da_model = gensimmodelsldamodelLdaModeltfidf_matrix num_topics=8 id2word=dictenumeratefeature_names passes=10报错：TypeError sparse matrix length is ambiguous; use getnnz or shape0怎么修改

可以尝试将tfidf_matrix转换成稠密矩阵再传入LdaModel中：

da_model = gensim.models.ldamodel.LdaModel(tfidf_matrix.todense(), num_topics=8, id2word=dict(enumerate(feature_names)), passes=10)

或者直接在构造tfidf_matrix时指定dtype为float32：

tfidf_matrix = TfidfVectorizer(max_df=0.95, min_df=2, max_features=n_features, stop_words='english', dtype=np.float32).fit_transform(docs_clean)
da_model = gensim.models.ldamodel.LdaModel(tfidf_matrix, num_topics=8, id2word=dict(enumerate(feature_names)), passes=10)