code: def eval_lin_constraint(
      x: np.ndarray,
      flat_idxr: List[int],
      coeffs: np.ndarray,
      rhs: float,
  ) -> np.float64:
      r"""Evaluate a single linear constraint.
  
      Args:
          x: The input array.
          flat_idxr: The indices in `x` to consider.
          coeffs: The coefficients corresponding to the indices.
          rhs: The right-hand-side of the constraint.
  
      Returns:
          The evaluted constraint: `\sum_i (coeffs[i] * x[i]) - rhs`
      """
      return np.sum(x[flat_idxr] * coeffs, -1) - rhs
  
imports: from __future__ import annotations
  from functools import partial
  from typing import Callable, Dict, List, Optional, Tuple, Union
  import numpy
  import torch
  from botorch.exceptions.errors import CandidateGenerationError, UnsupportedError
  from scipy.optimize import Bounds
  from torch import Tensor
label_desc: Use image node_id 3 for calling a global function with example usage: eval_lin_constraint(x, flat_idxr, coeffs, rhs) and returns: unknown