assertEquals(Boolean.TRUE, pom.getValue("reporting/excludeDefaults"));
        assertPathSuffixEquals("docs", pom.getValue("reporting/outputDirectory"));

        assertEquals(1, ((List<?>) pom.getValue("reporting/plugins")).size());
        assertEquals("org.apache.maven.its.plugins", pom.getValue("reporting/plugins[1]/groupId"));
        assertEquals("maven-it-plugin-reporting", pom.getValue("reporting/plugins[1]/artifactId"));

            }

            Reporting reporting = m.getReporting();
            if (reporting != null) {
                for (ReportPlugin p : reporting.getPlugins()) {
                    validateStringNotEmpty(
                            "reporting.plugins.plugin.artifactId",
                            problems,
                            Severity.ERROR,

            }
        }
        return Collections.unmodifiableList(list);
    }

    @Deprecated
    public void setReporting(Reporting reporting) {
        getModel().setReporting(reporting);
    }

    @Deprecated
    public Reporting getReporting() {
        return getModel().getReporting();
    }

    @Deprecated

                                execution. While this /may/ work fine, please look for plugin updates and/or \
                                request plugins be made thread-safe. If reporting an issue, report it against the \
                                plugin in question, not against Apache Maven.""")) {
                        logger.warn(s);
                    }

    * This fixed environments where CPU and Memory Accounting were not enabled on the unit that launched the kubelet or docker from reporting the root cgroup when monitoring usage stats for those components.
* New default horizontalpodautoscaler/v1 generator for kubectl autoscale. ([#26775](https://github.com/kubernetes/kubernetes/pull/26775), [@piosz](https://github.com/piosz))

    return entryHelper.valueStrength().defaultEquivalence();
  }

  // ConcurrentMap methods

  @Override
  public boolean isEmpty() {
    /*
     * Sum per-segment modCounts to avoid mis-reporting when elements are concurrently added and
     * removed in one segment while checking another, in which case the table was never actually
     * empty at any point. (The sum ensures accuracy up through at least 1<<31 per-segment

        if (depMgmt == null) {
            return;
        }

        String importing = model.getGroupId() + ':' + model.getArtifactId() + ':' + model.getVersion();

        importIds.add(importing);

        final WorkspaceModelResolver workspaceResolver = request.getWorkspaceModelResolver();

# build is static and TensorFlow symbols (in Python only) are loaded into the
# global symbol table in order to support op registration. This means that
# projects building with Bazel and importing TensorFlow as a dependency will not
# depend on libtensorflow_framework.so unless they opt in.
tf_cc_shared_library(
    name = "tensorflow_framework",
    additional_linker_inputs = [

  }

  /**
   * Enable the accumulation of {@link CacheStats} during the operation of the cache. Without this
   * {@link Cache#stats} will return zero for all statistics. Note that recording stats requires
   * bookkeeping to be performed with each operation, and thus imposes a performance penalty on
   * cache operation.
   *
   * @return this {@code CacheBuilder} instance (for chaining)

# errors.
# There is ongoing work on Bazel team's side to provide support for transitive
# shared libraries. As part of migrating to transitive shared libraries, we
# hope to provide a better mechanism for control over symbol exporting, and
# then tackle this issue again.
#
# TODO: Remove the following two lines once TF doesn't depend on Bazel wrapping
# all library archives in -whole_archive -no_whole_archive.