docstr: Computes the sum of gradients of the given tensor w.r.t. graph leaves.
docstr_tok: ["Computes","the","sum","of","gradients","of","the","given","tensor","w.r.t",".","graph","leaves","."]
code: def backward(self, loss):
      """Computes the sum of gradients of the given tensor w.r.t. graph leaves."""
      loss.backward()
  
imports: import torch
  from fairseq import utils
  from fairseq.dataclass.utils import gen_parser_from_dataclass
  from collections import defaultdict
label_desc: Use image node_id 13 for calling the FairseqOptimizer obj's underlying member method code with example usage: obj.backward(loss) without return types