code: def populate_packed_sequence(batch_size: int = 3) -> PackedSequence:
      len_sequence = range(30, (30 - 2 * batch_size), -2)
      lengths = torch.tensor(len_sequence)
      sequences_vectors = []
      for length in lengths:
          sequences_vectors.append(torch.rand(length, 1))
  
      padded_sequences_vectors = pad_sequence(sequences_vectors)
      pack_padded_sequences_vectors = pack_padded_sequence(
          padded_sequences_vectors, lengths.cpu()
      )
      return pack_padded_sequences_vectors
  
imports: from copy import deepcopy
  from unittest.mock import MagicMock
  import torch
  from torch.nn.utils.rnn import PackedSequence, pack_padded_sequence, pad_sequence
label_desc: Use image node_id 1 for calling a global function with example usage: populate_packed_sequence(batch_size) and returns: pack_padded_sequences_vectors