// Validate if bucket exists.
	objAPI := api.ObjectAPI()
	if objAPI == nil {
		writeErrorResponse(ctx, w, errorCodes.ToAPIErr(ErrServerNotInitialized), r.URL)
		return
	}

	vars := mux.Vars(r)
	bucketName := vars["bucket"]

	if bucketName == "" {
		if s3Error := checkRequestAuthType(ctx, r, policy.ListenNotificationAction, bucketName, ""); s3Error != ErrNone {

      exit 1
    fi
  fi
}

# detect-subnetworks sets the SUBNETWORK var if not already set
# Assumed vars:
#   NETWORK
#   REGION
#   NETWORK_PROJECT
#
# Optional vars:
#   SUBNETWORK
#   IP_ALIAS_SUBNETWORK
function detect-subnetworks() {
  if [[ -n ${SUBNETWORK:-} ]]; then
    echo "Using subnet ${SUBNETWORK}"

func varsToPrint(line, lookfor string) []string {
	var vars []string
	if strings.Contains(line, lookfor) {
		x := line[strings.Index(line, lookfor)+len(lookfor):]
		end := strings.Index(x, ")")
		if end == -1 {
			panic(fmt.Sprintf("Saw variable list begin %s in %s but no closing ')'", lookfor, line))
		}
		vars = strings.Split(x[:end], ",")
		for i, y := range vars {
			vars[i] = strings.TrimSpace(y)
		}
	}
	return vars

					state.varParts[n] = []SlotID{SlotID(len(state.slots) - 1)}
					state.vars = append(state.vars, n)
				}
			}
		}
	}

	// Fill in the var<->slot mappings.
	if cap(state.varSlots) < len(state.vars) {
		state.varSlots = make([][]SlotID, len(state.vars))
	} else {
		state.varSlots = state.varSlots[:len(state.vars)]
		for i := range state.varSlots {
			state.varSlots[i] = state.varSlots[i][:0]
		}

    TF_SetStatus(status, TF_OK, "");
    return;
  }
  std::vector<tensorflow::Var*> vars;
  std::vector<tensorflow::mutex*> mutexes;
  std::vector<int32_t> acquire_order;
  for (auto input : input_ids) {
    tensorflow::Var* var;
    tensorflow::mutex* mutex = GetTrainingVariableMutex(ctx, input, &var);
    if (var) vars.push_back(var);
    // Only lock each mutex once if duplicates exist (n^2 but n is 2 or 3).

				// each argument mapping to the ... parameter.
				vars := make([]*Var, npars-1) // npars > 0 for variadic functions
				copy(vars, sig.params.vars)
				last := sig.params.vars[npars-1]
				typ := last.typ.(*Slice).elem
				for len(vars) < nargs {
					vars = append(vars, NewParam(last.pos, last.pkg, last.name, typ))
				}
				sigParams = NewTuple(vars...) // possibly nil!
				adjusted = true
				npars = nargs

	ctx := r.Context()

	objectAPI, _ := validateAdminReq(ctx, w, r, policy.SiteReplicationOperationAction)
	if objectAPI == nil {
		return
	}

	vars := mux.Vars(r)
	bucket := vars["bucket"]
	operation := madmin.BktOp(vars["operation"])

	var err error
	switch operation {
	default:
		err = errSRInvalidRequest(errInvalidArgument)
	case madmin.MakeWithVersioningBktOp:

    std::string shared_name = handle.getSharedName().str();
    if (container.empty()) {
      return absl::StrCat("vars.", shared_name);
    } else {
      return absl::StrCat("vars.", container, ".", shared_name);
    }
  } else if (auto global = dyn_cast<tf_saved_model::GlobalTensorOp>(op)) {
    return absl::StrCat("vars.", global.getSymName().str());
  }
  return "<no name>";
}

func (s *state) push(name string, value reflect.Value) {
	s.vars = append(s.vars, variable{name, value})
}

// mark returns the length of the variable stack.
func (s *state) mark() int {
	return len(s.vars)
}

// pop pops the variable stack up to the mark.
func (s *state) pop(mark int) {
	s.vars = s.vars[0:mark]
}

// setVar overwrites the last declared variable with the given name.

    %0 = "tf.VarHandleOp"() {_class = ["loc:@dense/kernel"], allowed_devices = [], container = "", device = "/job:worker/replica:0/task:1/device:CPU:0", shared_name = "var1"} : () -> tensor<!tf_type.resource<tensor<100x50xf32>>>
    %1 = "tf.ReadVariableOp"(%0) {device = ""} : (tensor<!tf_type.resource<tensor<100x50xf32>>>) -> tensor<100x50xf32>
    func.return %1 : tensor<100x50xf32>
  }