class_docstr: Intel Habana(HPU) accelerators.
class_docstr_tok: ["Intel","Habana","(","HPU",")","accelerators","."]
docstr: Attempt to check if HPU backend is initialized.
  Returns:
      True if backend initialized else False.
docstr_tok: ["Attempt","to","check","if","HPU","backend","is","initialized",".","Returns",":","True","if","backend","initialized","else","False","."]
code: def is_initialized() -> bool:
      """Attempt to check if HPU backend is initialized.
      Returns:
          True if backend initialized else False.
      """
      if HPU_PACKAGE_AVAILABLE:
          import habana_frameworks.torch.hpu as torch_hpu
  
          if torch_hpu.is_available() and torch_hpu.is_initialized():
              return True
          else:
              return False
      else:
          return False
  
file_path: ray/python/ray/_private/accelerators/hpu.py
imports: import os
  import logging
  from typing import Optional, List, Tuple
  from functools import lru_cache
  from importlib.util import find_spec
  from ray._private.accelerators.accelerator import AcceleratorManager
label_desc: Use image node_id 5 for calling the HPUAcceleratorManager obj's underlying member method code with example usage: obj.is_initialized() and returns: False, True, False