class_docstr: DatasetBuilder for wit_kaggle dataset.
class_docstr_tok: ["DatasetBuilder","for","wit_kaggle","dataset","."]
docstr: Returns SplitGenerators.
docstr_tok: ["Returns","SplitGenerators","."]
code: def _split_generators(self, dl_manager, pipeline):
      """Returns SplitGenerators."""
      archive_path = {
          "samples": [
              tfds.download.Resource(  # pylint:disable=g-complex-comprehension
                  path=dl_manager.manual_dir / filename,
                  extract_method=tfds.download.ExtractMethod.ZIP,
              )
              for filename in self.builder_config.sample_files
          ],
          "images": tfds.download.Resource(
              path=dl_manager.manual_dir
              / self.builder_config.image_folder
          ),
      }
  
      extracted_paths = dl_manager.extract(archive_path)
  
      return {
          self.builder_config.name: self._generate_examples(
              pipeline=pipeline,
              samples_path=extracted_paths["samples"],
              image_pixels_path=extracted_paths["images"]
              / "image_pixels",
              image_resnet_path=extracted_paths["images"]
              / "resnet_embeddings",
          )
      }
  
file_path: datasets/tensorflow_datasets/vision_language/wit_kaggle/wit_kaggle.py
imports: from __future__ import annotations
  import base64
  import csv
  import functools
  import gzip
  import io
  import sys
  from typing import List, Optional
  import numpy
  from tensorflow_datasets.core.utils import bool_utils
  from tensorflow_datasets.core.utils.lazy_imports_utils import tensorflow
  import tensorflow_datasets.public_api
label_desc: Use image node_id 2 for calling the WitKaggle obj's underlying member method code with example usage: obj._split_generators(dl_manager, pipeline) and returns: dict