code: def input_shape(self) -> torch.Size:
      if self.max_sequence_length:
          return torch.Size([self.max_sequence_length, self.input_size])
      return torch.Size([self.input_size])
  
file_path: ludwig/ludwig/modules/recurrent_modules.py
imports: import logging
  from typing import Optional
  import torch
  from torch.nn import GRU, LSTM, RNN
  from ludwig.utils.misc_utils import get_from_registry
  from ludwig.utils.torch_utils import LudwigModule
label_desc: Use image node_id 2 for calling the RecurrentStack obj's underlying member method code with example usage: obj.input_shape() and returns: torch, torch