Datasets:

---

NjNBrl

/

fashion

like 0

Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
Accessories: struct<precision: double, recall: double, f1-score: double, support: double>
  child 0, precision: double
  child 1, recall: double
  child 2, f1-score: double
  child 3, support: double
Apparel: struct<precision: double, recall: double, f1-score: double, support: double>
  child 0, precision: double
  child 1, recall: double
  child 2, f1-score: double
  child 3, support: double
Footwear: struct<precision: double, recall: double, f1-score: double, support: double>
  child 0, precision: double
  child 1, recall: double
  child 2, f1-score: double
  child 3, support: double
Free Items: struct<precision: double, recall: double, f1-score: double, support: double>
  child 0, precision: double
  child 1, recall: double
  child 2, f1-score: double
  child 3, support: double
Personal Care: struct<precision: double, recall: double, f1-score: double, support: double>
  child 0, precision: double
  child 1, recall: double
  child 2, f1-score: double
  child 3, support: double
Sporting Goods: struct<precision: double, recall: double, f1-score: double, support: double>
  child 0, precision: double
  child 1, recall: double
  child 2, f1-score: double
  child 3, support: double
accuracy: double
macro avg: struct<precision: double, recall: double, f1-score: double, support: double>
  child 0, precision: double
  child 1, recall: double
  child 2, f1-score: double
  child 3, support: double
weighted avg: struct<precision: double, recall: double, f1-score: double, support: double>
  child 0, precision: double
  child 1, recall: double
  child 2, f1-score: double
  child 3, support: double
macro_f1: double
macro_recall: double
macro_precision: double
weighted_precision: double
confusion_matrix: list<item: list<item: int64>>
  child 0, item: list<item: int64>
      child 0, item: int64
weighted_f1: double
loss: double
weighted_recall: double
to
{'accuracy': Value('float64'), 'macro_precision': Value('float64'), 'macro_recall': Value('float64'), 'macro_f1': Value('float64'), 'weighted_precision': Value('float64'), 'weighted_recall': Value('float64'), 'weighted_f1': Value('float64'), 'confusion_matrix': List(List(Value('int64'))), 'loss': 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 289, 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 124, 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 2272, in table_cast
                  return cast_table_to_schema(table, schema)
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2218, in cast_table_to_schema
                  raise CastError(
              datasets.table.CastError: Couldn't cast
              Accessories: struct<precision: double, recall: double, f1-score: double, support: double>
                child 0, precision: double
                child 1, recall: double
                child 2, f1-score: double
                child 3, support: double
              Apparel: struct<precision: double, recall: double, f1-score: double, support: double>
                child 0, precision: double
                child 1, recall: double
                child 2, f1-score: double
                child 3, support: double
              Footwear: struct<precision: double, recall: double, f1-score: double, support: double>
                child 0, precision: double
                child 1, recall: double
                child 2, f1-score: double
                child 3, support: double
              Free Items: struct<precision: double, recall: double, f1-score: double, support: double>
                child 0, precision: double
                child 1, recall: double
                child 2, f1-score: double
                child 3, support: double
              Personal Care: struct<precision: double, recall: double, f1-score: double, support: double>
                child 0, precision: double
                child 1, recall: double
                child 2, f1-score: double
                child 3, support: double
              Sporting Goods: struct<precision: double, recall: double, f1-score: double, support: double>
                child 0, precision: double
                child 1, recall: double
                child 2, f1-score: double
                child 3, support: double
              accuracy: double
              macro avg: struct<precision: double, recall: double, f1-score: double, support: double>
                child 0, precision: double
                child 1, recall: double
                child 2, f1-score: double
                child 3, support: double
              weighted avg: struct<precision: double, recall: double, f1-score: double, support: double>
                child 0, precision: double
                child 1, recall: double
                child 2, f1-score: double
                child 3, support: double
              macro_f1: double
              macro_recall: double
              macro_precision: double
              weighted_precision: double
              confusion_matrix: list<item: list<item: int64>>
                child 0, item: list<item: int64>
                    child 0, item: int64
              weighted_f1: double
              loss: double
              weighted_recall: double
              to
              {'accuracy': Value('float64'), 'macro_precision': Value('float64'), 'macro_recall': Value('float64'), 'macro_f1': Value('float64'), 'weighted_precision': Value('float64'), 'weighted_recall': Value('float64'), 'weighted_f1': Value('float64'), 'confusion_matrix': List(List(Value('int64'))), 'loss': Value('float64')}
              because column names don't match