class_docstr: Implement multiple optimizers needed for sparse adam
class_docstr_tok: ["Implement","multiple","optimizers","needed","for","sparse","adam"]
docstr: ?
docstr_tok: ["?"]
code: def step(self):
      """?"""
      for op in self.optimizers:
          op.step()
  
imports: import torch
  import torch.optim
  from torch.nn.utils import clip_grad_norm_
  import operator
  import functools
  from copy import copy
  from math import sqrt
  import types
  import os
  import importlib
  from onmt.utils.misc import fn_args
label_desc: Use image node_id 4 for calling the MultipleOptimizer obj's underlying member method code with example usage: obj.step() without return types