code: def get_sequence(center_idx, half_len, sample_rate, num_frames):
      """
      Sample frames among the corresponding clip.
  
      Args:
          center_idx (int): center frame idx for current clip
          half_len (int): half of the clip length
          sample_rate (int): sampling rate for sampling frames inside of the clip
          num_frames (int): number of expected sampled frames
  
      Returns:
          seq (list): list of indexes of sampled frames in this clip.
      """
      seq = list(
          range(
              center_idx - half_len, center_idx + half_len, sample_rate
          )
      )
  
      for seq_idx in range(len(seq)):
          if seq[seq_idx] < 0:
              seq[seq_idx] = 0
          elif seq[seq_idx] >= num_frames:
              seq[seq_idx] = num_frames - 1
      return seq
  
imports: import logging
  import numpy
  import os
  import random
  import time
  from collections import defaultdict
  import cv2
  import torch
  from torch.utils.data.distributed import DistributedSampler
  from torchvision import transforms
  from slowfast.utils.env import pathmgr
  from .None import transform
  from .random_erasing import RandomErasing
  from .transform import create_random_augment
label_desc: Use image node_id 2 for calling a global function with example usage: get_sequence(center_idx, half_len, sample_rate, num_frames) and returns: seq