MOCK_METHOD(absl::StatusOr<std::string>, SerializeExecutable,
              (const xla::LocalExecutable& executable), (override));
  MOCK_METHOD(absl::StatusOr<std::string>, BuildSerializedExecutable,
              (const XlaCompiler::Options& options,
               const XlaCompiler::CompilationResult& result),
              (override));
  MOCK_METHOD(absl::StatusOr<std::unique_ptr<xla::LocalExecutable>>,

#include <optional>
#include <string>
#include <utility>
#include <vector>

#include <gmock/gmock.h>
#include <gtest/gtest.h>
#include "absl/status/status.h"
#include "absl/status/statusor.h"
#include "absl/strings/string_view.h"
#include "llvm/ADT/STLExtras.h"
#include "mlir/IR/BuiltinOps.h"  // from @llvm-project
#include "mlir/IR/OwningOpRef.h"  // from @llvm-project

#include "tensorflow/compiler/mlir/quantization/common/lift_as_function_call.h"

#include <gmock/gmock.h>
#include <gtest/gtest.h>
#include "absl/algorithm/container.h"
#include "absl/status/status.h"
#include "absl/status/statusor.h"
#include "absl/strings/string_view.h"
#include "llvm/ADT/SmallVector.h"
#include "mlir/Dialect/Func/IR/FuncOps.h"  // from @llvm-project
#include "mlir/IR/Attributes.h"  // from @llvm-project

std::vector<TensorHandlePtr> DeviceThread::Join(TF_Status* status) {
  std::vector<TensorHandlePtr> result;
  {
    tensorflow::mutex_lock l(execution_mutex_);
    while (execution_state_ != ExecutionState::kHasResult) {
      finished_execute_.wait(l);
    }
    if (TF_GetCode(status_.get()) != TF_OK) {
      TF_SetStatus(status, TF_GetCode(status_.get()),
                   TF_Message(status_.get()));

#include "tensorflow/core/lib/core/status_test_util.h"
#include "tensorflow/core/platform/errors.h"
#include "tensorflow/core/platform/notification.h"
#include "tensorflow/core/platform/status.h"
#include "tensorflow/core/platform/status_matchers.h"
#include "tensorflow/core/platform/statusor.h"

namespace tensorflow {
namespace {
using ::testing::_;
using ::testing::Return;

using XlaDeviceCompiler =

#include <utility>
#include <vector>

#include "absl/algorithm/container.h"
#include "absl/container/flat_hash_map.h"
#include "absl/container/flat_hash_set.h"
#include "absl/log/log.h"
#include "absl/status/status.h"
#include "absl/status/statusor.h"
#include "absl/strings/str_cat.h"
#include "absl/strings/string_view.h"
#include "absl/types/span.h"
#include "llvm/ADT/SmallVector.h"
#include "mlir/IR/BuiltinOps.h"  // from @llvm-project

      TF_NewStatus(), TF_DeleteStatus);
  int assign = TF_OpIsStateful("AssignAddVariableOp", status.get());
  ASSERT_EQ(TF_OK, TF_GetCode(status.get())) << TF_Message(status.get());
  EXPECT_EQ(assign, 1);
  int id = TF_OpIsStateful("Identity", status.get());
  ASSERT_EQ(TF_OK, TF_GetCode(status.get())) << TF_Message(status.get());
  EXPECT_EQ(id, 0);
}

class ShapeInferenceTest : public ::testing::Test {
 protected:

	testHandlerWithHealth(hcs, nsn3, http.StatusOK, 7, true, t)
	testHandlerWithHealth(hcs, nsn4, http.StatusOK, 6, true, t)
}

func testHandler(hcs *server, nsn types.NamespacedName, status int, endpoints int, t *testing.T) {
	tHandler(hcs, nsn, status, endpoints, true, t)
}

func testHandlerWithHealth(hcs *server, nsn types.NamespacedName, status int, endpoints int, kubeProxyHealthy bool, t *testing.T) {

    }
    auto imm_t =
        static_cast<tensorflow::ImmediateExecutionTensorHandle*>(abstract_t);
    tensorflow::Status status;
    t.reset(imm_t->Resolve(&status));
    if (!status.ok()) {
      return status;
    }
  }
  if (data.size() != t->NumElements()) {
    return tensorflow::errors::InvalidArgument(absl::StrCat(

	}
}

func resourceClaimStatusesEqual(statusA, statusB []api.PodResourceClaimStatus) bool {
	if len(statusA) != len(statusB) {
		return false
	}
	// In most cases, status entries only get added once and not modified.
	// But this cannot be guaranteed, so for the sake of correctness in all
	// cases this code here has to check.
	for i := range statusA {
		if statusA[i].Name != statusB[i].Name {
			return false
		}