class_docstr: an UNet wrapper to implement additional operations in `forward()` method.
  
  ...
  
  Attributes
  ----------
  model : AcceleratedLightningModule
      the original nano-optimized model
docstr: Initialize the model.
code: def __init__(self, model: AcceleratedLightningModule):
      """Initialize the model."""
      super().__init__()
      self.model = model
      self.config = model.config
      self.in_channels = model.in_channels
  
file_path: BigDL/python/nano/src/bigdl/nano/diffusion/diffusers/modules/unet.py
imports: import torch
  from typing import Any, Dict, List, Optional, Tuple, Union
  from diffusers.models.unet_2d_condition import UNet2DConditionOutput
  from bigdl.nano.pytorch.model import AcceleratedLightningModule
  from bigdl.nano.deps.openvino.pytorch.model import PytorchOpenVINOModel
  from bigdl.nano.diffusion.utils.pipeline import get_dummy_unet_additional_residuals
label_desc: Use image node_id 1 to create a new NanoUNet object from inherited base classes: torch.nn with example: obj = NanoUNet(model)