TypeError: got multiple values for argument 'dictionary'
TypeError: got multiple values for argument 'dictionary'
我阅读了其他被问及此错误的问题 earlier.but 仍然我没有得到我正在制作的地方 mistake.when 我调用了这个错误的函数。我是这个论坛的新手,解决我的问题的任何帮助都是 appreciated.here 是我的代码
def lda_train(self, documents):
# create dictionary
dictionary= corpora.Dictionary(documents)
dictionary.compactify()
dictionary.save(self.DICTIONARY_FILE) # store the dictionary, for future reference
print ("============ Dictionary Generated and Saved ============")
############# Create Corpus##########################
corpus = [dictionary.doc2bow(text) for text in documents]
print('Number of unique tokens: %d' % len(dictionary))
print('Number of documents: %d' % len(corpus))
return dictionary,corpus
def compute_coherence_values(dictionary,corpus,documents, limit, start=2, step=3):
num_topics = 10
coherence_values = []
model_list = []
for num_topics in range(start, limit, step):
lda_model = gensim.models.ldamodel.LdaModel(corpus=corpus,id2word=dictionary, num_topics=num_topics, random_state=100, alpha='auto')
model_list.append(model)
coherencemodel = CoherenceModel(model=model, texts=texts, dictionary=dictionary, coherence='c_v')
coherence_values.append(coherencemodel.get_coherence())
return model_list, coherence_values
当我使用以下代码在 main 中调用此函数时:
if __name__ == '__main__':
limit=40
start=2
step=6
obj = LDAModel()
lda_input = get_lda_input_from_corpus_folder('./dataset/TRAIN')
dictionary,corpus =obj.lda_train(lda_input)
model_list, coherence_values = obj.compute_coherence_values(dictionary=dictionary,corpus=corpus, texts=lda_input, start=2, limit=40, step=6)
我收到一条错误消息:
model_list, coherence_values=obj.compute_coherence_values(dictionary=dictionary,corpus=corpus, texts=lda_input, start=2, limit=40, step=6)
TypeError: compute_coherence_values() got multiple values for argument 'dictionary'
TL;DR
改变
def compute_coherence_values(dictionary, corpus, documents, limit, start=2, step=3)
到
def compute_coherence_values(self, dictionary, corpus, documents, limit, start=2, step=3)
您忘记将 self
作为第一个参数传递,因此实例将作为 dictionary
参数传递,但您也将 dictionary
作为显式关键字参数传递。
这种行为很容易重现:
class Foo:
def bar(a):
pass
Foo().bar(a='a')
TypeError: bar() got multiple values for argument 'a'
我阅读了其他被问及此错误的问题 earlier.but 仍然我没有得到我正在制作的地方 mistake.when 我调用了这个错误的函数。我是这个论坛的新手,解决我的问题的任何帮助都是 appreciated.here 是我的代码
def lda_train(self, documents):
# create dictionary
dictionary= corpora.Dictionary(documents)
dictionary.compactify()
dictionary.save(self.DICTIONARY_FILE) # store the dictionary, for future reference
print ("============ Dictionary Generated and Saved ============")
############# Create Corpus##########################
corpus = [dictionary.doc2bow(text) for text in documents]
print('Number of unique tokens: %d' % len(dictionary))
print('Number of documents: %d' % len(corpus))
return dictionary,corpus
def compute_coherence_values(dictionary,corpus,documents, limit, start=2, step=3):
num_topics = 10
coherence_values = []
model_list = []
for num_topics in range(start, limit, step):
lda_model = gensim.models.ldamodel.LdaModel(corpus=corpus,id2word=dictionary, num_topics=num_topics, random_state=100, alpha='auto')
model_list.append(model)
coherencemodel = CoherenceModel(model=model, texts=texts, dictionary=dictionary, coherence='c_v')
coherence_values.append(coherencemodel.get_coherence())
return model_list, coherence_values
当我使用以下代码在 main 中调用此函数时:
if __name__ == '__main__':
limit=40
start=2
step=6
obj = LDAModel()
lda_input = get_lda_input_from_corpus_folder('./dataset/TRAIN')
dictionary,corpus =obj.lda_train(lda_input)
model_list, coherence_values = obj.compute_coherence_values(dictionary=dictionary,corpus=corpus, texts=lda_input, start=2, limit=40, step=6)
我收到一条错误消息:
model_list, coherence_values=obj.compute_coherence_values(dictionary=dictionary,corpus=corpus, texts=lda_input, start=2, limit=40, step=6)
TypeError: compute_coherence_values() got multiple values for argument 'dictionary'
TL;DR
改变
def compute_coherence_values(dictionary, corpus, documents, limit, start=2, step=3)
到
def compute_coherence_values(self, dictionary, corpus, documents, limit, start=2, step=3)
您忘记将 self
作为第一个参数传递,因此实例将作为 dictionary
参数传递,但您也将 dictionary
作为显式关键字参数传递。
这种行为很容易重现:
class Foo:
def bar(a):
pass
Foo().bar(a='a')
TypeError: bar() got multiple values for argument 'a'