code: def ProbitLinkMean(
      mean: torch.Tensor, var: torch.Tensor
  ) -> torch.Tensor:
      a = mean / torch.sqrt(1 + var)
      return torch.distributions.Normal(0, 1).cdf(a)
  
imports: from copy import deepcopy
  from typing import Any, Callable, Dict, List, Optional, Union
  import numpy
  import torch
  from ax.modelbridge.torch import TorchModelBridge
  from ax.models.torch.botorch import BotorchModel
  from ax.models.torch.botorch_modular.model import BoTorchModel
  from ax.utils.common.typeutils import checked_cast
  from botorch.models.model import Model, ModelList
  from botorch.posteriors.gpytorch import GPyTorchPosterior
  from botorch.sampling.normal import SobolQMCNormalSampler
  from botorch.utils.sampling import draw_sobol_samples
  from botorch.utils.transforms import unnormalize
  from torch import Tensor
label_desc: Use image node_id 2 for calling a global function with example usage: ProbitLinkMean(mean, var) and returns: torch