code: def get_ALEBO(
      experiment: Experiment,
      search_space: SearchSpace,
      data: Data,
      B: torch.Tensor,
      **model_kwargs: Any,
  ) -> TorchModelBridge:
      if search_space is None:
          search_space = experiment.search_space
      return TorchModelBridge(
          experiment=experiment,
          search_space=search_space,
          data=data,
          model=ALEBO(B=B, **model_kwargs),
          transforms=ALEBO_X_trans + ALEBO_Y_trans,
          torch_dtype=B.dtype,
          torch_device=B.device,
      )
  
file_path: Ax/ax/modelbridge/strategies/alebo.py
imports: from typing import Any, Dict, Optional
  import numpy
  import torch
  from ax.core.data import Data
  from ax.core.experiment import Experiment
  from ax.core.search_space import SearchSpace
  from ax.modelbridge.factory import DEFAULT_TORCH_DEVICE
  from ax.modelbridge.generation_strategy import GenerationStep, GenerationStrategy
  from ax.modelbridge.random import RandomModelBridge
  from ax.modelbridge.registry import ALEBO_X_trans, ALEBO_Y_trans
  from ax.modelbridge.torch import TorchModelBridge
  from ax.models.random.alebo_initializer import ALEBOInitializer
  from ax.models.torch.alebo import ALEBO
label_desc: Use image node_id 2 for calling a global function with example usage: get_ALEBO(experiment, search_space, data, B) and returns: TorchModelBridge