无法生成带有markovify、textacy和spacy>srsly.msgpack.exceptions异常.ExtraData：解包（b）收到额外的数据

Question

我正在尝试从单词列表中生成句子，使用markovify、textacy和spacy，遵循https://joshuanewlan.com/spacy-and-markovify的教程。我真的不了解他，所以请考虑一下。 我使用的训练框架只是一个简单框架的列表，小写，保存到一个.txt文件中。你知道吗

代码

import textacy
from textacy import preprocessing
import re
from unidecode import unidecode
import spacy

# Loads portuguese dictionary from spacy
lang = spacy.load('pt_core_news_sm')
# Loads the training keywords and sets up language
frases = ('~/git/SentGen/frasestreino/teste.txt') 
corpus = textacy.Corpus.load (lang,frases)

class TaggedText(markovify.Text):

    def sentence_split(self, text):
        # Splits full-text string into a list of sentences.
        sentence_list = []
        for doc in corpus:
            sentence_list += list(doc.sents)
        return sentence_list

    def word_split(self, sentence):
        #Splits a sentence into a list of words.
        return ["::".join((word.orth_,word.pos_)) for word in sentence]

    def word_join(self, words):
        sentence = " ".join(word.split("::")[0] for word in words)
        return sentence

    def test_sentence_input(self, sentence):
        # rejects sentences that contain the type of punctuation 
        # that would look strange on its own
        # in a randomly-generated sentence. 
        sentence = sentence.text
        reject_pat = re.compile(r"(^')|('$)|\s'|'\s|[\"(\(\)\[\])]")
        # Decode unicode, mainly to normalize fancy quotation marks
        if sentence.__class__.__name__ == "str":
            decoded = sentence
        else:
            decoded = unidecode(sentence)
        # Sentence shouldn't contain problematic characters
        if re.search(reject_pat, decoded): return False
        return True

    def generate_corpus(self, text):
        #Given a text string, returns a list of lists; that is, a list of
        #"sentences," each of which is a list of words. 
        #Before splitting into words, the sentences are filtered through 
        # pip in`self.test_sentence_input`
        sentences = self.sentence_split(text)
        passing = filter(self.test_sentence_input, sentences)
        runs = map(self.word_split, sentences)
        print(runs[0])
        return runs
    # Generated the model
model = TaggedText(corpus)
# A sentence based on the model
print(model.make_sentence())


the errors I'm getting:


```Traceback (most recent call last):
  File "/home/mdinis/git/SentGen/Markowo.py", line 12, in <module>
    corpus = textacy.Corpus.load (lang,frases)
  File "/home/mdinis/.local/lib/python2.7/site-packages/textacy/corpus.py", line 604, in load
    msg = srsly.msgpack_loads(f.read())
  File "/home/mdinis/.local/lib/python2.7/site-packages/srsly/_msgpack_api.py", line 29, in msgpack_loads
    msg = msgpack.loads(data, raw=False, use_list=use_list)
  File "/home/mdinis/.local/lib/python2.7/site-packages/srsly/msgpack/__init__.py", line 60, in unpackb
    return _unpackb(packed, **kwargs)
  File "_unpacker.pyx", line 199, in srsly.msgpack._unpacker.unpackb
srsly.msgpack.exceptions.ExtraData: unpack(b) received extra data.```