class_docstr: Indexing edges for fast graph queries
  Sorted edges and represent edges in compressed style like csc_matrix or csr_matrix.
  
      Args:
          u: A list of node id to be compressed.
          v: A list of node id that are connected with u.
          num_nodes: The exactive number of nodes.
      
docstr: Return the compressed v for given u.
          
docstr_tok: ["Return","the","compressed","v","for","given","u","."]
code: def view_v(self, u=None):
      """Return the compressed v for given u."""
      if self._is_tensor:
          raise NotImplementedError("not implemented!")
      else:
          if u is None:
              return np.split(self._sorted_v, self._indptr[1:-1])
          else:
              u = np.array(u, dtype="int64")
              return graph_kernel.slice_by_index(
                  self._sorted_v, self._indptr, index=u
              )
  
imports: import os
  import json
  import copy
  import numpy
  import paddle
  from paddle.framework import core
  from pgl.utils import op
  import pgl.graph_kernel
  from pgl.utils.helper import check_is_tensor, to_paddle_tensor
label_desc: Use image node_id 5 for calling the EdgeIndex obj's underlying member method code with example usage: obj.view_v(u) and returns: np, graph_kernel