code: def _limit_sequence_length(sequences, max_len):
      assert max_len > 0
      new_sequences = []
      for sequence in sequences:
          while len(sequence) > max_len:
              new_sequences.append(sequence[:max_len])
              sequence = sequence[max_len:]
          assert 0 < len(sequence) <= max_len
          new_sequences.append(sequence)
      return new_sequences
  
imports: import collections
  import itertools
  import random
  import numpy
  import torch
  import torch.nn.functional
  import pfrl
  from pfrl import agent
  from pfrl.utils.batch_states import batch_states
  from pfrl.utils.mode_of_distribution import mode_of_distribution
  from pfrl.utils.recurrent import concatenate_recurrent_states, flatten_sequences_time_first, get_recurrent_state_at, mask_recurrent_state_at, one_step_forward, pack_and_forward
label_desc: Use image node_id 7 for calling a global function with example usage: _limit_sequence_length(sequences, max_len) and returns: new_sequences