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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 18 new columns ({'q_mean', 'in_training', 'q_late_mean', 'v_max', 'q_s0', 'pen_x', 'adv_s0', 'policy_id', 'repo_id', 'v_final', 'v_mean', 'q_final', 'source_episode_index', 'pen_y', 'pen_yaw', 'policy_name', 'v_late_mean', 'n_frames'}) and 17 missing columns ({'sel_z', 'q_top_gap_med', 'argmax_act_outlier', 'adv_mean', 'disag_ratio', 'adv_argmax', 'act_diversity', 'q_cand_mean', 'q_spread', 'disag_argmax', 'q_cand_max', 'num_candidates', 'executed_minus_cand_mean', 'executed_q0', 'disag_mean', 'q_top_gap', 'critic_rank_corr'}).
This happened while the csv dataset builder was generating data using
hf://datasets/mulligan/paper-evidence/real/value_learning/training/125000/per_episode_features.csv (at revision 9db323805b28983849eccccde8ab392b7468f31f), ['hf://datasets/mulligan/paper-evidence@9db323805b28983849eccccde8ab392b7468f31f/real/value_learning/training/125000/candidate_probe.csv', 'hf://datasets/mulligan/paper-evidence@9db323805b28983849eccccde8ab392b7468f31f/real/value_learning/training/125000/per_episode_features.csv', 'hf://datasets/mulligan/paper-evidence@9db323805b28983849eccccde8ab392b7468f31f/real/value_learning/training/150000/candidate_probe.csv', 'hf://datasets/mulligan/paper-evidence@9db323805b28983849eccccde8ab392b7468f31f/real/value_learning/training/150000/per_episode_features.csv', 'hf://datasets/mulligan/paper-evidence@9db323805b28983849eccccde8ab392b7468f31f/real/value_learning/training/200000/candidate_probe.csv', 'hf://datasets/mulligan/paper-evidence@9db323805b28983849eccccde8ab392b7468f31f/real/value_learning/training/200000/per_episode_features.csv', 'hf://datasets/mulligan/paper-evidence@9db323805b28983849eccccde8ab392b7468f31f/real/value_learning/training/225000/candidate_probe.csv', 'hf://datasets/mulligan/paper-evidence@9db323805b28983849eccccde8ab392b7468f31f/real/value_learning/training/225000/per_episode_features.csv', 'hf://datasets/mulligan/paper-evidence@9db323805b28983849eccccde8ab392b7468f31f/real/value_learning/training/250000/candidate_probe.csv', 'hf://datasets/mulligan/paper-evidence@9db323805b28983849eccccde8ab392b7468f31f/real/value_learning/training/250000/per_episode_features.csv', 'hf://datasets/mulligan/paper-evidence@9db323805b28983849eccccde8ab392b7468f31f/real/value_learning/training/300000/candidate_probe.csv', 'hf://datasets/mulligan/paper-evidence@9db323805b28983849eccccde8ab392b7468f31f/real/value_learning/training/300000/per_episode_features.csv', 'hf://datasets/mulligan/paper-evidence@9db323805b28983849eccccde8ab392b7468f31f/real/value_learning/training/400000/candidate_probe.csv', 'hf://datasets/mulligan/paper-evidence@9db323805b28983849eccccde8ab392b7468f31f/real/value_learning/training/400000/per_episode_features.csv', 'hf://datasets/mulligan/paper-evidence@9db323805b28983849eccccde8ab392b7468f31f/real/value_learning/training/450000/candidate_probe.csv', 'hf://datasets/mulligan/paper-evidence@9db323805b28983849eccccde8ab392b7468f31f/real/value_learning/training/450000/per_episode_features.csv', 'hf://datasets/mulligan/paper-evidence@9db323805b28983849eccccde8ab392b7468f31f/real/value_learning/training/475000/candidate_probe.csv', 'hf://datasets/mulligan/paper-evidence@9db323805b28983849eccccde8ab392b7468f31f/real/value_learning/training/475000/per_episode_features.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 784, 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 795, 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
block: string
arm: string
in_training: bool
episode_index: int64
manifest_idx: int64
success: int64
n_frames: int64
v_s0: double
q_s0: double
adv_s0: double
v_mean: double
v_late_mean: double
v_max: double
q_mean: double
q_late_mean: double
v_final: double
q_final: double
source_episode_index: int64
policy_id: int64
policy_name: string
pen_x: double
pen_y: double
pen_yaw: double
repo_id: string
-- schema metadata --
pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 3049
to
{'block': Value('string'), 'arm': Value('string'), 'episode_index': Value('int64'), 'manifest_idx': Value('int64'), 'success': Value('int64'), 'num_candidates': Value('int64'), 'q_cand_mean': Value('float64'), 'q_cand_max': Value('float64'), 'q_spread': Value('float64'), 'q_top_gap': Value('float64'), 'q_top_gap_med': Value('float64'), 'sel_z': Value('float64'), 'adv_argmax': Value('float64'), 'adv_mean': Value('float64'), 'disag_mean': Value('float64'), 'disag_argmax': Value('float64'), 'disag_ratio': Value('float64'), 'critic_rank_corr': Value('float64'), 'act_diversity': Value('float64'), 'argmax_act_outlier': Value('float64'), 'executed_q0': Value('float64'), 'executed_minus_cand_mean': Value('float64'), 'v_s0': Value('float64')}
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 18 new columns ({'q_mean', 'in_training', 'q_late_mean', 'v_max', 'q_s0', 'pen_x', 'adv_s0', 'policy_id', 'repo_id', 'v_final', 'v_mean', 'q_final', 'source_episode_index', 'pen_y', 'pen_yaw', 'policy_name', 'v_late_mean', 'n_frames'}) and 17 missing columns ({'sel_z', 'q_top_gap_med', 'argmax_act_outlier', 'adv_mean', 'disag_ratio', 'adv_argmax', 'act_diversity', 'q_cand_mean', 'q_spread', 'disag_argmax', 'q_cand_max', 'num_candidates', 'executed_minus_cand_mean', 'executed_q0', 'disag_mean', 'q_top_gap', 'critic_rank_corr'}).
This happened while the csv dataset builder was generating data using
hf://datasets/mulligan/paper-evidence/real/value_learning/training/125000/per_episode_features.csv (at revision 9db323805b28983849eccccde8ab392b7468f31f), ['hf://datasets/mulligan/paper-evidence@9db323805b28983849eccccde8ab392b7468f31f/real/value_learning/training/125000/candidate_probe.csv', 'hf://datasets/mulligan/paper-evidence@9db323805b28983849eccccde8ab392b7468f31f/real/value_learning/training/125000/per_episode_features.csv', 'hf://datasets/mulligan/paper-evidence@9db323805b28983849eccccde8ab392b7468f31f/real/value_learning/training/150000/candidate_probe.csv', 'hf://datasets/mulligan/paper-evidence@9db323805b28983849eccccde8ab392b7468f31f/real/value_learning/training/150000/per_episode_features.csv', 'hf://datasets/mulligan/paper-evidence@9db323805b28983849eccccde8ab392b7468f31f/real/value_learning/training/200000/candidate_probe.csv', 'hf://datasets/mulligan/paper-evidence@9db323805b28983849eccccde8ab392b7468f31f/real/value_learning/training/200000/per_episode_features.csv', 'hf://datasets/mulligan/paper-evidence@9db323805b28983849eccccde8ab392b7468f31f/real/value_learning/training/225000/candidate_probe.csv', 'hf://datasets/mulligan/paper-evidence@9db323805b28983849eccccde8ab392b7468f31f/real/value_learning/training/225000/per_episode_features.csv', 'hf://datasets/mulligan/paper-evidence@9db323805b28983849eccccde8ab392b7468f31f/real/value_learning/training/250000/candidate_probe.csv', 'hf://datasets/mulligan/paper-evidence@9db323805b28983849eccccde8ab392b7468f31f/real/value_learning/training/250000/per_episode_features.csv', 'hf://datasets/mulligan/paper-evidence@9db323805b28983849eccccde8ab392b7468f31f/real/value_learning/training/300000/candidate_probe.csv', 'hf://datasets/mulligan/paper-evidence@9db323805b28983849eccccde8ab392b7468f31f/real/value_learning/training/300000/per_episode_features.csv', 'hf://datasets/mulligan/paper-evidence@9db323805b28983849eccccde8ab392b7468f31f/real/value_learning/training/400000/candidate_probe.csv', 'hf://datasets/mulligan/paper-evidence@9db323805b28983849eccccde8ab392b7468f31f/real/value_learning/training/400000/per_episode_features.csv', 'hf://datasets/mulligan/paper-evidence@9db323805b28983849eccccde8ab392b7468f31f/real/value_learning/training/450000/candidate_probe.csv', 'hf://datasets/mulligan/paper-evidence@9db323805b28983849eccccde8ab392b7468f31f/real/value_learning/training/450000/per_episode_features.csv', 'hf://datasets/mulligan/paper-evidence@9db323805b28983849eccccde8ab392b7468f31f/real/value_learning/training/475000/candidate_probe.csv', 'hf://datasets/mulligan/paper-evidence@9db323805b28983849eccccde8ab392b7468f31f/real/value_learning/training/475000/per_episode_features.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.
block string | arm string | episode_index int64 | manifest_idx int64 | success int64 | num_candidates int64 | q_cand_mean float64 | q_cand_max float64 | q_spread float64 | q_top_gap float64 | q_top_gap_med float64 | sel_z float64 | adv_argmax float64 | adv_mean float64 | disag_mean float64 | disag_argmax float64 | disag_ratio float64 | critic_rank_corr float64 | act_diversity float64 | argmax_act_outlier float64 | executed_q0 float64 | executed_minus_cand_mean float64 | v_s0 float64 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
r4_baseline_no_cf_heldout_s2026070604 | baseline_no_cf | 200 | 0 | 0 | 32 | 0.006419 | 0.009968 | 0.001847 | 0.00355 | 0.003484 | 1.921976 | 0.007591 | 0.004041 | 0.001859 | 0.002134 | 1.147894 | 0.158724 | 1.50457 | 1.156376 | 0.006649 | 0.00023 | 0.002377 |
r4_baseline_no_cf_heldout_s2026070604 | baseline_no_cf | 201 | 1 | 0 | 32 | -0.000714 | 0.015948 | 0.006393 | 0.016662 | 0.016093 | 2.606093 | 0.012032 | -0.004629 | 0.006666 | 0.000581 | 0.087143 | -0.186217 | 1.914308 | 1.312931 | 0.004553 | 0.005267 | 0.003916 |
r4_baseline_no_cf_heldout_s2026070604 | baseline_no_cf | 202 | 2 | 0 | 32 | 0.007874 | 0.010755 | 0.001526 | 0.00288 | 0.003174 | 1.887573 | 0.001939 | -0.000941 | 0.002809 | 0.000119 | 0.04222 | -0.100073 | 1.686221 | 1.224928 | 0.008649 | 0.000774 | 0.008816 |
r4_baseline_no_cf_heldout_s2026070604 | baseline_no_cf | 203 | 3 | 0 | 32 | 0.006704 | 0.008992 | 0.000873 | 0.002287 | 0.002338 | 2.620552 | 0.005789 | 0.003502 | 0.000672 | 0.000888 | 1.321163 | 0.642229 | 1.567037 | 2.900869 | 0.00305 | -0.003654 | 0.003203 |
r4_baseline_no_cf_heldout_s2026070604 | baseline_no_cf | 204 | 4 | 0 | 32 | 0.007561 | 0.012236 | 0.002614 | 0.004675 | 0.003477 | 1.788136 | 0.003399 | -0.001276 | 0.001586 | 0.001549 | 0.976696 | 0.336144 | 1.608705 | 1.093711 | 0.016043 | 0.008482 | 0.008838 |
r4_baseline_no_cf_heldout_s2026070604 | baseline_no_cf | 205 | 5 | 1 | 32 | 0.006596 | 0.008816 | 0.00159 | 0.002219 | 0.001917 | 1.395453 | 0.006911 | 0.004691 | 0.001354 | 0.000398 | 0.293542 | -0.660191 | 1.65562 | 0.683952 | 0.000022 | -0.006575 | 0.001905 |
r4_baseline_no_cf_heldout_s2026070604 | baseline_no_cf | 206 | 6 | 0 | 32 | 0.002656 | 0.007699 | 0.002272 | 0.005042 | 0.00515 | 2.219101 | 0.007571 | 0.002529 | 0.001732 | 0.001491 | 0.860863 | 0.21151 | 1.791056 | 1.472656 | -0.001896 | -0.004552 | 0.000127 |
r4_baseline_no_cf_heldout_s2026070604 | baseline_no_cf | 207 | 7 | 1 | 32 | 0.004427 | 0.017729 | 0.00326 | 0.013302 | 0.013378 | 4.080471 | 0.013687 | 0.000386 | 0.001599 | 0.004786 | 2.992215 | 0.159457 | 1.604276 | 1.395465 | -0.003668 | -0.008095 | 0.004042 |
r4_baseline_no_cf_heldout_s2026070604 | baseline_no_cf | 208 | 8 | 0 | 32 | 0.003843 | 0.006158 | 0.001273 | 0.002315 | 0.00223 | 1.817499 | 0.0028 | 0.000486 | 0.000825 | 0.00081 | 0.980963 | 0.256598 | 1.122493 | 1.374402 | -0.006864 | -0.010707 | 0.003358 |
r4_baseline_no_cf_heldout_s2026070604 | baseline_no_cf | 209 | 9 | 0 | 32 | 0.011431 | 0.025982 | 0.006544 | 0.01455 | 0.013747 | 2.223405 | 0.019671 | 0.00512 | 0.002826 | 0.000585 | 0.207102 | 0.743768 | 1.897619 | 1.138255 | 0.007384 | -0.004047 | 0.006311 |
r4_baseline_no_cf_heldout_s2026070604 | baseline_no_cf | 210 | 10 | 0 | 32 | 0.009847 | 0.017153 | 0.003655 | 0.007307 | 0.00745 | 1.999022 | 0.014825 | 0.007518 | 0.004051 | 0.002769 | 0.683496 | -0.265762 | 1.283659 | 1.028741 | 0.006772 | -0.003074 | 0.002328 |
r4_baseline_no_cf_heldout_s2026070604 | baseline_no_cf | 211 | 11 | 0 | 32 | -0.011745 | -0.004095 | 0.002597 | 0.007649 | 0.008187 | 2.945902 | 0.002047 | -0.005602 | 0.004676 | 0.006067 | 1.297526 | 0.503666 | 1.485099 | 1.799762 | -0.006009 | 0.005736 | -0.006143 |
r4_baseline_no_cf_heldout_s2026070604 | baseline_no_cf | 212 | 12 | 1 | 32 | 0.005131 | 0.007841 | 0.001164 | 0.002711 | 0.002857 | 2.328644 | 0.005598 | 0.002888 | 0.002155 | 0.000589 | 0.273154 | -0.562683 | 2.224747 | 2.233084 | 0.002524 | -0.002607 | 0.002243 |
r4_baseline_no_cf_heldout_s2026070604 | baseline_no_cf | 213 | 13 | 1 | 32 | 0.001058 | 0.008564 | 0.003876 | 0.007507 | 0.006735 | 1.936772 | 0.007683 | 0.000176 | 0.003351 | 0.00195 | 0.581822 | 0.105572 | 1.911215 | 1.744648 | 0.000195 | -0.000863 | 0.000881 |
r4_baseline_no_cf_heldout_s2026070604 | baseline_no_cf | 214 | 14 | 0 | 32 | 0.01023 | 0.021192 | 0.006821 | 0.010962 | 0.009217 | 1.606988 | 0.017066 | 0.006105 | 0.00353 | 0.002679 | 0.758825 | 0.854472 | 1.700641 | 1.234547 | 0.002598 | -0.007631 | 0.004125 |
r4_baseline_no_cf_heldout_s2026070604 | baseline_no_cf | 215 | 15 | 1 | 32 | 0.005331 | 0.006651 | 0.000676 | 0.00132 | 0.001214 | 1.953652 | 0.004563 | 0.003242 | 0.001172 | 0.000641 | 0.546761 | -0.420455 | 2.091841 | 1.200476 | 0.004104 | -0.001227 | 0.002089 |
r4_baseline_no_cf_heldout_s2026070604 | baseline_no_cf | 216 | 16 | 1 | 32 | 0.005684 | 0.007803 | 0.001055 | 0.002119 | 0.001832 | 2.008816 | 0.002529 | 0.000411 | 0.001628 | 0.000253 | 0.155273 | -0.437683 | 1.758148 | 0.695168 | 0.007493 | 0.001808 | 0.005274 |
r4_baseline_no_cf_heldout_s2026070604 | baseline_no_cf | 217 | 17 | 1 | 32 | 0.004514 | 0.016598 | 0.006269 | 0.012084 | 0.011113 | 1.927625 | 0.013404 | 0.001319 | 0.008151 | 0.000001 | 0.000139 | -0.663856 | 1.67488 | 0.72138 | 0.001467 | -0.003047 | 0.003194 |
r4_baseline_no_cf_heldout_s2026070604 | baseline_no_cf | 218 | 18 | 1 | 32 | 0.004248 | 0.01009 | 0.001834 | 0.005842 | 0.006233 | 3.185124 | 0.006107 | 0.000265 | 0.000918 | 0.000541 | 0.589657 | 0.660191 | 1.77548 | 2.159054 | 0.008046 | 0.003798 | 0.003983 |
r4_baseline_no_cf_heldout_s2026070604 | baseline_no_cf | 219 | 19 | 0 | 32 | 0.007612 | 0.01294 | 0.002533 | 0.005329 | 0.005477 | 2.103825 | 0.011178 | 0.005849 | 0.001544 | 0.000551 | 0.356964 | 0.511364 | 2.183848 | 0.963339 | -0.000131 | -0.007742 | 0.001763 |
r4_baseline_no_cf_heldout_s2026070604 | baseline_no_cf | 220 | 20 | 1 | 32 | 0.006537 | 0.021535 | 0.004105 | 0.014998 | 0.016113 | 3.653406 | 0.016932 | 0.001934 | 0.001593 | 0.001738 | 1.090967 | 0.693182 | 2.308618 | 1.533092 | 0.003452 | -0.003085 | 0.004603 |
r4_baseline_no_cf_heldout_s2026070604 | baseline_no_cf | 221 | 21 | 0 | 32 | -0.014984 | 0.007152 | 0.006553 | 0.022136 | 0.023866 | 3.377993 | 0.01701 | -0.005126 | 0.003255 | 0.014124 | 4.339891 | 0.414223 | 2.144226 | 1.25603 | -0.010768 | 0.004216 | -0.009859 |
r4_baseline_no_cf_heldout_s2026070604 | baseline_no_cf | 222 | 22 | 0 | 32 | 0.004168 | 0.008909 | 0.002604 | 0.004741 | 0.004318 | 1.820442 | 0.005545 | 0.000804 | 0.001516 | 0.000607 | 0.400195 | 0.248534 | 1.929878 | 1.202396 | 0.005309 | 0.001142 | 0.003364 |
r4_baseline_no_cf_heldout_s2026070604 | baseline_no_cf | 223 | 23 | 1 | 32 | 0.001661 | 0.017703 | 0.003832 | 0.016041 | 0.017551 | 4.186316 | 0.016069 | 0.000028 | 0.002204 | 0.001312 | 0.595144 | 0.494135 | 1.816362 | 2.009668 | -0.00291 | -0.004571 | 0.001634 |
r4_baseline_no_cf_heldout_s2026070604 | baseline_no_cf | 224 | 24 | 0 | 32 | 0.004823 | 0.007859 | 0.001588 | 0.003037 | 0.003007 | 1.912682 | 0.003158 | 0.000121 | 0.00242 | 0.000164 | 0.067897 | 0.295088 | 1.818676 | 1.586702 | 0.002926 | -0.001896 | 0.004701 |
r4_baseline_no_cf_heldout_s2026070604 | baseline_no_cf | 225 | 25 | 0 | 32 | 0.002721 | 0.010772 | 0.003611 | 0.008051 | 0.007851 | 2.229569 | 0.008514 | 0.000462 | 0.006662 | 0.003193 | 0.479328 | -0.210044 | 1.120516 | 0.879418 | 0.002767 | 0.000046 | 0.002258 |
r4_baseline_no_cf_heldout_s2026070604 | baseline_no_cf | 226 | 26 | 1 | 32 | -0.003849 | 0.011229 | 0.005595 | 0.015078 | 0.015105 | 2.695103 | 0.013977 | -0.001101 | 0.005537 | 0.003471 | 0.626824 | 0.196481 | 1.872829 | 1.215864 | -0.004659 | -0.00081 | -0.002748 |
r4_baseline_no_cf_heldout_s2026070604 | baseline_no_cf | 227 | 27 | 0 | 32 | 0.029865 | 0.049286 | 0.013125 | 0.019421 | 0.019724 | 1.479638 | 0.044 | 0.024579 | 0.002607 | 0.002173 | 0.833292 | 0.861437 | 1.938262 | 0.845315 | -0.001849 | -0.031714 | 0.005286 |
r4_baseline_no_cf_heldout_s2026070604 | baseline_no_cf | 228 | 28 | 1 | 32 | 0.006006 | 0.011255 | 0.003388 | 0.005248 | 0.005271 | 1.549116 | 0.004852 | -0.000396 | 0.004585 | 0.003748 | 0.817489 | -0.187683 | 1.930764 | 1.030923 | 0.006277 | 0.000271 | 0.006402 |
r4_baseline_no_cf_heldout_s2026070604 | baseline_no_cf | 229 | 29 | 1 | 32 | 0.003228 | 0.009666 | 0.001709 | 0.006438 | 0.006226 | 3.767964 | 0.008361 | 0.001923 | 0.002571 | 0.004855 | 1.888474 | 0.534091 | 1.677135 | 3.359654 | 0.003007 | -0.00022 | 0.001305 |
r4_baseline_no_cf_heldout_s2026070604 | baseline_no_cf | 230 | 30 | 1 | 32 | 0.004299 | 0.009145 | 0.001538 | 0.004846 | 0.005168 | 3.150605 | 0.006671 | 0.001825 | 0.001918 | 0.000259 | 0.135271 | 0.547654 | 2.368993 | 1.561693 | 0.004281 | -0.000018 | 0.002474 |
r4_baseline_no_cf_heldout_s2026070604 | baseline_no_cf | 231 | 31 | 1 | 32 | 0.005243 | 0.007762 | 0.002067 | 0.002519 | 0.002366 | 1.219014 | 0.006264 | 0.003745 | 0.001125 | 0.00038 | 0.337828 | 0.019062 | 2.288029 | 0.785804 | -0.003689 | -0.008932 | 0.001498 |
r4_baseline_no_cf_heldout_s2026070604 | baseline_no_cf | 232 | 32 | 0 | 32 | 0.001908 | 0.00676 | 0.002974 | 0.004852 | 0.004655 | 1.631444 | 0.005756 | 0.000903 | 0.002163 | 0.000242 | 0.111895 | -0.029326 | 1.971759 | 1.013419 | 0.005293 | 0.003386 | 0.001004 |
r4_baseline_no_cf_heldout_s2026070604 | baseline_no_cf | 233 | 34 | 0 | 32 | 0.005577 | 0.009513 | 0.002015 | 0.003936 | 0.003896 | 1.953445 | 0.006648 | 0.002712 | 0.009055 | 0.00204 | 0.22528 | -0.43915 | 1.901543 | 1.163046 | 0.005703 | 0.000126 | 0.002865 |
r4_baseline_no_cf_heldout_s2026070604 | baseline_no_cf | 234 | 33 | 0 | 32 | -0.008205 | 0.028077 | 0.014429 | 0.036283 | 0.037476 | 2.514586 | 0.037902 | 0.001619 | 0.008046 | 0.001464 | 0.18202 | 0.781525 | 2.440704 | 1.007559 | 0.020678 | 0.028883 | -0.009825 |
r4_baseline_no_cf_heldout_s2026070604 | baseline_no_cf | 235 | 35 | 1 | 32 | 0.02335 | 0.057838 | 0.01358 | 0.034488 | 0.035621 | 2.53969 | 0.051489 | 0.017001 | 0.006432 | 0.019252 | 2.992972 | 0.705279 | 1.959724 | 1.345416 | 0.010147 | -0.013203 | 0.006349 |
r4_baseline_no_cf_heldout_s2026070604 | baseline_no_cf | 236 | 36 | 1 | 32 | 0.010931 | 0.022396 | 0.00251 | 0.011465 | 0.011975 | 4.567676 | 0.012337 | 0.000872 | 0.001336 | 0.002804 | 2.098247 | 0.285924 | 1.516635 | 3.452151 | 0.033196 | 0.022265 | 0.010059 |
r4_baseline_no_cf_heldout_s2026070604 | baseline_no_cf | 237 | 37 | 0 | 32 | 0.006361 | 0.011559 | 0.002387 | 0.005197 | 0.005377 | 2.177361 | 0.009024 | 0.003826 | 0.001237 | 0.001677 | 1.355561 | 0.389296 | 1.518789 | 1.089501 | 0.007042 | 0.00068 | 0.002535 |
r4_baseline_no_cf_heldout_s2026070604 | baseline_no_cf | 238 | 38 | 1 | 32 | 0.02149 | 0.042098 | 0.006975 | 0.020608 | 0.022274 | 2.954378 | 0.033842 | 0.013234 | 0.011428 | 0.004261 | 0.37286 | 0.479839 | 1.801333 | 1.240943 | 0.004471 | -0.01702 | 0.008256 |
r4_baseline_no_cf_heldout_s2026070604 | baseline_no_cf | 239 | 39 | 0 | 32 | 0.001627 | 0.014982 | 0.003386 | 0.013356 | 0.013733 | 3.94431 | 0.014925 | 0.00157 | 0.001294 | 0.002304 | 1.78041 | 0.656891 | 1.907554 | 1.732045 | -0.002318 | -0.003944 | 0.000057 |
r4_baseline_no_cf_heldout_s2026070604 | baseline_no_cf | 240 | 40 | 1 | 32 | 0.002912 | 0.022877 | 0.008208 | 0.019965 | 0.021103 | 2.432462 | 0.023608 | 0.003642 | 0.005502 | 0.011915 | 2.165731 | 0.708578 | 1.858915 | 1.025603 | -0.00185 | -0.004762 | -0.00073 |
r4_baseline_no_cf_heldout_s2026070604 | baseline_no_cf | 241 | 41 | 1 | 32 | 0.025554 | 0.054327 | 0.010665 | 0.028773 | 0.030059 | 2.697853 | 0.047774 | 0.019002 | 0.008479 | 0.002199 | 0.259403 | 0.18585 | 1.620546 | 1.105782 | 0.005935 | -0.01962 | 0.006553 |
r4_baseline_no_cf_heldout_s2026070604 | baseline_no_cf | 242 | 42 | 0 | 32 | 0.005258 | 0.010262 | 0.002514 | 0.005004 | 0.004473 | 1.990607 | 0.00773 | 0.002726 | 0.001571 | 0.002585 | 1.645088 | 0.415323 | 1.458376 | 0.987963 | 0.000233 | -0.005026 | 0.002532 |
r4_baseline_no_cf_heldout_s2026070604 | baseline_no_cf | 243 | 43 | 0 | 32 | 0.009671 | 0.016718 | 0.003157 | 0.007047 | 0.006845 | 2.232483 | 0.010868 | 0.003821 | 0.00203 | 0.000272 | 0.134105 | -0.044355 | 1.722705 | 0.843806 | 0.004989 | -0.004682 | 0.00585 |
r4_baseline_no_cf_heldout_s2026070604 | baseline_no_cf | 244 | 44 | 0 | 32 | 0.031469 | 0.058426 | 0.013638 | 0.026956 | 0.027407 | 1.976598 | 0.048749 | 0.021793 | 0.020333 | 0.043834 | 2.1558 | 0.553519 | 1.970075 | 1.31932 | 0.002866 | -0.028603 | 0.009676 |
r4_baseline_no_cf_heldout_s2026070604 | baseline_no_cf | 245 | 45 | 1 | 32 | -0.000177 | 0.015908 | 0.005127 | 0.016086 | 0.017192 | 3.137681 | 0.002848 | -0.013238 | 0.012733 | 0.001114 | 0.087486 | 0.058284 | 2.241982 | 1.529694 | 0.011431 | 0.011609 | 0.013061 |
r4_baseline_no_cf_heldout_s2026070604 | baseline_no_cf | 246 | 46 | 0 | 32 | 0.011251 | 0.019645 | 0.003288 | 0.008394 | 0.008616 | 2.553023 | 0.016724 | 0.00833 | 0.001133 | 0.001892 | 1.669962 | 0.819282 | 2.244223 | 0.857557 | 0.007317 | -0.003934 | 0.002921 |
r4_baseline_no_cf_heldout_s2026070604 | baseline_no_cf | 247 | 47 | 1 | 32 | 0.041866 | 0.149152 | 0.042362 | 0.107286 | 0.115237 | 2.532597 | 0.137924 | 0.030639 | 0.007307 | 0.018576 | 2.542282 | 0.902859 | 2.586978 | 1.211483 | -0.010163 | -0.052029 | 0.011227 |
r4_baseline_no_cf_heldout_s2026070604 | baseline_no_cf | 248 | 48 | 0 | 32 | 0.002072 | 0.005032 | 0.002005 | 0.002961 | 0.002761 | 1.476924 | 0.005533 | 0.002572 | 0.004586 | 0.000646 | 0.140975 | -0.715543 | 2.041598 | 0.802227 | -0.0008 | -0.002872 | -0.000501 |
r4_baseline_no_cf_heldout_s2026070604 | baseline_no_cf | 249 | 49 | 1 | 32 | 0.000604 | 0.012992 | 0.005417 | 0.012388 | 0.013614 | 2.287095 | 0.020906 | 0.008518 | 0.002577 | 0.001205 | 0.467597 | 0.259531 | 1.875313 | 0.840128 | 0.001262 | 0.000658 | -0.007914 |
r1_heldout_fixedinit_c100k | baseline_no_cf | 0 | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 0.009472 |
r1_heldout_fixedinit_c100k | baseline_no_cf | 3 | 1 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | -0.009464 |
r1_heldout_fixedinit_c100k | baseline_no_cf | 5 | 2 | 1 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 0.0036 |
r1_heldout_fixedinit_c100k | baseline_no_cf | 6 | 3 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 0.002682 |
r1_heldout_fixedinit_c100k | baseline_no_cf | 9 | 4 | 1 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 0.002014 |
r1_heldout_fixedinit_c100k | baseline_no_cf | 10 | 5 | 1 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 0.01632 |
r1_heldout_fixedinit_c100k | baseline_no_cf | 13 | 6 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 0.008392 |
r1_heldout_fixedinit_c100k | baseline_no_cf | 15 | 7 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | -0.001319 |
r1_heldout_fixedinit_c100k | baseline_no_cf | 16 | 8 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 0.002188 |
r1_heldout_fixedinit_c100k | baseline_no_cf | 18 | 9 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 0.003922 |
r1_heldout_fixedinit_c100k | baseline_no_cf | 21 | 10 | 1 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 0.008397 |
r1_heldout_fixedinit_c100k | baseline_no_cf | 23 | 11 | 1 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 0.009097 |
r1_heldout_fixedinit_c100k | baseline_no_cf | 24 | 12 | 1 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 0.002248 |
r1_heldout_fixedinit_c100k | baseline_no_cf | 27 | 13 | 1 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 0.006257 |
r1_heldout_fixedinit_c100k | baseline_no_cf | 28 | 14 | 1 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 0.001418 |
r1_heldout_fixedinit_c100k | baseline_no_cf | 30 | 15 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 0.041078 |
r1_heldout_fixedinit_c100k | baseline_no_cf | 33 | 16 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 0.009299 |
r1_heldout_fixedinit_c100k | baseline_no_cf | 35 | 17 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 0.011384 |
r1_heldout_fixedinit_c100k | baseline_no_cf | 36 | 18 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 0.005222 |
r1_heldout_fixedinit_c100k | baseline_no_cf | 38 | 19 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 0.013939 |
r1_heldout_fixedinit_c100k | baseline_no_cf | 40 | 20 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 0.006442 |
r1_heldout_fixedinit_c100k | baseline_no_cf | 42 | 21 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 0.007064 |
r1_heldout_fixedinit_c100k | baseline_no_cf | 45 | 22 | 1 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | -0.007163 |
r1_heldout_fixedinit_c100k | baseline_no_cf | 46 | 23 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 0.003407 |
r1_heldout_fixedinit_c100k | baseline_no_cf | 49 | 24 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | -0.004128 |
r1_heldout_fixedinit_c100k | baseline_no_cf | 51 | 25 | 1 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 0.004172 |
r1_heldout_fixedinit_c100k | baseline_no_cf | 53 | 26 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 0.013319 |
r1_heldout_fixedinit_c100k | baseline_no_cf | 55 | 27 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | -0.002347 |
r1_heldout_fixedinit_c100k | baseline_no_cf | 56 | 28 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 0.000017 |
r1_heldout_fixedinit_c100k | baseline_no_cf | 58 | 29 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 0.012468 |
r1_heldout_fixedinit_c100k | baseline_no_cf | 61 | 30 | 1 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 0.002553 |
r1_heldout_fixedinit_c100k | baseline_no_cf | 63 | 31 | 1 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 0.005382 |
r1_heldout_fixedinit_c100k | baseline_no_cf | 65 | 32 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 0.001548 |
r1_heldout_fixedinit_c100k | baseline_no_cf | 67 | 33 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 0.00476 |
r1_heldout_fixedinit_c100k | baseline_no_cf | 69 | 34 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 0.038539 |
r1_heldout_fixedinit_c100k | baseline_no_cf | 70 | 35 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 0.02839 |
r1_heldout_fixedinit_c100k | baseline_no_cf | 72 | 36 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | -0.003338 |
r1_heldout_fixedinit_c100k | baseline_no_cf | 75 | 37 | 1 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | -0.000114 |
r1_heldout_fixedinit_c100k | baseline_no_cf | 77 | 38 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 0.005258 |
r1_heldout_fixedinit_c100k | baseline_no_cf | 79 | 39 | 1 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 0.198653 |
r1_heldout_fixedinit_c100k | baseline_no_cf | 81 | 40 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 0.007348 |
r1_heldout_fixedinit_c100k | baseline_no_cf | 82 | 41 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 0.004599 |
r1_heldout_fixedinit_c100k | baseline_no_cf | 85 | 42 | 1 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 0.011079 |
r1_heldout_fixedinit_c100k | baseline_no_cf | 87 | 43 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 0.007379 |
r1_heldout_fixedinit_c100k | baseline_no_cf | 89 | 44 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 0.003795 |
r1_heldout_fixedinit_c100k | baseline_no_cf | 90 | 45 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 0.002099 |
r1_heldout_fixedinit_c100k | baseline_no_cf | 93 | 46 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 0.002262 |
r1_heldout_fixedinit_c100k | baseline_no_cf | 94 | 47 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 0.005754 |
r1_heldout_fixedinit_c100k | baseline_no_cf | 97 | 48 | 1 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 0.004871 |
r1_heldout_fixedinit_c100k | baseline_no_cf | 99 | 49 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 0.005426 |
End of preview.
Mulligan paper evidence
The frozen inputs behind the figures and appendix tables of the Mulligan paper
(mulligan.page) that are not in the released datasets themselves: evaluation
summaries and headline tables, collection ledgers, value-learning studies, simulation critic
studies and the reset-range photo composites. The Mulligan code reads
them through paper/appendix/artifacts.py, which checks every file against the sha256 and size
locked in the code repository (paper/appendix/*/inputs.json); manifest.json lists the sha256
and size of every file here.
| Path | Contents |
|---|---|
real/results/{marker,square,routing}/ |
real-robot evaluation outcomes, summaries and headline tables |
real/collection/ |
collection ledgers, split episodes, collection success |
real/training/, real/value_learning/ |
training-run records and offline value-learning studies |
sim/{critic,results,collection,sampling,efficiency}/ |
simulation studies |
assets/ |
restored illustration exports and the reset-range composites |
fixtures/rlpd_sac_parity.npz |
reference outputs for the RLPD agent parity test |
Models and datasets are named by their release ids (mulligan/<repo>, mulligan/<repo>/<seed>);
runs and recordings that were not released are unreleased/.... Use the release-1 tag or its
commit for reproducible reads.
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