docstr: d: representation vector dimension
docstr_tok: ["d",":","representation","vector","dimension"]
code: def __init__(self, graph, d):
      """
      d: representation vector dimension
      """
      self._d = d
      self._graph = graph.G
      self.g = graph
      self._node_num = graph.node_size
      self.learn_embedding()
  
file_path: OpenNE/src/openne/hope.py
imports: import networkx
  import numpy
  import scipy.io
  import scipy.sparse
  import scipy.sparse.linalg
  from .None import graph
  import tensorflow
  from sklearn.preprocessing import normalize
label_desc: Use image node_id 1 to create a new HOPE object from inherited base classes: object with example: obj = HOPE(graph, d)