class_docstr: inverse the seq_item, like this
      [1,2,3,0,0,0,0] -- after inverse -->> [0,0,0,0,1,2,3]
class_docstr_tok: ["inverse","the","seq_item",",","like","this","[","1,2,3,0,0,0,0","]","--","after","inverse","--",">",">","[","0,0,0,0,1,2,3","]"]
code: def __call__(self, dataset, interaction):
      item_seq = interaction[self.ITEM_SEQ]
      item_seq_len = interaction[self.ITEM_SEQ_LEN]
      device = item_seq.device
      item_seq = item_seq.cpu().numpy()
      item_seq_len = item_seq_len.cpu().numpy()
      new_item_seq = []
      for items, length in zip(item_seq, item_seq_len):
          item = list(items[:length])
          zeros = list(items[length:])
          seqs = zeros + item
          new_item_seq.append(seqs)
      inverse_item_seq = torch.tensor(
          new_item_seq, dtype=torch.long, device=device
      )
      new_dict = {self.INVERSE_ITEM_SEQ: inverse_item_seq}
      interaction.update(Interaction(new_dict))
      return interaction
  
imports: import math
  import numpy
  import random
  import torch
  from copy import deepcopy
  from recbole.data.interaction import Interaction, cat_interactions
label_desc: Use image node_id 2 for calling the InverseItemSequence obj's underlying member method code with example usage: obj.__call__(dataset, interaction) and returns: interaction