code: def template_cluster_allocation(
      input_data,
      cluster_sizes,
      number_cluster,
      number_represent_points=5,
      compression=0.5,
      ccore_flag=False,
      **kwargs,
  ):
      if isinstance(input_data, str):
          sample = read_sample(input_data)
      else:
          sample = input_data
  
      numpy_usage = kwargs.get("numpy_usage", False)
      if numpy_usage is True:
          sample = numpy.array(sample)
  
      cure_instance = cure(
          sample,
          number_cluster,
          number_represent_points,
          compression,
          ccore=ccore_flag,
      )
      cure_instance.process()
  
      clusters = cure_instance.get_clusters()
      representors = cure_instance.get_representors()
      means = cure_instance.get_means()
  
      assertion.eq(len(clusters), number_cluster)
      assertion.eq(len(representors), number_cluster)
      assertion.eq(len(means), number_cluster)
  
      obtained_cluster_sizes = [len(cluster) for cluster in clusters]
  
      total_length = sum(obtained_cluster_sizes)
      assertion.eq(total_length, len(sample))
  
      cluster_sizes.sort()
      obtained_cluster_sizes.sort()
      assertion.eq(cluster_sizes, obtained_cluster_sizes)
  
file_path: pyclustering/pyclustering/cluster/tests/cure_templates.py
imports: import numpy
  from pyclustering.samples.definitions import SIMPLE_SAMPLES
  from pyclustering.utils import read_sample
  from pyclustering.cluster.cure import cure
  from pyclustering.cluster.encoder import type_encoding, cluster_encoder
  from pyclustering.tests.assertion import assertion
  from random import random
label_desc: Use image node_id 1 for calling the CureTestTemplates obj's underlying member method code with example usage: obj.template_cluster_allocation(input_data, cluster_sizes, number_cluster, number_represent_points, compression, ccore_flag) without return types