class_docstr: The LSTM-encoder-decoder module. Both the encoder and decoder are LSTMs.
  
  :meta private:
code: def init_hidden_state(self, batch_size):
      h = torch.zeros(
          (self.n_layers[0], batch_size, self.hidden_size)
      ).to(self.device)
      c = torch.zeros(
          (self.n_layers[0], batch_size, self.hidden_size)
      ).to(self.device)
      return h, c
  
imports: from typing import Sequence
  import numpy
  import pandas
  from merlion.models.base import NormalizingConfig
  from merlion.models.anomaly.base import DetectorBase, DetectorConfig
  from merlion.post_process.threshold import AggregateAlarms
  from merlion.utils.misc import ProgressBar, initializer
  from merlion.models.utils.rolling_window_dataset import RollingWindowDataset
label_desc: Use image node_id 2 for calling the LSTMEDModule obj's underlying member method code with example usage: obj.init_hidden_state(batch_size) and returns: h,  c