return {};

  // First tensor dimension is dynamic.
  auto arg_ty = tensor.getType().dyn_cast<ShapedType>();
  if (!arg_ty || !arg_ty.hasRank() || arg_ty.getNumDynamicDims() != 1 ||
      !arg_ty.isDynamicDim(0))
    return {};

  // Argument tensor rank is equal to the number of packed dimensions.
  if (arg_ty.getRank() != getValues().size()) return {};

(Add64  (Const64 [c])  (Const64 [d]))  => (Const64 [c+d])
(Add32F (Const32F [c]) (Const32F [d])) && c+d == c+d => (Const32F [c+d])
(Add64F (Const64F [c]) (Const64F [d])) && c+d == c+d => (Const64F [c+d])
(AddPtr <t> x (Const64 [c])) => (OffPtr <t> x [c])
(AddPtr <t> x (Const32 [c])) => (OffPtr <t> x [int64(c)])

(Sub8   (Const8 [c]) (Const8 [d]))     => (Const8 [c-d])
(Sub16  (Const16 [c]) (Const16 [d]))   => (Const16 [c-d])

	allglock mutex
	allgs    []*g

	// allglen and allgptr are atomic variables that contain len(allgs) and
	// &allgs[0] respectively. Proper ordering depends on totally-ordered
	// loads and stores. Writes are protected by allglock.
	//
	// allgptr is updated before allglen. Readers should read allglen
	// before allgptr to ensure that allglen is always <= len(allgptr). New

		arns = append(arns, rCfg.RoleArn)
	} else {
		for _, rule := range rCfg.Rules {
			arns = append(arns, rule.Destination.String())
		}
	}
	var sameTarget bool
	for _, arnStr := range arns {
		arn, err := madmin.ParseARN(arnStr)
		if err != nil {
			return sameTarget, errorCodes.ToAPIErrWithErr(ErrBucketRemoteArnInvalid, err)
		}
		if arn.Type != madmin.ReplicationService {