code: def augment_train_example(example, num_frames=30, stride=1):
      """Augment the given video for training.
  
      Args:
        example: dict; Example that has an 'inputs'.
        num_frames: Number of frames per subclip.
        stride: Temporal stride to sample frames.
  
      Returns:
        dict; Example that has an 'inputs'.
      """
      frames = example["inputs"]
      frames = processors.sample_sequence(
          frames, num_frames, True, stride
      )
      frames = processors.random_flip_left_right(frames)
      return {"inputs": frames}
  
file_path: scenic/scenic/dataset_lib/bair_dataset.py
imports: import functools
  from typing import Optional
  from absl import logging
  from dmvr import processors
  from flax import jax_utils
  import jax.numpy
  from scenic.dataset_lib import dataset_utils
  from scenic.dataset_lib import datasets
  import tensorflow
label_desc: Use image node_id 2 for calling a global function with example usage: augment_train_example(example, num_frames, stride) and returns: dict