Datasets:

---

jantrom

/

tile-obstacle-maps

Like 0

Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
data: string
data_rows: int64
data_sha256: string
test_rows: int64
test_frac: double
seed: int64
n_max: int64
success_key: string
created_utc: timestamp[s]
test_indices: list<item: int64>
  child 0, item: int64
note: string
removed_row_positions: list<item: int64>
  child 0, item: int64
descriptor: string
removed_rows: int64
source_test_sha256: string
percentile: double
source_test: string
per_bin_thresholds: list<item: struct<bin_n: string, test_tiles: int64, threshold: double, threshold_train_sample: int64 (... 115 chars omitted)
  child 0, item: struct<bin_n: string, test_tiles: int64, threshold: double, threshold_train_sample: int64, below_thr (... 103 chars omitted)
      child 0, bin_n: string
      child 1, test_tiles: int64
      child 2, threshold: double
      child 3, threshold_train_sample: int64
      child 4, below_threshold: int64
      child 5, fraction: double
      child 6, nn_median: double
      child 7, nn_min: double
      child 8, exact_descriptor_duplicates: int64
source_test_rows: int64
dedup_rows: int64
to
{'source_test': Value('string'), 'source_test_sha256': Value('string'), 'source_test_rows': Value('int64'), 'dedup_rows': Value('int64'), 'removed_rows': Value('int64'), 'removed_row_positions': List(Value('int64')), 'descriptor': Value('string'), 'percentile': Value('float64'), 'per_bin_thresholds': List({'bin_n': Value('string'), 'test_tiles': Value('int64'), 'threshold': Value('float64'), 'threshold_train_sample': Value('int64'), 'below_threshold': Value('int64'), 'fraction': Value('float64'), 'nn_median': Value('float64'), 'nn_min': Value('float64'), 'exact_descriptor_duplicates': Value('int64')}), 'created_utc': Value('timestamp[s]'), 'note': Value('string')}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 147, in get_rows_or_raise
                  return get_rows(
                      dataset=dataset,
                  ...<4 lines>...
                      column_names=column_names,
                  )
                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 127, in get_rows
                  rows_plus_one = list(itertools.islice(safe_iter(ds, dataset=dataset), rows_max_number + 1))
                File "/src/services/worker/src/worker/utils.py", line 483, in safe_iter
                  yield from ds.decode(False) if ds.features else ds
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2951, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2461, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2486, in _iter_arrow
                  for key, pa_table in self.ex_iterable._iter_arrow():
                                       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 547, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 430, in _iter_arrow
                  for key, pa_table in self.generate_tables_fn(**gen_kwags):
                                       ~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
                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 2378, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2306, in cast_table_to_schema
                  raise CastError(
                  ...<3 lines>...
                  )
              datasets.table.CastError: Couldn't cast
              data: string
              data_rows: int64
              data_sha256: string
              test_rows: int64
              test_frac: double
              seed: int64
              n_max: int64
              success_key: string
              created_utc: timestamp[s]
              test_indices: list<item: int64>
                child 0, item: int64
              note: string
              removed_row_positions: list<item: int64>
                child 0, item: int64
              descriptor: string
              removed_rows: int64
              source_test_sha256: string
              percentile: double
              source_test: string
              per_bin_thresholds: list<item: struct<bin_n: string, test_tiles: int64, threshold: double, threshold_train_sample: int64 (... 115 chars omitted)
                child 0, item: struct<bin_n: string, test_tiles: int64, threshold: double, threshold_train_sample: int64, below_thr (... 103 chars omitted)
                    child 0, bin_n: string
                    child 1, test_tiles: int64
                    child 2, threshold: double
                    child 3, threshold_train_sample: int64
                    child 4, below_threshold: int64
                    child 5, fraction: double
                    child 6, nn_median: double
                    child 7, nn_min: double
                    child 8, exact_descriptor_duplicates: int64
              source_test_rows: int64
              dedup_rows: int64
              to
              {'source_test': Value('string'), 'source_test_sha256': Value('string'), 'source_test_rows': Value('int64'), 'dedup_rows': Value('int64'), 'removed_rows': Value('int64'), 'removed_row_positions': List(Value('int64')), 'descriptor': Value('string'), 'percentile': Value('float64'), 'per_bin_thresholds': List({'bin_n': Value('string'), 'test_tiles': Value('int64'), 'threshold': Value('float64'), 'threshold_train_sample': Value('int64'), 'below_threshold': Value('int64'), 'fraction': Value('float64'), 'nn_median': Value('float64'), 'nn_min': Value('float64'), 'exact_descriptor_duplicates': Value('int64')}), 'created_utc': Value('timestamp[s]'), 'note': Value('string')}
              because column names don't match