class_docstr: The abstract dist sparse optimizer.
  
  Note: dgl dist sparse optimizer only work with dgl.distributed.DistEmbedding
  
  Parameters
  ----------
  params : list of DistEmbedding
      The list of DistEmbedding.
  lr : float
      The learning rate.
docstr: clean grad cache
docstr_tok: ["clean","grad","cache"]
code: def zero_grad(self):
      """clean grad cache"""
      self._clean_grad = True
  
imports: import abc
  import warnings
  from abc import abstractmethod
  from os.path import exists
  import torch
  import dgl
  from ....None import backend
  from ...dist_tensor import DistTensor
  from ...graph_partition_book import EDGE_PART_POLICY, NODE_PART_POLICY
  from ...nn.pytorch import DistEmbedding
  from .utils import alltoall, alltoallv
label_desc: Use image node_id 10 for calling the DistSparseGradOptimizer obj's underlying member method code with example usage: obj.zero_grad() without return types