code: def video_pixel_noise_bottom(x, model_hparams, vocab_size):
    
    input_noise = getattr(model_hparams, "video_modality_input_noise", 0.25)
    inputs = x
    if model_hparams.mode == tf.estimator.ModeKeys.TRAIN:
      background = tfp.stats.percentile(inputs, 50., axis=[0, 1, 2, 3])
      input_shape = common_layers.shape_list(inputs)
      input_size = tf.reduce_prod(input_shape[:-1])
      input_mask = tf.multinomial(
          tf.log([[input_noise, 1.-input_noise]]), input_size)
      input_mask = tf.reshape(tf.cast(input_mask, tf.int32),
                              input_shape[:-1]+[1])
      inputs = inputs * input_mask + background * (1 - input_mask)
    return video_bottom(inputs, model_hparams, vocab_size)
docs: Bottom transformation for video.