class_docstr: A function that scores inputs with respect
  to a specific criterion.
docstr: Args:
      inputs: inputs (of shape n x d)
  
  Returns:
      A tensor of quality scores for each input, of shape [n]
docstr_tok: ["Args",":","inputs",":","inputs","(","of","shape","n","x","d",")","Returns",":","A","tensor","of","quality","scores","for","each","input",",","of","shape","[","n","]"]
code: def __call__(self, inputs: Tensor) -> Tensor:  # [n, d] -> [n]
      """
      Args:
          inputs: inputs (of shape n x d)
  
      Returns:
          A tensor of quality scores for each input, of shape [n]
      """
  
imports: from __future__ import annotations
  from abc import ABC, abstractmethod
  from typing import Union
  import torch
  from botorch.exceptions.errors import UnsupportedError
  from botorch.models.model import Model
  from botorch.utils.probability.utils import ndtr, phi
  from gpytorch.module import Module
  from linear_operator.operators import LinearOperator
  from torch import Tensor
label_desc: Use image node_id 1 for calling the QualityFunction obj's underlying member method code with example usage: obj.__call__(inputs) without return types