code: def forward(self, X):
      return torch.ones(*X.shape[:-1]) * -1.0
  
imports: from typing import List
  import torch
  from botorch.acquisition import LinearMCObjective, ScalarizedPosteriorTransform
  from botorch.acquisition.acquisition import AcquisitionFunction
  from botorch.acquisition.analytic import ExpectedImprovement
  from botorch.acquisition.monte_carlo import qExpectedImprovement
  from botorch.acquisition.proximal import ProximalAcquisitionFunction
  from botorch.exceptions.errors import UnsupportedError
  from botorch.models import ModelListGP, SingleTaskGP
  from botorch.models.gpytorch import GPyTorchModel
  from botorch.models.model import Model
  from botorch.models.transforms.input import Normalize
  from botorch.utils.testing import BotorchTestCase
  from torch.distributions.multivariate_normal import MultivariateNormal
label_desc: Use image node_id 1 for calling the NegativeAcquisitionFunction obj's underlying member method code with example usage: obj.forward(X) and returns: unknown