code: def backward(self, indexes, grad_outputs):
      a, b = self.get_retained_inputs()
      (g_sp,) = grad_outputs
      ret = []
      if 0 in indexes:
          g_a = CooMatMul(
              self.sp_row,
              self.sp_col,
              self.sp_shape,
              self.sp_order,
              self.transc,
              not self.transb,
              self.transa,
              dtype=a.dtype,
          ).apply((g_sp, b))[0]
          ret.append(g_a)
      if 1 in indexes:
          g_b = CooMatMul(
              self.sp_row,
              self.sp_col,
              self.sp_shape,
              self.sp_order,
              not self.transc,
              self.transa,
              not self.transb,
              dtype=b.dtype,
          ).apply((g_sp, a))[0]
          ret.append(g_b)
      return ret
  
imports: import numpy
  import chainer
  from chainer import backend
  from chainer.backends import cuda
  from chainer import function_node
  from chainer import utils
  from chainer.utils import type_check
label_desc: Use image node_id 4 for calling the CooMatMulGradSP obj's underlying member method code with example usage: obj.backward(indexes, grad_outputs) and returns: ret