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afabench

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AFABench 1

Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
job_record_version: int64
stage: string
name: string
dataset_key: string
dataset_realization_index: int64
pretrain_seed: int64
train_seed: int64
eval_seed: int64
train_hard_budget: int64
train_soft_budget_param: null
eval_hard_budget: int64
eval_soft_budget_param: null
eval_batch_size: int64
started_at: string
ended_at: string
job_duration_seconds: double
exit_status: string
exit_code: int64
device: string
cpus: int64
gpus: int64
time_limit_minutes: int64
gpu_model: string
cpu_model: string
host: string
slurm_job_id: string
slurm_cluster: string
code_commit: string
smoke_test: bool
bundle_version: string
class_name: string
metadata: struct<dataset_realization_index: int64, seed_for_split: int64, generated_at: string, kwargs: struct (... 31 chars omitted)
  child 0, dataset_realization_index: int64
  child 1, seed_for_split: int64
  child 2, generated_at: string
  child 3, kwargs: struct<root: string, sha256: string>
      child 0, root: string
      child 1, sha256: string
provenance: struct<provenance_version: int64, stage: string, created_at: string, code_commit: string, code_dirty (... 818 chars omitted)
  child 0, provenance_version: int64
  child 1, stage: string
  child 2, created_at: string
  child 3, code_commit: string
  child 4, code_dirty: bool
  child 5, resolved_config: struct<save_path: string, dataset_realization_indices: list<item: int64>, seeds: list<item: int64>,  (... 145 chars omitted)
      child 0, save_path: string
      child 1, dataset_realization_ind
...
in: double
          child 1, val: double
          child 2, test: double
      child 4, dataset: struct<class_name: string, kwargs: struct<root: string, sha256: string>>
          child 0, class_name: string
          child 1, kwargs: struct<root: string, sha256: string>
              child 0, root: string
              child 1, sha256: string
  child 6, seed: int64
  child 7, smoke_test: bool
  child 8, method_name: null
  child 9, dataset_key: string
  child 10, dataset_realization_index: int64
  child 11, split: string
  child 12, inputs: list<item: null>
      child 0, item: null
  child 13, environment: struct<python_version: string, afabench_version: string, torch_version: string, numpy_version: strin (... 69 chars omitted)
      child 0, python_version: string
      child 1, afabench_version: string
      child 2, torch_version: string
      child 3, numpy_version: string
      child 4, pandas_version: string
      child 5, lockfile_sha256: string
      child 6, platform: string
  child 14, compute: struct<device: string, accelerator_name: null, cuda_version: string, cudnn_version: int64, float32_m (... 106 chars omitted)
      child 0, device: string
      child 1, accelerator_name: null
      child 2, cuda_version: string
      child 3, cudnn_version: int64
      child 4, float32_matmul_precision: string
      child 5, cudnn_deterministic: bool
      child 6, cudnn_benchmark: bool
      child 7, deterministic_algorithms: bool
class_version: null
content_hash: string
to
{'bundle_version': Value('string'), 'class_name': Value('string'), 'class_version': Value('null'), 'metadata': {'dataset_realization_index': Value('int64'), 'seed_for_split': Value('int64'), 'generated_at': Value('string'), 'kwargs': {'root': Value('string'), 'sha256': Value('string')}}, 'provenance': {'provenance_version': Value('int64'), 'stage': Value('string'), 'created_at': Value('string'), 'code_commit': Value('string'), 'code_dirty': Value('bool'), 'resolved_config': {'save_path': Value('string'), 'dataset_realization_indices': List(Value('int64')), 'seeds': List(Value('int64')), 'split_ratio': {'train': Value('float64'), 'val': Value('float64'), 'test': Value('float64')}, 'dataset': {'class_name': Value('string'), 'kwargs': {'root': Value('string'), 'sha256': Value('string')}}}, 'seed': Value('int64'), 'smoke_test': Value('bool'), 'method_name': Value('null'), 'dataset_key': Value('string'), 'dataset_realization_index': Value('int64'), 'split': Value('string'), 'inputs': List(Value('null')), 'environment': {'python_version': Value('string'), 'afabench_version': Value('string'), 'torch_version': Value('string'), 'numpy_version': Value('string'), 'pandas_version': Value('string'), 'lockfile_sha256': Value('string'), 'platform': Value('string')}, 'compute': {'device': Value('string'), 'accelerator_name': Value('null'), 'cuda_version': Value('string'), 'cudnn_version': Value('int64'), 'float32_matmul_precision': Value('string'), 'cudnn_deterministic': Value('bool'), 'cudnn_benchmark': Value('bool'), 'deterministic_algorithms': Value('bool')}}, 'content_hash': Value('string')}
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 2951, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2461, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2486, 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 547, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 430, 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
              job_record_version: int64
              stage: string
              name: string
              dataset_key: string
              dataset_realization_index: int64
              pretrain_seed: int64
              train_seed: int64
              eval_seed: int64
              train_hard_budget: int64
              train_soft_budget_param: null
              eval_hard_budget: int64
              eval_soft_budget_param: null
              eval_batch_size: int64
              started_at: string
              ended_at: string
              job_duration_seconds: double
              exit_status: string
              exit_code: int64
              device: string
              cpus: int64
              gpus: int64
              time_limit_minutes: int64
              gpu_model: string
              cpu_model: string
              host: string
              slurm_job_id: string
              slurm_cluster: string
              code_commit: string
              smoke_test: bool
              bundle_version: string
              class_name: string
              metadata: struct<dataset_realization_index: int64, seed_for_split: int64, generated_at: string, kwargs: struct (... 31 chars omitted)
                child 0, dataset_realization_index: int64
                child 1, seed_for_split: int64
                child 2, generated_at: string
                child 3, kwargs: struct<root: string, sha256: string>
                    child 0, root: string
                    child 1, sha256: string
              provenance: struct<provenance_version: int64, stage: string, created_at: string, code_commit: string, code_dirty (... 818 chars omitted)
                child 0, provenance_version: int64
                child 1, stage: string
                child 2, created_at: string
                child 3, code_commit: string
                child 4, code_dirty: bool
                child 5, resolved_config: struct<save_path: string, dataset_realization_indices: list<item: int64>, seeds: list<item: int64>,  (... 145 chars omitted)
                    child 0, save_path: string
                    child 1, dataset_realization_ind
              ...
              in: double
                        child 1, val: double
                        child 2, test: double
                    child 4, dataset: struct<class_name: string, kwargs: struct<root: string, sha256: string>>
                        child 0, class_name: string
                        child 1, kwargs: struct<root: string, sha256: string>
                            child 0, root: string
                            child 1, sha256: string
                child 6, seed: int64
                child 7, smoke_test: bool
                child 8, method_name: null
                child 9, dataset_key: string
                child 10, dataset_realization_index: int64
                child 11, split: string
                child 12, inputs: list<item: null>
                    child 0, item: null
                child 13, environment: struct<python_version: string, afabench_version: string, torch_version: string, numpy_version: strin (... 69 chars omitted)
                    child 0, python_version: string
                    child 1, afabench_version: string
                    child 2, torch_version: string
                    child 3, numpy_version: string
                    child 4, pandas_version: string
                    child 5, lockfile_sha256: string
                    child 6, platform: string
                child 14, compute: struct<device: string, accelerator_name: null, cuda_version: string, cudnn_version: int64, float32_m (... 106 chars omitted)
                    child 0, device: string
                    child 1, accelerator_name: null
                    child 2, cuda_version: string
                    child 3, cudnn_version: int64
                    child 4, float32_matmul_precision: string
                    child 5, cudnn_deterministic: bool
                    child 6, cudnn_benchmark: bool
                    child 7, deterministic_algorithms: bool
              class_version: null
              content_hash: string
              to
              {'bundle_version': Value('string'), 'class_name': Value('string'), 'class_version': Value('null'), 'metadata': {'dataset_realization_index': Value('int64'), 'seed_for_split': Value('int64'), 'generated_at': Value('string'), 'kwargs': {'root': Value('string'), 'sha256': Value('string')}}, 'provenance': {'provenance_version': Value('int64'), 'stage': Value('string'), 'created_at': Value('string'), 'code_commit': Value('string'), 'code_dirty': Value('bool'), 'resolved_config': {'save_path': Value('string'), 'dataset_realization_indices': List(Value('int64')), 'seeds': List(Value('int64')), 'split_ratio': {'train': Value('float64'), 'val': Value('float64'), 'test': Value('float64')}, 'dataset': {'class_name': Value('string'), 'kwargs': {'root': Value('string'), 'sha256': Value('string')}}}, 'seed': Value('int64'), 'smoke_test': Value('bool'), 'method_name': Value('null'), 'dataset_key': Value('string'), 'dataset_realization_index': Value('int64'), 'split': Value('string'), 'inputs': List(Value('null')), 'environment': {'python_version': Value('string'), 'afabench_version': Value('string'), 'torch_version': Value('string'), 'numpy_version': Value('string'), 'pandas_version': Value('string'), 'lockfile_sha256': Value('string'), 'platform': Value('string')}, 'compute': {'device': Value('string'), 'accelerator_name': Value('null'), 'cuda_version': Value('string'), 'cudnn_version': Value('int64'), 'float32_matmul_precision': Value('string'), 'cudnn_deterministic': Value('bool'), 'cudnn_benchmark': Value('bool'), 'deterministic_algorithms': Value('bool')}}, 'content_hash': Value('string')}
              because column names don't match