class_docstr: HDFS storage backend for saving ckpt
  
  This backend will be used when runner contains a CheckpointHook and
  CheckpointHook's out_dir starts with hdfs://
class_docstr_tok: ["HDFS","storage","backend","for","saving","ckpt","This","backend","will","be","used","when","runner","contains","a","CheckpointHook","and","CheckpointHook","'s","out_dir","starts","with","hdfs",":","\/\/"]
code: def get_text(self, filepath: str, encoding: str = "utf-8") -> str:
      temp_file = self._hdfs_to_local(filepath)
  
      with open(temp_file, encoding=encoding) as f:
          value_buf = f.read()
      os.remove(temp_file)
      return value_buf
  
imports: import os
  import re
  import tempfile
  import time
  import mmcv
  import numpy
  import torch
  import warnings
  from collections import OrderedDict
  from torch.optim import Optimizer
  from mmcv.runner import EpochBasedRunner, DistEvalHook
  from mmcv.runner.utils import get_host_info
  from mmcv.parallel import is_module_wrapper
  from mmcv.fileio.file_client import BaseStorageBackend
  from mmcv.utils.misc import is_list_of
  from mmcv.runner.checkpoint import CheckpointLoader
  from bigdl.orca.learn.pytorch.utils import get_batchsize
  from bigdl.dllib.utils.log4Error import invalidInputError
  from bigdl.orca.learn.pytorch.core.base_runner import BaseRunner
  from .distributed import MMDistributedDataParallel
  from typing import TYPE_CHECKING, Union, Any, Dict, List, Optional, Tuple, Callable
label_desc: Use image node_id 2 for calling the HDFSBackend obj's underlying member method code with example usage: obj.get_text(filepath, encoding) and returns: value_buf