class_docstr: A Shapenet config for loading the original .obj files.
class_docstr_tok: ["A","Shapenet","config","for","loading","the","original",".obj","files","."]
code: def split_generators(self, dl_manager, dataset_builder):
      # Extract the synset ids from the taxonomy file and update the ClassLabel
      # feature.
      with tf.io.gfile.GFile(
          os.path.join(dl_manager.manual_dir, _TAXONOMY_FILE_NAME)
      ) as taxonomy_file:
          labels = [
              x["synsetId"] for x in json.loads(taxonomy_file.read())
          ]
          # Remove duplicate labels (the json file contains two identical entries
          # for synset '04591713').
          labels = list(collections.OrderedDict.fromkeys(labels))
      dataset_builder.info.features["label"].names = labels
  
      split_file = dl_manager.download(_SPLIT_FILE_URL)
      fieldnames = ["id", "synset", "sub_synset", "model_id", "split"]
      model_items = collections.defaultdict(list)
      with tf.io.gfile.GFile(split_file) as csvfile:
          for row in csv.DictReader(csvfile, fieldnames):
              model_items[row["split"]].append(row)
  
      return [
          tfds.core.SplitGenerator(
              name=tfds.Split.TRAIN,
              gen_kwargs={
                  "base_dir": dl_manager.manual_dir,
                  "models": model_items["train"],
              },
          ),
          tfds.core.SplitGenerator(
              name=tfds.Split.TEST,
              gen_kwargs={
                  "base_dir": dl_manager.manual_dir,
                  "models": model_items["test"],
              },
          ),
          tfds.core.SplitGenerator(
              name=tfds.Split.VALIDATION,
              gen_kwargs={
                  "base_dir": dl_manager.manual_dir,
                  "models": model_items["val"],
              },
          ),
      ]
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import collections
  import csv
  import json
  import os
  import textwrap
  import tensorflow.compat.v2
  import tensorflow_datasets
  from tensorflow_datasets import features
  from tensorflow_graphics.datasets import features
label_desc: Use image node_id 3 for calling the MeshConfig obj's underlying member method code with example usage: obj.split_generators(dl_manager, dataset_builder) and returns: list