code: def make_train_transform(args: argparse.Namespace) -> torch.nn.Module:
      return StereoMatchingTrainPreset(
          resize_size=args.resize_size,
          crop_size=args.crop_size,
          rescale_prob=args.rescale_prob,
          scaling_type=args.scaling_type,
          scale_range=args.scale_range,
          scale_interpolation_type=args.interpolation_strategy,
          use_grayscale=args.use_grayscale,
          mean=args.norm_mean,
          std=args.norm_std,
          horizontal_flip_prob=args.flip_prob,
          gpu_transforms=args.gpu_transforms,
          max_disparity=args.max_disparity,
          spatial_shift_prob=args.spatial_shift_prob,
          spatial_shift_max_angle=args.spatial_shift_max_angle,
          spatial_shift_max_displacement=args.spatial_shift_max_displacement,
          spatial_shift_interpolation_type=args.interpolation_strategy,
          gamma_range=args.gamma_range,
          brightness=args.brightness_range,
          contrast=args.contrast_range,
          saturation=args.saturation_range,
          hue=args.hue_range,
          asymmetric_jitter_prob=args.asymmetric_jitter_prob,
      )
  
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 1 for calling a global function with example usage: make_train_transform(args) and returns: StereoMatchingTrainPreset