code: def backward(ctx, dc):
      # saved for backward
      a, b = ctx.saved_tensors
      mode = ctx.mode
      # gradients w.r.t. a
      if ctx.needs_input_grad[0]:
          mode_da = mode[1] + mode[0] + mode[2]
          da = _sparse_matmul.fn[mode_da](
              dc,
              b,
              False,
              not ctx.trans_b,
              ctx.trans_a,
              ctx.spdims,
              ctx.block,
              ctx.da_lut,
              ctx.da_num_locks,
              ctx.da_width,
              ctx.da_packs,
              ctx.da_bench,
              ctx.da_time,
          )
      # gradients w.r.t. b
      if ctx.needs_input_grad[1]:
          mode_db = mode[2] + mode[1] + mode[0]
          db = _sparse_matmul.fn[mode_db](
              a,
              dc,
              not ctx.trans_a,
              False,
              ctx.trans_b,
              ctx.spdims,
              ctx.block,
              ctx.db_lut,
              ctx.db_num_locks,
              ctx.db_width,
              ctx.db_packs,
              ctx.db_bench,
              ctx.db_time,
          )
      return (
          da,
          db,
          None,
          None,
          None,
          None,
          None,
          None,
          None,
          None,
          None,
          None,
          None,
          None,
          None,
          None,
          None,
          None,
          None,
          None,
          None,
          None,
          None,
          None,
          None,
          None,
          None,
      )
  
imports: import importlib
  import torch
  import triton
  import triton.language
  import triton._C.libtriton
  from deepspeed.accelerator import get_accelerator
label_desc: Use image node_id 9 for calling the _sparse_matmul obj's underlying member method code with example usage: obj.backward(ctx, dc) and returns: da,  db,  None,  None,  None,  None,  None,  None,  None,  None,  None,  None,  None,  None,  None,  None,  None,  None,  None,  None,  None,  None,  None,  None,  None,  None,  None