type ConfigGenerator interface {
	// BuildListeners returns the list of inbound/outbound listeners for the given proxy. This is the LDS output
	// Internally, the computation will be optimized to ensure that listeners are computed only
	// once and shared across multiple invocations of this function.
	BuildListeners(node *model.Proxy, push *model.PushContext) []*listener.Listener

import java.util.Set;

/**
 * Collects all registered processors' supported options.
 *
 * <p>This is a workaround for https://bugs.openjdk.java.net/browse/JDK-8162455, which
 * will be triggered a lot more during incremental compilations, and can fail builds
 * when combined with {@code -Werror}.
 *
 * <p>This processor needs to be added last to make sure that all other processors
 * have been {@linkplain Processor#init(ProcessingEnvironment) initialized} when

  }
}

// The number of times a lazy compilation must be requested for a specific
// signature before  we attempt to compile it.
constexpr int64_t kDefaultCompilationThreshold = 2;

// Maximum number of ongoing compilations.
constexpr int64_t kMaxNumOngoingCompilations = kNumAsyncDeviceCompilerThreads;

}  // namespace

DeviceCompilationProfiler::~DeviceCompilationProfiler() {
  mutex_lock lock(mu_);
  cluster_compile_stats_.clear();

            public T completeAndGet() {
                return successfulResult;
            }
        };
    }

    /**
     * An invocation with no pre-computed result, requiring to do the expensive computation on {@link #completeAndGet()}.
     */
    static <T> Deferrable<T> deferred(Supplier<T> result) {
        return new Deferrable<T>() {
            private volatile T value;

            @Override

// TFL op interface for sparse operands.

def TFL_SparseOp : OpInterface<"SparseOpInterface"> {
  let description = [{
    Interface for ops that support sparse computation.
  }];

  let methods = [
    InterfaceMethod<
      [{Returns the indices of sparse operands.}],
      "std::vector<int>", "GetSparseOperands", (ins)
    >,
    InterfaceMethod<

}

tensorflow::XlaCompilationResult CreateXlaComputationResult(
    const char* hlo_name) {
  auto result = tensorflow::XlaCompilationResult();
  xla::HloModuleProto hlo;
  hlo.set_name(hlo_name);
  result.computation = std::make_shared<xla::XlaComputation>(hlo);
  return result;
}

TEST(TestUtil, ComputationContainsOk) {
  constexpr char arbitrary_hlo[] = "arbitrary_hlo";
  auto result = CreateXlaComputationResult(arbitrary_hlo);

   *     ExecutionException} is thrown <a
   *     href="https://github.com/google/guava/wiki/CachesExplained#interruption">even if
   *     computation was interrupted by an {@code InterruptedException}</a>.)
   * @throws UncheckedExecutionException if an unchecked exception was thrown while loading the
   *     value

# out if the fake clang doesn't work.
env CGO_ENABLED=1

# The bug in https://go.dev/issue/64423 resulted in cache keys that
# didn't contain any information about the C compiler.
# Since the bug was in cache key computation, isolate the cache:
# if we change the way caching works, we want the test to fail
# instead of accidentally reusing the cached information from a
# previous test run.
env GOCACHE=$WORK${/}.cache
mkdir $GOCACHE

#include "tensorflow/compiler/mlir/tensorflow/ir/tf_ops.h"

namespace mlir {
namespace TFTPU {

namespace {

// This pass removes Identity/IdentityN ops from the TPU computation and
// reachable functions.
// TODO(lyandy): Remove this pass once resource op lifting is migrated to use
// resource alias analysis and support region based control flow. Removing

   * expected</i>, but not absolutely required, to have the following properties:
   *
   * <ul>
   *   <li>Its execution does not cause any observable side effects.
   *   <li>The computation is <i>consistent with equals</i>; that is, {@link Objects#equal
   *       Objects.equal}{@code (a, b)} implies that {@code Objects.equal(function.apply(a),
   *       function.apply(b))}.
   * </ul>
   *