code: def concat_sequences(
      sequences: Union[List[torch.Tensor], List[rnn.PackedSequence]]
  ) -> Union[torch.Tensor, rnn.PackedSequence]:
      """
      Concatenate RNN sequences.
  
      Args:
          sequences (Union[List[torch.Tensor], List[rnn.PackedSequence]): list of RNN packed sequences or tensors of which
              first index are samples and second are timesteps
  
      Returns:
          Union[torch.Tensor, rnn.PackedSequence]: concatenated sequence
      """
      if isinstance(sequences[0], rnn.PackedSequence):
          return rnn.pack_sequence(sequences, enforce_sorted=False)
      elif isinstance(sequences[0], torch.Tensor):
          return torch.cat(sequences, dim=1)
      elif isinstance(sequences[0], (tuple, list)):
          return tuple(
              concat_sequences(
                  [sequences[ii][i] for ii in range(len(sequences))]
              )
              for i in range(len(sequences[0]))
          )
      else:
          raise ValueError("Unsupported sequence type")
  
imports: from collections import namedtuple
  from contextlib import redirect_stdout
  import inspect
  import os
  from typing import Any, Callable, Dict, List, Tuple, Union
  import lightning.pytorch
  import torch
  from torch import nn
  from torch.fft import irfft, rfft
  import torch.nn.functional
  from torch.nn.utils import rnn
label_desc: Use image node_id 9 for calling a global function with example usage: concat_sequences(sequences) and returns: rnn, torch, tuple