text: Title: encoder-decoder attention?
  Body: Dear Author,
  
  Thank you very much for the visualization tool. It is super helpful.                                 
  Now, we need to visualize the encoder-decoder attention instead of the self-attention. For instance, while using the following code, we only can visualize the self-attention one. It would be great if you can give some clue on how to visualize the encoder-decoder attention of BART. 
  
  ```
  from bertviz import model_view
  from bertviz import head_view
  from transformers import BartForConditionalGeneration, BartTokenizer
  model = BartForConditionalGeneration.from_pretrained("facebook/bart-large", force_bos_token_to_be_generated=True)
  tokenizer = BartTokenizer.from_pretrained('facebook/bart-large')
  sentence_a = "The cat sat on the mat"
  sentence_b = "The cat lay on the rug"
  inputs = tokenizer.encode_plus(sentence_a, sentence_b, return_tensors='pt', add_special_tokens=True)
  input_ids = inputs['input_ids']
  attention = model(input_ids,output_attentions=True)[2] ####
  #print (attention.size())
  input_id_list = input_ids[0].tolist() # Batch index 0
  tokens = tokenizer.convert_ids_to_tokens(input_id_list)
  model_view(attention, tokens)
  head_view(attention, tokens)
  ```
  Thank you!
  Best,
  Shirley