class_docstr: This object contains a DeepSpeed configuration dictionary and can be quickly queried for things like zero stage.
  
  A `weakref` of this object is stored in the module's globals to be able to access the config from areas where
  things like the Trainer object is not available (e.g. `from_pretrained` and `_get_resized_embeddings`). Therefore
  it's important that this object remains alive while the program is still running.
  
  [`Trainer`] uses the `HfTrainerDeepSpeedConfig` subclass instead. That subclass has logic to sync the configuration
  with values of [`TrainingArguments`] by replacing special placeholder values: `"auto"`. Without this special logic
  the DeepSpeed configuration is not modified in any way.
  
  Args:
      config_file_or_dict (`Union[str, Dict]`): path to DeepSpeed config file or dict.
code: def __init__(self, config_file_or_dict):
      # set global weakref object
      set_hf_deepspeed_config(self)
      dep_version_check("accelerate")
      dep_version_check("deepspeed")
      super().__init__(config_file_or_dict)
  
imports: import importlib.metadata
  import importlib.util
  import weakref
  from functools import partialmethod
  from ..dependency_versions_check import dep_version_check
  from ..utils import is_accelerate_available, is_torch_available, logging
label_desc: Use image node_id 1 to create a new HfDeepSpeedConfig object from inherited base classes: DeepSpeedConfig with example: obj = HfDeepSpeedConfig(config_file_or_dict)