Datasets:

---

aalisha

/

srmdtranslations

like 0

Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
input: string
output: string
start_s: double
end_s: double
srt_index: int64
confidence: null
reasoning: string
content_id: string
hypothesis: string
semantic_accuracy: null
spiritual_fidelity: null
expression_quality: null
asr_robustness: null
contextual_coherence: null
issues: null
overall_reasoning: null
overall: null
index: int64
weighted_score: null
intent_score: int64
intent_explanation: string
entity_score: double
ground_truth_entities: string
preserved_entities: string
missing_entities: string
entity_explanation: string
to
{'input': Value('string'), 'output': Value('string'), 'start_s': Value('float64'), 'end_s': Value('float64'), 'srt_index': Value('int64'), 'confidence': Value('string'), 'reasoning': Value('string'), 'content_id': Value('string'), 'hypothesis': Value('string'), 'semantic_accuracy': {'reasoning': Value('string'), 'score': Value('int64')}, 'spiritual_fidelity': {'reasoning': Value('string'), 'score': Value('int64')}, 'expression_quality': {'reasoning': Value('string'), 'score': Value('int64')}, 'asr_robustness': {'reasoning': Value('string'), 'score': Value('int64')}, 'contextual_coherence': {'reasoning': Value('string'), 'score': Value('int64')}, 'issues': List({'type': Value('string'), 'description': Value('string'), 'severity': Value('string')}), 'overall_reasoning': Value('string'), 'overall': Value('int64'), 'index': Value('int64'), 'weighted_score': 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
              input: string
              output: string
              start_s: double
              end_s: double
              srt_index: int64
              confidence: null
              reasoning: string
              content_id: string
              hypothesis: string
              semantic_accuracy: null
              spiritual_fidelity: null
              expression_quality: null
              asr_robustness: null
              contextual_coherence: null
              issues: null
              overall_reasoning: null
              overall: null
              index: int64
              weighted_score: null
              intent_score: int64
              intent_explanation: string
              entity_score: double
              ground_truth_entities: string
              preserved_entities: string
              missing_entities: string
              entity_explanation: string
              to
              {'input': Value('string'), 'output': Value('string'), 'start_s': Value('float64'), 'end_s': Value('float64'), 'srt_index': Value('int64'), 'confidence': Value('string'), 'reasoning': Value('string'), 'content_id': Value('string'), 'hypothesis': Value('string'), 'semantic_accuracy': {'reasoning': Value('string'), 'score': Value('int64')}, 'spiritual_fidelity': {'reasoning': Value('string'), 'score': Value('int64')}, 'expression_quality': {'reasoning': Value('string'), 'score': Value('int64')}, 'asr_robustness': {'reasoning': Value('string'), 'score': Value('int64')}, 'contextual_coherence': {'reasoning': Value('string'), 'score': Value('int64')}, 'issues': List({'type': Value('string'), 'description': Value('string'), 'severity': Value('string')}), 'overall_reasoning': Value('string'), 'overall': Value('int64'), 'index': Value('int64'), 'weighted_score': Value('float64')}
              because column names don't match