quarkus/test-framework/junit5/pom.xml
quarkus/extensions/smallrye-fault-tolerance/deployment/pom.xml
	quarkus/core/deployment/pom.xml
	quarkus/extensions/arc/deployment/pom.xml
	quarkus/extensions/smallrye-context-propagation/deployment/pom.xml
	quarkus/extensions/mutiny/deployment/pom.xml
	quarkus/extensions/smallrye-fault-tolerance/runtime/pom.xml
	quarkus/test-framework/junit5-internal/pom.xml

*   Fixed a set of minor issues with Cluster Autoscaler 1.0.1 ([#54298](https://github.com/kubernetes/kubernetes/pull/54298),[ @mwielgus](https://github.com/mwielgus))
*   HPA tolerance is now configurable by setting the `horizontal-pod-autoscaler-tolerance` flag. ([#52275](https://github.com/kubernetes/kubernetes/pull/52275),[ @mattjmcnaughton](https://github.com/mattjmcnaughton))

    register a dataset with the tf.data service, and another process to consume
    data from the dataset.
*   Adds support for dispatcher fault tolerance. To enable fault tolerance,
    configure a `work_dir` when running your dispatcher server and set
    `dispatcher_fault_tolerance=True`. The dispatcher will store its state to

import org.junit.jupiter.api.Test

/**
 * Integration test to confirm that [TaskRunner] works with a real backend. Business logic is all
 * exercised by [TaskRunnerTest].
 *
 * This test is doing real sleeping with tolerances of 250 ms. Hopefully that's enough for even the
 * busiest of CI servers.
 */
@Tag("Slowish")
class TaskRunnerRealBackendTest {
  private val log = LinkedBlockingDeque<String>()

      ctx_.reset(ctx_raw);
    }

    // Computing numerical gradients with TensorFloat-32 is numerically
    // unstable. Some forward pass tests also fail with TensorFloat-32 due to
    // low tolerances
    enable_tensor_float_32_execution(false);
  }

  AbstractContextPtr ctx_;

 public:
  bool UseMlir() const { return strcmp(std::get<0>(GetParam()), "mlir") == 0; }

  }

  /*
   * Our implementation works fine with a null `dir`. However, there's nothing in the documentation
   * of the supertype that suggests that implementations are expected to tolerate null. That said, I
   * see calls in Google code that pass a null `dir` to a FilenameFilter.... So let's declare the
   * parameter as non-nullable (since passing null to a FilenameFilter is unsafe in general), but if

        // Returning successfully is not ideal, but tolerated.
      } catch (NullPointerException tolerated) {
      }
    } else {
      try {
        entrySet.retainAll(null);
        // We have to tolerate a successful return (Sun bug 4802647)
      } catch (UnsupportedOperationException | NullPointerException e) {
        // Expected.
      }
    }
    assertInvariants(map);
  }

   * identical inputs: This sounds like it ought to be a problem here, since the goals of this class
   * include testing that {@code equals()} is reflexive and is tolerant of {@code null}. However,
   * there's no problem. The reason: {@link EqualsTester} tests {@code null} and identical inputs
   * directly against {@code equals()} rather than through the {@code Equivalence}.
   */

     *
     * TODO(cpovirk): decide what the best long-term action here is: force users
     * to suppress (as we do now), stop testing entrySet().add() at all, make
     * entrySet().add() tests tolerant of either behavior, introduce a map
     * feature for entrySet() that supports add(), or something else
     */
    return asList(
        getAddUnsupportedNotPresentMethod(),

        // Returning successfully is not ideal, but tolerated.
      } catch (NullPointerException tolerated) {
      }
    } else {
      try {
        entrySet.retainAll(null);
        // We have to tolerate a successful return (Sun bug 4802647)
      } catch (UnsupportedOperationException | NullPointerException e) {
        // Expected.
      }
    }
    assertInvariants(map);
  }