</dependencies>
				<configuration>
					<target>
						<ant antfile="${basedir}/dbflute.xml" target="download.dbflute" />
						<ant antfile="${basedir}/module.xml" target="install.modules">
							<property name="with.fess" value="true" />
							<property name="opensearch.version" value="${opensearch.version}" />
						</ant>
						<ant antfile="${basedir}/plugin.xml" target="install.plugins">

EOF

  # Get the full list of files and targets which get included into the pip
  # package
  bazel cquery --keep_going 'deps(//tensorflow/tools/pip_package:wheel)' | sort -u > $BATS_TEST_TMPDIR/pip_deps
  # Find all Python py_test targets not tagged "no_pip" or "manual", excluding
  # any targets in ignored packages. Combine this list of targets into a bazel
  # query list (e.g. the list becomes "target+target2+target3")

	errs := make([]error, len(proxyTargets.Targets))
	tagSlc := make([]map[string]string, len(proxyTargets.Targets))
	for idx, t := range proxyTargets.Targets {
		tgt := globalBucketTargetSys.GetRemoteTargetClient(bucket, t.Arn)
		if tgt == nil || globalBucketTargetSys.isOffline(tgt.EndpointURL()) {
			continue
		}
		// if proxying explicitly disabled on remote target
		if tgt.disableProxy {
			continue
		}

  // once unless the tape is persistent) and produces the gradient of the target
  // tensors with respect to the source tensors. The output gradients are used
  // if not empty and not null. The result is populated with one tensor per
  // target element.
  absl::Status ComputeGradient(
      AbstractContext* ctx, absl::Span<AbstractTensorHandle* const> targets,
      absl::Span<AbstractTensorHandle* const> sources,

# START MACOS CROSS-COMPILE CONFIGS
build:cross_compile_macos_x86 --config=cross_compile_base
build:cross_compile_macos_x86 --config=nonccl
# Target Catalina (10.15) as the minimum supported OS
build:cross_compile_macos_x86 --action_env  MACOSX_DEPLOYMENT_TARGET=10.15

# Set the target CPU to Darwin x86
build:cross_compile_macos_x86 --platforms=//tensorflow/tools/toolchains/cross_compile/config:darwin_x86_64

)

# To avoid duplication, check that the C++ or python library does not depend on
# the stream executor cuda plugins. Targets that want to use cuda APIs should
# instead depend on the dummy plugins in @local_tsl//tsl/platform/default/build_config
# and use header only targets.
# TODO(ddunleavy): This seems completely broken. :tensorflow_cc depends on
# cuda_platform from tf_additional_binary_deps and this doesn't break.

        final SystemHelper systemHelper = ComponentUtil.getSystemHelper();
        final String[] targets = fessConfig.getThumbnailGeneratorTargetsAsArray();
        final List<ThumbnailQueue> list = new ArrayList<>();
        taskList.stream().filter(entity -> entity != null).forEach(task -> {
            for (final String target : targets) {
                final ThumbnailQueue entity = new ThumbnailQueue();

- Admin UI: http://localhost:8080/admin/ (default username/password is admin/admin)

![Admin UI](https://fess.codelibs.org/_images/fess_admin_dashboard.png)

You can register crawling targets in the Admin UI on the (Web, File, Data Store) crawler configuration pages, and then start the Crawler manually on the [Scheduler page](https://fess.codelibs.org/14.17/admin/scheduler-guide.html).

  }

  private void expectReturnsTrue(Target target) {
    String message = Platform.format("retainAll(%s) should return true", target);
    assertTrue(message, collection.retainAll(target.toRetain));
  }

  private void expectReturnsFalse(Target target) {
    String message = Platform.format("retainAll(%s) should return false", target);
    assertFalse(message, collection.retainAll(target.toRetain));
  }

 * All others can simply be copied from source to target to restore the locationTracker
 *
 * @since 4.0.0
 * @deprecated use {@link org.apache.maven.api.services.ModelBuilder} instead
 */
@Deprecated(since = "4.0.0")
class FileToRawModelMerger extends MavenMerger {

    @Override
    protected void mergeBuild_Extensions(