class_docstr: Megatron specific extensions of torch Module with support
  for pipelining.
code: def sync_initial_word_embeddings(self):
      if torch.distributed.is_initialized():
          if (
              parallel_state.is_rank_in_embedding_group()
              and self.share_token_embeddings
          ):
              torch.distributed.all_reduce(
                  self.word_embeddings_weight().data,
                  group=parallel_state.get_embedding_group(),
              )
      else:
          logging.warning(
              "WARNING! Distributed processes aren't initialized, so "
              "word embeddings in the last layer are not synchronized. "
              "If you are just manipulating a model this is fine, but "
              "this needs to be handled manually. If you are training "
              "something is definitely wrong."
          )
  
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 8 for calling the MegatronModule obj's underlying member method code with example usage: obj.sync_initial_word_embeddings() without return types