class_docstr: Data Reader for Open Graph Benchmark datasets.
code: def __next__(self):
      graphs = []
      if self._dynamically_batch:
          # If we are using pmap we need each batch to have the same size in both
          # number of nodes and number of edges. So we use dynamically batch which
          # guarantees this.
          return next(self._generator)
      else:
          for _ in range(self._batch_size):
              graph = next(self._generator)
              graphs.append(graph)
          return jraph.batch(graphs)
  
file_path: jraph/jraph/ogb_examples/data_utils.py
imports: import pathlib
  import jraph
  import numpy
  import pandas
label_desc: Use image node_id 5 for calling the DataReader obj's underlying member method code with example usage: obj.__next__() and returns: next, jraph