code: def simclr_style_augmentation(frames, height, width, zero_centre):
      """Applies SimCLR-style random augmentations to frames.
  
      Args:
        frames: `Tensor` of shape [timesteps, height, width, 3].
        height: Image height.
        width: Image width.
        zero_centre: Bool. If true, frames are between [-1. 1]. Otherwise, they are
          in the range [0, 1]
  
      Returns:
        A Tensor of shape [timesteps, height, width, channels] being random
        augmented with the same operation.
      """
      num_frames = frames.shape[0]
      frames = simclr_aug_fn(frames, num_frames)
      blur_frames = batch_random_blur(frames, height, width)
      solarize_frames = random_solarization(blur_frames)
      reversed_frames = random_time_reverse(solarize_frames)
      reversed_frames = tf.clip_by_value(reversed_frames, 0.0, 1.0)
  
      if zero_centre:
          return reversed_frames * 2.0 - 1.0
      else:
          return reversed_frames
  
imports: import functools
  import math
  from typing import Optional
  from absl import logging
  from dmvr import builders
  from dmvr import processors
  import simclr.tf2.data_util
  import tensorflow
  from official.vision.image_classification import augment
label_desc: Use image node_id 9 for calling a global function with example usage: simclr_style_augmentation(frames, height, width, zero_centre) and returns: unknown, reversed_frames