code: def __init__(
      self, torch_model: ScriptModule, device: Device, **kwargs
  ):
      super().__init__(**kwargs)
      self.model = torch_model.eval()
      if device.type is DeviceType.GPU:
          self.model.to(device.to_torch_format())
      self.device = device
      self._is_gpu_ready = self.device.type is DeviceType.GPU
  
file_path: nebuly/optimization/nebullvm/nebullvm/operations/inference_learners/torchscript.py
imports: from pathlib import Path
  from typing import Tuple, Union, Optional, List
  from nebullvm.core.models import Device, DeviceType, ModelParams
  from nebullvm.operations.inference_learners.base import PytorchBaseInferenceLearner, LearnerMetadata
  from nebullvm.optional_modules.torch import torch, symbolic_trace, Module, ScriptModule, GraphModule
  from nebullvm.tools.transformations import MultiStageTransformation
label_desc: Use image node_id 1 to create a new TorchScriptInferenceLearner object from inherited base classes: PytorchBaseInferenceLearner with example: obj = TorchScriptInferenceLearner(torch_model, device)