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Error code: DatasetGenerationError
Exception: CastError
Message: Couldn't cast
episode_index: int64
tasks: list<item: string>
child 0, item: string
length: int64
task_index: int64
frame_index: int64
action: list<item: double>
child 0, item: double
index: int64
observation.state: list<item: double>
child 0, item: double
timestamp: double
to
{'observation.state': List(Value('float64')), 'action': List(Value('float64')), 'timestamp': Value('float64'), 'frame_index': Value('int64'), 'episode_index': Value('int64'), 'index': Value('int64'), 'task_index': Value('int64')}
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
episode_index: int64
tasks: list<item: string>
child 0, item: string
length: int64
task_index: int64
frame_index: int64
action: list<item: double>
child 0, item: double
index: int64
observation.state: list<item: double>
child 0, item: double
timestamp: double
to
{'observation.state': List(Value('float64')), 'action': List(Value('float64')), 'timestamp': Value('float64'), 'frame_index': Value('int64'), 'episode_index': Value('int64'), 'index': Value('int64'), 'task_index': Value('int64')}
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.
observation.state list | action list | timestamp float64 | frame_index int64 | episode_index int64 | index int64 | task_index int64 |
|---|---|---|---|---|---|---|
[
0.24847296934126012,
0.1452941169385835,
0.1728078415071549,
0.09503819089569471,
-0.3470526039235333,
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0.2670526039235333
] | [
0.039958188190726954,
0.027038511624397982,
0.013429926371122222
] | 0 | 0 | 0 | 0 | 0 |
[
0.24999621653723877,
0.148504216429528,
0.174805559731999,
0.09267361264201684,
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0.26589935921345503
] | [
0.03967625799745975,
0.026909445454696094,
0.013380008210520832
] | 0.016667 | 1 | 0 | 1 | 0 |
[
0.2541968399029178,
0.15452028445244312,
0.1784531905931686,
0.0874617955978414,
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0.2633760673597409
] | [
0.039056620332170194,
0.02660786387859195,
0.01325751245924742
] | 0.033333 | 2 | 0 | 2 | 0 |
[
0.2621521940388072,
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0.07870565940724517,
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0.2590621647707874
] | [
0.038008490091026415,
0.026077449154382364,
0.013034759929141975
] | 0.05 | 3 | 0 | 3 | 0 |
[
0.2742662365299243,
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0.1902438517733283,
0.06631721206577412,
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0.2527070916412662
] | [
0.0365016081626369,
0.02529410897741015,
0.012699126583901987
] | 0.066667 | 4 | 0 | 4 | 0 |
[
0.2904917733218341,
0.1907775448853728,
0.19799704294543782,
0.050610846823305244,
-0.32416267632039986,
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0.24416267632039984
] | [
0.034544756434438696,
0.02425533573269347,
0.012248369478608183
] | 0.083333 | 5 | 0 | 5 | 0 |
[
0.31049161145903204,
0.20798802139244327,
0.20668504194879733,
0.03215323786207708,
-0.31336413944904284,
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0.23336413944904283
] | [
0.0321730217919081,
0.022974238174306667,
0.011687994758084443
] | 0.1 | 6 | 0 | 6 | 0 |
[
0.33375273076448786,
0.22697628966409691,
0.21607279198656318,
0.011649131531887569,
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0.2203326281319143
] | [
0.02943972297367966,
0.021475942539821196,
0.01102961234954797
] | 0.116667 | 7 | 0 | 7 | 0 |
[
0.3596657745215577,
0.24721378433195987,
0.22593262784074508,
-0.010146248904743027,
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0.20518235072600327
] | [
0.026410712868850227,
0.019794929371997224,
0.01028961542770122
] | 0.133333 | 8 | 0 | 8 | 0 |
[
0.38689324052972096,
0.26883686749374264,
0.23617018515414995,
-0.03233174404789929,
-0.26818310764312503,
-0.09766825595210066,
0.188183107643125
] | [
0.02317728088093844,
0.017990496634663507,
0.009496151078968904
] | 0.15 | 9 | 0 | 9 | 0 |
[
0.4145731120241749,
0.290613728937681,
0.2464953507212823,
-0.05391726291354432,
-0.24995938340921242,
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0.1699593834092124
] | [
0.019870956560451,
0.016133869954969064,
0.008682720303465069
] | 0.166667 | 10 | 0 | 10 | 0 |
[
0.4422811810269754,
0.3120090980044075,
0.25666996160375105,
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0.15089740856444284
] | [
-0.0017658490078226459,
0.0020287176457000513,
0.002087757148445127
] | 0.183333 | 11 | 0 | 11 | 0 |
[
0.4690167556877923,
0.33164209415597096,
0.2658148870327875,
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0.13207349043583688
] | [
-0.04,
-0.04,
-0.025978844776269067
] | 0.2 | 12 | 0 | 12 | 0 |
[
0.4933724664378139,
0.3442568629805891,
0.2696213215470402,
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0.11670438655414778
] | [
-0.04,
-0.04,
-0.04
] | 0.216667 | 13 | 0 | 13 | 0 |
[
0.5123839954007545,
0.3492893847338535,
0.26618283594619896,
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0.10701496775846736
] | [
-0.04,
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-0.04
] | 0.233333 | 14 | 0 | 14 | 0 |
[
0.52455934074895,
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0.10382655403480884
] | [
-0.04,
-0.04,
-0.04
] | 0.25 | 15 | 0 | 15 | 0 |
[
0.52951300531779,
0.3373399600563934,
0.24138602565641512,
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0.10710700878914553
] | [
-0.04,
-0.04,
-0.04
] | 0.266667 | 16 | 0 | 16 | 0 |
[
0.5274957929040393,
0.32170253440295016,
0.22177788223694545,
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0.11625521188416615
] | [
-0.04,
-0.04,
-0.04
] | 0.283333 | 17 | 0 | 17 | 0 |
[
0.5190893456998155,
0.3007741876104441,
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0.1303345017831295
] | [
-0.04,
-0.04,
-0.03295609774091422
] | 0.3 | 18 | 0 | 18 | 0 |
[
0.5049283681736695,
0.2754048404409244,
0.1731002672472521,
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0.1481034167663295
] | [
-0.0197058051937929,
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-0.004088240840702043
] | 0.316667 | 19 | 0 | 19 | 0 |
[
0.4853433528874386,
0.250064061158845,
0.1509332369944322,
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0.1669217496161905
] | [
0.01853134778768466,
0.014546365986434287,
0.007463934478187916
] | 0.333333 | 20 | 0 | 20 | 0 |
[
0.4637303136677914,
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0.13300078796239606,
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0.18421976074218088
] | [
0.021605729931588727,
0.016175353396802858,
0.00810925553239667
] | 0.35 | 21 | 0 | 21 | 0 |
[
0.4434968782691396,
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0.11905673988864639,
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0.19847903983767873
] | [
0.024262703390432093,
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] | 0.366667 | 22 | 0 | 22 | 0 |
[
0.42668803278519735,
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] | [
0.02633505240088622,
0.018709016456813263,
0.00912881453651835
] | 0.383333 | 23 | 0 | 23 | 0 |
[
0.414432601819506,
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0.2162470720332345
] | [
0.027754756997861334,
0.019480487167992565,
0.009439709738118626
] | 0.4 | 24 | 0 | 24 | 0 |
[
0.4072262249115176,
0.18565864811083882,
0.09765110954905931,
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0.21995389998424547
] | [
0.02851528077801034,
0.019903606576673328,
0.009607686596808416
] | 0.416667 | 25 | 0 | 25 | 0 |
[
0.4051275898365388,
0.1868872297983467,
0.09602181552500809,
0.00045322461818519955,
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0.22056248697990705
] | [
0.02864654351269104,
0.019992149326894536,
0.0096371765573491
] | 0.433333 | 26 | 0 | 26 | 0 |
[
0.40789827158517394,
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0.09650414735294435,
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0.21834904489346735
] | [
0.028199348296305524,
0.019770300627558145,
0.009537168921605143
] | 0.45 | 27 | 0 | 27 | 0 |
[
0.4151044056452621,
0.20034607925560774,
0.09874215111274139,
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0.21356427394759875
] | [
0.027236252556386654,
0.019268123974859202,
0.009319280535266247
] | 0.466667 | 28 | 0 | 28 | 0 |
[
0.42619111947458643,
0.21141193290937468,
0.10240603716224891,
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0.20644092553531362
] | [
0.025826414634234778,
0.01851941039862891,
0.008996935014880168
] | 0.483333 | 29 | 0 | 29 | 0 |
[
0.4405367079068507,
0.22459678453847393,
0.10719422877949718,
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0.19721142755255489
] | [
0.024042624775784012,
0.01756067768501435,
0.008585037922295358
] | 0.5 | 30 | 0 | 30 | 0 |
[
0.4574917817397108,
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0.18612513618821608
] | [
0.02195934543327211,
0.016430518971469465,
0.008099752794079552
] | 0.516667 | 31 | 0 | 31 | 0 |
[
0.47640761045210916,
0.25518088052388166,
0.11908288146614218,
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0.1734597641302436
] | [
0.01965107105638535,
0.015168863213462917,
0.007558172124062828
] | 0.533333 | 32 | 0 | 32 | 0 |
[
0.49665687104768125,
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0.12572565630222834,
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0.15952496031797186
] | [
0.013858683899370654,
0.011625801454979165,
0.0059617264723756305
] | 0.55 | 33 | 0 | 33 | 0 |
[
0.5175588762354553,
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0.13244648944616674,
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0.14477352380356118
] | [
-0.03427225785050299,
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] | 0.566667 | 34 | 0 | 34 | 0 |
[
0.5371890174689999,
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0.13130797872211403
] | [
-0.04,
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] | 0.583333 | 35 | 0 | 35 | 0 |
[
0.553639993578324,
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0.12199623626730144
] | [
-0.04,
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] | 0.6 | 36 | 0 | 36 | 0 |
[
0.5647419963966548,
0.30733378807730655,
0.128799425890351,
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0.11826324621748324
] | [
-0.04,
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] | 0.616667 | 37 | 0 | 37 | 0 |
[
0.5695106157081651,
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] | [
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] | 0.633333 | 38 | 0 | 38 | 0 |
[
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] | [
-0.04,
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] | 0.65 | 39 | 0 | 39 | 0 |
[
0.5598924250103827,
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] | [
-0.04,
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] | 0.666667 | 40 | 0 | 40 | 0 |
[
0.5458385438383833,
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0.1566473799433104
] | [
0.002742599317841218,
0.0038666938742834616,
0.002019500402288221
] | 0.683333 | 41 | 0 | 41 | 0 |
[
0.5272529459629729,
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0.03705827524757141,
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0.17302135545493108
] | [
0.019139465221225446,
0.014147427351961436,
0.006601861279536123
] | 0.7 | 42 | 0 | 42 | 0 |
[
0.5078366169193447,
0.20264624078969812,
0.022668099656452424,
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-0.07962256072642276,
0.18771047751583853
] | [
0.021818559880391414,
0.015545772296926923,
0.007142776387640729
] | 0.716667 | 43 | 0 | 43 | 0 |
[
0.4903611688044547,
0.18774453618071768,
0.011571974467898302,
-0.03498768617326009,
-0.27955127791988865,
-0.09501231382673986,
0.19955127791988864
] | [
0.02406617810456007,
0.01672878923167731,
0.007604553083593677
] | 0.733333 | 44 | 0 | 44 | 0 |
[
0.4764647195695034,
0.177410089799108,
0.0035069562819411496,
-0.023053517713959748,
-0.288149983947112,
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0.20814998394711198
] | [
0.0257535823821888,
0.017623904605116227,
0.007954327395996792
] | 0.75 | 45 | 0 | 45 | 0 |
[
0.4670095489855103,
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0.2135160575259764
] | [
0.026833543502714326,
0.018203709790542557,
0.00817919187360812
] | 0.766667 | 46 | 0 | 46 | 0 |
[
0.4623214509176003,
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0.21583477019284675
] | [
0.027309200761278886,
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physicalai-bmi/forge-arm-reach
An open robot-trajectory dataset generated fully in the browser, on-device with Institute for Physical AI · Forge (in-browser MuJoCo, on-device).
- Robot:
forge_arm - Task: Reach the target with the end effector
- Episodes: 11 · Frames: 3777 · Control rate: 60 Hz
- observation.state: 7 dims · action: 3 dims
Format
LeRobot v2.1-compatible. meta/ holds info.json, episodes.jsonl, tasks.jsonl, and stats.json.
Per-episode frames are provided both ways under data/chunk-000/:
episode_*.parquet— canonical LeRobot parquet (whatinfo.json'sdata_pathpoints at). Ready to load.episode_*.jsonl— the exact source produced client-side by the in-browser exporter, kept for provenance.
to_parquet.py is the (already-applied) converter, included so anyone can reproduce the parquet from the JSONL.
Load
from lerobot.common.datasets.lerobot_dataset import LeRobotDataset
ds = LeRobotDataset("physicalai-bmi/forge-arm-reach")
print(ds[0]["observation.state"], ds[0]["action"])
How it was made
Recorded in a real browser against the live Forge: the "Reach Trials" arm preset, auto-expert demonstrations, exported on-device. No hardware, no cloud, no install. Reproduce it yourself in about a minute.
See DATASHEET.md for provenance, composition, and intended uses. Licensed CC-BY-4.0.
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