code: def sum_constraint(samples: Tensor) -> Tensor:
      """Represents the constraint `samples.sum(dim=-1) > 0`.
  
      Args:
          samples: A `b x q x m`-dim Tensor.
  
      Returns:
          A `b x q`-dim Tensor representing constraint feasibility.
      """
      return -samples.sum(dim=-1)
  
imports: from __future__ import annotations
  import itertools
  import math
  from abc import abstractmethod
  from itertools import combinations, product
  from typing import Callable
  import torch
  from botorch.exceptions import UnsupportedError
  from botorch.utils import safe_math
  from botorch.utils.constants import get_constants_like
  from botorch.utils.objective import compute_smoothed_feasibility_indicator
  from botorch.utils.safe_math import _pareto, cauchy, fatmax, fatmaximum, fatminimum, fatmoid, fatplus, log_fatmoid, log_fatplus, log_softplus, logdiffexp, logexpit, logmeanexp, logplusexp, sigmoid, smooth_amax
  from botorch.utils.testing import BotorchTestCase
  from torch import finfo, Tensor
  from torch.nn.functional import softplus
label_desc: Use image node_id 1 for calling a global function with example usage: sum_constraint(samples) and returns: unknown