code: def __init__(
      self,
      dataset,
      model="GraphSAGE",
      device=0,
      rank=0,
      world_size=1,
      num_epochs=1,
      sample_dir=".",
      **kwargs,
  ):
      self.__data = None
      self.__device = device
      self.__rank = rank
      self.__world_size = world_size
      self.__num_epochs = num_epochs
      self.__dataset = dataset
      self.__sample_dir = sample_dir
      self.__loader_kwargs = kwargs
      self.__model = self.get_model(model)
      self.__optimizer = None
  
imports: from .trainers_pyg import PyGTrainer
  from models.pyg import CuGraphSAGE
  import torch
  import numpy
  from torch.nn.parallel import DistributedDataParallel
  from cugraph.gnn import FeatureStore
  from cugraph_pyg.data import CuGraphStore
  from cugraph_pyg.loader import BulkSampleLoader
  import os
label_desc: Use image node_id 1 to create a new PyGCuGraphTrainer object from inherited base classes: PyGTrainer with example: obj = PyGCuGraphTrainer(dataset, model, device, rank, world_size, num_epochs, sample_dir)