class_docstr: DatasetBuilder for dolphin_number_word problem dataset.
docstr: Parses available JSON files in a given split, returns TF examples.
docstr_tok: ["Parses","available","JSON","files","in","a","given","split",",","returns","TF","examples","."]
code: def _generate_examples(self, json_paths, split):
      """Parses available JSON files in a given split, returns TF examples."""
      # Currently assume all files in archive are json-formatted.
      for file in json_paths.glob(
          "*" + split + "*"
      ):  # pytype: disable=attribute-error  # gen-stub-imports
          json_string = file.read_text()
          examples = json.loads(json_string)
          for e in examples:
              # Per author's recommendation, we discard the ans_simple field.
              e.pop("ans_simple")
              # 'equations' and 'sources' will be a RaggedTensor unless we flatten
              # them into a single string. RaggedTensors are not compatible with
              # t5 tasks.
              if "sources" in e:
                  e["sources"] = "  ".join(e["sources"])
              else:
                  e["sources"] = ""
              e["equations"] = "  ".join(e["equations"])
              # Dataset appears to have duplicate entries, we add an internal
              # count to the provided entry's ID to bypass this error.
              e["id"] = e["id"] + str(self.__count__)
              self.__count__ += 1
              yield e["id"], e
  
file_path: datasets/tensorflow_datasets/text/dolphin_number_word/dolphin_number_word.py
imports: from __future__ import annotations
  import json
  import numpy
  import tensorflow_datasets.public_api
label_desc: Use image node_id 3 for calling the DolphinNumberWord obj's underlying member method code with example usage: obj._generate_examples(json_paths, split) without return types