Datasets:

---

ppxscal

/

HiDRA-assets

like 0

Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
cell: string
direction: string
healthy_source: string
n_samples: int64
n_landmarks: int64
landmark_genes: list<item: string>
  child 0, item: string
disease_expression: list<item: double>
  child 0, item: double
healthy_expression: list<item: double>
  child 0, item: double
expr_deltas: list<item: double>
  child 0, item: double
final_epoch: int64
history: list<item: struct<epoch: int64, resp: double, disc: double, ess: double, val_h1: double, val_h5: dou (... 22 chars omitted)
  child 0, item: struct<epoch: int64, resp: double, disc: double, ess: double, val_h1: double, val_h5: double, val_h1 (... 10 chars omitted)
      child 0, epoch: int64
      child 1, resp: double
      child 2, disc: double
      child 3, ess: double
      child 4, val_h1: double
      child 5, val_h5: double
      child 6, val_h10: double
best_val_hits1: double
args: struct<batch_size: int64, epochs: int64, patience: int64, lr: double, seed: int64, no_cycle: bool, c (... 99 chars omitted)
  child 0, batch_size: int64
  child 1, epochs: int64
  child 2, patience: int64
  child 3, lr: double
  child 4, seed: int64
  child 5, no_cycle: bool
  child 6, checkpoint_dir: string
  child 7, protrek_pkl: string
  child 8, depmap_pkl: string
  child 9, shrna_pkl: string
  child 10, kg_path: string
to
{'best_val_hits1': Value('float64'), 'final_epoch': Value('int64'), 'history': List({'epoch': Value('int64'), 'resp': Value('float64'), 'disc': Value('float64'), 'ess': Value('float64'), 'val_h1': Value('float64'), 'val_h5': Value('float64'), 'val_h10': Value('float64')}), 'args': {'batch_size': Value('int64'), 'epochs': Value('int64'), 'patience': Value('int64'), 'lr': Value('float64'), 'seed': Value('int64'), 'no_cycle': Value('bool'), 'checkpoint_dir': Value('string'), 'protrek_pkl': Value('string'), 'depmap_pkl': Value('string'), 'shrna_pkl': Value('string'), 'kg_path': Value('string')}}
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 295, 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 2281, in table_cast
                  return cast_table_to_schema(table, schema)
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2227, in cast_table_to_schema
                  raise CastError(
              datasets.table.CastError: Couldn't cast
              cell: string
              direction: string
              healthy_source: string
              n_samples: int64
              n_landmarks: int64
              landmark_genes: list<item: string>
                child 0, item: string
              disease_expression: list<item: double>
                child 0, item: double
              healthy_expression: list<item: double>
                child 0, item: double
              expr_deltas: list<item: double>
                child 0, item: double
              final_epoch: int64
              history: list<item: struct<epoch: int64, resp: double, disc: double, ess: double, val_h1: double, val_h5: dou (... 22 chars omitted)
                child 0, item: struct<epoch: int64, resp: double, disc: double, ess: double, val_h1: double, val_h5: double, val_h1 (... 10 chars omitted)
                    child 0, epoch: int64
                    child 1, resp: double
                    child 2, disc: double
                    child 3, ess: double
                    child 4, val_h1: double
                    child 5, val_h5: double
                    child 6, val_h10: double
              best_val_hits1: double
              args: struct<batch_size: int64, epochs: int64, patience: int64, lr: double, seed: int64, no_cycle: bool, c (... 99 chars omitted)
                child 0, batch_size: int64
                child 1, epochs: int64
                child 2, patience: int64
                child 3, lr: double
                child 4, seed: int64
                child 5, no_cycle: bool
                child 6, checkpoint_dir: string
                child 7, protrek_pkl: string
                child 8, depmap_pkl: string
                child 9, shrna_pkl: string
                child 10, kg_path: string
              to
              {'best_val_hits1': Value('float64'), 'final_epoch': Value('int64'), 'history': List({'epoch': Value('int64'), 'resp': Value('float64'), 'disc': Value('float64'), 'ess': Value('float64'), 'val_h1': Value('float64'), 'val_h5': Value('float64'), 'val_h10': Value('float64')}), 'args': {'batch_size': Value('int64'), 'epochs': Value('int64'), 'patience': Value('int64'), 'lr': Value('float64'), 'seed': Value('int64'), 'no_cycle': Value('bool'), 'checkpoint_dir': Value('string'), 'protrek_pkl': Value('string'), 'depmap_pkl': Value('string'), 'shrna_pkl': Value('string'), 'kg_path': Value('string')}}
              because column names don't match