class_docstr: Persistent buffer for main gradients that remains allocated between training iterations
code: def get_allreduce_tensor(self):
      if (
          self.computed_numel_per_chunk[self.current_chunk]
          == self.numel_per_chunk[self.current_chunk]
      ):
          chunk_start_index = self.start_index_per_chunk[
              self.current_chunk
          ]
          chunk_end_index = (
              chunk_start_index
              + self.numel_per_chunk[self.current_chunk]
          )
          allreduce_tensor = self.data[
              chunk_start_index:chunk_end_index
          ]
  
          self.computed_numel_per_chunk[self.current_chunk] = 0
          self.current_chunk += 1
          if self.current_chunk == self.num_chunks:
              self.current_chunk = 0
  
          return allreduce_tensor
  
      return None
  
imports: from contextlib import contextmanager
  import torch
  from nemo.utils import logging
label_desc: Use image node_id 6 for calling the GradBucket obj's underlying member method code with example usage: obj.get_allreduce_tensor() and returns: None, allreduce_tensor