How do I evaluate a n-gram language model with NLTK?

I have a corpus with a list of sentences and I want to build a n-gram language model with it. I use the padded\_everygram\_pipeline function from NLTK to build my ngrams and then fit a model. This works fine. I want to calculate the perplexity with lm.perplexity(test\_data). The NLTK doc says that the function expects a list of ngrams. If I transform my test data with the padded\_everygram\_pipeline to ngrams, the lm.perplexity functions gives me a DivisionByZero error. What is …

function language language model languagetechnology list ngrams nltk test