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The dataset generation failed
Error code:   DatasetGenerationError
Exception:    CastError
Message:      Couldn't cast
step: int64
prompt_id: string
sample_idx: int64
eq_correct: int64
gt_pass_rate: double
mutated_v_passrate: double
tests: list<item: struct<id: string, src: string, visibility: string, mutated: bool, passed: int64>>
  child 0, item: struct<id: string, src: string, visibility: string, mutated: bool, passed: int64>
      child 0, id: string
      child 1, src: string
      child 2, visibility: string
      child 3, mutated: bool
      child 4, passed: int64
real_v: list<item: int64>
  child 0, item: int64
eq_hinted: int64
to
{'step': Value('int64'), 'prompt_id': Value('string'), 'sample_idx': Value('int64'), 'eq_correct': Value('int64'), 'eq_hinted': Value('int64'), 'gt_pass_rate': Value('float64'), 'tests': List({'id': Value('string'), 'src': Value('string'), 'visibility': Value('string'), 'passed': Value('int64')})}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1816, in _prepare_split_single
                  for key, table in generator:
                                    ^^^^^^^^^
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 613, in wrapped
                  for item in generator(*args, **kwargs):
                              ~~~~~~~~~^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 343, in _generate_tables
                  self._cast_table(pa_table, json_field_paths=json_field_paths),
                  ~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 132, in _cast_table
                  pa_table = table_cast(pa_table, self.info.features.arrow_schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2369, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2297, in cast_table_to_schema
                  raise CastError(
                  ...<3 lines>...
                  )
              datasets.table.CastError: Couldn't cast
              step: int64
              prompt_id: string
              sample_idx: int64
              eq_correct: int64
              gt_pass_rate: double
              mutated_v_passrate: double
              tests: list<item: struct<id: string, src: string, visibility: string, mutated: bool, passed: int64>>
                child 0, item: struct<id: string, src: string, visibility: string, mutated: bool, passed: int64>
                    child 0, id: string
                    child 1, src: string
                    child 2, visibility: string
                    child 3, mutated: bool
                    child 4, passed: int64
              real_v: list<item: int64>
                child 0, item: int64
              eq_hinted: int64
              to
              {'step': Value('int64'), 'prompt_id': Value('string'), 'sample_idx': Value('int64'), 'eq_correct': Value('int64'), 'eq_hinted': Value('int64'), 'gt_pass_rate': Value('float64'), 'tests': List({'id': Value('string'), 'src': Value('string'), 'visibility': Value('string'), 'passed': Value('int64')})}
              because column names don't match
              
              The above exception was the direct cause of the following exception:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1369, in compute_config_parquet_and_info_response
                  parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
                                                                        ~~~~~~~~~~~~~~~~~~~~~~~~~^
                      builder, max_dataset_size_bytes=max_dataset_size_bytes
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                  )
                  ^
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 948, in stream_convert_to_parquet
                  builder._prepare_split(split_generator=splits_generators[split], file_format="parquet")
                  ~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1683, in _prepare_split
                  for job_id, done, content in self._prepare_split_single(
                                               ~~~~~~~~~~~~~~~~~~~~~~~~~~^
                      gen_kwargs=gen_kwargs, job_id=job_id, **_prepare_split_args
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                  ):
                  ^
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1869, in _prepare_split_single
                  raise DatasetGenerationError("An error occurred while generating the dataset") from e
              datasets.exceptions.DatasetGenerationError: An error occurred while generating the dataset

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step
int64
prompt_id
string
sample_idx
int64
eq_correct
int64
eq_hinted
int64
gt_pass_rate
float64
tests
list
0
2579
0
0
0
0
[ { "id": "2579#0", "src": "assert Solution().coloredCells(n = 3) == 13", "visibility": "reward", "passed": 0 }, { "id": "2579#1", "src": "assert Solution().coloredCells(n = 100000) == 19999800001", "visibility": "reward", "passed": 0 }, { "id": "2579#2", "src": "assert...
0
2579
1
0
0
0
[ { "id": "2579#0", "src": "assert Solution().coloredCells(n = 3) == 13", "visibility": "reward", "passed": 0 }, { "id": "2579#1", "src": "assert Solution().coloredCells(n = 100000) == 19999800001", "visibility": "reward", "passed": 0 }, { "id": "2579#2", "src": "assert...
0
41
2
1
0
1
[ { "id": "41#0", "src": "assert Solution().firstMissingPositive(nums = [1000000, -1000000, 500000]) == 1", "visibility": "reward", "passed": 1 }, { "id": "41#1", "src": "assert Solution().firstMissingPositive(nums = [1000000, -1000000, 1]) == 2", "visibility": "reward", "passed": ...
0
763
3
0
0
0.265625
[ { "id": "763#0", "src": "assert Solution().partitionLabels(s = \"abcdabcde\") == [8, 1]", "visibility": "reward", "passed": 0 }, { "id": "763#1", "src": "assert Solution().partitionLabels(s = \"aaaaaabbbbbccccc\") == [6, 5, 5]", "visibility": "reward", "passed": 1 }, { "i...
0
763
4
0
0
0.265625
[ { "id": "763#0", "src": "assert Solution().partitionLabels(s = \"abcdabcde\") == [8, 1]", "visibility": "reward", "passed": 0 }, { "id": "763#1", "src": "assert Solution().partitionLabels(s = \"aaaaaabbbbbccccc\") == [6, 5, 5]", "visibility": "reward", "passed": 1 }, { "i...
0
763
5
0
0
0.265625
[ { "id": "763#0", "src": "assert Solution().partitionLabels(s = \"abcdabcde\") == [8, 1]", "visibility": "reward", "passed": 0 }, { "id": "763#1", "src": "assert Solution().partitionLabels(s = \"aaaaaabbbbbccccc\") == [6, 5, 5]", "visibility": "reward", "passed": 1 }, { "i...
0
1072
8
1
0
1
[ { "id": "1072#0", "src": "assert Solution().maxEqualRowsAfterFlips(matrix = [[0,1],[1,0]]) == 2", "visibility": "reward", "passed": 1 }, { "id": "1072#1", "src": "assert Solution().maxEqualRowsAfterFlips(matrix = [[1,0,0,1],[1,0,0,1],[0,1,1,0]]) == 3", "visibility": "reward", "pa...
0
1055
10
1
0
1
[ { "id": "1055#0", "src": "assert Solution().shortestWay(source = \"abcd\", target = \"dddbbbccccaaa\") == 12", "visibility": "reward", "passed": 1 }, { "id": "1055#1", "src": "assert Solution().shortestWay(source = \"a\", target = \"a\") == 1", "visibility": "reward", "passed": 1...
0
1072
11
1
0
1
[ { "id": "1072#0", "src": "assert Solution().maxEqualRowsAfterFlips(matrix = [[0,1],[1,0]]) == 2", "visibility": "reward", "passed": 1 }, { "id": "1072#1", "src": "assert Solution().maxEqualRowsAfterFlips(matrix = [[1,0,0,1],[1,0,0,1],[0,1,1,0]]) == 3", "visibility": "reward", "pa...
0
2498
12
0
0
0
[ { "id": "2498#0", "src": "assert Solution().maxJump(stones = [0,10,15,20,25]) == 15", "visibility": "reward", "passed": 0 }, { "id": "2498#1", "src": "assert Solution().maxJump(stones = [0,1,2,3,4,5]) == 2", "visibility": "reward", "passed": 0 }, { "id": "2498#2", "sr...
0
2498
13
0
0
0
[ { "id": "2498#0", "src": "assert Solution().maxJump(stones = [0,10,15,20,25]) == 15", "visibility": "reward", "passed": 0 }, { "id": "2498#1", "src": "assert Solution().maxJump(stones = [0,1,2,3,4,5]) == 2", "visibility": "reward", "passed": 0 }, { "id": "2498#2", "sr...
0
1130
14
0
0
0
[ { "id": "1130#0", "src": "assert Solution().mctFromLeafValues(arr = [1,2,3,4]) == 20", "visibility": "reward", "passed": 0 }, { "id": "1130#1", "src": "assert Solution().mctFromLeafValues(arr = [3,2,1]) == 8", "visibility": "reward", "passed": 0 }, { "id": "1130#2", "...
0
870
15
0
0
0.42
[ { "id": "870#0", "src": "assert Solution().advantageCount(nums1 = [10,20,30,40,50], nums2 = [5,15,25,35,45]) == [10, 20, 30, 40, 50]", "visibility": "reward", "passed": 1 }, { "id": "870#1", "src": "assert Solution().advantageCount(nums1 = [5,15,25,35], nums2 = [10,20,30,40]) == [15, 25,...
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