[英]Gensim: TypeError: doc2bow expects an array of unicode tokens on input, not a single string
I am starting with some python task, I am facing a problem while using gensim.我从一些 python 任务开始,我在使用 gensim 时遇到了一个问题。 I am trying to load files from my disk and process them (split them and lowercase() them)我正在尝试从我的磁盘加载文件并处理它们(将它们拆分并小写()它们)
The code I have is below:我的代码如下:
dictionary_arr=[]
for file_path in glob.glob(os.path.join(path, '*.txt')):
with open (file_path, "r") as myfile:
text=myfile.read()
for words in text.lower().split():
dictionary_arr.append(words)
dictionary = corpora.Dictionary(dictionary_arr)
The list (dictionary_arr) contains the list of all words across all the file, I then use gensim corpora.Dictionary to process the list.列表 (dictionary_arr) 包含所有文件中所有单词的列表,然后我使用 gensim corpora.Dictionary 来处理列表。 However I face a error.但是我面临一个错误。
TypeError: doc2bow expects an array of unicode tokens on input, not a single string
I cant understand whats a problem, A little guidance would be appreciated.我不明白有什么问题,请提供一点指导,我们将不胜感激。
In dictionary.py, the initialize function is:在dictionary.py中,初始化函数是:
def __init__(self, documents=None):
self.token2id = {} # token -> tokenId
self.id2token = {} # reverse mapping for token2id; only formed on request, to save memory
self.dfs = {} # document frequencies: tokenId -> in how many documents this token appeared
self.num_docs = 0 # number of documents processed
self.num_pos = 0 # total number of corpus positions
self.num_nnz = 0 # total number of non-zeroes in the BOW matrix
if documents is not None:
self.add_documents(documents)
Function add_documents Build dictionary from a collection of documents.函数 add_documents 从文档集合构建字典。 Each document is a list of tokens:每个文档都是一个令牌列表:
def add_documents(self, documents):
for docno, document in enumerate(documents):
if docno % 10000 == 0:
logger.info("adding document #%i to %s" % (docno, self))
_ = self.doc2bow(document, allow_update=True) # ignore the result, here we only care about updating token ids
logger.info("built %s from %i documents (total %i corpus positions)" %
(self, self.num_docs, self.num_pos))
So ,if you initialize Dictionary in this way, you must pass documents but not a single document.所以,如果你以这种方式初始化 Dictionary ,你必须传递文档而不是单个文档。 For example,例如,
dic = corpora.Dictionary([a.split()])
is OK.没问题。
Dictionary needs a tokenized strings for its input:字典的输入需要一个标记化的字符串:
dataset = ['driving car ',
'drive car carefully',
'student and university']
# be sure to split sentence before feed into Dictionary
dataset = [d.split() for d in dataset]
vocab = Dictionary(dataset)
Hello everyone i ran into the same problem.大家好,我遇到了同样的问题。 This is what worked for me这对我有用
#Tokenize the sentence into words
tokens = [word for word in sentence.split()]
#Create dictionary
dictionary = corpora.Dictionary([tokens])
print(dictionary)
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