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The dataset generation failed
Error code: DatasetGenerationError
Exception: CastError
Message: Couldn't cast
archive: string
archive_sha256: string
cli_help_sha256: string
import_probe: struct<av: string, config_names: list<item: string>, datasets: string, jax: string, jaxlib: string, (... 227 chars omitted)
child 0, av: string
child 1, config_names: list<item: string>
child 0, item: string
child 2, datasets: string
child 3, jax: string
child 4, jaxlib: string
child 5, numpy: string
child 6, numpy_file: string
child 7, openpi_file: string
child 8, parallel_vla_file: string
child 9, pyarrow: string
child 10, python: string
child 11, torch: string
child 12, torch_cuda: string
child 13, torch_file: string
child 14, torchvision: string
child 15, transformers: string
child 16, tyro: string
import_probe_sha256: string
manifest_sha256: string
manifest_verified: bool
portable_python_relocation_verified: bool
source_commits: struct<OpenPI_RoboTwin: string, parallelVLA: string>
child 0, OpenPI_RoboTwin: string
child 1, parallelVLA: string
status: string
validated_at_utc: string
action_representation: string
allow_synthetic_fixture: bool
episode_end_padding: string
implementation_sha256: string
dataset_root: string
population_std_ddof: int64
parquet_inventory_sha256: string
masked_action_padding_vector_count: int64
training_split: string
episode_lengths: list<item: int64>
child 0, item: int64
episode_count: int64
action_horizon: int64
statistics_dtype: string
action_vector_count: int64
training_episode_indices: list<item: int64>
child 0, item: int64
action_dim: int64
copied_from_meta_stats: bool
norm_stats_sha256: string
state_dim: int64
dataset_codebase_version: string
action_padding_mask_source: string
statistics_source: string
dataset_revision: string
delta_action_dims: list<item: null>
child 0, item: null
model_action_dim: int64
implementation: string
frame_count: int64
meta_info_sha256: string
training_split_name: string
parquet_inventory: list<item: struct<path: string, sha256: string, size: int64>>
child 0, item: struct<path: string, sha256: string, size: int64>
child 0, path: string
child 1, sha256: string
child 2, size: int64
quantile_method: string
to
{'action_dim': Value('int64'), 'action_horizon': Value('int64'), 'action_padding_mask_source': Value('string'), 'action_representation': Value('string'), 'action_vector_count': Value('int64'), 'allow_synthetic_fixture': Value('bool'), 'copied_from_meta_stats': Value('bool'), 'dataset_codebase_version': Value('string'), 'dataset_revision': Value('string'), 'dataset_root': Value('string'), 'delta_action_dims': List(Value('null')), 'episode_count': Value('int64'), 'episode_end_padding': Value('string'), 'episode_lengths': List(Value('int64')), 'frame_count': Value('int64'), 'implementation': Value('string'), 'implementation_sha256': Value('string'), 'masked_action_padding_vector_count': Value('int64'), 'meta_info_sha256': Value('string'), 'model_action_dim': Value('int64'), 'norm_stats_sha256': Value('string'), 'parquet_inventory': List({'path': Value('string'), 'sha256': Value('string'), 'size': Value('int64')}), 'parquet_inventory_sha256': Value('string'), 'population_std_ddof': Value('int64'), 'quantile_method': Value('string'), 'state_dim': Value('int64'), 'statistics_dtype': Value('string'), 'statistics_source': Value('string'), 'status': Value('string'), 'training_episode_indices': List(Value('int64')), 'training_split': Value('string'), 'training_split_name': Value('string')}
because column names don't match
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1816, in _prepare_split_single
for key, table in generator:
^^^^^^^^^
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 613, in wrapped
for item in generator(*args, **kwargs):
~~~~~~~~~^^^^^^^^^^^^^^^^^
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 2369, in table_cast
return cast_table_to_schema(table, schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2297, in cast_table_to_schema
raise CastError(
...<3 lines>...
)
datasets.table.CastError: Couldn't cast
archive: string
archive_sha256: string
cli_help_sha256: string
import_probe: struct<av: string, config_names: list<item: string>, datasets: string, jax: string, jaxlib: string, (... 227 chars omitted)
child 0, av: string
child 1, config_names: list<item: string>
child 0, item: string
child 2, datasets: string
child 3, jax: string
child 4, jaxlib: string
child 5, numpy: string
child 6, numpy_file: string
child 7, openpi_file: string
child 8, parallel_vla_file: string
child 9, pyarrow: string
child 10, python: string
child 11, torch: string
child 12, torch_cuda: string
child 13, torch_file: string
child 14, torchvision: string
child 15, transformers: string
child 16, tyro: string
import_probe_sha256: string
manifest_sha256: string
manifest_verified: bool
portable_python_relocation_verified: bool
source_commits: struct<OpenPI_RoboTwin: string, parallelVLA: string>
child 0, OpenPI_RoboTwin: string
child 1, parallelVLA: string
status: string
validated_at_utc: string
action_representation: string
allow_synthetic_fixture: bool
episode_end_padding: string
implementation_sha256: string
dataset_root: string
population_std_ddof: int64
parquet_inventory_sha256: string
masked_action_padding_vector_count: int64
training_split: string
episode_lengths: list<item: int64>
child 0, item: int64
episode_count: int64
action_horizon: int64
statistics_dtype: string
action_vector_count: int64
training_episode_indices: list<item: int64>
child 0, item: int64
action_dim: int64
copied_from_meta_stats: bool
norm_stats_sha256: string
state_dim: int64
dataset_codebase_version: string
action_padding_mask_source: string
statistics_source: string
dataset_revision: string
delta_action_dims: list<item: null>
child 0, item: null
model_action_dim: int64
implementation: string
frame_count: int64
meta_info_sha256: string
training_split_name: string
parquet_inventory: list<item: struct<path: string, sha256: string, size: int64>>
child 0, item: struct<path: string, sha256: string, size: int64>
child 0, path: string
child 1, sha256: string
child 2, size: int64
quantile_method: string
to
{'action_dim': Value('int64'), 'action_horizon': Value('int64'), 'action_padding_mask_source': Value('string'), 'action_representation': Value('string'), 'action_vector_count': Value('int64'), 'allow_synthetic_fixture': Value('bool'), 'copied_from_meta_stats': Value('bool'), 'dataset_codebase_version': Value('string'), 'dataset_revision': Value('string'), 'dataset_root': Value('string'), 'delta_action_dims': List(Value('null')), 'episode_count': Value('int64'), 'episode_end_padding': Value('string'), 'episode_lengths': List(Value('int64')), 'frame_count': Value('int64'), 'implementation': Value('string'), 'implementation_sha256': Value('string'), 'masked_action_padding_vector_count': Value('int64'), 'meta_info_sha256': Value('string'), 'model_action_dim': Value('int64'), 'norm_stats_sha256': Value('string'), 'parquet_inventory': List({'path': Value('string'), 'sha256': Value('string'), 'size': Value('int64')}), 'parquet_inventory_sha256': Value('string'), 'population_std_ddof': Value('int64'), 'quantile_method': Value('string'), 'state_dim': Value('int64'), 'statistics_dtype': Value('string'), 'statistics_source': Value('string'), 'status': Value('string'), 'training_episode_indices': List(Value('int64')), 'training_split': Value('string'), 'training_split_name': Value('string')}
because column names don't match
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1369, in compute_config_parquet_and_info_response
parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
~~~~~~~~~~~~~~~~~~~~~~~~~^
builder, max_dataset_size_bytes=max_dataset_size_bytes
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
)
^
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 948, in stream_convert_to_parquet
builder._prepare_split(split_generator=splits_generators[split], file_format="parquet")
~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1683, in _prepare_split
for job_id, done, content in self._prepare_split_single(
~~~~~~~~~~~~~~~~~~~~~~~~~~^
gen_kwargs=gen_kwargs, job_id=job_id, **_prepare_split_args
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
):
^
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1869, in _prepare_split_single
raise DatasetGenerationError("An error occurred while generating the dataset") from e
datasets.exceptions.DatasetGenerationError: An error occurred while generating the datasetNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
action_dim int64 | action_horizon int64 | action_padding_mask_source string | action_representation string | action_vector_count int64 | allow_synthetic_fixture bool | copied_from_meta_stats bool | dataset_codebase_version string | dataset_revision string | dataset_root string | delta_action_dims list | episode_count int64 | episode_end_padding string | episode_lengths list | frame_count int64 | implementation string | implementation_sha256 string | masked_action_padding_vector_count int64 | meta_info_sha256 string | model_action_dim int64 | norm_stats_sha256 string | parquet_inventory list | parquet_inventory_sha256 string | population_std_ddof int64 | quantile_method string | state_dim int64 | statistics_dtype string | statistics_source string | status string | training_episode_indices list | training_split string | training_split_name string |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
12 | 50 | LeRobot action_is_pad | absolute | 3,154,425 | false | false | v2.1 | 76fd84d2f254f7acc95d5a5b4caafc00a03207a1 | /home/coder/share/datasets/Shiki42/sortletters_parallel_121_v21_openpi | [] | 121 | repeat_last_action_excluded_by_action_is_pad | [
664,
674,
579,
601,
705,
689,
600,
585,
615,
868,
545,
595,
569,
786,
570,
734,
549,
752,
505,
533,
542,
646,
681,
565,
669,
756,
626,
549,
540,
532,
503,
566,
793,
508,
485,
477,
488,
559,
492,
518,
544,
484,
557,
499,
617,
5... | 66,053 | parallel_vla.pi05_training_stats.v1 | f30f0260c9580de988bf6948d1f4ed10f21bbfd083bbe849ce6590c3109457f8 | 148,225 | 70a71b39a2ec529c48f9c86650e7f74b720db0de49293c2d256436030487263a | 32 | 83d9444a9a0f65e63240d35c540ec0c19080fda7fde96fc53eb610bca858e764 | [
{
"path": "data/chunk-000/episode_000000.parquet",
"sha256": "ea88a1090ab9faf3f58c73a0263c85815c6bb2fe0d08516eea319eb9fc23937d",
"size": 53906
},
{
"path": "data/chunk-000/episode_000001.parquet",
"sha256": "662059030460ddcb3feb5e96f508f723e3e0f3ce687dcb63121598b6de6cce1e",
"size": 48362... | 0fcf98694c071f17db27b4326c378ebc181bb4c40716d1484b0ddbc1010e4407 | 0 | numpy_linear | 12 | float64 | v2.1_training_split_valid_action_targets | passed | [
0,
1,
2,
3,
4,
5,
6,
7,
8,
9,
10,
11,
12,
13,
14,
15,
16,
17,
18,
19,
20,
21,
22,
23,
24,
25,
26,
27,
28,
29,
30,
31,
32,
33,
34,
35,
36,
37,
38,
39,
40,
41,
42,
43,
44,
45,
46,
47,
48,
49,
50,
51,
52,
53,
54... | 0:121 | train |
parallelVLA sortletters engineering preflight bundle
STOP — the bundled dataset is rejected for behavior training. This public bundle exists only to reproduce loader, action-mask, checkpoint save/reload, and training-throughput engineering checks. It must not be used to claim a valid real-robot policy, sortletters behavior quality, or real-robot success rate.
警告：配套数据已被行为训练资格门拒绝。 本 bundle 只能复现 loader、动作 mask、 checkpoint 保存/恢复和训练吞吐工程验证；不得据此声称有效真机策略或真机成功率。
Qualification
The structured audit status is rejected_for_behavior_training:
- 65,532 / 66,053 frames (99.211%) use a right-front observation from a different source timestamp than the reference arm timeline.
- 65,533 frames compose left/right arm sources from different timestamps.
- 121 / 121 episodes are affected.
- Median source-time delta is 531 frames (17.7 seconds at 30 FPS); maximum is 868 frames.
Audit SHA-256:
2a60f082001f977b141fd718634e9c4932201c7bd92414411e390c1494a1d9d3.
Fixed provenance
- parallelVLA merge commit:
24b6274d21ce3011296bbdfb6b829f5fa750d8a4 - OpenPI/RoboTwin commit:
3a438a4f3c9f3245bbc9e1cec601dce6ccf8aa8b - source dataset revision:
76fd84d2f254f7acc95d5a5b4caafc00a03207a1 - public dataset repo:
Shiki42/sortletters_parallel_121_v21_openpi - immutable payload commit:
78783c2e34087cb8d099f022f75c877aa7afc363 - warning-card commit:
4768da956d5aa3a25e0c6d290c3d74b37ef80eb7
artifacts/ contains the portable CPython 3.11 runtime, CUDA 12.8 PyTorch overlay,
non-conflicting support site-packages, and the two fixed source archives. wheelhouse/
is retained for reproducibility and can be omitted by a host using the validated overlay.
normalizer/ and receipts/ contain exact global-quantile statistics and validation evidence.
The PI0.5 base checkpoint is intentionally not republished. Required SHA-256:
0eb11ca9587678c1d2ef8cf32807c29f8ce53a2bfdfc1aa4a4c96f16fca59b0f.
Allowed use
- loader and schema validation
action_is_padand 12D-to-32D loss-mask validation- one-step checkpoint save and cross-process reload validation
- runtime and throughput engineering
Prohibited claims
- valid real-robot policy training
- sortletters behavior quality
- real-robot success rate
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