code: def compute_backward_degandrad(dtype, ndim, req, n):
      ishape = [tvm.te.size_var() for _ in range(ndim)]
      in_grad_tmp = tvm.te.placeholder(
          ishape, name="in_grad_tmp", dtype=dtype
      )
      in_grad = tvm.te.placeholder(ishape, name="in_grad", dtype=dtype)
      out_grad = tvm.te.placeholder(
          ishape, name="out_grad", dtype=dtype
      )
      import math
  
      if n == 0:
          ret = tvm.te.compute(
              ishape,
              lambda *index: out_grad[index]
              * tvm.tir.const(math.pi, dtype)
              / tvm.tir.const(180, dtype),
          )
      else:
          ret = tvm.te.compute(
              ishape,
              lambda *index: out_grad[index]
              / tvm.tir.const(math.pi, dtype)
              * tvm.tir.const(180, dtype),
          )
      if req == "kAddTo":
          in_grad = tvm.te.compute(
              ishape, lambda *index: in_grad_tmp[index] + ret[index]
          )
      else:
          in_grad = tvm.te.compute(ishape, lambda *index: ret[index])
      s = tvm.te.create_schedule(in_grad.op)
      return s, out_grad, in_grad_tmp, in_grad, [ret, in_grad]
  
file_path: mxnet/contrib/tvmop/basic/ufunc.py
imports: import tvm
  from ..None import defop, AllTypes, RealTypes
  from ..None import assign_by_req, reduce_axes
label_desc: Use image node_id 12 for calling a global function with example usage: compute_backward_degandrad(dtype, ndim, req, n) and returns: s,  out_grad,  in_grad_tmp,  in_grad,  list