我正在尝试对从预训练的BERT模型获得的张量（句子嵌入）进行k均值聚类。
from sklearn.cluster import KMeans
embedding = BERTembeddingGenerator.generateSentenceEmbedding(sentence)
embeddingMapping[embedding] = sentence
sentenceEmbeddingsList = list(embeddingMapping.keys())
model = KMeans(n_clusters=10, init='k-means++', max_iter=100, n_init=1)
labels = model.fit_predict(sentenceEmbeddingsList)
这会引发错误
ValueError: only one element tensors can be converted to Python scalars
句子嵌入的大小为768
我试图将张量转换为numpy数组。任何有关我弄错地方的指针