tensorflow::string device_name;
  tensorflow::string underlying_device;
  // Set to true whenever a TensorHandle is copied onto the device
  bool* arrived_flag;
  // Set to true whenever an operation is executed
  bool* executed_flag;
  // If true, only explicit op placements are accepted. If false, uses
  // type-based dispatch.
  bool strict_scope_placement;
};

struct LoggedTensor {
  TFE_TensorHandle* tensor;

// a map (`tensorflow::eager::TensorTape`) from the wrapped tensor to the id of
// the op that produced it (or -1 if this tensor was watched using
// `GradientTape::Watch`.) The op_id is simply a unique index assigned to each
// op executed under the tape. A separate map (`tensorflow::eager::OpTape`)
// maintains the map from `op_id` to a `OpTapeEntry` which stores the `op_type`,
// inputs and outputs and the gradient function These data structures combined

 *
 * All event methods must execute fast, without external locking, cannot throw exceptions, attempt
 * to mutate the event parameters, or be re-entrant back into the client. Any IO - writing to files
 * or network should be done asynchronously.
 */
abstract class EventListener {
  /**
   * Invoked as soon as a call is enqueued or executed by a client. In case of thread or stream

    #   [true]
    #     The customize entities for procedure's out-parameter
    #     and not-param-result are auto-generated.
    #     And also not-param-result's properties are auto-generated.
    #     Target procedures are executed actually at Sql2Entity task.
    #     (because of getting from execution meta data (result set meta data))
    #     This property is valid only when isGenerateProcedureParameterBean is true.
    #

programs that TensorFlow executes. TensorFlow programs are encoded as
computation
[**graphs**](https://developers.google.com/machine-learning/glossary/#graph).
Since models are practically programs that TensorFlow executes, using untrusted
models or graphs is equivalent to running untrusted code.

If you need to run untrusted models, execute them inside a

#
#   JAVA_HOME           (Optional) Points to a Java installation.
#   MAVEN_ARGS          (Optional) Arguments passed to Maven before CLI arguments.
#   MAVEN_OPTS          (Optional) Java runtime options used when Maven is executed.
#   MAVEN_SKIP_RC       (Optional) Flag to disable loading of mavenrc files.

If the effect of an atomic operation <i>A</i> is observed by atomic operation <i>B</i>,
then <i>A</i> is synchronized before <i>B</i>.
All the atomic operations executed in a program behave as though executed
in some sequentially consistent order.
</p>

<p>
The preceding definition has the same semantics as C++’s sequentially consistent atomics
and Java’s <code>volatile</code> variables.
</p>