code: def from_torch_model(
      cls,
      model: ScriptModule,
      network_parameters: ModelParams,
      device: Device,
      input_tfms: Optional[MultiStageTransformation] = None,
      input_data: DataManager = None,
  ):
      return cls(
          torch_model=model,
          network_parameters=network_parameters,
          input_tfms=input_tfms,
          input_data=input_data,
          device=device,
      )
  
file_path: nebuly/optimization/nebullvm/nebullvm/operations/inference_learners/blade_disc.py
imports: from typing import Optional
  from nebullvm.core.models import ModelParams, Device
  from nebullvm.operations.inference_learners.torchscript import TorchScriptInferenceLearner
  from nebullvm.optional_modules.torch import ScriptModule
  from nebullvm.tools.data import DataManager
  from nebullvm.tools.transformations import MultiStageTransformation
label_desc: Use image node_id 1 for calling the BladeDISCInferenceLearner obj's underlying member method code with example usage: obj.from_torch_model(cls, model, network_parameters, device, input_tfms, input_data) and returns: cls