import jakarta.annotation.Resource;

public class AllJobScheduler implements LaJobScheduler {

    private static final Logger logger = LogManager.getLogger(AllJobScheduler.class);

    protected static final String APP_TYPE = "JOB";

    @Resource
    private TimeManager timeManager;

    @Resource
    private FessConfig fessConfig;

    @Resource
    private AccessContextLogic accessContextLogic;

    @Resource

    private static final Logger logger = LogManager.getLogger(FessBaseAction.class);

    /** The application type for FESs, e.g. used by access context. */
    protected static final String APP_TYPE = "FES"; // #change_it_first

    /** The user type for Admin, e.g. used by access context. */
    protected static final String USER_TYPE = "A";

fi

git clone --filter=tree:0 "https://${REPO}" "${API_TMP}" && cd "${API_TMP}"
git checkout "${SHA}"
if [ ! -f "${API_TMP}/kubernetes/customresourcedefinitions.gen.yaml" ]; then
  echo "Generated Custom Resource Definitions file does not exist in the commit SHA ${SHA}. Not updating the CRD file."
  exit
fi
rm -f "${ROOTDIR}/manifests/charts/base/files/crd-all.gen.yaml"

        return fessConfig.getFesenHttpUrl();
    }

    public static String getAppType() {
        final String appType = System.getenv(FESS_APP_TYPE);
        if (StringUtil.isNotBlank(appType)) {
            return appType;
        }
        return StringUtil.EMPTY;
    }

    public static OptionalEntity<String> getOverrideConfPath() {

                           TF_Status* s) {
  unwrap(o)->outputs.push_back(unwrap(tensor));
}

void TF_AbstractOpSetOpType(TF_AbstractOp* op, const char* const op_type,
                            TF_Status* s) {
  tsl::Set_TF_Status_from_Status(
      s, unwrap(op)->Reset(op_type,
                           /*raw_device_name=*/nullptr));
}

void TF_AbstractOpSetOpName(TF_AbstractOp* op, const char* const op_name,

TF_AbstractOp* TF_NewAbstractOp(TF_ExecutionContext* ctx);
void TF_DeleteAbstractOp(TF_AbstractOp*);

// TODO(srbs): Add APIs for specifying attrs etc.
// `op_type` must outlive `op`.
void TF_AbstractOpSetOpType(TF_AbstractOp* op, const char* const op_type,
                            TF_Status* s);
// `op_name` must outlive `op`.
void TF_AbstractOpSetOpName(TF_AbstractOp* op, const char* const op_name,

  TF_Graph* parent;
  TF_Output* parent_inputs;
};

struct TF_OperationDescription {
  TF_OperationDescription(TF_Graph* g, const char* op_type,
                          const char* node_name)
      : node_builder(node_name, op_type, g->graph.op_registry()), graph(g) {}

  tensorflow::NodeBuilder node_builder;
  TF_Graph* graph;
  std::set<tensorflow::string> colocation_constraints;
};

// `GradientTape::Watch`.) The op_id is simply a unique index assigned to each
// op executed under the tape. A separate map (`tensorflow::eager::OpTape`)
// maintains the map from `op_id` to a `OpTapeEntry` which stores the `op_type`,
// inputs and outputs and the gradient function These data structures combined
// allow us to trace the data dependencies between operations and hence compute
// gradients.
//