code: def make_eval_transform(args: argparse.Namespace) -> torch.nn.Module:
      if args.eval_size is None:
          resize_size = args.crop_size
      else:
          resize_size = args.eval_size
  
      return StereoMatchingEvalPreset(
          mean=args.norm_mean,
          std=args.norm_std,
          use_grayscale=args.use_grayscale,
          resize_size=resize_size,
          interpolation_type=args.interpolation_strategy,
      )
  
file_path: vision/references/depth/stereo/parsing.py
imports: import argparse
  from functools import partial
  import torch
  from presets import StereoMatchingEvalPreset, StereoMatchingTrainPreset
  from torchvision.datasets import CarlaStereo, CREStereo, ETH3DStereo, FallingThingsStereo, InStereo2k, Kitti2012Stereo, Kitti2015Stereo, Middlebury2014Stereo, SceneFlowStereo, SintelStereo
label_desc: Use image node_id 2 for calling a global function with example usage: make_eval_transform(args) and returns: StereoMatchingEvalPreset