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The dataset generation failed because of a cast error
Error code: DatasetGenerationCastError
Exception: DatasetGenerationCastError
Message: An error occurred while generating the dataset
All the data files must have the same columns, but at some point there are 4 new columns ({'value_loss', 'critic_acc', 'value_acc', 'critic_loss'}) and 4 missing columns ({'ortho_loss', 'fb_loss', 'fb_offdiag', 'fb_diag'}).
This happened while the csv dataset builder was generating data using
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'hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed/checkpoints/hilp_density__pick-cube-expert-fixed__s2/train.csv', 'hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed/checkpoints/hilp_density__poke-cube-expert-fixed__s0/train.csv', 'hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed/checkpoints/hilp_density__poke-cube-expert-fixed__s1/train.csv', 'hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed/checkpoints/hilp_density__poke-cube-expert-fixed__s2/train.csv', 'hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed/checkpoints/hilp_density__push-cube-expert-fixed__s0/train.csv', 'hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed/checkpoints/hilp_density__push-cube-expert-fixed__s1/train.csv', 'hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed/checkpoints/hilp_density__push-cube-expert-fixed__s2/train.csv', 'hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed/checkpoints/hilp_density__push-expert-fixed__s0/train.csv', 'hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed/checkpoints/hilp_density__push-expert-fixed__s1/train.csv', 'hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed/checkpoints/hilp_density__push-expert-fixed__s2/train.csv', 'hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed/checkpoints/hilp_density__stack-cube-expert-fixed__s0/train.csv', 'hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed/checkpoints/hilp_density__stack-cube-expert-fixed__s1/train.csv', 'hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed/checkpoints/hilp_density__stack-cube-expert-fixed__s2/train.csv', 'hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed/checkpoints/rldp__bin-picking-expert-fixed__s0/train.csv', 'hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed/checkpoints/rldp__bin-picking-expert-fixed__s1/train.csv', 'hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed/checkpoints/rldp__bin-picking-expert-fixed__s2/train.csv', 'hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed/checkpoints/rldp__box-close-expert-fixed__s0/train.csv', 'hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed/checkpoints/rldp__box-close-expert-fixed__s1/train.csv', 'hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed/checkpoints/rldp__box-close-expert-fixed__s2/train.csv', 'hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed/checkpoints/rldp__lift-peg-expert-fixed__s0/train.csv', 'hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed/checkpoints/rldp__lift-peg-expert-fixed__s1/train.csv', 'hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed/checkpoints/rldp__lift-peg-expert-fixed__s2/train.csv', 'hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed/checkpoints/rldp__pick-cube-expert-fixed__s0/train.csv', 'hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed/checkpoints/rldp__pick-cube-expert-fixed__s1/train.csv', 'hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed/checkpoints/rldp__pick-cube-expert-fixed__s2/train.csv', 'hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed/checkpoints/rldp__poke-cube-expert-fixed__s0/train.csv', 'hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed/checkpoints/rldp__poke-cube-expert-fixed__s1/train.csv', 'hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed/checkpoints/rldp__poke-cube-expert-fixed__s2/train.csv', 'hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed/checkpoints/rldp__push-cube-expert-fixed__s0/train.csv', 'hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed/checkpoints/rldp__push-cube-expert-fixed__s1/train.csv', 'hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed/checkpoints/rldp__push-cube-expert-fixed__s2/train.csv', 'hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed/checkpoints/rldp__push-expert-fixed__s0/train.csv', 'hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed/checkpoints/rldp__push-expert-fixed__s1/train.csv', 'hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed/checkpoints/rldp__push-expert-fixed__s2/train.csv', 'hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed/checkpoints/rldp__stack-cube-expert-fixed__s0/train.csv', 'hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed/checkpoints/rldp__stack-cube-expert-fixed__s1/train.csv', 'hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed/checkpoints/rldp__stack-cube-expert-fixed__s2/train.csv', 'hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed/checkpoints/rldp_density__bin-picking-expert-fixed__s0/train.csv', 'hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed/checkpoints/rldp_density__bin-picking-expert-fixed__s1/train.csv', 'hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed/checkpoints/rldp_density__bin-picking-expert-fixed__s2/train.csv', 'hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed/checkpoints/rldp_density__box-close-expert-fixed__s0/train.csv', 'hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed/checkpoints/rldp_density__box-close-expert-fixed__s1/train.csv', 'hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed/checkpoints/rldp_density__box-close-expert-fixed__s2/train.csv', 'hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed/checkpoints/rldp_density__lift-peg-expert-fixed__s0/train.csv', 'hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed/checkpoints/rldp_density__lift-peg-expert-fixed__s1/train.csv', 'hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed/checkpoints/rldp_density__lift-peg-expert-fixed__s2/train.csv', 'hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed/checkpoints/rldp_density__pick-cube-expert-fixed__s0/train.csv', 'hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed/checkpoints/rldp_density__pick-cube-expert-fixed__s1/train.csv', 'hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed/checkpoints/rldp_density__pick-cube-expert-fixed__s2/train.csv', 'hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed/checkpoints/rldp_density__poke-cube-expert-fixed__s0/train.csv', 'hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed/checkpoints/rldp_density__poke-cube-expert-fixed__s1/train.csv', 'hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed/checkpoints/rldp_density__poke-cube-expert-fixed__s2/train.csv', 'hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed/checkpoints/rldp_density__push-cube-expert-fixed__s0/train.csv', 'hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed/checkpoints/rldp_density__push-cube-expert-fixed__s1/train.csv', 'hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed/checkpoints/rldp_density__push-cube-expert-fixed__s2/train.csv', 'hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed/checkpoints/rldp_density__push-expert-fixed__s0/train.csv', 'hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed/checkpoints/rldp_density__push-expert-fixed__s1/train.csv', 'hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed/checkpoints/rldp_density__push-expert-fixed__s2/train.csv', 'hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed/checkpoints/rldp_density__stack-cube-expert-fixed__s0/train.csv', 'hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed/checkpoints/rldp_density__stack-cube-expert-fixed__s1/train.csv', 'hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed/checkpoints/rldp_density__stack-cube-expert-fixed__s2/train.csv']
Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1848, in _prepare_split_single
writer.write_table(table)
~~~~~~~~~~~~~~~~~~^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 765, in write_table
self._write_table(pa_table, writer_batch_size=writer_batch_size)
~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 773, in _write_table
pa_table = table_cast(pa_table, self._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
action_gap_l2: double
actor_loss: double
bc_error: double
bc_flow_loss: double
critic_acc: double
critic_loss: double
q: double
q_gap_data_minus_actor: double
value_acc: double
value_loss: double
step: int64
-- schema metadata --
pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 1606
to
{'action_gap_l2': Value('float64'), 'actor_loss': Value('float64'), 'bc_error': Value('float64'), 'bc_flow_loss': Value('float64'), 'fb_diag': Value('float64'), 'fb_loss': Value('float64'), 'fb_offdiag': Value('float64'), 'ortho_loss': Value('float64'), 'q': Value('float64'), 'q_gap_data_minus_actor': Value('float64'), 'step': Value('int64')}
because column names don't match
During handling of the above exception, another exception occurred:
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 1850, in _prepare_split_single
raise DatasetGenerationCastError.from_cast_error(
...<4 lines>...
)
datasets.exceptions.DatasetGenerationCastError: An error occurred while generating the dataset
All the data files must have the same columns, but at some point there are 4 new columns ({'value_loss', 'critic_acc', 'value_acc', 'critic_loss'}) and 4 missing columns ({'ortho_loss', 'fb_loss', 'fb_offdiag', 'fb_diag'}).
This happened while the csv dataset builder was generating data using
hf://datasets/TommyShen/factored-fb-play/density-expert-fixed-1m/checkpoints/crl__bin-picking-expert-fixed__s0/train.csv (at revision 2e681ade3fc1c1ba028212a3cb7870f6f559bcab), ['hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed-1m/checkpoints/bc__bin-picking-expert-fixed__s0/train.csv', 'hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed-1m/checkpoints/bc__bin-picking-expert-fixed__s1/train.csv', 'hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed-1m/checkpoints/bc__bin-picking-expert-fixed__s2/train.csv', 'hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed-1m/checkpoints/bc__bin-picking-expert-fixed__s3/train.csv', 'hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed-1m/checkpoints/bc__bin-picking-expert-fixed__s4/train.csv', 'hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed-1m/checkpoints/bc__box-close-expert-fixed__s0/train.csv', 'hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed-1m/checkpoints/bc__box-close-expert-fixed__s1/train.csv', 'hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed-1m/checkpoints/bc__box-close-expert-fixed__s2/train.csv', 'hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed-1m/checkpoints/bc__box-close-expert-fixed__s3/train.csv', 'hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed-1m/checkpoints/bc__box-close-expert-fixed__s4/train.csv', 'hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed-1m/checkpoints/bc__lift-peg-expert-fixed__s0/train.csv', 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'hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed/checkpoints/rldp__pick-cube-expert-fixed__s1/train.csv', 'hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed/checkpoints/rldp__pick-cube-expert-fixed__s2/train.csv', 'hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed/checkpoints/rldp__poke-cube-expert-fixed__s0/train.csv', 'hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed/checkpoints/rldp__poke-cube-expert-fixed__s1/train.csv', 'hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed/checkpoints/rldp__poke-cube-expert-fixed__s2/train.csv', 'hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed/checkpoints/rldp__push-cube-expert-fixed__s0/train.csv', 'hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed/checkpoints/rldp__push-cube-expert-fixed__s1/train.csv', 'hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed/checkpoints/rldp__push-cube-expert-fixed__s2/train.csv', 'hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed/checkpoints/rldp__push-expert-fixed__s0/train.csv', 'hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed/checkpoints/rldp__push-expert-fixed__s1/train.csv', 'hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed/checkpoints/rldp__push-expert-fixed__s2/train.csv', 'hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed/checkpoints/rldp__stack-cube-expert-fixed__s0/train.csv', 'hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed/checkpoints/rldp__stack-cube-expert-fixed__s1/train.csv', 'hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed/checkpoints/rldp__stack-cube-expert-fixed__s2/train.csv', 'hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed/checkpoints/rldp_density__bin-picking-expert-fixed__s0/train.csv', 'hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed/checkpoints/rldp_density__bin-picking-expert-fixed__s1/train.csv', 'hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed/checkpoints/rldp_density__bin-picking-expert-fixed__s2/train.csv', 'hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed/checkpoints/rldp_density__box-close-expert-fixed__s0/train.csv', 'hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed/checkpoints/rldp_density__box-close-expert-fixed__s1/train.csv', 'hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed/checkpoints/rldp_density__box-close-expert-fixed__s2/train.csv', 'hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed/checkpoints/rldp_density__lift-peg-expert-fixed__s0/train.csv', 'hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed/checkpoints/rldp_density__lift-peg-expert-fixed__s1/train.csv', 'hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed/checkpoints/rldp_density__lift-peg-expert-fixed__s2/train.csv', 'hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed/checkpoints/rldp_density__pick-cube-expert-fixed__s0/train.csv', 'hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed/checkpoints/rldp_density__pick-cube-expert-fixed__s1/train.csv', 'hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed/checkpoints/rldp_density__pick-cube-expert-fixed__s2/train.csv', 'hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed/checkpoints/rldp_density__poke-cube-expert-fixed__s0/train.csv', 'hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed/checkpoints/rldp_density__poke-cube-expert-fixed__s1/train.csv', 'hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed/checkpoints/rldp_density__poke-cube-expert-fixed__s2/train.csv', 'hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed/checkpoints/rldp_density__push-cube-expert-fixed__s0/train.csv', 'hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed/checkpoints/rldp_density__push-cube-expert-fixed__s1/train.csv', 'hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed/checkpoints/rldp_density__push-cube-expert-fixed__s2/train.csv', 'hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed/checkpoints/rldp_density__push-expert-fixed__s0/train.csv', 'hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed/checkpoints/rldp_density__push-expert-fixed__s1/train.csv', 'hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed/checkpoints/rldp_density__push-expert-fixed__s2/train.csv', 'hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed/checkpoints/rldp_density__stack-cube-expert-fixed__s0/train.csv', 'hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed/checkpoints/rldp_density__stack-cube-expert-fixed__s1/train.csv', 'hf://datasets/TommyShen/factored-fb-play@2e681ade3fc1c1ba028212a3cb7870f6f559bcab/density-expert-fixed/checkpoints/rldp_density__stack-cube-expert-fixed__s2/train.csv']
Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)Need 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_gap_l2 float64 | actor_loss float64 | bc_error float64 | bc_flow_loss float64 | fb_diag float64 | fb_loss float64 | fb_offdiag float64 | ortho_loss float64 | q float64 | q_gap_data_minus_actor float64 | step int64 |
|---|---|---|---|---|---|---|---|---|---|---|
0.218189 | 0.123697 | 0.009788 | 0.094333 | -56.579117 | 8.425213 | 69.424446 | -4.420116 | 16.581097 | -0.18 | 5,000 |
0.161756 | 0.131079 | 0.017584 | 0.078327 | -68.155548 | 43.098869 | 113.356407 | -2.10199 | 25.246758 | -0.112827 | 10,000 |
0.136461 | 0.069299 | 0.005712 | 0.052162 | -64.132523 | 138.6409 | 205.752869 | -2.979446 | 35.589508 | -0.104568 | 15,000 |
0.137239 | 0.077699 | 0.011056 | 0.044531 | -42.131771 | 73.135651 | 116.685471 | -1.418049 | 39.094887 | 0.385574 | 20,000 |
0.12294 | 0.114996 | 0.007125 | 0.09362 | -55.545307 | 168.635193 | 225.799713 | -1.619209 | 23.210558 | 0.018694 | 25,000 |
0.143937 | 0.079342 | 0.00809 | 0.055073 | -65.069328 | 469.882904 | 541.158691 | -6.206459 | 29.747042 | 0.509527 | 30,000 |
0.108679 | 0.081628 | 0.006018 | 0.063575 | -79.122681 | 234.181961 | 318.844269 | -5.539623 | 40.119011 | 0.047836 | 35,000 |
0.089746 | 0.045519 | 0.003882 | 0.033875 | -85.817566 | 2,012.59082 | 2,103.399414 | -4.990925 | 75.163338 | 0.071693 | 40,000 |
0.118028 | 0.047071 | 0.004661 | 0.03309 | -49.609974 | 992.476501 | 1,043.096313 | -1.009834 | 23.668486 | -0.127062 | 45,000 |
0.073872 | 0.070025 | 0.003916 | 0.058278 | -53.376396 | 1,578.536255 | 1,637.314697 | -5.4021 | 46.16404 | -0.188686 | 50,000 |
0.084956 | 0.03833 | 0.005545 | 0.021694 | -48.178284 | 1,086.581543 | 1,135.763672 | -1.003891 | 66.094513 | -0.153915 | 55,000 |
0.092608 | 0.061475 | 0.007365 | 0.03938 | -56.752888 | 1,333.553467 | 1,391.07373 | -0.767338 | 24.697292 | 0.662983 | 60,000 |
0.10192 | 0.06252 | 0.012778 | 0.024187 | -24.752699 | 1,741.363892 | 1,766.365356 | -0.248749 | 88.846008 | -0.339371 | 65,000 |
0.08218 | 0.040376 | 0.004744 | 0.026144 | -61.114708 | 1,192.668457 | 1,251.220459 | 2.562794 | 63.695461 | -0.021614 | 70,000 |
0.093158 | 0.085182 | 0.012469 | 0.047776 | 24.232618 | 6,707.518066 | 6,687.755371 | -4.469902 | 52.783287 | 0.100197 | 75,000 |
0.07866 | 0.037059 | 0.003552 | 0.026402 | -38.064259 | 3,069.086182 | 3,101.419189 | 5.731174 | 113.956474 | -0.223 | 80,000 |
0.095904 | 0.053438 | 0.009767 | 0.024137 | -38.852478 | 668.07605 | 701.32428 | 5.604259 | 25.407818 | 0.035995 | 85,000 |
0.0673 | 0.03459 | 0.00198 | 0.02865 | -15.59026 | 527.453064 | 534.384033 | 8.659286 | 64.006256 | -0.171227 | 90,000 |
0.067034 | 0.022578 | 0.001852 | 0.017021 | -68.717056 | 1,657.700684 | 1,721.203491 | 5.214207 | 42.009911 | -0.299648 | 95,000 |
0.081963 | 0.043765 | 0.004224 | 0.031092 | -15.523484 | 759.31604 | 767.101685 | 7.737839 | 31.500233 | -0.17585 | 100,000 |
0.080487 | 0.044999 | 0.006094 | 0.026719 | -38.556057 | 947.52887 | 933.772522 | 52.312386 | 96.473938 | -0.229767 | 105,000 |
0.072804 | 0.069964 | 0.007687 | 0.046904 | -49.520458 | 1,254.823608 | 1,290.026245 | 14.317833 | 12.828161 | -0.068598 | 110,000 |
0.074134 | 0.034296 | 0.004844 | 0.019764 | 1.952197 | 5,161.657227 | 5,146.838867 | 12.866085 | 41.901104 | -0.052387 | 115,000 |
0.090843 | 0.06626 | 0.007837 | 0.042748 | -87.250641 | 1,832.990601 | 1,909.357788 | 10.883381 | 111.078209 | -0.328827 | 120,000 |
0.061604 | 0.032578 | 0.002995 | 0.023593 | -49.763756 | 618.41449 | 656.842346 | 11.335884 | 47.993488 | 0.162914 | 125,000 |
0.075079 | 0.052609 | 0.005895 | 0.034925 | -29.210131 | 2,641.386719 | 2,665.602783 | 4.994137 | 13.31031 | 0.398834 | 130,000 |
0.084461 | 0.050726 | 0.006379 | 0.031589 | -57.917271 | 363.113403 | 412.595673 | 8.435005 | -83.762146 | -0.076294 | 135,000 |
0.078709 | 0.028764 | 0.003274 | 0.018944 | -76.368805 | 461.112427 | 529.735413 | 7.745804 | 123.399704 | 0.162277 | 140,000 |
0.08526 | 0.051787 | 0.007857 | 0.028215 | 272.093384 | 10,785.270508 | 10,500.415039 | 12.761959 | 30.071434 | -0.164528 | 145,000 |
0.067601 | 0.036898 | 0.002203 | 0.030289 | -83.439217 | 1,057.835693 | 1,134.901733 | 6.373127 | 5.439692 | -0.215092 | 150,000 |
0.071492 | 0.044316 | 0.004242 | 0.031591 | -40.959507 | 384.363708 | 415.524292 | 9.798923 | 24.7019 | 0.786156 | 155,000 |
0.061637 | 0.045035 | 0.00341 | 0.034804 | -22.852936 | 2,890.006104 | 2,894.898926 | 17.960136 | 65.470734 | -0.593262 | 160,000 |
0.07063 | 0.047997 | 0.003825 | 0.036521 | 5.094798 | 3,682.833252 | 3,665.212158 | 12.526463 | 18.466013 | 0.612875 | 165,000 |
0.066653 | 0.030523 | 0.002922 | 0.021757 | -93.962158 | 618.288513 | 698.615784 | 13.634914 | 62.306335 | 0.131725 | 170,000 |
0.083085 | 0.048272 | 0.003113 | 0.038931 | -160.820663 | 535.704102 | 684.519958 | 12.004807 | 55.074181 | -0.463493 | 175,000 |
0.05068 | 0.031856 | 0.002991 | 0.022884 | -35.022438 | 1,447.949951 | 1,472.566284 | 10.406067 | 245.627014 | -0.18898 | 180,000 |
0.068165 | 0.050785 | 0.006372 | 0.031668 | -89.242325 | 513.510559 | 594.149719 | 8.603142 | 98.135674 | 0.551796 | 185,000 |
0.05907 | 0.043956 | 0.001785 | 0.038602 | -32.537025 | 3,044.947998 | 3,062.831299 | 14.653927 | 75.920166 | 0.043617 | 190,000 |
0.054834 | 0.030006 | 0.004427 | 0.016723 | -67.210052 | 630.118103 | 686.778259 | 10.549889 | 43.923203 | 0.557671 | 195,000 |
0.092951 | 0.046466 | 0.006024 | 0.028393 | -79.252785 | 1,729.033203 | 1,800.182983 | 8.103088 | 78.557556 | -0.029984 | 200,000 |
0.078529 | 0.031632 | 0.004068 | 0.01943 | -80.352539 | 3,908.580078 | 3,981.023438 | 7.909187 | 22.75169 | -0.527861 | 205,000 |
0.060103 | 0.034765 | 0.004082 | 0.02252 | -54.344147 | 609.53949 | 652.316956 | 11.566692 | -1.129776 | 0.0742 | 210,000 |
0.067285 | 0.060433 | 0.009684 | 0.03138 | -81.321701 | 349.802856 | 422.674042 | 8.450485 | 63.478989 | -0.337086 | 215,000 |
0.053711 | 0.047592 | 0.004555 | 0.033929 | -9.464495 | 620.931274 | 617.155762 | 13.23999 | 52.664066 | -0.146255 | 220,000 |
0.070546 | 0.068456 | 0.002938 | 0.059643 | 96.538483 | 5,395.636719 | 5,287.686523 | 11.411865 | 62.42033 | 0.187561 | 225,000 |
0.054904 | 0.036672 | 0.002294 | 0.029791 | -33.804012 | 2,990.330566 | 3,008.059082 | 16.075562 | 11.018988 | -0.864867 | 230,000 |
0.056235 | 0.044462 | 0.005277 | 0.028631 | -124.175232 | 1,548.29895 | 1,654.966431 | 17.507683 | 71.561874 | 0.768967 | 235,000 |
0.060738 | 0.034891 | 0.00497 | 0.01998 | -91.022362 | 1,198.953369 | 1,282.497192 | 7.47847 | 59.812309 | -0.108406 | 240,000 |
0.082716 | 0.040728 | 0.006388 | 0.021564 | -35.48032 | 846.908875 | 871.242126 | 11.147087 | -35.47332 | 0.148571 | 245,000 |
0.070454 | 0.029134 | 0.0035 | 0.018636 | -2.673132 | 926.453064 | 907.562683 | 21.563522 | 98.896332 | -0.093025 | 250,000 |
0.052602 | 0.038 | 0.001916 | 0.032252 | 17.760597 | 1,398.136475 | 1,369.016846 | 11.35899 | 43.346409 | -0.285107 | 255,000 |
0.066243 | 0.038264 | 0.006828 | 0.01778 | -51.554398 | 651.265503 | 686.960693 | 15.8592 | 54.488834 | 0.196148 | 260,000 |
0.051022 | 0.048429 | 0.007617 | 0.025579 | -85.618896 | 2,449.523682 | 2,528.026367 | 7.116322 | 44.7677 | 0.330578 | 265,000 |
0.043736 | 0.028957 | 0.003731 | 0.017765 | 21.959791 | 1,336.603882 | 1,305.710693 | 8.933357 | -3.804567 | -0.481466 | 270,000 |
0.052465 | 0.026174 | 0.002213 | 0.019536 | -61.517662 | 637.825745 | 687.934448 | 11.408936 | 16.145542 | -0.64459 | 275,000 |
0.073087 | 0.042336 | 0.004702 | 0.028228 | -51.591072 | 1,792.689331 | 1,830.652954 | 13.627411 | 86.752701 | -0.872971 | 280,000 |
0.065067 | 0.03051 | 0.003641 | 0.019588 | -36.79187 | 833.8349 | 857.363098 | 13.26368 | 17.883141 | -0.279709 | 285,000 |
0.047168 | 0.038768 | 0.004936 | 0.023959 | -23.87999 | 3,224.937012 | 3,239.253662 | 9.56319 | 65.496033 | 0.344704 | 290,000 |
0.061876 | 0.058199 | 0.008164 | 0.033707 | 209.204254 | 8,323.291992 | 8,088.583984 | 25.503639 | 69.649292 | 0.230682 | 295,000 |
0.049175 | 0.026212 | 0.002367 | 0.01911 | -90.133904 | 546.243713 | 621.445068 | 14.932564 | 52.055832 | -0.077492 | 300,000 |
0.057558 | 0.032071 | 0.003714 | 0.020927 | -95.457207 | 931.486328 | 1,014.130371 | 12.813145 | 108.782478 | -0.063797 | 305,000 |
0.070936 | 0.04317 | 0.004425 | 0.029894 | 115.671745 | 4,894.906738 | 4,762.065918 | 17.1689 | 41.655807 | -0.077206 | 310,000 |
0.040798 | 0.053255 | 0.005021 | 0.038192 | -37.900124 | 2,752.347656 | 2,776.788818 | 13.459019 | 110.851898 | -0.122894 | 315,000 |
0.055639 | 0.023123 | 0.002664 | 0.01513 | -54.310211 | 323.665558 | 356.474152 | 21.50161 | 50.093758 | 0.027584 | 320,000 |
0.07012 | 0.04037 | 0.007082 | 0.019124 | -50.672157 | 2,915.352539 | 2,951.735596 | 14.289093 | 77.64534 | -0.111687 | 325,000 |
0.063499 | 0.036833 | 0.002842 | 0.028306 | -33.084763 | 3,442.210693 | 3,458.180176 | 17.115143 | 43.989582 | -0.111084 | 330,000 |
0.061605 | 0.031776 | 0.002296 | 0.024889 | -121.296967 | 2,482.007813 | 2,591.54834 | 11.75629 | 136.111267 | -0.011475 | 335,000 |
0.056048 | 0.03066 | 0.003135 | 0.021254 | -131.728867 | 1,589.421265 | 1,706.047729 | 15.102432 | 60.422279 | 0.235329 | 340,000 |
0.054873 | 0.058901 | 0.00407 | 0.046692 | -30.713642 | 2,657.09668 | 2,675.397949 | 12.412407 | 23.886993 | -0.612415 | 345,000 |
0.070552 | 0.050468 | 0.007605 | 0.027653 | -50.262104 | 810.339417 | 844.415222 | 16.186264 | 18.282646 | -0.001476 | 350,000 |
0.064648 | 0.045796 | 0.007483 | 0.023346 | -62.604797 | 882.961243 | 928.375549 | 17.190514 | 4.305097 | 0.688508 | 355,000 |
0.043864 | 0.038051 | 0.004004 | 0.026039 | -95.889877 | 3,587.881104 | 3,666.809082 | 16.961815 | 62.76643 | -0.484879 | 360,000 |
0.047352 | 0.017685 | 0.001849 | 0.012137 | -52.154236 | 2,121.013916 | 2,164.855713 | 8.312527 | 118.987801 | 0.229973 | 365,000 |
0.057904 | 0.045889 | 0.007401 | 0.023686 | -98.845055 | 1,323.19812 | 1,406.402832 | 15.640415 | 45.844414 | -0.648777 | 370,000 |
0.055119 | 0.034094 | 0.003241 | 0.024371 | 115.222595 | 18,170.136719 | 18,039.382813 | 15.532021 | 60.75782 | -0.12693 | 375,000 |
0.072719 | 0.032814 | 0.003773 | 0.021496 | -78.728485 | 1,240.764893 | 1,301.693237 | 17.800167 | 52.937649 | 1.060467 | 380,000 |
0.045799 | 0.027057 | 0.001663 | 0.022067 | -80.825867 | 1,177.686523 | 1,241.685303 | 16.827091 | 74.126083 | -0.268013 | 385,000 |
0.039427 | 0.021671 | 0.002658 | 0.013696 | -125.998764 | 1,083.790894 | 1,196.288696 | 13.500931 | 40.62619 | 0.006172 | 390,000 |
0.050958 | 0.030476 | 0.005 | 0.015477 | -36.904625 | 437.521454 | 455.540253 | 18.885822 | 20.672806 | 0.783855 | 395,000 |
0.066683 | 0.032678 | 0.003698 | 0.021585 | -155.48616 | 10,589.225586 | 10,724.679688 | 20.032585 | 36.954201 | 0.079193 | 400,000 |
0.043915 | 0.035805 | 0.002255 | 0.029039 | -58.359283 | 1,054.42981 | 1,094.486572 | 18.302483 | 88.231758 | 0.321899 | 405,000 |
0.060901 | 0.039033 | 0.003926 | 0.027254 | -66.669334 | 1,281.864014 | 1,328.006104 | 20.527245 | 77.857361 | 0.365097 | 410,000 |
0.048363 | 0.054412 | 0.009331 | 0.026419 | -98.653816 | 866.042236 | 947.463928 | 17.232094 | 71.741615 | -0.322273 | 415,000 |
0.053158 | 0.037106 | 0.001714 | 0.031965 | -53.19278 | 1,243.532471 | 1,282.754395 | 13.970806 | 92.967583 | 1.527046 | 420,000 |
0.041873 | 0.02135 | 0.001837 | 0.015838 | -24.7605 | 3,089.380615 | 3,092.253174 | 21.887886 | 44.502136 | 0.022999 | 425,000 |
0.052979 | 0.042164 | 0.003719 | 0.031009 | -37.293674 | 418.832184 | 436.50415 | 19.621712 | 44.663208 | -1.613396 | 430,000 |
0.049768 | 0.038016 | 0.006857 | 0.017444 | -57.148529 | 515.532837 | 554.826843 | 17.8545 | 41.589478 | -0.169724 | 435,000 |
0.051129 | 0.028894 | 0.003016 | 0.019847 | -56.510941 | 825.637207 | 864.488403 | 17.659721 | 47.119019 | -0.270782 | 440,000 |
0.035091 | 0.049895 | 0.007417 | 0.027645 | -63.360722 | 717.894165 | 762.021667 | 19.2332 | 104.645523 | -0.133011 | 445,000 |
0.048082 | 0.034045 | 0.004705 | 0.019929 | -91.650497 | 225.861786 | 301.810089 | 15.702187 | 126.497665 | 0.087479 | 450,000 |
0.043137 | 0.037967 | 0.002604 | 0.030156 | -32.945168 | 679.22998 | 699.099854 | 13.075317 | -47.265282 | -0.559238 | 455,000 |
0.06471 | 0.040232 | 0.007962 | 0.016346 | -40.242912 | 348.704193 | 369.388672 | 19.558437 | 40.770584 | -0.009933 | 460,000 |
0.042211 | 0.022602 | 0.001766 | 0.017304 | -66.999718 | 1,128.77478 | 1,177.251221 | 18.523308 | -104.257568 | -1.195183 | 465,000 |
0.040562 | 0.031929 | 0.001821 | 0.026465 | -60.734543 | 825.963318 | 867.15863 | 19.539223 | 74.074211 | -0.354111 | 470,000 |
0.048745 | 0.042893 | 0.004141 | 0.030469 | -103.110512 | 1,528.899902 | 1,614.604858 | 17.405525 | 82.60257 | 0.077148 | 475,000 |
0.038494 | 0.020332 | 0.002436 | 0.013025 | -110.390167 | 1,793.179077 | 1,884.869507 | 18.699738 | 13.585734 | -0.348603 | 480,000 |
0.043184 | 0.038064 | 0.002181 | 0.031521 | -90.268921 | 646.896423 | 718.695313 | 18.47002 | 122.176735 | 0.824318 | 485,000 |
0.043547 | 0.034681 | 0.001389 | 0.030513 | -43.982193 | 753.641113 | 777.866028 | 19.757271 | 43.442368 | 0.436172 | 490,000 |
0.039661 | 0.022524 | 0.001254 | 0.018763 | -66.214981 | 447.890839 | 453.259979 | 60.845863 | -36.045521 | -0.478317 | 495,000 |
0.050155 | 0.047918 | 0.005464 | 0.031527 | -111.073807 | 366.301666 | 430.972412 | 46.403053 | 47.582108 | -0.28698 | 500,000 |
End of preview.
Factored-FB play data
Offline datasets for the Factored-FB testbed (Box2D / Metaworld / ManiSkill dev tasks), in the
unified per-episode .npz schema (observation, action, next_observation, reward, terminal, timeout, success). Two subsets, produced by rolling trained TD-MPC2 checkpoints (Box2D +
ManiSkill) or the Metaworld scripted oracle:
play-noise/
Single-goal, exploration-augmented rollouts. Each episode draws a per-episode exploration level
(an expert_frac run clean; the rest add ε-random + Gaussian action noise), runs the full
horizon with no stop-at-success. Diverse states around one task goal — noisy demos.
1.35M transitions, 9 tasks (5 Box2D × 1000 ep, 2 ManiSkill × 3000 ep, 2 Metaworld × 1000 ep).
play-resample/
OGBench-style diverse-goal play: one long continuous episode chains many goals — reach the goal, hold it briefly, then resample a new valid goal (Box2D: not inside a wall, not too close) and continue. No env reset between goals, so goal-relabeling sees a broad goal distribution. (Box2D goal-conditioned tasks; see that subset's manifest for coverage.)
Each <Family>__<task>/ holds buffer/episode_*.npz + meta.json. _videos/ has a rollout
grid per task. Load with env/unified.py::load_unified from the Factored-FB repo.
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