code: def __enter__(self):
      Module.load_state_dict = (
          lambda *args, **kwargs: _IncompatibleKeys([], [])
      )
      Module._load_from_state_dict = lambda *args, **kwargs: None
      Module.to = lambda self, *args, **kwargs: self
  
      def skip_init_on_meta(module_cls, *args, **kwargs):
          kwargs["device"] = "meta"
          return self._old_skip_init(module_cls, *args, **kwargs)
  
      torch.nn.utils.skip_init = skip_init_on_meta
  
imports: import torch
  import os
  import json
  from .transformers import ggml_convert_low_bit
  from torch.nn.modules import Module
  from torch.nn.modules.module import _IncompatibleKeys
  from accelerate import init_empty_weights
  from accelerate.utils import set_module_tensor_to_device
  from bigdl.llm.ggml.quantize import ggml_tensor_qtype
  from bigdl.llm.utils.common import invalidInputError
  from bigdl.llm.transformers.utils import extract_local_archive_file, get_local_shard_files
  import transformers
  import warnings
  from transformers import PreTrainedModel
  from .utils.common import MuteHFLogger
  from .utils.lazy_load_torch import LazyLoadTensors
  from contextlib import ExitStack, contextmanager
label_desc: Use image node_id 2 for calling the DisableTorchAllocTensor obj's underlying member method code with example usage: obj.__enter__() and returns: self