.Attr("Nresources: int >= 0")
    .Output("results: Tresults")
    .Attr("Tresults: list(type) >= 0")
    .Attr("function: func")
    // XLA random-number generation ops are stateful.
    // TODO(phawkins): create stateful and non-stateful variants of XlaLaunch.
    .SetIsStateful()
    .Doc("XLA Launch Op. For use by the XLA JIT only.");

REGISTER_OP("XlaLaunchV2")
    .Input("args: Targs")
    .Output("results: Tresults")

        def serializer = Mock(Serializer)
        def decoder = Mock(Decoder)
        def encoder = Mock(Encoder)

        given:
        def stateful = Serializers.stateful(serializer)
        def reader = stateful.newReader(decoder)
        def writer = stateful.newWriter(encoder)

        when:
        def result1 = reader.read()
        def result2 = reader.read()

        then:
        result1 == "one"

// TFL op interface for stateful operands.

def TFL_StatefulOp : OpInterface<"StatefulOpInterface"> {
  let description = [{
    Interface for ops that are stateful and need to identify stateful operands.

    Stateful operands correspond to TF's variables semantics. An op that has 1
    or more stateful operands is a stateful op.
  }];

  let methods = [
    InterfaceMethod<

 */
public interface ExternalComponentGraphResolveState extends ComponentGraphResolveState {

    /**
     * @deprecated Try to avoid using this. This method exposes legacy stateful metadata. Usages should be
     * replaced by using the stateful types like {@link ComponentGraphResolveState} and
     * {@link org.gradle.internal.component.model.ComponentArtifactResolveState}.
     */
    @Deprecated

import java.lang.annotation.Retention;
import java.lang.annotation.RetentionPolicy;
import java.lang.annotation.Target;

/**
 * Attached to a listener interface to indicate that its events are stateful.
 *
 * <p>The listener infrastructure will ensure that a listener of this type will either receive all events, or no events.

// merging same input values if they're identical. These optimizations are
// desirable but not for those TFLite ops which have variable tensors as inputs.
// Yes, they have identical input values, but those identical values are
// "stateful", their values can change during invocations.
//
// A typical example is unidirectional_sequence_lstm have two variable tensor
// inputs: activation state & cell state. They may have same initial values

 * limitations under the License.
 */

package org.gradle.internal.serialize;

public class Serializers {
    public static <T> StatefulSerializer<T> stateful(final Serializer<T> serializer) {
        return new StatefulSerializerAdapter<T>(serializer);
    }

    private static class StatefulSerializerAdapter<T> implements StatefulSerializer<T> {

Either side can use `rb.CloseWithError(err error)` to signal an error and close the ring buffer. 
Any reads or writes will return the error on next call.

 * Reuses these prefixes and suffixes to efficiently store names or parts of names it has seen before.
 *
 * This class is stateful. Use a new one for each serialization/deserialization attempt.
 */
public class HierarchicalNameSerializer extends AbstractSerializer<String> {

See the License for the specific language governing permissions and
limitations under the License.
==============================================================================*/

// This transformation pass converts stateful and stateless partitioned calls
// with _xla_compile_device_type attribute to XLA launch ops.

#include <stack>

#include "mlir/Support/LLVM.h"  // from @llvm-project