class_docstr: Multi-layer BiLSTM model for language detecting. A recreation of "A reproduction of Apple's bi-directional LSTM models
  for language identification in short strings." (Toftrup et al 2021)
  
  Arxiv: https://arxiv.org/abs/2102.06282
  GitHub: https://github.com/AU-DIS/LSTM_langid
  
  This class is similar to https://github.com/AU-DIS/LSTM_langid/blob/main/src/LSTMLID.py
code: def prediction_scores(self, x):
      prediction_probs = self(x)
      if self.lang_subset:
          prediction_batch_size = prediction_probs.size()[0]
          batch_mask = torch.stack(
              [self.lang_mask for _ in range(prediction_batch_size)]
          )
          prediction_probs = prediction_probs + batch_mask
      return torch.argmax(prediction_probs, dim=1)
  
file_path: stanza/stanza/models/langid/model.py
imports: import os
  import torch
  import torch.nn
label_desc: Use image node_id 5 for calling the LangIDBiLSTM obj's underlying member method code with example usage: obj.prediction_scores(x) and returns: torch