The dataset viewer is not available for this split.
Error code: StreamingRowsError
Exception: TypeError
Message: Couldn't cast array of type
struct<mode: string, target: null>
to
{'declared_corpus_sha256': Value('string'), 'file_sha256': Value('string'), 'mode': Value('string'), 'path': Value('string'), 'sequence_count': Value('int64')}
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 149, 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 129, 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 489, 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 2818, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2355, in __iter__
for key, pa_table in self._iter_arrow():
~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2380, 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 2369, in table_cast
return cast_table_to_schema(table, schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2303, 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 1852, 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 2149, 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<mode: string, target: null>
to
{'declared_corpus_sha256': Value('string'), 'file_sha256': Value('string'), 'mode': Value('string'), 'path': Value('string'), 'sequence_count': Value('int64')}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.
SO-101 Keyboard Typing Checkpoints
Reproducibility bundle for the SO-101 six-letter keyboard-typing comparisons. The policies use a fixed Cartesian keyboard map, proprioceptive joint state, registered keypress feedback, and no vision or online pose correction.
Code
The matched three-actuator IsaacLab task, PPO configuration, actuator profiles, and evaluation scripts are in:
- Repository:
https://github.com/es-rl/so101_keyboard_task - Pinned branch/commit:
vignesh/physical-abc-5kat1b8cb7e81
The branch includes the USD-drive, Workshop-baseline, and AnchorBench actuator profiles. The Sparse VBD checkpoint uses the same fixed-Cartesian task contract with Sparse VBD as its Newton solver.
Contents
| Artifact | Solver | Actuator profile | PPO updates | Checkpoint |
|---|---|---|---|---|
| MJWarp AnchorBench | Newton MJWarp | AnchorBench | 19,000 | checkpoints/mjwarp-anchorbench-19k/model_19000.pt |
| MJWarp Workshop | Newton MJWarp | Workshop baseline | 19,000 | checkpoints/mjwarp-workshop-19k/model_19000.pt |
| MJWarp USD | Newton MJWarp | USD drive | 19,000 | checkpoints/mjwarp-usd-19k/model_19000.pt |
| Sparse VBD AnchorBench | Newton Sparse VBD | AnchorBench | 20,000 | checkpoints/sparse-vbd-anchorbench-20k/model_19999.pt |
model_19999.pt is the checkpoint produced after 20,000 updates because the
training loop numbers checkpoints from zero.
Every checkpoint has an exact matching configs/*.env.yaml file. Verify
downloaded weights with SHA256SUMS; manifest.json records the code revision,
task ID, solver, actuator profile, and matching evaluation artifacts.
Evaluation
The evaluation/ directory contains saved deterministic simulator reports and
the final real-robot comparison summary. The reported real-robot protocol uses
the same ordered bank of 100 six-letter sequences, strict press-release-
clearance completion, and no vision. These artifacts are evidence for the
stated experiment only; robot, calibration, and fixture changes require a new
physical evaluation.
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