code: def __init__(
      self,
      dataset,
      batch_size,
      collate_fn=collate,
      seed=0,
      shuffle=True,
      split_name="fold10",
      fold_idx=0,
      split_ratio=0.7,
  ):
      self.shuffle = shuffle
      self.seed = seed
  
      labels = [l for _, l in dataset]
  
      if split_name == "fold10":
          train_idx, valid_idx = self._split_fold10(
              labels, fold_idx, seed, shuffle
          )
      elif split_name == "rand":
          train_idx, valid_idx = self._split_rand(
              labels, split_ratio, seed, shuffle
          )
      else:
          raise NotImplementedError()
  
      train_sampler = SubsetRandomSampler(train_idx)
      valid_sampler = SubsetRandomSampler(valid_idx)
  
      self.train_loader = DataLoader(
          dataset,
          sampler=train_sampler,
          batch_size=batch_size,
          batchify_fn=collate_fn,
      )
      self.valid_loader = DataLoader(
          dataset,
          sampler=valid_sampler,
          batch_size=batch_size,
          batchify_fn=collate_fn,
      )
  
file_path: dgl/examples/mxnet/gin/dataloader.py
imports: import math
  import dgl
  import numpy
  from mxnet import nd
  from mxnet.gluon.data import DataLoader, Sampler
  from sklearn.model_selection import StratifiedKFold
label_desc: Use image node_id 1 to create a new GraphDataLoader object  with example: obj = GraphDataLoader(dataset, batch_size, collate_fn, seed, shuffle, split_name, fold_idx, split_ratio)