code: def forward(self, x):
      with torch.no_grad():
          prediction = self.model(x)
      return prediction
  
file_path: lavis/lavis/common/annotator/midas/api.py
imports: import cv2
  import os
  import torch
  import torch.nn
  from torchvision.transforms import Compose
  from .midas.dpt_depth import DPTDepthModel
  from .midas.midas_net import MidasNet
  from .midas.midas_net_custom import MidasNet_small
  from .midas.transforms import Resize, NormalizeImage, PrepareForNet
  from annotator.util import annotator_ckpts_path
label_desc: Use image node_id 2 for calling the MiDaSInference obj's underlying member method code with example usage: obj.forward(x) and returns: prediction