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Cannot extract the features (columns) for the split 'test' of the config 'default' of the dataset.
Error code:   FeaturesError
Exception:    ArrowInvalid
Message:      JSON parse error: Invalid value. in row 0
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 324, in _generate_tables
                  df = pandas_read_json(f)
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 38, in pandas_read_json
                  return pd.read_json(path_or_buf, **kwargs)
                         ~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/pandas/io/json/_json.py", line 815, in read_json
                  return json_reader.read()
                         ~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/pandas/io/json/_json.py", line 1014, in read
                  obj = self._get_object_parser(self.data)
                File "/usr/local/lib/python3.14/site-packages/pandas/io/json/_json.py", line 1040, in _get_object_parser
                  obj = FrameParser(json, **kwargs).parse()
                File "/usr/local/lib/python3.14/site-packages/pandas/io/json/_json.py", line 1176, in parse
                  self._parse()
                  ~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/pandas/io/json/_json.py", line 1392, in _parse
                  ujson_loads(json, precise_float=self.precise_float), dtype=None
                  ~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
              ValueError: Expected object or value
              
              During handling of the above exception, another exception occurred:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 244, in compute_first_rows_from_streaming_response
                  iterable_dataset = iterable_dataset._resolve_features()
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 4408, in _resolve_features
                  features = _infer_features_from_batch(self.with_format(None)._head())
                                                        ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2679, in _head
                  return next(iter(self.iter(batch_size=n)))
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2861, in iter
                  for key, pa_table in ex_iterable.iter_arrow():
                                       ~~~~~~~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2395, in _iter_arrow
                  yield from 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 327, in _generate_tables
                  raise e
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 290, in _generate_tables
                  pa_table = paj.read_json(
                      io.BytesIO(batch), read_options=paj.ReadOptions(block_size=block_size)
                  )
                File "pyarrow/_json.pyx", line 342, in pyarrow._json.read_json
                File "pyarrow/error.pxi", line 155, in pyarrow.lib.pyarrow_internal_check_status
                  return check_status(status)
                File "pyarrow/error.pxi", line 92, in pyarrow.lib.check_status
                  raise convert_status(status)
              pyarrow.lib.ArrowInvalid: JSON parse error: Invalid value. in row 0

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LIBERO-90 offline-eval validation rig — day 1 (2026-09-09, box 40110) and day 2 (2026-09-10, box 42146)

Root: day-1 zips (see the table below). day2_2026-09-10/: the same folders re-zipped after day 2 plus the new ones.

day-2 zip contents
cimse.zip CI-MSE run on the held-out set: task-aware 4-segment VLM annotation (annot/intervals.json), report.md (per episode per segment + ranking), rollouts_report.md (same on the 150 rollouts), confusion.md, scripts
offline_eval.zip metric package + out/: day-2 outputs llr.* (likelihood ratio), sim_object_pose.* (object-relative event pose, outcome stage hits, v1–v4), sim_event_pose.*, REPORT_2026-09-10.md, plus everything from day 1
runs.zip the 150 recorded rollouts (unchanged)
libero_ds.zip held-out set, training-demo sample, raw parquet, 15 LIBERO-90 HDF5s (unchanged)
renders.zip / renders_pairs.zip 15 rendered rollouts (5 success / 5 failed holding / 5 closed on air) and the same 15 side by side with a demo, CI-MSE worst-segment flags
eval.zip / ci_mse.tgz the fd-studio ci_mse package (annotator + validate.py) as used
eval_run.zip / logs.zip dataset builders, launch scripts, recorder patch; every job log

Reports: fd/sdk/contexts/reports/offline_eval_validation_libero90_2026-09-{09,10}.md. Checkpoint: lerobot/pi05_libero_finetuned_v044 (not included).

Day-1 zips (root)

zip contents
offline_eval.zip the metric package (run_all.sh, scripts, sim/), all outputs in out/ incl. REPORT.md, profile.md, pairing.md, chunk dumps (h5), anchors, defect ladder, sim replay results
runs.zip the 150 recorded rollouts (libero90_10tasks_n10_s1000/recordings, v3 datasets with both cameras), eval_info.json, the aborted sync run, the async speed test
libero_ds.zip libero90_eval50 (held-out set), libero_eval120 (training-demo sample), libero_partial (raw HuggingFaceVLA/libero files), libero90_raw (raw jesbu1 parquet), libero90_hdf5 (15 LIBERO-90 task HDF5s with MuJoCo states)
eval_run.zip dataset builders, selection files, closed-loop launch scripts, recorder patch
logs.zip every job log
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