// `oper` and `num_dims` with the corresponding number of dimensions. On return,
// for every i where `num_dims[i]` > 0, `dims[i]` will be an array of
// `num_dims[i]` elements. A value of -1 for `num_dims[i]` indicates that the
// i-th shape in the list is unknown.
//
// The elements of `dims` will point to addresses in `storage` which must be
// large enough to hold at least `storage_size` int64_ts.  Ideally, `num_shapes`

  // once) and produces the gradient of the target tensors with respect to the
  // source tensors. The output gradients are used if not empty and not
  // null. The result is populated with one tensor per target element.
  // When running backward functions, builds zeros-like tensors for
  // incoming grads which are nullptrs, unless `build_default_zeros_grads`
  // is set to false.
  Status ComputeGradient(