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The dataset generation failed
Error code: DatasetGenerationError
Exception: TypeError
Message: Couldn't cast array of type
struct<action_mode: string, max_steps: int64>
to
{'action_mode': Value('string')}
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1827, 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 2378, in table_cast
return cast_table_to_schema(table, schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2312, in cast_table_to_schema
cast_array_to_feature(
~~~~~~~~~~~~~~~~~~~~~^
table[name] if name in table_column_names else pa.array([None] * len(table), type=schema.field(name).type),
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
feature,
^^^^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 1861, in wrapper
return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks])
~~~~^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2158, in cast_array_to_feature
raise TypeError(f"Couldn't cast array of type\n{_short_str(array.type)}\nto\n{_short_str(feature)}")
TypeError: Couldn't cast array of type
struct<action_mode: string, max_steps: int64>
to
{'action_mode': Value('string')}
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 1694, 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 1880, 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.
pool_id string | layout_key string | env_id string | env_kwargs dict | seed int64 | episode_seed int64 | dim_room list | num_boxes int64 | max_steps int64 | room_fixed list | player_position list | box_positions list | solution_len int64 | num_gen_steps int64 | init_state dict | source dict |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
hard_train_000000 | 056b1eb0b153e5fb5d213cda1370ac39f9e7518a5974e0bec4638344555577b8 | sokoban/hard | {
"action_mode": "move_only"
} | 120,260,416 | 120,260,416 | [
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... | {
"dataset": "sokoban_hard_v8_ordered_plain_matched_cot100k_20260604_ordered",
"split": "train",
"shard": "batch_000000.jsonl.gz",
"row": 0
} |
hard_train_000001 | bcc9c76940eebd0d9509801373ab96bfba0f4797f17ae204198d612e59b31628 | sokoban/hard | {
"action_mode": "move_only"
} | 120,260,417 | 120,260,417 | [
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... | {
"dataset": "sokoban_hard_v8_ordered_plain_matched_cot100k_20260604_ordered",
"split": "train",
"shard": "batch_000000.jsonl.gz",
"row": 1
} |
hard_train_000002 | 8e42d1b3833789fcb6966f4f946744d65aec3194ee4d231fe74e5b4946062d4f | sokoban/hard | {
"action_mode": "move_only"
} | 120,260,418 | 120,260,418 | [
10,
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] | 4 | 120 | [
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... | {
"dataset": "sokoban_hard_v8_ordered_plain_matched_cot100k_20260604_ordered",
"split": "train",
"shard": "batch_000000.jsonl.gz",
"row": 2
} |
hard_train_000003 | 4e54ccb9ef764d6a4b35d6197121d7a02c4043148ec11ecbcbfc19cbbd2a517b | sokoban/hard | {
"action_mode": "move_only"
} | 120,260,419 | 120,260,419 | [
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... | {
"dataset": "sokoban_hard_v8_ordered_plain_matched_cot100k_20260604_ordered",
"split": "train",
"shard": "batch_000000.jsonl.gz",
"row": 3
} |
hard_train_000004 | 6234cee61293cb0fe3f02a669cd42e6ff5ec6adac3a78087be69b721f38a1044 | sokoban/hard | {
"action_mode": "move_only"
} | 120,260,420 | 120,260,420 | [
10,
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] | 4 | 120 | [
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[
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],
[
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] | 19 | 34 | {
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... | {
"dataset": "sokoban_hard_v8_ordered_plain_matched_cot100k_20260604_ordered",
"split": "train",
"shard": "batch_000000.jsonl.gz",
"row": 4
} |
hard_train_000005 | 35f375827c376f93a27f1969c140ee49b58ca32326367cea8c6c0927223ce6ca | sokoban/hard | {
"action_mode": "move_only"
} | 120,260,421 | 120,260,421 | [
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] | 4 | 120 | [
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... | {
"dataset": "sokoban_hard_v8_ordered_plain_matched_cot100k_20260604_ordered",
"split": "train",
"shard": "batch_000000.jsonl.gz",
"row": 5
} |
hard_train_000006 | f3f85c226f35f87fd0d8e8465bae3f02a729433aaca9624a5ddd7223e759694b | sokoban/hard | {
"action_mode": "move_only"
} | 120,260,422 | 120,260,422 | [
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] | 4 | 120 | [
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... | {
"dataset": "sokoban_hard_v8_ordered_plain_matched_cot100k_20260604_ordered",
"split": "train",
"shard": "batch_000000.jsonl.gz",
"row": 6
} |
hard_train_000007 | 2c666552a5713f29c9dc5e49f1bcce37c7c37e1384e315e99f35269cac6f600d | sokoban/hard | {
"action_mode": "move_only"
} | 120,260,423 | 120,260,423 | [
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... | {
"dataset": "sokoban_hard_v8_ordered_plain_matched_cot100k_20260604_ordered",
"split": "train",
"shard": "batch_000000.jsonl.gz",
"row": 7
} |
hard_train_000008 | 6f6f62b7f3af15030e09df22c4a9eea9028362de2ebf9d4d0263639995074eb4 | sokoban/hard | {
"action_mode": "move_only"
} | 120,260,424 | 120,260,424 | [
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[
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... | {
"dataset": "sokoban_hard_v8_ordered_plain_matched_cot100k_20260604_ordered",
"split": "train",
"shard": "batch_000000.jsonl.gz",
"row": 8
} |
hard_train_000009 | 6087c11e0567bf428b7a97768c22dc1e12f88a4beab567c0aa273d9d25aaca69 | sokoban/hard | {
"action_mode": "move_only"
} | 120,260,425 | 120,260,425 | [
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[
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... | {
"dataset": "sokoban_hard_v8_ordered_plain_matched_cot100k_20260604_ordered",
"split": "train",
"shard": "batch_000000.jsonl.gz",
"row": 9
} |
hard_train_000010 | c5d451bf5b0e3b54315761cec0a047d217eeb06c12f703d2ee7baeec4b72a7ba | sokoban/hard | {
"action_mode": "move_only"
} | 120,260,426 | 120,260,426 | [
10,
10
] | 4 | 120 | [
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[
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[
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[
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[
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] | 19 | 34 | {
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... | {
"dataset": "sokoban_hard_v8_ordered_plain_matched_cot100k_20260604_ordered",
"split": "train",
"shard": "batch_000000.jsonl.gz",
"row": 10
} |
hard_train_000011 | 16d338750ef41f344a8e165e14b7a14cbb7e3ddf840d2e5680cd1a3ae76106ad | sokoban/hard | {
"action_mode": "move_only"
} | 120,260,427 | 120,260,427 | [
10,
10
] | 4 | 120 | [
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[
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[
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[
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[
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] | 19 | 34 | {
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... | {
"dataset": "sokoban_hard_v8_ordered_plain_matched_cot100k_20260604_ordered",
"split": "train",
"shard": "batch_000000.jsonl.gz",
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hard_train_000012 | 4aabd1c477df76cbfd081dfdd63a3419e60bfda07fa7d2364fb74b249e8ecdad | sokoban/hard | {
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hard_train_000014 | 0c6c8e9a26f8652cf66b8a7225f599f23e824db3e8b69c75b2694c756174edca | sokoban/hard | {
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hard_train_000015 | 47f599d497929b8895f903416a48a3e6216ca6bfd2a7bbefbfa627974f620657 | sokoban/hard | {
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hard_train_000016 | 7a073538a98698a2008812939cd8cd93ae2de1961f31ba15dafd9f6179743b52 | sokoban/hard | {
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hard_train_000017 | c64c9929828c3c9cfdae3d7b244af09978ef3cfcd4e27dc6339f895dba80f67e | sokoban/hard | {
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hard_train_000018 | d3c2df2208dbdd8537da9b276396f352538e26a0c3c636c804fca9d7ae6f750e | sokoban/hard | {
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hard_train_000019 | c30a92d7f3cf00079603f299e15ccf76085c5034cd0f49c6fad262e8bc73464a | sokoban/hard | {
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hard_train_000020 | f0c3a096a84813d218fa258b90baf3be339b1d2cd70a3a5739bd763a672e647a | sokoban/hard | {
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hard_train_000021 | fe635552215e85a5d9053a506be11d6f2771e4b62e514a9003321f81eef6bdee | sokoban/hard | {
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hard_train_000022 | 7565b56a3d15b34a23216e0b614b578dcbf9bb92987de8662278a8edf3d733aa | sokoban/hard | {
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hard_train_000023 | ced95ce8832b3fa34306fe55b6b0719e3c9e9bb072ab6326920c947631b96113 | sokoban/hard | {
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hard_train_000024 | 06b0ac077dff38e78c053165ac6e7e9ad6e6ef919ae64808096edb2f2dbb0114 | sokoban/hard | {
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hard_train_000025 | b0aed839d80ef706af300d98ad3e22be0af206bdb440b770c9c66b057086b527 | sokoban/hard | {
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hard_train_000026 | a223159e8ea0139932f9b986ebd21ae7ff2c49670f320c4645e1029ccd686742 | sokoban/hard | {
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hard_train_000035 | 4157fe4d7df33e6d919f1b2982eaaa47d52ed0c18b339b7f87c3601222545a94 | sokoban/hard | {
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hard_train_000061 | a194b7f7c1a3ece84dab38f7f2b95d4548e7c93f55215c47aafcdefc43401346 | sokoban/hard | {
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hard_train_000072 | bc46213d318e8ad2342b29603138cdbb71ba9bed071f90dc6ba516e052d15698 | sokoban/hard | {
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hard_train_000073 | 00ca00376e72fe354549c84183ccfc5c93034347bebe3cf940f1716a24aa4fd8 | sokoban/hard | {
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hard_train_000074 | 5d0d0de2828a59f09d9cac8605fe4c8c3ce7d2ce919b5ec59cdeda9bb7bd9980 | sokoban/hard | {
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hard_train_000075 | b88f20f6d38fcee397258d76a39d3b20519af0989417902bb745fcf6eb6d0ea7 | sokoban/hard | {
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hard_train_000076 | cd73f723608bc6bdb602524bcbfc3ec87e901a9edaf25068fc8bc5d4d0a7909b | sokoban/hard | {
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hard_train_000077 | fa2db50dd930ca958ac8557ae21b1c9ed81c8aebde7b6df9c290c9777ca92249 | sokoban/hard | {
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hard_train_000078 | 37a7a7aad15defae660d994bdbb745397459fb15901354ed8a29428434b25186 | sokoban/hard | {
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hard_train_000079 | 452abe02e2e94dda427e8d123cd35bcc6a060fd7ded41fd9580ed958bddec660 | sokoban/hard | {
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hard_train_000080 | 4479c5be0853c2a12a1979d33e20cf8d3af2746a9adeb202a812749a66870d54 | sokoban/hard | {
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hard_train_000081 | 10bd4bb799bbc619d36be6800997ea7ec01658ef20264d0ce5cc15cf55d48bc1 | sokoban/hard | {
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hard_train_000082 | 5c595cfa361ae3e451168184fe35e0b45a5faa946797af3311ece16e4de59d36 | sokoban/hard | {
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hard_train_000083 | 964a41a36a3b6d95df248ea6cb8bcb2cfcb78ecddc9ad1bcfe6215878055d239 | sokoban/hard | {
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hard_train_000086 | 365bffb8f0864e158b62c422bc9146aa4943a1cad909dbe1e8cbba82d4ea030b | sokoban/hard | {
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hard_train_000088 | f7253bed6d44774df647a210a28700284d638b8d38854ba66a79b0575d8da886 | sokoban/hard | {
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hard_train_000089 | e8c5c35a08f5f6095ee59bb8d00784e35b93bb9f657a1a95dc7b6a1ad4a825ea | sokoban/hard | {
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hard_train_000090 | f9f0f839c146d66e4b089c273cc39dd66f72603d11455f72411d289d8dd6bca2 | sokoban/hard | {
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hard_train_000091 | 546c4c08aa78b8ad93da93bad6c00529e8d17dafc17331bede06b473a0ef129b | sokoban/hard | {
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hard_train_000092 | 324674ad238b7ebfd7ef8cdba24a990d79c59b3de85aded1f83facd71dffb709 | sokoban/hard | {
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hard_train_000093 | 9c973cab1bccc3861a76f36eb0acb1872c3d518691d1b72a69d4ad96d9d9d8a4 | sokoban/hard | {
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hard_train_000094 | 710f432ecb49f34c639edb0f68491da1c5267f5681f136e7a784c80b064a2cb7 | sokoban/hard | {
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hard_train_000095 | d80f31b171d12c27bdfaf60b36be4d3c33cbae27bf84d8e81f2e9924d7d724d1 | sokoban/hard | {
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hard_train_000098 | 8b1550f6f51d5fdefdd7a1efe6605bb883a81761278f455092a02a2aeb99493d | sokoban/hard | {
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hard_train_000099 | 866fcf2c25b0ab72a48b6b3a795071c575c63a236cc4f9e1c8991f5a45dc139c | sokoban/hard | {
"action_mode": "move_only"
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End of preview.
sokoban_hard_init_state_pool
BAGEL VLM-Gym world-model dataset (sokoban / eval).
- Held-out hard init-state pool (train-disjoint) for world-model evaluation.
- layout: Init-state pool.
train.jsonl.gz/test.jsonl.gzat the repo root; one init state per row. - images are base64-encoded JPEG frames stored inline in each JSONL row.
Pairs with the matching sokoban checkpoint(s) under the companion model org; CoT and non-CoT
variants share the same underlying rollouts.
- Downloads last month
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