class_docstr: Implement of GPRGNN
class_docstr_tok: ["Implement","of","GPRGNN"]
code: def __init__(
      self,
      input_size,
      hidden_size,
      num_class,
      num_layers=10,
      drop=0.5,
      dprate=0.5,
      alpha=0.1,
      init_method="PPR",
      gamma=None,
  ):
      super(GPRGNN, self).__init__()
      self.num_class = num_class
      self.num_layers = num_layers
      self.hidden_size = hidden_size
      self.drop = drop
      self.dprate = dprate
      self.alpha = alpha
      self.init_method = init_method
      self.gamma = gamma
  
      self.gpr = pgl.nn.GPRConv(
          input_size=input_size,
          hidden_size=self.hidden_size,
          output_size=self.num_class,
          drop=self.drop,
          dprate=self.dprate,
          alpha=self.alpha,
          k_hop=self.num_layers,
          init_method=self.init_method,
          gamma=self.gamma,
      )
  
file_path: PGL/examples/gpr/train.py
imports: import tqdm
  import pgl
  import paddle
  import paddle.nn
  from pgl.utils.logger import log
  import numpy
  import time
  import argparse
  from paddle.optimizer import Adam
label_desc: Use image node_id 1 to create a new GPRGNN object from inherited base classes: nn with example: obj = GPRGNN(input_size, hidden_size, num_class, num_layers, drop, dprate, alpha, init_method, gamma)