class_docstr: Sort Pooling from `An End-to-End Deep Learning Architecture for Graph Classification
  <https://www.cse.wustl.edu/~ychen/public/DGCNN.pdf>`__
  
  Parameters
  ----------
  k : int
      The number of nodes to hold for each graph.
class_docstr_tok: ["Sort","Pooling","from","`","An","End-to-End","Deep","Learning","Architecture","for","Graph","Classification","<","https",":","\/\/www.cse.wustl.edu\/~ychen\/public\/DGCNN.pdf",">","`","__","Parameters","--","--","--","--","--","k",":","int","The","number","of","nodes","to","hold","for","each","graph","."]
code: def __init__(self, k):
      super(SortPooling, self).__init__()
      self.k = k
  
imports: import tensorflow
  from tensorflow.keras import layers
  from ...readout import max_nodes, mean_nodes, softmax_nodes, sum_nodes, topk_nodes
label_desc: Use image node_id 1 to create a new SortPooling object from inherited base classes: layers with example: obj = SortPooling(k)