class_docstr: NOTE: If you are using this feature with a container that
  also inherits from `HybridEngineContainer`, ensure that `MetaTensorContainer`
  is inherited before `HybridEngineContainer` in the class definition.
class_docstr_tok: ["NOTE",":","If","you","are","using","this","feature","with","a","container","that","also","inherits","from","`","HybridEngineContainer","`",",","ensure","that","`","MetaTensorContainer","`","is","inherited","before","`","HybridEngineContainer","`","in","the","class","definition","."]
code: def __init__(self, **kwargs):
      if pkg_version.parse("1.10") > pkg_version.parse(
          torch.__version__
      ):
          raise NotImplementedError(
              "Meta tensor support is not available, please upgrade to torch 1.10+"
          )
      super().__init__(**kwargs)
      self.is_meta = False
      self.ckpt_load_enabled = True
  
file_path: DeepSpeed/deepspeed/module_inject/containers/features/meta_tensor.py
imports: from abc import ABC, abstractmethod
  from packaging import version
  import torch
label_desc: Use image node_id 1 to create a new MetaTensorContainer object from inherited base classes: ABC with example: obj = MetaTensorContainer()