Augmenting the LSTM PoS tagger with Character-level features (PyTorch)

LSTMAug.ipynb

Hello @jhumigas,

I tried out the code you have compiled for the character level LSTM. It generates the following error (with traceback):
Can you help me figure out what has gone wrong?
Thank you.

IndexError                                Traceback (most recent call last)
<ipython-input-11-16c14b79baf2> in <module>
      6 inputs = prepare_sequence(training_data[0][0], word_to_ix)
      7 words_tensors = prepare_words_tensor(word_to_ix, char_to_ix)
----> 8 tag_scores = model(inputs, words_tensors)
      9 # print(tag_scores)
     10 

~/anaconda3/lib/python3.7/site-packages/torch/nn/modules/module.py in __call__(self, *input, **kwargs)
    530             result = self._slow_forward(*input, **kwargs)
    531         else:
--> 532             result = self.forward(*input, **kwargs)
    533         for hook in self._forward_hooks.values():
    534             hook_result = hook(self, input, result)

<ipython-input-8-6bb1b6181605> in forward(self, sentence_seq, words_tensor_dict)
     66             # Now here we will only keep the final hidden state of the character level LSTM
     67             # i.e lstm_char_out[-1]
---> 68             embeds_cat = torch.cat((embeds, lstm_char_out[-1]), dim=1)
     69 
     70             lstm_out, self.hidden_words = self.lstm_words(embeds_cat, self.hidden_words)

IndexError: Dimension out of range (expected to be in range of [-1, 0], but got 1)```