class_docstr: The abstract sparse optimizer.
  
  Note: dgl sparse optimizer only work with dgl.NodeEmbedding
  
  Parameters
  ----------
  params : list of NodeEmbedding
      The list of NodeEmbeddings.
  lr : float
      The learning rate.
docstr: Load the optimizer states. This method must be called by all
  processes sharing the underlying embedding with identical
  :attr:`state_dict`.
  
  NOTE: This method must be called by all processes sharing the
  underlying embedding, or it may result in a deadlock.
  
  Parameters
  ----------
  state_dict : dictionary of optimizer states
      The global states to pull values from.
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code: def load_state_dict(
      self, state_dict, **kwargs
  ):  # pylint: disable=unused-argument
      """Load the optimizer states. This method must be called by all
      processes sharing the underlying embedding with identical
      :attr:`state_dict`.
  
      NOTE: This method must be called by all processes sharing the
      underlying embedding, or it may result in a deadlock.
  
      Parameters
      ----------
      state_dict : dictionary of optimizer states
          The global states to pull values from.
      """
      for emb in self._params:
          emb._all_set_optm_state(state_dict["state"][emb.name])
      self._set_param_groups(state_dict["param_groups"])
  
imports: import abc
  from abc import abstractmethod
  import torch
  from ...cuda import nccl
  from ...nn.pytorch import NodeEmbedding
  from ...partition import NDArrayPartition
  from ...utils import create_shared_mem_array, gather_pinned_tensor_rows, get_shared_mem_array, pin_memory_inplace, scatter_pinned_tensor_rows
label_desc: Use image node_id 11 for calling the SparseGradOptimizer obj's underlying member method code with example usage: obj.load_state_dict(state_dict) without return types