class_docstr: DROP is a QA dataset which tests comprehensive understanding of paragraphs.
code: def _generate_examples(self, filepath, split):
      with open(filepath, encoding="utf-8") as f:
          data = json.load(f)
          key = 0
          for section_id, example in data.items():
              # Each example (passage) has multiple sub-question-answer pairs.
              for qa in example["qa_pairs"]:
                  # Build answer.
                  answer = qa["answer"]
                  answer = {
                      "number": answer["number"],
                      "date": {
                          "day": answer["date"].get("day", ""),
                          "month": answer["date"].get("month", ""),
                          "year": answer["date"].get("year", ""),
                      },
                      "spans": answer["spans"],
                      "worker_id": answer.get("worker_id", ""),
                      "hit_id": answer.get("hit_id", ""),
                  }
                  validated_answers = []
                  if "validated_answers" in qa:
                      for validated_answer in qa["validated_answers"]:
                          va = {
                              "number": validated_answer.get(
                                  "number", ""
                              ),
                              "date": {
                                  "day": validated_answer["date"].get(
                                      "day", ""
                                  ),
                                  "month": validated_answer["date"].get(
                                      "month", ""
                                  ),
                                  "year": validated_answer["date"].get(
                                      "year", ""
                                  ),
                              },
                              "spans": validated_answer.get(
                                  "spans", ""
                              ),
                              "worker_id": validated_answer.get(
                                  "worker_id", ""
                              ),
                              "hit_id": validated_answer.get(
                                  "hit_id", ""
                              ),
                          }
                          validated_answers.append(va)
                  else:
                      validated_answers = _EMPTY_VALIDATED_ANSWER
                  yield key, {
                      "section_id": section_id,
                      "passage": example["passage"],
                      "question": qa["question"],
                      "query_id": qa["query_id"],
                      "answer": answer,
                      "validated_answers": validated_answers,
                  }
                  key += 1
  
file_path: lm-evaluation-harness/lm_eval/datasets/drop/drop.py
imports: import json
  import os
  import datasets
label_desc: Use image node_id 3 for calling the Drop obj's underlying member method code with example usage: obj._generate_examples(filepath, split) without return types