class_docstr: Megatron specific extensions of torch Module with support
  for pipelining.
code: def __init__(
      self,
      config: ModelParallelConfig = None,
      share_token_embeddings=True,
  ):
      if not HAVE_MEGATRON_CORE:
          raise ImportError(
              "megatron-core was not found. Please see the NeMo README for installation instructions: https://github.com/NVIDIA/NeMo#megatron-gpt."
          )
      super(MegatronModule, self).__init__()
      self.config = config
      self.share_token_embeddings = share_token_embeddings
  
imports: import torch
  from torch.autograd import Variable
  from torch.nn.parameter import Parameter
  from nemo.collections.nlp.modules.common.megatron.utils import ApexGuardDefaults
  from nemo.utils import logging
label_desc: Use image node_id 1 to create a new MegatronModule object from inherited base classes: torch.nn with example: obj = MegatronModule(config, share_token_embeddings)