Datasets:

---

emads

/

urdu-podcasts-pl-v3

like 0

Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
seg_id: string
stage: string
hyp: string
hyp2: string
avg_logprob: double
no_speech_prob: double
duration: double
ref_id: string
jaccard: double
n_proxy_dropped_devanagari: int64
table: list<item: struct<avg_logprob_min: double, no_speech_max: double, agreement_wer_max: double, kept_we (... 41 chars omitted)
  child 0, item: struct<avg_logprob_min: double, no_speech_max: double, agreement_wer_max: double, kept_wer: double,  (... 29 chars omitted)
      child 0, avg_logprob_min: double
      child 1, no_speech_max: double
      child 2, agreement_wer_max: double
      child 3, kept_wer: double
      child 4, yield: double
      child 5, n_kept: int64
target_wer: double
n_proxy: int64
n_kept: int64
unfiltered_wer: double
min_yield: double
kept_wer: double
fallback_wer: double
yield: double
thresholds: struct<avg_logprob_min: double, no_speech_max: double, compression_max: double, agreement_wer_max: d (... 331 chars omitted)
  child 0, avg_logprob_min: double
  child 1, no_speech_max: double
  child 2, compression_max: double
  child 3, agreement_wer_max: double
  child 4, latin_word_frac_max: double
  child 5, density_min: double
  child 6, density_max: double
  child 7, repeat_ngram: int64
  child 8, repeat_count: int64
  child 9, min_duration: double
  child 10, max_duration: double
  child 11, max_label_tokens: int64
  child 12, fuzzy_jaccard_min: double
  child 13, fuzzy_min_words: int64
  child 14, episode_hits_drop: int64
  child 15, channel_cap_hours: double
  child 16, calibrated_on: string
  child 17, train_ok: bool
to
{'thresholds': {'avg_logprob_min': Value('float64'), 'no_speech_max': Value('float64'), 'compression_max': Value('float64'), 'agreement_wer_max': Value('float64'), 'latin_word_frac_max': Value('float64'), 'density_min': Value('float64'), 'density_max': Value('float64'), 'repeat_ngram': Value('int64'), 'repeat_count': Value('int64'), 'min_duration': Value('float64'), 'max_duration': Value('float64'), 'max_label_tokens': Value('int64'), 'fuzzy_jaccard_min': Value('float64'), 'fuzzy_min_words': Value('int64'), 'episode_hits_drop': Value('int64'), 'channel_cap_hours': Value('float64'), 'calibrated_on': Value('string'), 'train_ok': Value('bool')}, 'n_proxy': Value('int64'), 'n_proxy_dropped_devanagari': Value('int64'), 'unfiltered_wer': Value('float64'), 'kept_wer': Value('float64'), 'yield': Value('float64'), 'n_kept': Value('int64'), 'target_wer': Value('float64'), 'fallback_wer': Value('float64'), 'min_yield': Value('float64'), 'table': List({'avg_logprob_min': Value('float64'), 'no_speech_max': Value('float64'), 'agreement_wer_max': Value('float64'), 'kept_wer': Value('float64'), 'yield': Value('float64'), 'n_kept': Value('int64')})}
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 2840, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2373, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2398, 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 536, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 419, 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
              seg_id: string
              stage: string
              hyp: string
              hyp2: string
              avg_logprob: double
              no_speech_prob: double
              duration: double
              ref_id: string
              jaccard: double
              n_proxy_dropped_devanagari: int64
              table: list<item: struct<avg_logprob_min: double, no_speech_max: double, agreement_wer_max: double, kept_we (... 41 chars omitted)
                child 0, item: struct<avg_logprob_min: double, no_speech_max: double, agreement_wer_max: double, kept_wer: double,  (... 29 chars omitted)
                    child 0, avg_logprob_min: double
                    child 1, no_speech_max: double
                    child 2, agreement_wer_max: double
                    child 3, kept_wer: double
                    child 4, yield: double
                    child 5, n_kept: int64
              target_wer: double
              n_proxy: int64
              n_kept: int64
              unfiltered_wer: double
              min_yield: double
              kept_wer: double
              fallback_wer: double
              yield: double
              thresholds: struct<avg_logprob_min: double, no_speech_max: double, compression_max: double, agreement_wer_max: d (... 331 chars omitted)
                child 0, avg_logprob_min: double
                child 1, no_speech_max: double
                child 2, compression_max: double
                child 3, agreement_wer_max: double
                child 4, latin_word_frac_max: double
                child 5, density_min: double
                child 6, density_max: double
                child 7, repeat_ngram: int64
                child 8, repeat_count: int64
                child 9, min_duration: double
                child 10, max_duration: double
                child 11, max_label_tokens: int64
                child 12, fuzzy_jaccard_min: double
                child 13, fuzzy_min_words: int64
                child 14, episode_hits_drop: int64
                child 15, channel_cap_hours: double
                child 16, calibrated_on: string
                child 17, train_ok: bool
              to
              {'thresholds': {'avg_logprob_min': Value('float64'), 'no_speech_max': Value('float64'), 'compression_max': Value('float64'), 'agreement_wer_max': Value('float64'), 'latin_word_frac_max': Value('float64'), 'density_min': Value('float64'), 'density_max': Value('float64'), 'repeat_ngram': Value('int64'), 'repeat_count': Value('int64'), 'min_duration': Value('float64'), 'max_duration': Value('float64'), 'max_label_tokens': Value('int64'), 'fuzzy_jaccard_min': Value('float64'), 'fuzzy_min_words': Value('int64'), 'episode_hits_drop': Value('int64'), 'channel_cap_hours': Value('float64'), 'calibrated_on': Value('string'), 'train_ok': Value('bool')}, 'n_proxy': Value('int64'), 'n_proxy_dropped_devanagari': Value('int64'), 'unfiltered_wer': Value('float64'), 'kept_wer': Value('float64'), 'yield': Value('float64'), 'n_kept': Value('int64'), 'target_wer': Value('float64'), 'fallback_wer': Value('float64'), 'min_yield': Value('float64'), 'table': List({'avg_logprob_min': Value('float64'), 'no_speech_max': Value('float64'), 'agreement_wer_max': Value('float64'), 'kept_wer': Value('float64'), 'yield': Value('float64'), 'n_kept': Value('int64')})}
              because column names don't match