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msc-thesis-org

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msc-thesis-org 2

Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
full: struct<counts: struct<encoder_valid_residues: int64, proteins: int64>, output: string, probe_split_c (... 75 chars omitted)
  child 0, counts: struct<encoder_valid_residues: int64, proteins: int64>
      child 0, encoder_valid_residues: int64
      child 1, proteins: int64
  child 1, output: string
  child 2, probe_split_counts: struct<probe_test: int64, probe_train: int64>
      child 0, probe_test: int64
      child 1, probe_train: int64
  child 3, storage_bytes: int64
pilot: struct<counts: struct<encoder_valid_residues: int64, proteins: int64>, output: string, probe_split_c (... 75 chars omitted)
  child 0, counts: struct<encoder_valid_residues: int64, proteins: int64>
      child 0, encoder_valid_residues: int64
      child 1, proteins: int64
  child 1, output: string
  child 2, probe_split_counts: struct<probe_test: int64, probe_train: int64>
      child 0, probe_test: int64
      child 1, probe_train: int64
  child 3, storage_bytes: int64
provenance: struct<checkpoint_path: string, checkpoint_sha256: string, ema_metadata: struct<decay: double, effec (... 537 chars omitted)
  child 0, checkpoint_path: string
  child 1, checkpoint_sha256: string
  child 2, ema_metadata: struct<decay: double, effective_decay: double, exclude: list<item: null>, include: list<item: string (... 111 chars omitted)
      child 0, decay: double
      child 1, effective_decay: double
      child 2, exclude: list<item: null>
          child 0, item: null
      child 3, include: list<item: st
...
e_train: int64>, seed: int64, selected_prot (... 46 chars omitted)
  child 0, probe_split_counts: struct<probe_test: int64, probe_train: int64>
      child 0, probe_test: int64
      child 1, probe_train: int64
  child 1, seed: int64
  child 2, selected_protein_ids: list<item: string>
      child 0, item: string
  child 3, strategy: string
mode: string
counts: struct<encoder_valid_residues: int64, proteins: int64>
  child 0, encoder_valid_residues: int64
  child 1, proteins: int64
shard_size_proteins: int64
shards: list<item: struct<path: string, proteins: int64, residues: int64, sha256: string, size_bytes: int64> (... 1 chars omitted)
  child 0, item: struct<path: string, proteins: int64, residues: int64, sha256: string, size_bytes: int64>
      child 0, path: string
      child 1, proteins: int64
      child 2, residues: int64
      child 3, sha256: string
      child 4, size_bytes: int64
capture: struct<batch_size: int64, blocks: struct<block_1: int64, block_12: int64, block_6: int64>, context:  (... 178 chars omitted)
  child 0, batch_size: int64
  child 1, blocks: struct<block_1: int64, block_12: int64, block_6: int64>
      child 0, block_1: int64
      child 1, block_12: int64
      child 2, block_6: int64
  child 2, context: string
  child 3, dtype: string
  child 4, encoder_validity_expression: string
  child 5, hidden_width: int64
  child 6, latent_representation: string
  child 7, latent_width: int64
  child 8, rotation: null
  child 9, sampled_z_latent_saved: bool
to
{'artifact': Value('string'), 'capture': {'batch_size': Value('int64'), 'blocks': {'block_1': Value('int64'), 'block_12': Value('int64'), 'block_6': Value('int64')}, 'context': Value('string'), 'dtype': Value('string'), 'encoder_validity_expression': Value('string'), 'hidden_width': Value('int64'), 'latent_representation': Value('string'), 'latent_width': Value('int64'), 'rotation': Value('null'), 'sampled_z_latent_saved': Value('bool')}, 'counts': {'encoder_valid_residues': Value('int64'), 'proteins': Value('int64')}, 'mode': Value('string'), 'provenance': {'checkpoint_path': Value('string'), 'checkpoint_sha256': Value('string'), 'ema_metadata': {'decay': Value('float64'), 'effective_decay': Value('float64'), 'exclude': List(Value('null')), 'include': List(Value('string')), 'last_ema_step': Value('int64'), 'num_updates': Value('int64'), 'start_step': Value('int64'), 'update_every': Value('int64'), 'upstream_revision': Value('string')}, 'encoder_config_path': Value('string'), 'encoder_config_sha256': Value('string'), 'encoder_source': Value('string'), 'global_step': Value('int64'), 'staged_evaluation_path': Value('string'), 'staged_evaluation_provenance': {'encoder_source': Value('string'), 'latent_dim': Value('int64'), 'projector': Value('null'), 'schema_version': Value('int64'), 'source_checkpoint_sha256': Value('string'), 'source_global_step': Value('int64')}, 'staged_evaluation_sha256': Value('string')}, 'schema_version': Value('int64'), 'selection': {'probe_split_counts': {'probe_test': Value('int64'), 'probe_train': Value('int64')}, 'seed': Value('int64'), 'selected_protein_ids': List(Value('string')), 'strategy': Value('string')}, 'shard_size_proteins': Value('int64'), 'shards': List({'path': Value('string'), 'proteins': Value('int64'), 'residues': Value('int64'), 'sha256': Value('string'), 'size_bytes': 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
              full: struct<counts: struct<encoder_valid_residues: int64, proteins: int64>, output: string, probe_split_c (... 75 chars omitted)
                child 0, counts: struct<encoder_valid_residues: int64, proteins: int64>
                    child 0, encoder_valid_residues: int64
                    child 1, proteins: int64
                child 1, output: string
                child 2, probe_split_counts: struct<probe_test: int64, probe_train: int64>
                    child 0, probe_test: int64
                    child 1, probe_train: int64
                child 3, storage_bytes: int64
              pilot: struct<counts: struct<encoder_valid_residues: int64, proteins: int64>, output: string, probe_split_c (... 75 chars omitted)
                child 0, counts: struct<encoder_valid_residues: int64, proteins: int64>
                    child 0, encoder_valid_residues: int64
                    child 1, proteins: int64
                child 1, output: string
                child 2, probe_split_counts: struct<probe_test: int64, probe_train: int64>
                    child 0, probe_test: int64
                    child 1, probe_train: int64
                child 3, storage_bytes: int64
              provenance: struct<checkpoint_path: string, checkpoint_sha256: string, ema_metadata: struct<decay: double, effec (... 537 chars omitted)
                child 0, checkpoint_path: string
                child 1, checkpoint_sha256: string
                child 2, ema_metadata: struct<decay: double, effective_decay: double, exclude: list<item: null>, include: list<item: string (... 111 chars omitted)
                    child 0, decay: double
                    child 1, effective_decay: double
                    child 2, exclude: list<item: null>
                        child 0, item: null
                    child 3, include: list<item: st
              ...
              e_train: int64>, seed: int64, selected_prot (... 46 chars omitted)
                child 0, probe_split_counts: struct<probe_test: int64, probe_train: int64>
                    child 0, probe_test: int64
                    child 1, probe_train: int64
                child 1, seed: int64
                child 2, selected_protein_ids: list<item: string>
                    child 0, item: string
                child 3, strategy: string
              mode: string
              counts: struct<encoder_valid_residues: int64, proteins: int64>
                child 0, encoder_valid_residues: int64
                child 1, proteins: int64
              shard_size_proteins: int64
              shards: list<item: struct<path: string, proteins: int64, residues: int64, sha256: string, size_bytes: int64> (... 1 chars omitted)
                child 0, item: struct<path: string, proteins: int64, residues: int64, sha256: string, size_bytes: int64>
                    child 0, path: string
                    child 1, proteins: int64
                    child 2, residues: int64
                    child 3, sha256: string
                    child 4, size_bytes: int64
              capture: struct<batch_size: int64, blocks: struct<block_1: int64, block_12: int64, block_6: int64>, context:  (... 178 chars omitted)
                child 0, batch_size: int64
                child 1, blocks: struct<block_1: int64, block_12: int64, block_6: int64>
                    child 0, block_1: int64
                    child 1, block_12: int64
                    child 2, block_6: int64
                child 2, context: string
                child 3, dtype: string
                child 4, encoder_validity_expression: string
                child 5, hidden_width: int64
                child 6, latent_representation: string
                child 7, latent_width: int64
                child 8, rotation: null
                child 9, sampled_z_latent_saved: bool
              to
              {'artifact': Value('string'), 'capture': {'batch_size': Value('int64'), 'blocks': {'block_1': Value('int64'), 'block_12': Value('int64'), 'block_6': Value('int64')}, 'context': Value('string'), 'dtype': Value('string'), 'encoder_validity_expression': Value('string'), 'hidden_width': Value('int64'), 'latent_representation': Value('string'), 'latent_width': Value('int64'), 'rotation': Value('null'), 'sampled_z_latent_saved': Value('bool')}, 'counts': {'encoder_valid_residues': Value('int64'), 'proteins': Value('int64')}, 'mode': Value('string'), 'provenance': {'checkpoint_path': Value('string'), 'checkpoint_sha256': Value('string'), 'ema_metadata': {'decay': Value('float64'), 'effective_decay': Value('float64'), 'exclude': List(Value('null')), 'include': List(Value('string')), 'last_ema_step': Value('int64'), 'num_updates': Value('int64'), 'start_step': Value('int64'), 'update_every': Value('int64'), 'upstream_revision': Value('string')}, 'encoder_config_path': Value('string'), 'encoder_config_sha256': Value('string'), 'encoder_source': Value('string'), 'global_step': Value('int64'), 'staged_evaluation_path': Value('string'), 'staged_evaluation_provenance': {'encoder_source': Value('string'), 'latent_dim': Value('int64'), 'projector': Value('null'), 'schema_version': Value('int64'), 'source_checkpoint_sha256': Value('string'), 'source_global_step': Value('int64')}, 'staged_evaluation_sha256': Value('string')}, 'schema_version': Value('int64'), 'selection': {'probe_split_counts': {'probe_test': Value('int64'), 'probe_train': Value('int64')}, 'seed': Value('int64'), 'selected_protein_ids': List(Value('string')), 'strategy': Value('string')}, 'shard_size_proteins': Value('int64'), 'shards': List({'path': Value('string'), 'proteins': Value('int64'), 'residues': Value('int64'), 'sha256': Value('string'), 'size_bytes': Value('int64')})}
              because column names don't match