op_key: The unique key to identify this op.
    num_args: The number of inputs.
    device: The tensorflow device. eg. "/CPU:0"
    op_attrs: The tensorflow attributes excluding the func attrs.
    op_func_attrs: The func attrs.
    op_name: The tensorflow op name. eg. "tf.AddV2"

    Example:
      %out_ch = tfrt_fallback_async.createop(%in_ch) key(0) device("/CPU:0")

    <T> T selectOutputWithFailureLogging(T stdout, T stderr);

    /**
     * Returns true if this version logs different build outcome messages for tooling API requests that run tasks and to requests that do not run tasks (eg fetch a model).
     */
    boolean isToolingApiLogsConfigureSummary();

    /**
     * Returns true if this version generates a build operation that wraps the execution phase
     */

     * the include and exclude patterns of this source directory set. Generally, the filter patterns are used to
     * restrict the contents to certain types of files, eg {@code *.java}.
     *
     * @return The filter patterns.
     */
    PatternFilterable getFilter();

    /**
     * Configure the directory to assemble the compiled classes into.
     *

		if source, ok := pod.Annotations[ConfigSourceAnnotationKey]; ok {
			return source, nil
		}
	}
	return "", fmt.Errorf("cannot get source of pod %q", pod.UID)
}

// SyncPodType classifies pod updates, eg: create, update.
type SyncPodType int

const (
	// SyncPodSync is when the pod is synced to ensure desired state
	SyncPodSync SyncPodType = iota
	// SyncPodUpdate is when the pod is updated from source

	FilterChains []FilterChainTest

	// Assert the listener contains these ListenerFilters (in order, if TotalMatch)
	Filters []string

	// TotalMatch will require that the all elements exactly match (eg, if I have 3 elements in the
	// check, the listener must as well). Otherwise, we only validate the assertions we provided are
	// present.
	TotalMatch bool
}

type FilterChainTest struct {

setattr(_current_module, "optimizers", _optimizers)
setattr(_current_module, "initializers", _initializers)


# Do an eager load for Keras' code so that any function/method that needs to
# happen at load time will trigger, eg registration of optimizers in the
# SavedModel registry.
# See b/196254385 for more details.
try:
  if _tf_uses_legacy_keras:
    importlib.import_module("tf_keras.src.optimizers")
  else:

	cmd.PersistentFlags().StringVar(&args.common.watchedNamespaces, "watchedNamespaces", constants.IstioSystemNamespace,
		"The namespaces the operator controller watches, could be namespace list separated by comma, eg. 'ns1,ns2'")
	cmd.PersistentFlags().StringVarP(&args.common.manifestsPath, "charts", "", "", ChartsDeprecatedStr)
	cmd.PersistentFlags().StringVarP(&args.common.manifestsPath, "manifests", "d", "", ManifestsFlagHelpStr)

            }
            return instance.get();
        }
    }

    private Try<T> instantiate() {
        // TODO - extract some shared infrastructure to take care of instantiation (eg which services are visible, strict vs lenient, decorated or not?)
        // TODO - should hold the project lock to do the isolation. Should work the same way as artifact transforms (a work node does the isolation, etc)

            // The parameters of the transforms should already be isolated prior to visiting this set.
            // However, in certain cases, the transform's parameters may not be isolated (eg https://github.com/gradle/gradle/issues/23116), so do this now
            // Those cases should be improved so that the parameters are always isolated, for example by always using work nodes to do this work

	// FileNameFunc specifies the name a new file will take.
	// FileNameFunc must ensure collisions in filenames do not occur.
	// Do not rely on timestamps to be unique, high throughput writes
	// may fall on the same timestamp.
	// Eg.
	// 	2020-03-28_15-00-945-<random-hash>.log
	// When FileNameFunc is not specified, DefaultFilenameFunc will be used.
	FileNameFunc func() string

	// Compress specify if you want the logs to be compressed after rotation.