>>> import spacy
>>> nlp = spacy.load('en')
>>> text = 'The library respects your time, and tries to avoid wasting it.'
>>> text_with_ws = ' '.join(text.split())
>>> text_with_lb = '\n'.join(text.split())
>>> doc = nlp(text)
>>> print([t.pos_ for t in doc])
['DET', 'NOUN', 'VERB', 'ADJ', 'NOUN', 'PUNCT', 'CCONJ', 'VERB', 'PART', 'VERB', 'VERB', 'PRON', 'PUNCT']
>>> doc = nlp(text_with_ws)
>>> print([t.pos_ for t in doc if t.pos_ is not 'SPACE'])
['DET', 'NOUN', 'VERB', 'ADJ', 'NOUN', 'PUNCT', 'CCONJ', 'VERB', 'PART', 'VERB', 'VERB', 'PRON', 'PUNCT']
>>> doc = nlp(text_with_lb)
>>> print([t.pos_ for t in doc if t.pos_ is not 'SPACE'])
['DET', 'NOUN', 'NOUN', 'ADJ', 'NOUN', 'PUNCT', 'CCONJ', 'NOUN', 'PART', 'NOUN', 'NOUN', 'PRON', 'PUNCT']
现在,我不明白spacy的卷积神经网络是如何工作的,但预期会有不同的结果吗?