class_docstr: Augmentation used to generate a mask for Vision Transformers
  Typically used in approaches such as iBOT (https://arxiv.org/pdf/2111.07832.pdf)
code: def from_config(cls, config: Dict[str, Any]) -> "MaskedImageModeling":
      return cls(
          pred_ratio_mean=config.get("pred_ratio_mean", [0.3]),
          pred_ratio_var=config.get("pred_ratio_var", [0.0]),
          patch_size=config.get("patch_size", 16),
          log_aspect_ratio=config.get(
              "log_aspect_ratio", (0.3, 1 / 0.3)
          ),
      )
  
file_path: vissl/vissl/data/ssl_transforms/masked_image_modeling.py
imports: import math
  import random
  from typing import Any, Dict, List, Tuple
  import numpy
  import torch
  from classy_vision.dataset.transforms import register_transform
  from classy_vision.dataset.transforms.classy_transform import ClassyTransform
label_desc: Use image node_id 3 for calling the MaskedImageModeling obj's underlying member method code with example usage: obj.from_config(cls, config) and returns: cls