predict error for kmeans

[BeHappyForMe]

`from pyclustering.cluster.kmeans import kmeans, kmeans_visualizer
from pyclustering.cluster.center_initializer import kmeans_plusplus_initializer
from pyclustering.samples.definitions import FCPS_SAMPLES
from pyclustering.utils import read_sample
samples = read_sample(FCPS_SAMPLES.SAMPLE_TWO_DIAMONDS)
initial_centers = kmeans_plusplus_initializer(samples, 2).initialize()
kmeans_instance = kmeans(samples, initial_centers)
kmeans_instance.process()
clusters = kmeans_instance.get_clusters()
final_centers = kmeans_instance.get_centers()

kmeans_instance.predict(samples)`

and i meet this:

---

AttributeError Traceback (most recent call last)
/tmp/ipykernel_20827/3994711565.py in
----> 1 kmeans_instance.predict(samples)

~/envs/envs/spark_seg/lib/python3.7/site-packages/pyclustering/cluster/kmeans.py in predict(self, points)
441 for index_point in range(len(nppoints)):
442 if self.__metric.get_type() != type_metric.USER_DEFINED:
--> 443 differences[index_point] = self.__metric(nppoints[index_point], self.__centers)
444 else:
445 differences[index_point] = [self.__metric(nppoints[index_point], center) for center in self.__centers]

~/envs/envs/spark_seg/lib/python3.7/site-packages/pyclustering/utils/metric.py in call(self, point1, point2)
130
131 """
--> 132 return self.__calculator(point1, point2)
133
134

~/envs/envs/spark_seg/lib/python3.7/site-packages/pyclustering/utils/metric.py in euclidean_distance_square_numpy(object1, object2)
368
369 """
--> 370 if len(object1.shape) > 1 or len(object2.shape) > 1:
371 return numpy.sum(numpy.square(object1 - object2), axis=1).T
372 else:

AttributeError: 'list' object has no attribute 'shape'