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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
ic_ph50: struct<lift: struct<sim_gt_sr_Ta=1: struct<model_epoch10_successrate0.1000_n50_tmax500_tmin53_tavg45 (... 4394 chars omitted)
child 0, lift: struct<sim_gt_sr_Ta=1: struct<model_epoch10_successrate0.1000_n50_tmax500_tmin53_tavg455.96: double, (... 1369 chars omitted)
child 0, sim_gt_sr_Ta=1: struct<model_epoch10_successrate0.1000_n50_tmax500_tmin53_tavg455.96: double, model_epoch12_successr (... 613 chars omitted)
child 0, model_epoch10_successrate0.1000_n50_tmax500_tmin53_tavg455.96: double
child 1, model_epoch12_successrate0.3600_n50_tmax500_tmin43_tavg339.46: double
child 2, model_epoch15_successrate0.2800_n50_tmax500_tmin39_tavg373.32: double
child 3, model_epoch15_successrate0.4800_n50_tmax500_tmin43_tavg284.72: double
child 4, model_epoch18_successrate0.6200_n50_tmax500_tmin38_tavg221.10: double
child 5, model_epoch23_successrate0.7600_n50_tmax500_tmin39_tavg157.34: double
child 6, model_epoch30_successrate0.9000_n50_tmax500_tmin37_tavg92.50: double
child 7, model_epoch500_successrate1.0000_n50_tmax500_tmin33_tavg44.12: double
child 8, model_epoch6_successrate0.0000_n50_tmax500_tminNA_tavg500.00: double
child 9, model_epoch8_successrate0.1800_n50_tmax500_tmin59_tavg426.14: double
child 1, sim_gt_sr_Ta=12: struct<model_epoch10_successrate0.1000_n50_tmax500_tmin53_tavg455.96: double, model_epoch12_successr (... 613 chars omitted)
child 0, mod
...
double>, can (... 451 chars omitted)
child 0, lift_mh: struct<pearson: double, rho: double, tau: double, mmrv: double, regret: double>
child 0, pearson: double
child 1, rho: double
child 2, tau: double
child 3, mmrv: double
child 4, regret: double
child 1, can_mh: struct<pearson: double, rho: double, tau: double, mmrv: double, regret: double>
child 0, pearson: double
child 1, rho: double
child 2, tau: double
child 3, mmrv: double
child 4, regret: double
child 2, square_mh: struct<pearson: double, rho: double, tau: double, mmrv: double, regret: double>
child 0, pearson: double
child 1, rho: double
child 2, tau: double
child 3, mmrv: double
child 4, regret: double
child 3, lift_mhf: struct<pearson: double, rho: double, tau: double, mmrv: double, regret: double>
child 0, pearson: double
child 1, rho: double
child 2, tau: double
child 3, mmrv: double
child 4, regret: double
child 4, can_mhf: struct<pearson: double, rho: double, tau: double, mmrv: double, regret: double>
child 0, pearson: double
child 1, rho: double
child 2, tau: double
child 3, mmrv: double
child 4, regret: double
child 5, square_mhf: struct<pearson: double, rho: double, tau: double, mmrv: double, regret: double>
child 0, pearson: double
child 1, rho: double
child 2, tau: double
child 3, mmrv: double
child 4, regret: double
to
{'multitask': {'lift_mh': {'pearson': Value('float64'), 'rho': Value('float64'), 'tau': Value('float64'), 'mmrv': Value('float64'), 'regret': Value('float64')}, 'can_mh': {'pearson': Value('float64'), 'rho': Value('float64'), 'tau': Value('float64'), 'mmrv': Value('float64'), 'regret': Value('float64')}, 'square_mh': {'pearson': Value('float64'), 'rho': Value('float64'), 'tau': Value('float64'), 'mmrv': Value('float64'), 'regret': Value('float64')}, 'lift_mhf': {'pearson': Value('float64'), 'rho': Value('float64'), 'tau': Value('float64'), 'mmrv': Value('float64'), 'regret': Value('float64')}, 'can_mhf': {'pearson': Value('float64'), 'rho': Value('float64'), 'tau': Value('float64'), 'mmrv': Value('float64'), 'regret': Value('float64')}, 'square_mhf': {'pearson': Value('float64'), 'rho': Value('float64'), 'tau': Value('float64'), 'mmrv': Value('float64'), 'regret': Value('float64')}}, 'individual': {'lift_mh': {'pearson': Value('float64'), 'rho': Value('float64'), 'tau': Value('float64'), 'mmrv': Value('float64'), 'regret': Value('float64')}, 'can_mh': {'pearson': Value('float64'), 'rho': Value('float64'), 'tau': Value('float64'), 'mmrv': Value('float64'), 'regret': Value('float64')}, 'square_mh': {'pearson': Value('float64'), 'rho': Value('float64'), 'tau': Value('float64'), 'mmrv': Value('float64'), 'regret': Value('float64')}, 'lift_mhf': {'pearson': Value('float64'), 'rho': Value('float64'), 'tau': Value('float64'), 'mmrv': Value('float64'), 'regret': Value('float64')}, 'can_mhf': {'pearson': Value('float64'), 'rho': Value('float64'), 'tau': Value('float64'), 'mmrv': Value('float64'), 'regret': Value('float64')}, 'square_mhf': {'pearson': Value('float64'), 'rho': Value('float64'), 'tau': Value('float64'), 'mmrv': Value('float64'), 'regret': Value('float64')}}}
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
ic_ph50: struct<lift: struct<sim_gt_sr_Ta=1: struct<model_epoch10_successrate0.1000_n50_tmax500_tmin53_tavg45 (... 4394 chars omitted)
child 0, lift: struct<sim_gt_sr_Ta=1: struct<model_epoch10_successrate0.1000_n50_tmax500_tmin53_tavg455.96: double, (... 1369 chars omitted)
child 0, sim_gt_sr_Ta=1: struct<model_epoch10_successrate0.1000_n50_tmax500_tmin53_tavg455.96: double, model_epoch12_successr (... 613 chars omitted)
child 0, model_epoch10_successrate0.1000_n50_tmax500_tmin53_tavg455.96: double
child 1, model_epoch12_successrate0.3600_n50_tmax500_tmin43_tavg339.46: double
child 2, model_epoch15_successrate0.2800_n50_tmax500_tmin39_tavg373.32: double
child 3, model_epoch15_successrate0.4800_n50_tmax500_tmin43_tavg284.72: double
child 4, model_epoch18_successrate0.6200_n50_tmax500_tmin38_tavg221.10: double
child 5, model_epoch23_successrate0.7600_n50_tmax500_tmin39_tavg157.34: double
child 6, model_epoch30_successrate0.9000_n50_tmax500_tmin37_tavg92.50: double
child 7, model_epoch500_successrate1.0000_n50_tmax500_tmin33_tavg44.12: double
child 8, model_epoch6_successrate0.0000_n50_tmax500_tminNA_tavg500.00: double
child 9, model_epoch8_successrate0.1800_n50_tmax500_tmin59_tavg426.14: double
child 1, sim_gt_sr_Ta=12: struct<model_epoch10_successrate0.1000_n50_tmax500_tmin53_tavg455.96: double, model_epoch12_successr (... 613 chars omitted)
child 0, mod
...
double>, can (... 451 chars omitted)
child 0, lift_mh: struct<pearson: double, rho: double, tau: double, mmrv: double, regret: double>
child 0, pearson: double
child 1, rho: double
child 2, tau: double
child 3, mmrv: double
child 4, regret: double
child 1, can_mh: struct<pearson: double, rho: double, tau: double, mmrv: double, regret: double>
child 0, pearson: double
child 1, rho: double
child 2, tau: double
child 3, mmrv: double
child 4, regret: double
child 2, square_mh: struct<pearson: double, rho: double, tau: double, mmrv: double, regret: double>
child 0, pearson: double
child 1, rho: double
child 2, tau: double
child 3, mmrv: double
child 4, regret: double
child 3, lift_mhf: struct<pearson: double, rho: double, tau: double, mmrv: double, regret: double>
child 0, pearson: double
child 1, rho: double
child 2, tau: double
child 3, mmrv: double
child 4, regret: double
child 4, can_mhf: struct<pearson: double, rho: double, tau: double, mmrv: double, regret: double>
child 0, pearson: double
child 1, rho: double
child 2, tau: double
child 3, mmrv: double
child 4, regret: double
child 5, square_mhf: struct<pearson: double, rho: double, tau: double, mmrv: double, regret: double>
child 0, pearson: double
child 1, rho: double
child 2, tau: double
child 3, mmrv: double
child 4, regret: double
to
{'multitask': {'lift_mh': {'pearson': Value('float64'), 'rho': Value('float64'), 'tau': Value('float64'), 'mmrv': Value('float64'), 'regret': Value('float64')}, 'can_mh': {'pearson': Value('float64'), 'rho': Value('float64'), 'tau': Value('float64'), 'mmrv': Value('float64'), 'regret': Value('float64')}, 'square_mh': {'pearson': Value('float64'), 'rho': Value('float64'), 'tau': Value('float64'), 'mmrv': Value('float64'), 'regret': Value('float64')}, 'lift_mhf': {'pearson': Value('float64'), 'rho': Value('float64'), 'tau': Value('float64'), 'mmrv': Value('float64'), 'regret': Value('float64')}, 'can_mhf': {'pearson': Value('float64'), 'rho': Value('float64'), 'tau': Value('float64'), 'mmrv': Value('float64'), 'regret': Value('float64')}, 'square_mhf': {'pearson': Value('float64'), 'rho': Value('float64'), 'tau': Value('float64'), 'mmrv': Value('float64'), 'regret': Value('float64')}}, 'individual': {'lift_mh': {'pearson': Value('float64'), 'rho': Value('float64'), 'tau': Value('float64'), 'mmrv': Value('float64'), 'regret': Value('float64')}, 'can_mh': {'pearson': Value('float64'), 'rho': Value('float64'), 'tau': Value('float64'), 'mmrv': Value('float64'), 'regret': Value('float64')}, 'square_mh': {'pearson': Value('float64'), 'rho': Value('float64'), 'tau': Value('float64'), 'mmrv': Value('float64'), 'regret': Value('float64')}, 'lift_mhf': {'pearson': Value('float64'), 'rho': Value('float64'), 'tau': Value('float64'), 'mmrv': Value('float64'), 'regret': Value('float64')}, 'can_mhf': {'pearson': Value('float64'), 'rho': Value('float64'), 'tau': Value('float64'), 'mmrv': Value('float64'), 'regret': Value('float64')}, 'square_mhf': {'pearson': Value('float64'), 'rho': Value('float64'), 'tau': Value('float64'), 'mmrv': Value('float64'), 'regret': Value('float64')}}}
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.
Robomimic mhf dense datasets
Mixed-human/filtered (mhf) dense-reward Robomimic datasets used by infOPE / VGPS experiments.
Datasets
| Path | Successful / total trajectories |
|---|---|
lift/mhf_densev1 |
202 / 300 |
lift/mhf_densev1_ntrajs=1020 |
775 / 1020 |
can/mhf_densev1 |
210 / 300 |
square/mhf_densev1 |
48 / 300 |
square/mhf2_densev1 |
207 / 300 |
Layout
lift/
mhf_densev1/dataset.hdf5
mhf_densev1_ntrajs=1020/dataset.hdf5
can/
mhf_densev1/dataset.hdf5
square/
mhf_densev1/dataset.hdf5
mhf2_densev1/dataset.hdf5
Download
# full repo
hf download infope/robomimic --repo-type dataset --local-dir ./robomimic
# one variant
hf download infope/robomimic lift/mhf_densev1/dataset.hdf5 --repo-type dataset
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