title: Using nlp.pipe() with pre-segmented and pre-tokenized text with spaCy
body: <p>I am trying to tag and parse text that has already been split up in sentences and has already been tokenized. As an example:</p>
  
  <pre class="lang-py prettyprint-override"><code>sents = [['I', 'like', 'cookies', '.'], ['Do', 'you', '?']]
  </code></pre>
  
  <p>The fastest approach to process batches of text is <code>.pipe()</code>. However, it is not clear to me how I can use that with pre-tokenized, and pre-segmented text. Performance is key here. I tried the following, but that threw an error</p>
  
  <pre class="lang-py prettyprint-override"><code>docs = [nlp.tokenizer.tokens_from_list(sentence) for sentence in sents]
  nlp.tagger(docs)
  nlp.parser(docs)
  </code></pre>
  
  <p>Trace:</p>
  
  <pre><code>Traceback (most recent call last):
    File "C:\Python\Python37\Lib\multiprocessing\pool.py", line 121, in worker
      result = (True, func(*args, **kwds))
    File "C:\Python\projects\PreDicT\predicting-wte\build_id_dictionary.py", line 204, in process_batch
      self.nlp.tagger(docs)
    File "pipes.pyx", line 377, in spacy.pipeline.pipes.Tagger.__call__
    File "pipes.pyx", line 396, in spacy.pipeline.pipes.Tagger.predict
    File "C:\Users\bmvroy\.virtualenvs\predicting-wte-YKqW76ba\lib\site-packages\thinc\neural\_classes\model.py", line 169, in __call__
      return self.predict(x)
    File "C:\Users\bmvroy\.virtualenvs\predicting-wte-YKqW76ba\lib\site-packages\thinc\neural\_classes\feed_forward.py", line 40, in predict
      X = layer(X)
    File "C:\Users\bmvroy\.virtualenvs\predicting-wte-YKqW76ba\lib\site-packages\thinc\neural\_classes\model.py", line 169, in __call__
      return self.predict(x)
    File "C:\Users\bmvroy\.virtualenvs\predicting-wte-YKqW76ba\lib\site-packages\thinc\neural\_classes\model.py", line 133, in predict
      y, _ = self.begin_update(X, drop=None)
    File "C:\Users\bmvroy\.virtualenvs\predicting-wte-YKqW76ba\lib\site-packages\thinc\neural\_classes\feature_extracter.py", line 14, in begin_update
      features = [self._get_feats(doc) for doc in docs]
    File "C:\Users\bmvroy\.virtualenvs\predicting-wte-YKqW76ba\lib\site-packages\thinc\neural\_classes\feature_extracter.py", line 14, in &lt;listcomp&gt;
      features = [self._get_feats(doc) for doc in docs]
    File "C:\Users\bmvroy\.virtualenvs\predicting-wte-YKqW76ba\lib\site-packages\thinc\neural\_classes\feature_extracter.py", line 21, in _get_feats
      arr = doc.doc.to_array(self.attrs)[doc.start : doc.end]
  AttributeError: 'list' object has no attribute 'doc'
  </code></pre>