class_docstr: GESModel
      
class_docstr_tok: ["GESModel"]
code: def __init__(
      self,
      num_nodes,
      num_featuers,
      hidden_size=16,
      neg_num=5,
      is_sparse=False,
      num_part=1,
  ):
      self.pyreader = L.py_reader(
          capacity=70,
          shapes=[
              [-1, 1, num_featuers, 1],
              [-1, neg_num + 1, num_featuers, 1],
          ],
          dtypes=["int64", "int64"],
          lod_levels=[0, 0],
          name="train",
          use_double_buffer=True,
      )
  
      self.num_nodes = num_nodes
      self.num_featuers = num_featuers
      self.neg_num = neg_num
      self.embed_init = F.initializer.TruncatedNormal(
          scale=1.0 / math.sqrt(hidden_size)
      )
      self.is_sparse = is_sparse
      self.num_part = num_part
      self.hidden_size = hidden_size
      self.loss = None
  
file_path: PGL/legacy/examples/ges/model.py
imports: from __future__ import division
  from __future__ import absolute_import
  from __future__ import print_function
  from __future__ import unicode_literals
  import math
  import paddle.fluid.layers
  import paddle.fluid
label_desc: Use image node_id 1 to create a new GESModel object from inherited base classes: object with example: obj = GESModel(num_nodes, num_featuers, hidden_size, neg_num, is_sparse, num_part)