const SavedModelBundle& bundle,
      std::optional<absl::Span<const std::string>> exported_names,
      mlir::MLIRContext* context, tensorflow::MLIRImportOptions options) {
    // debug_info might not be loaded with loader_lite.
    GraphDebugInfo debug_info;
    if (bundle.debug_info != nullptr) debug_info = *bundle.debug_info;

    TF_ASSIGN_OR_RETURN(auto input,

  for (int i = 0; i < tags_len; i++) {
    tag_set.insert(string(tags[i]));
  }

  tensorflow::SavedModelBundle bundle;
  status->status =
      tensorflow::LoadSavedModel(session_options->options, run_options_proto,
                                 export_dir, tag_set, &bundle);
  if (!status->status.ok()) return nullptr;

  // Create a TF_Graph from the MetaGraphDef. This is safe as long as Session

			},
			"", "",
		},
		{
			"simple with client bundle",
			&networking.ServerTLSSettings{
				Mode:              networking.ServerTLSSettings_SIMPLE,
				ServerCertificate: "Captain Jean-Luc Picard",
				PrivateKey:        "Khan Noonien Singh",
				CaCertificates:    "Commander William T. Riker",
			},
			"", "",
		},
		{
			"simple sds with client bundle",
			&networking.ServerTLSSettings{

		}
		// Since `apiRouter` satisfies `http.Handler` it has a ServeHTTP to execute the logic of the handler.
		// Call the ServeHTTP to execute the handler,`func (api objectAPIHandlers) GetObjectHandler`  handles the request.
		apiRouter.ServeHTTP(rec, req)

		// Assert the response code with the expected status.
		if rec.Code != testCase.expectedRespStatus {

                       ResourceEffects::TPUExecute::get());

  // Conservatively mark resource handles as read and write, as without
  // analyzing TPUCompile, there is not sufficient information to determine
  // effects on resources. For the MLIR bridge, this op will never be
  // populated with resource handles and tf.TPUExecuteAndUpdateVariables is
  // used instead.
  for (Value value : getArgs()) {

	// Cached MachineInfo returned by cadvisor.
	machineInfoLock sync.RWMutex
	machineInfo     *cadvisorapi.MachineInfo

	// Handles certificate rotations.
	serverCertificateManager certificate.Manager

	// Cloud provider interface.
	cloud cloudprovider.Interface
	// Handles requests to cloud provider with timeout
	cloudResourceSyncManager cloudresource.SyncManager

    decomposition/lifting occurs with the unpartitioned resource variables,
    transforming the IR in such a manner will allow for subsequent passes to operate
    on individual resource variable handles per core/device.

    For example, the following:

    ```mlir
    func @cluster(%arg0: tensor<!tf_type.resource<tensor<i32>>>, %arg1: tensor<!tf_type.resource<tensor<i32>>>) {

  //       the indices arugment,
  //     - first tranpose op takes perm [2, 1, 0, 3], and
  //     - second transpose op take perm [1, 2, 0, 3].
  //
  // Note the current pattern matching logic only handles when width == height.
  LogicalResult matchAndRewrite(TFL::GatherNdOp gather_nd_first,
                                PatternRewriter &rewriter) const override {
    auto result_value = gather_nd_first.getResult();

//			000000000000013d:  IMAGE_REL_AMD64_REL32	_errno
//
// The assembly below dispenses with the import symbol and just makes
// a direct call to _errno.
//
// The code below handles indirect refs by redirecting the target of
// the relocation from "__imp_XYZ" to "XYZ" (since the latter symbol
// is what the Windows loader is expected to resolve). For direct refs

			v = AppendValidation(v, fmt.Errorf("ISTIO_MUTUAL TLS cannot have associated private key"))
		}
		if tls.CaCertificates != "" {
			v = AppendValidation(v, fmt.Errorf("ISTIO_MUTUAL TLS cannot have associated CA bundle"))
		}
		if tls.CredentialName != "" {
			v = AppendValidation(v, fmt.Errorf("ISTIO_MUTUAL TLS cannot have associated credentialName"))
		}
		return
	}