Datasets:

---

anon4papersubmission

/

grasp

like 0

Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
qid: int64
query: string
plan: struct<retrieval_mode: string, anchors: list<item: struct<var: string, text: string, label: string,  (... 335 chars omitted)
  child 0, retrieval_mode: string
  child 1, anchors: list<item: struct<var: string, text: string, label: string, match_mode: string>>
      child 0, item: struct<var: string, text: string, label: string, match_mode: string>
          child 0, var: string
          child 1, text: string
          child 2, label: string
          child 3, match_mode: string
  child 2, hops: list<item: struct<from: string, rel: string, to_var: string, to_label: string>>
      child 0, item: struct<from: string, rel: string, to_var: string, to_label: string>
          child 0, from: string
          child 1, rel: string
          child 2, to_var: string
          child 3, to_label: string
  child 3, target: struct<var: string, labels: list<item: string>, relevance_text: string, numeric_constraints: list<it (... 97 chars omitted)
      child 0, var: string
      child 1, labels: list<item: string>
          child 0, item: string
      child 2, relevance_text: string
      child 3, numeric_constraints: list<item: struct<text: string, operator: string, value: string, unit: string>>
          child 0, item: struct<text: string, operator: string, value: string, unit: string>
              child 0, text: string
              child 1, operator: string
              child 2, value: string
              child 3, unit: string
      child 4, retrieval_m
...
uble
  child 7, recall_100: double
  child 8, recall_200: double
  child 9, recall_500: double
  child 10, recall_1000: double
  child 11, ndcg_cut_5: double
  child 12, ndcg_cut_10: double
  child 13, ndcg_cut_15: double
  child 14, ndcg_cut_20: double
  child 15, ndcg_cut_30: double
  child 16, ndcg_cut_100: double
  child 17, ndcg_cut_200: double
  child 18, ndcg_cut_500: double
  child 19, ndcg_cut_1000: double
  child 20, success_1: double
  child 21, success_5: double
  child 22, top1_objective: double
best_qres: string
source_val_summary: string
mode: string
inputs: struct<run_dir: string, qrels: string, graph_qres: string, mfar_qres: string, results_jsonl: string>
  child 0, run_dir: string
  child 1, qrels: string
  child 2, graph_qres: string
  child 3, mfar_qres: string
  child 4, results_jsonl: string
best: struct<k: int64, w_1_10: double, w_11_50: double, w_51_100: double, w_101_500: double, w_501_plus: d (... 248 chars omitted)
  child 0, k: int64
  child 1, w_1_10: double
  child 2, w_11_50: double
  child 3, w_51_100: double
  child 4, w_101_500: double
  child 5, w_501_plus: double
  child 6, m_no_trade: double
  child 7, m_weak: double
  child 8, m_normal: double
  child 9, m_aggressive: double
  child 10, success_1: double
  child 11, success_5: double
  child 12, recall_20: double
  child 13, ndcg_cut_10: double
  child 14, recip_rank: double
  child 15, map: double
  child 16, top1_objective: double
  child 17, constraints_satisfied: double
w_mfar: double
to
{'mode': Value('string'), 'source_val_summary': Value('string'), 'count_field': Value('string'), 'w_mfar': Value('float64'), 'inputs': {'run_dir': Value('string'), 'qrels': Value('string'), 'graph_qres': Value('string'), 'mfar_qres': Value('string'), 'results_jsonl': Value('string')}, 'best': {'k': Value('int64'), 'w_1_10': Value('float64'), 'w_11_50': Value('float64'), 'w_51_100': Value('float64'), 'w_101_500': Value('float64'), 'w_501_plus': Value('float64'), 'm_no_trade': Value('float64'), 'm_weak': Value('float64'), 'm_normal': Value('float64'), 'm_aggressive': Value('float64'), 'success_1': Value('float64'), 'success_5': Value('float64'), 'recall_20': Value('float64'), 'ndcg_cut_10': Value('float64'), 'recip_rank': Value('float64'), 'map': Value('float64'), 'top1_objective': Value('float64'), 'constraints_satisfied': Value('float64')}, 'best_qres': Value('string'), 'metrics': {'map': Value('float64'), 'recip_rank': Value('float64'), 'recall_5': Value('float64'), 'recall_10': Value('float64'), 'recall_15': Value('float64'), 'recall_20': Value('float64'), 'recall_30': Value('float64'), 'recall_100': Value('float64'), 'recall_200': Value('float64'), 'recall_500': Value('float64'), 'recall_1000': Value('float64'), 'ndcg_cut_5': Value('float64'), 'ndcg_cut_10': Value('float64'), 'ndcg_cut_15': Value('float64'), 'ndcg_cut_20': Value('float64'), 'ndcg_cut_30': Value('float64'), 'ndcg_cut_100': Value('float64'), 'ndcg_cut_200': Value('float64'), 'ndcg_cut_500': Value('float64'), 'ndcg_cut_1000': Value('float64'), 'success_1': Value('float64'), 'success_5': Value('float64'), 'top1_objective': Value('float64')}}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 99, in get_rows_or_raise
                  return get_rows(
                         ^^^^^^^^^
                File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
                  return func(*args, **kwargs)
                         ^^^^^^^^^^^^^^^^^^^^^
                File "/src/services/worker/src/worker/utils.py", line 77, in get_rows
                  rows_plus_one = list(itertools.islice(ds, rows_max_number + 1))
                                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2690, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2227, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2251, in _iter_arrow
                  for key, pa_table in self.ex_iterable._iter_arrow():
                                       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 494, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 384, in _iter_arrow
                  for key, pa_table in self.generate_tables_fn(**gen_kwags):
                                       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 299, in _generate_tables
                  self._cast_table(pa_table, json_field_paths=json_field_paths),
                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 128, in _cast_table
                  pa_table = table_cast(pa_table, self.info.features.arrow_schema)
                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2321, in table_cast
                  return cast_table_to_schema(table, schema)
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2249, in cast_table_to_schema
                  raise CastError(
              datasets.table.CastError: Couldn't cast
              qid: int64
              query: string
              plan: struct<retrieval_mode: string, anchors: list<item: struct<var: string, text: string, label: string,  (... 335 chars omitted)
                child 0, retrieval_mode: string
                child 1, anchors: list<item: struct<var: string, text: string, label: string, match_mode: string>>
                    child 0, item: struct<var: string, text: string, label: string, match_mode: string>
                        child 0, var: string
                        child 1, text: string
                        child 2, label: string
                        child 3, match_mode: string
                child 2, hops: list<item: struct<from: string, rel: string, to_var: string, to_label: string>>
                    child 0, item: struct<from: string, rel: string, to_var: string, to_label: string>
                        child 0, from: string
                        child 1, rel: string
                        child 2, to_var: string
                        child 3, to_label: string
                child 3, target: struct<var: string, labels: list<item: string>, relevance_text: string, numeric_constraints: list<it (... 97 chars omitted)
                    child 0, var: string
                    child 1, labels: list<item: string>
                        child 0, item: string
                    child 2, relevance_text: string
                    child 3, numeric_constraints: list<item: struct<text: string, operator: string, value: string, unit: string>>
                        child 0, item: struct<text: string, operator: string, value: string, unit: string>
                            child 0, text: string
                            child 1, operator: string
                            child 2, value: string
                            child 3, unit: string
                    child 4, retrieval_m
              ...
              uble
                child 7, recall_100: double
                child 8, recall_200: double
                child 9, recall_500: double
                child 10, recall_1000: double
                child 11, ndcg_cut_5: double
                child 12, ndcg_cut_10: double
                child 13, ndcg_cut_15: double
                child 14, ndcg_cut_20: double
                child 15, ndcg_cut_30: double
                child 16, ndcg_cut_100: double
                child 17, ndcg_cut_200: double
                child 18, ndcg_cut_500: double
                child 19, ndcg_cut_1000: double
                child 20, success_1: double
                child 21, success_5: double
                child 22, top1_objective: double
              best_qres: string
              source_val_summary: string
              mode: string
              inputs: struct<run_dir: string, qrels: string, graph_qres: string, mfar_qres: string, results_jsonl: string>
                child 0, run_dir: string
                child 1, qrels: string
                child 2, graph_qres: string
                child 3, mfar_qres: string
                child 4, results_jsonl: string
              best: struct<k: int64, w_1_10: double, w_11_50: double, w_51_100: double, w_101_500: double, w_501_plus: d (... 248 chars omitted)
                child 0, k: int64
                child 1, w_1_10: double
                child 2, w_11_50: double
                child 3, w_51_100: double
                child 4, w_101_500: double
                child 5, w_501_plus: double
                child 6, m_no_trade: double
                child 7, m_weak: double
                child 8, m_normal: double
                child 9, m_aggressive: double
                child 10, success_1: double
                child 11, success_5: double
                child 12, recall_20: double
                child 13, ndcg_cut_10: double
                child 14, recip_rank: double
                child 15, map: double
                child 16, top1_objective: double
                child 17, constraints_satisfied: double
              w_mfar: double
              to
              {'mode': Value('string'), 'source_val_summary': Value('string'), 'count_field': Value('string'), 'w_mfar': Value('float64'), 'inputs': {'run_dir': Value('string'), 'qrels': Value('string'), 'graph_qres': Value('string'), 'mfar_qres': Value('string'), 'results_jsonl': Value('string')}, 'best': {'k': Value('int64'), 'w_1_10': Value('float64'), 'w_11_50': Value('float64'), 'w_51_100': Value('float64'), 'w_101_500': Value('float64'), 'w_501_plus': Value('float64'), 'm_no_trade': Value('float64'), 'm_weak': Value('float64'), 'm_normal': Value('float64'), 'm_aggressive': Value('float64'), 'success_1': Value('float64'), 'success_5': Value('float64'), 'recall_20': Value('float64'), 'ndcg_cut_10': Value('float64'), 'recip_rank': Value('float64'), 'map': Value('float64'), 'top1_objective': Value('float64'), 'constraints_satisfied': Value('float64')}, 'best_qres': Value('string'), 'metrics': {'map': Value('float64'), 'recip_rank': Value('float64'), 'recall_5': Value('float64'), 'recall_10': Value('float64'), 'recall_15': Value('float64'), 'recall_20': Value('float64'), 'recall_30': Value('float64'), 'recall_100': Value('float64'), 'recall_200': Value('float64'), 'recall_500': Value('float64'), 'recall_1000': Value('float64'), 'ndcg_cut_5': Value('float64'), 'ndcg_cut_10': Value('float64'), 'ndcg_cut_15': Value('float64'), 'ndcg_cut_20': Value('float64'), 'ndcg_cut_30': Value('float64'), 'ndcg_cut_100': Value('float64'), 'ndcg_cut_200': Value('float64'), 'ndcg_cut_500': Value('float64'), 'ndcg_cut_1000': Value('float64'), 'success_1': Value('float64'), 'success_5': Value('float64'), 'top1_objective': Value('float64')}}
              because column names don't match