Dataset Viewer
The dataset viewer is not available for this split.
Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code: StreamingRowsError
Exception: CastError
Message: Couldn't cast
status: string
sforge_commit: string
images: struct<base: string, work: string, judge: string>
child 0, base: string
child 1, work: string
child 2, judge: string
deterministic_arrays: struct<train.npz: string, test_features.npz: string, test_labels.npz: string>
child 0, train.npz: string
child 1, test_features.npz: string
child 2, test_labels.npz: string
isolation: struct<judge_public_features_readable_by_nobody: bool, judge_private_labels_readable_by_nobody: bool (... 114 chars omitted)
child 0, judge_public_features_readable_by_nobody: bool
child 1, judge_private_labels_readable_by_nobody: bool
child 2, judge_evaluator_readable_by_nobody: bool
child 3, work_contains_test_features: bool
child 4, work_contains_private_labels: bool
baseline_eval: struct<submission_id: string, valid: bool, tests_passed: int64, tests_total: int64, pass_rate: doubl (... 96 chars omitted)
child 0, submission_id: string
child 1, valid: bool
child 2, tests_passed: int64
child 3, tests_total: int64
child 4, pass_rate: double
child 5, score: double
child 6, macro_f1_nsvf: double
child 7, minority_macro_f1_svf: double
child 8, runtime_seconds: double
qualification_boundary: string
checks: struct<sforge_schema: string, patient_disjoint_split: string, baseline_self_test: string, package_hy (... 14 chars omitted)
child 0, sforge_schema: string
child 1, patient_disjoint_split: string
child 2, baseline_self_test: string
child 3, package_hygiene: string
failures: list<item: null>
child 0, item: null
to
{'status': Value('string'), 'checks': {'sforge_schema': Value('string'), 'patient_disjoint_split': Value('string'), 'baseline_self_test': Value('string'), 'package_hygiene': Value('string')}, 'failures': List(Value('null'))}
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
status: string
sforge_commit: string
images: struct<base: string, work: string, judge: string>
child 0, base: string
child 1, work: string
child 2, judge: string
deterministic_arrays: struct<train.npz: string, test_features.npz: string, test_labels.npz: string>
child 0, train.npz: string
child 1, test_features.npz: string
child 2, test_labels.npz: string
isolation: struct<judge_public_features_readable_by_nobody: bool, judge_private_labels_readable_by_nobody: bool (... 114 chars omitted)
child 0, judge_public_features_readable_by_nobody: bool
child 1, judge_private_labels_readable_by_nobody: bool
child 2, judge_evaluator_readable_by_nobody: bool
child 3, work_contains_test_features: bool
child 4, work_contains_private_labels: bool
baseline_eval: struct<submission_id: string, valid: bool, tests_passed: int64, tests_total: int64, pass_rate: doubl (... 96 chars omitted)
child 0, submission_id: string
child 1, valid: bool
child 2, tests_passed: int64
child 3, tests_total: int64
child 4, pass_rate: double
child 5, score: double
child 6, macro_f1_nsvf: double
child 7, minority_macro_f1_svf: double
child 8, runtime_seconds: double
qualification_boundary: string
checks: struct<sforge_schema: string, patient_disjoint_split: string, baseline_self_test: string, package_hy (... 14 chars omitted)
child 0, sforge_schema: string
child 1, patient_disjoint_split: string
child 2, baseline_self_test: string
child 3, package_hygiene: string
failures: list<item: null>
child 0, item: null
to
{'status': Value('string'), 'checks': {'sforge_schema': Value('string'), 'patient_disjoint_split': Value('string'), 'baseline_self_test': Value('string'), 'package_hygiene': Value('string')}, 'failures': List(Value('null'))}
because column names don't matchNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
ECG-EdgeBench
EdgeBench-compatible real-science task: MIT-BIH cross-patient arrhythmia classification.
This package contains one locally runnable SForge task built from a real peer-reviewed protocol and a versioned public biomedical dataset. It is designed as a continuous, long-horizon model-improvement task rather than a one-shot unit-test exercise.
任务概览
- 领域： 生物医学信号处理 / ECG 心律失常分类
- 真实论文： de Chazal et al., IEEE TBME 2004
- 真实数据： MIT-BIH Arrhythmia Database v1.0.0
- 格式： 按照 EdgeBench 的 SForge、Work/Judge 隔离、隐藏标签和连续评分方式制作
- 难度： 44 位记录级跨患者划分，100,694 个真实心拍，类别严重不平衡
- Docker 基线： 37.1397/100，3/3 验证门通过，保留明显优化空间
Contents
sforge/BENCHMARK.yaml: benchmark base-image registry;sforge/mitbih_interpatient_arrhythmia.json: generated self-contained EdgeBench/SForge task;task_repo/: readable task source, starter baseline, deterministic data builder and hidden evaluator source;SOURCES.md: paper, dataset, DOI and license evidence;requirement_matrix.md: frozen acceptance requirements;validation_report.json: deterministic structural audit;baseline_report.json: real DS1-to-DS2 baseline result after data materialization;provenance/: immutable source and file ledgers.
Rebuild
python scripts/generate_task.py
python scripts/validate_delivery.py --upstream /path/to/EdgeBench
With Docker running and SForge installed from the pinned upstream checkout:
sforge --tasks-dir ./sforge build --task mitbih_interpatient_arrhythmia
sforge --tasks-dir ./sforge serve
sforge --tasks-dir ./sforge run --task mitbih_interpatient_arrhythmia --agent codex
Consult the exact CLI help for the pinned commit because command flags can evolve.
Qualification boundary
The task is structurally compatible with the checked upstream SForge commit and is locally validated against real data. It is not an official EdgeBench task and has not been accepted by the EdgeBench authors. Clinical use is prohibited.
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