#include "tensorflow/compiler/tf2xla/xla_helpers.h"
#include "xla/client/client_library.h"
#include "xla/stream_executor/platform_manager.h"
#include "tensorflow/core/lib/monitoring/cell_reader.h"
#include "tensorflow/core/lib/monitoring/test_utils.h"
#include "tensorflow/core/platform/env.h"
#include "tensorflow/core/platform/test.h"
#include "tensorflow/core/protobuf/config.pb.h"

#include "mlir/IR/OwningOpRef.h"  // from @llvm-project
#include "mlir/Parser/Parser.h"  // from @llvm-project
#include "tensorflow/compiler/mlir/register_common_dialects.h"
#include "tensorflow/core/lib/monitoring/cell_reader.h"
#include "tensorflow/core/platform/resource_loader.h"
#include "tsl/lib/core/status_test_util.h"

namespace tensorflow {
namespace tf2xla {
namespace v2 {
namespace {

#include "tensorflow/core/lib/monitoring/cell_reader.h"
#include "tsl/platform/statusor.h"

namespace tensorflow {
namespace tf2xla {
namespace internal {

namespace {

using ::mlir::LogicalResult;
using ::mlir::ModuleOp;
using ::mlir::mhlo::test::GetMlirModuleFromString;
using ::tensorflow::monitoring::testing::CellReader;

#include "tensorflow/core/lib/core/status_test_util.h"
#include "tensorflow/core/lib/monitoring/cell_reader.h"
#include "tsl/lib/core/status_test_util.h"
#include "tsl/platform/statusor.h"

namespace mlir::quant::stablehlo {
namespace {

using ::mlir::DialectRegistry;
using ::mlir::MLIRContext;
using ::mlir::ModuleOp;
using ::mlir::OwningOpRef;
using ::tensorflow::monitoring::testing::CellReader;
using ::testing::Test;

 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */

/**
 * Classes for monitoring build configuration.
 */
@org.gradle.api.NonNullApi

#include "tensorflow/compiler/mlir/tf2xla/transforms/passes.h"
#include "tensorflow/core/lib/monitoring/cell_reader.h"
#include "tsl/platform/statusor.h"

namespace tensorflow {
namespace {

using ::mlir::MLIRContext;
using ::mlir::ModuleOp;
using ::mlir::OwningOpRef;
using ::mlir::PassManager;
using ::tensorflow::monitoring::testing::CellReader;

absl::StatusOr<OwningOpRef<ModuleOp>> GetMlirModuleFromString(

#include "tensorflow/compiler/mlir/tensorflow/ir/tf_device.h"
#include "tensorflow/compiler/mlir/tensorflow/ir/tf_executor.h"
#include "tensorflow/compiler/mlir/tensorflow/utils/attribute_utils.h"
#include "tensorflow/core/lib/monitoring/cell_reader.h"
#include "tensorflow/core/platform/resource_loader.h"
#include "tsl/lib/core/status_test_util.h"
#include "tsl/platform/status.h"

namespace tensorflow {
namespace tf2xla {
namespace v2 {

	"istio.io/istio/pkg/kube/controllers"
	"istio.io/istio/pkg/kube/kclient"
	"istio.io/istio/pkg/log"
	"istio.io/istio/pkg/monitoring"
)

const (
	MultiClusterSecretLabel = "istio/multiCluster"
)

var (
	clusterLabel = monitoring.CreateLabel("cluster")
	timeouts     = monitoring.NewSum(
		"remote_cluster_sync_timeouts_total",

== Performance Monitoring

Gradle actively monitors heap usage to detect memory leaks in the Daemon.

When a memory leak exhausts available heap space, the Daemon:

. Finishes the currently running build.
. Restarts before running the next build.

Gradle enables this monitoring by default.

#include "tensorflow/core/framework/op_def.pb.h"
#include "tensorflow/core/framework/tensor.pb.h"
#include "tensorflow/core/lib/io/path.h"
#include "tensorflow/core/lib/monitoring/counter.h"
#include "tensorflow/core/lib/monitoring/sampler.h"
#include "tensorflow/core/lib/strings/str_util.h"
#include "tensorflow/core/lib/strings/strcat.h"
#include "tensorflow/core/platform/env.h"
#include "tensorflow/core/platform/errors.h"