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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 8 new columns ({'det_zone_rate', 'robust_zone_lo', 'stoch_crash_rate', 'mean', 'stoch_zone_rate', 'rank', 'worst_p1', 'det_crash_rate'}) and 10 missing columns ({'y', 'seed', 'td_speed', 'steps', 'in_zone', 'timeout', 'reward', 'x', 'mode', 'landed'}).
This happened while the csv dataset builder was generating data using
hf://datasets/privateboss/Continuous_MarsLander_NoWind_NoTurbulence/marsLander_v2/robust_eval/ranking_final.csv (at revision 2b1e481a7ac736b42d0717de972c9756250c8274), ['hf://datasets/privateboss/Continuous_MarsLander_NoWind_NoTurbulence@2b1e481a7ac736b42d0717de972c9756250c8274/marsLander_v2/robust_eval/episodes_final.csv', 'hf://datasets/privateboss/Continuous_MarsLander_NoWind_NoTurbulence@2b1e481a7ac736b42d0717de972c9756250c8274/marsLander_v2/robust_eval/episodes_screen.csv', 'hf://datasets/privateboss/Continuous_MarsLander_NoWind_NoTurbulence@2b1e481a7ac736b42d0717de972c9756250c8274/marsLander_v2/robust_eval/ranking_final.csv', 'hf://datasets/privateboss/Continuous_MarsLander_NoWind_NoTurbulence@2b1e481a7ac736b42d0717de972c9756250c8274/marsLander_v2/robust_eval/ranking_screen.csv', 'hf://datasets/privateboss/Continuous_MarsLander_NoWind_NoTurbulence@2b1e481a7ac736b42d0717de972c9756250c8274/marsLander_v2/robust_eval/summary_final.csv', 'hf://datasets/privateboss/Continuous_MarsLander_NoWind_NoTurbulence@2b1e481a7ac736b42d0717de972c9756250c8274/marsLander_v2/robust_eval/summary_screen.csv', 'hf://datasets/privateboss/Continuous_MarsLander_NoWind_NoTurbulence@2b1e481a7ac736b42d0717de972c9756250c8274/marsLander_v2/robust_eval/worst_final.csv', 'hf://datasets/privateboss/Continuous_MarsLander_NoWind_NoTurbulence@2b1e481a7ac736b42d0717de972c9756250c8274/marsLander_v2/robust_eval/worst_screen.csv', 'hf://datasets/privateboss/Continuous_MarsLander_NoWind_NoTurbulence@2b1e481a7ac736b42d0717de972c9756250c8274/marsLander_v2/robust_eval_confirm/episodes_screen.csv', 'hf://datasets/privateboss/Continuous_MarsLander_NoWind_NoTurbulence@2b1e481a7ac736b42d0717de972c9756250c8274/marsLander_v2/robust_eval_confirm/ranking_screen.csv', 'hf://datasets/privateboss/Continuous_MarsLander_NoWind_NoTurbulence@2b1e481a7ac736b42d0717de972c9756250c8274/marsLander_v2/robust_eval_confirm/summary_screen.csv', 'hf://datasets/privateboss/Continuous_MarsLander_NoWind_NoTurbulence@2b1e481a7ac736b42d0717de972c9756250c8274/marsLander_v2/robust_eval_confirm/worst_screen.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
rank: int64
era: string
robust_zone_lo: double
det_zone_rate: double
stoch_zone_rate: double
det_crash_rate: double
stoch_crash_rate: double
mean: double
worst_p1: double
-- schema metadata --
pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 1363
to
{'era': Value('string'), 'mode': Value('string'), 'seed': Value('int64'), 'reward': Value('float64'), 'landed': Value('bool'), 'in_zone': Value('bool'), 'x': Value('float64'), 'y': Value('float64'), 'td_speed': Value('float64'), 'steps': Value('int64'), 'timeout': Value('bool')}
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 8 new columns ({'det_zone_rate', 'robust_zone_lo', 'stoch_crash_rate', 'mean', 'stoch_zone_rate', 'rank', 'worst_p1', 'det_crash_rate'}) and 10 missing columns ({'y', 'seed', 'td_speed', 'steps', 'in_zone', 'timeout', 'reward', 'x', 'mode', 'landed'}).
This happened while the csv dataset builder was generating data using
hf://datasets/privateboss/Continuous_MarsLander_NoWind_NoTurbulence/marsLander_v2/robust_eval/ranking_final.csv (at revision 2b1e481a7ac736b42d0717de972c9756250c8274), ['hf://datasets/privateboss/Continuous_MarsLander_NoWind_NoTurbulence@2b1e481a7ac736b42d0717de972c9756250c8274/marsLander_v2/robust_eval/episodes_final.csv', 'hf://datasets/privateboss/Continuous_MarsLander_NoWind_NoTurbulence@2b1e481a7ac736b42d0717de972c9756250c8274/marsLander_v2/robust_eval/episodes_screen.csv', 'hf://datasets/privateboss/Continuous_MarsLander_NoWind_NoTurbulence@2b1e481a7ac736b42d0717de972c9756250c8274/marsLander_v2/robust_eval/ranking_final.csv', 'hf://datasets/privateboss/Continuous_MarsLander_NoWind_NoTurbulence@2b1e481a7ac736b42d0717de972c9756250c8274/marsLander_v2/robust_eval/ranking_screen.csv', 'hf://datasets/privateboss/Continuous_MarsLander_NoWind_NoTurbulence@2b1e481a7ac736b42d0717de972c9756250c8274/marsLander_v2/robust_eval/summary_final.csv', 'hf://datasets/privateboss/Continuous_MarsLander_NoWind_NoTurbulence@2b1e481a7ac736b42d0717de972c9756250c8274/marsLander_v2/robust_eval/summary_screen.csv', 'hf://datasets/privateboss/Continuous_MarsLander_NoWind_NoTurbulence@2b1e481a7ac736b42d0717de972c9756250c8274/marsLander_v2/robust_eval/worst_final.csv', 'hf://datasets/privateboss/Continuous_MarsLander_NoWind_NoTurbulence@2b1e481a7ac736b42d0717de972c9756250c8274/marsLander_v2/robust_eval/worst_screen.csv', 'hf://datasets/privateboss/Continuous_MarsLander_NoWind_NoTurbulence@2b1e481a7ac736b42d0717de972c9756250c8274/marsLander_v2/robust_eval_confirm/episodes_screen.csv', 'hf://datasets/privateboss/Continuous_MarsLander_NoWind_NoTurbulence@2b1e481a7ac736b42d0717de972c9756250c8274/marsLander_v2/robust_eval_confirm/ranking_screen.csv', 'hf://datasets/privateboss/Continuous_MarsLander_NoWind_NoTurbulence@2b1e481a7ac736b42d0717de972c9756250c8274/marsLander_v2/robust_eval_confirm/summary_screen.csv', 'hf://datasets/privateboss/Continuous_MarsLander_NoWind_NoTurbulence@2b1e481a7ac736b42d0717de972c9756250c8274/marsLander_v2/robust_eval_confirm/worst_screen.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.
era string | mode string | seed int64 | reward float64 | landed bool | in_zone bool | x float64 | y float64 | td_speed float64 | steps int64 | timeout bool |
|---|---|---|---|---|---|---|---|---|---|---|
era_iter_1900 | det | 10,100,218 | 269.318655 | true | true | -0.043994 | -0.000924 | 0.239492 | 287 | false |
era_iter_1900 | stoch | 10,100,218 | 268.626475 | true | true | -0.047648 | -0.00022 | 0.24095 | 288 | false |
era_iter_1300 | det | 10,100,219 | 282.873507 | true | true | -0.058715 | -0.000941 | 0.396784 | 180 | false |
era_iter_1300 | stoch | 10,100,219 | 284.381164 | true | true | -0.041224 | -0.001133 | 0.414204 | 193 | false |
era_iter_2200 | det | 10,100,219 | 284.129684 | true | true | -0.041129 | -0.000462 | 0.333141 | 190 | false |
era_iter_2200 | stoch | 10,100,219 | 284.541638 | true | true | -0.037341 | -0.001017 | 0.380063 | 184 | false |
era_iter_1900 | det | 10,100,219 | 284.680227 | true | true | -0.034611 | -0.000603 | 0.329412 | 188 | false |
era_iter_1900 | stoch | 10,100,219 | 285.192278 | true | true | -0.029771 | -0.000555 | 0.378483 | 186 | false |
era_iter_1300 | det | 10,100,220 | 284.680753 | true | true | 0.043624 | 0.000036 | 0.215764 | 177 | false |
era_iter_1300 | stoch | 10,100,220 | 284.888501 | true | true | 0.029876 | -0.000904 | 0.201946 | 176 | false |
era_iter_2200 | det | 10,100,220 | 283.993271 | true | true | 0.064038 | -0.00065 | 0.298405 | 178 | false |
era_iter_2200 | stoch | 10,100,220 | 285.360891 | true | true | 0.049179 | -0.000824 | 0.281444 | 179 | false |
era_iter_1900 | det | 10,100,220 | 283.535971 | true | true | 0.063621 | -0.000958 | 0.220297 | 174 | false |
era_iter_1900 | stoch | 10,100,220 | 284.476803 | true | true | 0.049367 | -0.001179 | 0.263684 | 180 | false |
era_iter_1300 | det | 10,100,221 | 289.717991 | true | true | -0.010948 | -0.000149 | 0.314131 | 234 | false |
era_iter_1300 | stoch | 10,100,221 | 289.478863 | true | true | -0.015339 | -0.000618 | 0.305118 | 232 | false |
era_iter_2200 | det | 10,100,221 | 286.048194 | true | true | -0.060949 | -0.000522 | 0.336097 | 210 | false |
era_iter_2200 | stoch | 10,100,221 | 275.479632 | true | true | -0.066206 | -0.00032 | 0.329496 | 206 | false |
era_iter_1900 | det | 10,100,221 | 287.939209 | true | true | -0.04102 | -0.000449 | 0.326026 | 220 | false |
era_iter_1900 | stoch | 10,100,221 | 288.203021 | true | true | -0.037858 | 0.000225 | 0.315867 | 224 | false |
era_iter_1300 | det | 10,100,222 | 273.90281 | true | true | -0.018746 | -0.000765 | 0.300828 | 305 | false |
era_iter_1300 | stoch | 10,100,222 | 262.447492 | true | true | -0.041567 | -0.000748 | 0.331412 | 291 | false |
era_iter_2200 | det | 10,100,222 | 272.647927 | true | true | -0.04623 | -0.000496 | 0.361808 | 283 | false |
era_iter_2200 | stoch | 10,100,222 | 261.79417 | true | true | -0.060782 | -0.000483 | 0.397031 | 283 | false |
era_iter_1900 | det | 10,100,222 | 274.196903 | true | true | -0.025191 | -0.000652 | 0.346648 | 296 | false |
era_iter_1900 | stoch | 10,100,222 | 261.992139 | true | true | -0.050471 | -0.000872 | 0.373506 | 286 | false |
era_iter_1300 | det | 10,100,223 | 281.234544 | true | true | 0.037018 | -0.001124 | 0.279794 | 172 | false |
era_iter_1300 | stoch | 10,100,223 | 283.110421 | true | true | 0.009839 | -0.000889 | 0.275748 | 173 | false |
era_iter_2200 | det | 10,100,223 | 280.709215 | true | true | 0.042719 | -0.000447 | 0.252686 | 178 | false |
era_iter_2200 | stoch | 10,100,223 | 282.367315 | true | true | 0.028128 | -0.000997 | 0.293605 | 180 | false |
era_iter_1900 | det | 10,100,223 | 279.406419 | true | true | 0.050565 | -0.000938 | 0.272508 | 168 | false |
era_iter_1900 | stoch | 10,100,223 | 282.016961 | true | true | 0.02486 | -0.000717 | 0.243816 | 181 | false |
era_iter_1300 | det | 10,100,144 | 246.919432 | true | true | 0.074682 | -0.000557 | 0.198724 | 211 | false |
era_iter_1300 | stoch | 10,100,144 | 246.650148 | true | true | 0.049924 | -0.000637 | 0.182286 | 212 | false |
era_iter_2200 | det | 10,100,144 | 247.283119 | true | true | 0.0817 | -0.000655 | 0.272668 | 206 | false |
era_iter_2200 | stoch | 10,100,144 | 246.99657 | true | true | 0.07072 | 0.000207 | 0.224926 | 209 | false |
era_iter_1900 | det | 10,100,144 | 246.326779 | true | true | 0.07884 | 0.00077 | 0.253184 | 210 | false |
era_iter_1900 | stoch | 10,100,144 | 247.958962 | true | true | 0.062772 | -0.0008 | 0.21432 | 220 | false |
era_iter_1300 | det | 10,100,145 | 282.058336 | true | true | 0.092175 | -0.000973 | 0.308161 | 313 | false |
era_iter_1300 | stoch | 10,100,145 | 295.596948 | true | true | 0.058043 | -0.000802 | 0.255257 | 309 | false |
era_iter_2200 | det | 10,100,145 | 299.423819 | true | true | -0.004462 | -0.001002 | 0.234702 | 323 | false |
era_iter_2200 | stoch | 10,100,145 | 298.829282 | true | true | -0.011135 | -0.000074 | 0.204401 | 324 | false |
era_iter_1900 | det | 10,100,145 | 292.63796 | true | true | 0.03889 | -0.000624 | 0.14211 | 325 | false |
era_iter_1900 | stoch | 10,100,145 | 294.232031 | true | true | 0.038752 | -0.000496 | 0.22475 | 319 | false |
era_iter_1300 | det | 10,100,146 | 244.735996 | true | true | -0.053906 | -0.000444 | 0.266642 | 191 | false |
era_iter_1300 | stoch | 10,100,146 | 247.013684 | true | true | -0.034432 | -0.000447 | 0.282521 | 204 | false |
era_iter_2200 | det | 10,100,146 | 246.070735 | true | true | -0.057354 | -0.000469 | 0.324346 | 196 | false |
era_iter_2200 | stoch | 10,100,146 | 246.79311 | true | true | -0.047797 | -0.000858 | 0.324366 | 208 | false |
era_iter_1900 | det | 10,100,146 | 245.927771 | true | true | -0.057172 | -0.000961 | 0.315625 | 196 | false |
era_iter_1900 | stoch | 10,100,146 | 247.559828 | true | true | -0.041073 | -0.001201 | 0.280542 | 196 | false |
era_iter_1300 | det | 10,100,147 | 282.942469 | true | true | -0.004795 | -0.000312 | 0.347382 | 226 | false |
era_iter_1300 | stoch | 10,100,147 | 282.667962 | true | true | -0.005752 | -0.000597 | 0.335248 | 225 | false |
era_iter_2200 | det | 10,100,147 | 280.210412 | true | true | -0.037871 | -0.000766 | 0.320183 | 204 | false |
era_iter_2200 | stoch | 10,100,147 | 279.817085 | true | true | -0.040616 | 0.000175 | 0.343356 | 200 | false |
era_iter_1900 | det | 10,100,147 | 281.255213 | true | true | -0.019814 | 0.000118 | 0.347984 | 214 | false |
era_iter_1900 | stoch | 10,100,147 | 280.543141 | true | true | -0.032286 | -0.000628 | 0.339625 | 203 | false |
era_iter_1300 | det | 10,100,148 | 269.630871 | true | true | 0.031085 | -0.00018 | 0.257647 | 173 | false |
era_iter_1300 | stoch | 10,100,148 | 270.686481 | true | true | 0.031911 | -0.000215 | 0.287763 | 181 | false |
era_iter_2200 | det | 10,100,148 | 269.974082 | true | true | 0.031072 | -0.000911 | 0.261399 | 170 | false |
era_iter_2200 | stoch | 10,100,148 | 269.864871 | true | true | 0.030292 | -0.000605 | 0.266664 | 183 | false |
era_iter_1900 | det | 10,100,148 | 269.676639 | true | true | 0.03134 | -0.000589 | 0.251624 | 170 | false |
era_iter_1900 | stoch | 10,100,148 | 269.466302 | true | true | 0.031443 | -0.000614 | 0.258073 | 181 | false |
era_iter_1300 | det | 10,100,149 | 272.654356 | true | true | 0.033548 | -0.001262 | 0.338807 | 257 | false |
era_iter_1300 | stoch | 10,100,149 | 273.293609 | true | true | 0.019856 | -0.001101 | 0.273487 | 250 | false |
era_iter_1900 | det | 10,100,234 | 305.506685 | true | true | 0.019241 | -0.000847 | 0.553933 | 286 | false |
era_iter_1900 | stoch | 10,100,234 | 304.790675 | true | true | 0.032122 | -0.000868 | 0.504558 | 288 | false |
era_iter_1300 | det | 10,100,235 | 266.308421 | true | true | -0.060794 | 0.000123 | 0.298439 | 292 | false |
era_iter_1300 | stoch | 10,100,235 | 265.366335 | true | true | -0.06835 | -0.000891 | 0.311043 | 323 | false |
era_iter_2200 | det | 10,100,235 | 266.824475 | true | true | -0.070568 | -0.000969 | 0.308793 | 274 | false |
era_iter_2200 | stoch | 10,100,235 | 267.568727 | true | true | -0.071988 | -0.000718 | 0.313745 | 282 | false |
era_iter_1900 | det | 10,100,235 | 267.02017 | true | true | -0.066844 | -0.000295 | 0.297364 | 279 | false |
era_iter_1900 | stoch | 10,100,235 | 265.969967 | true | true | -0.078692 | -0.000892 | 0.323978 | 281 | false |
era_iter_1300 | det | 10,100,236 | 271.730191 | true | true | -0.040697 | -0.001003 | 0.233494 | 314 | false |
era_iter_1300 | stoch | 10,100,236 | 268.563573 | true | true | -0.07362 | 0.000275 | 0.235636 | 304 | false |
era_iter_2200 | det | 10,100,236 | 274.398941 | true | true | -0.040913 | -0.000448 | 0.279653 | 298 | false |
era_iter_2200 | stoch | 10,100,236 | 272.299366 | true | true | -0.060902 | -0.00056 | 0.27299 | 298 | false |
era_iter_1900 | det | 10,100,236 | 270.97863 | true | true | -0.0617 | -0.000102 | 0.278293 | 293 | false |
era_iter_1900 | stoch | 10,100,236 | 270.369618 | true | true | -0.069427 | -0.00075 | 0.251212 | 293 | false |
era_iter_1300 | det | 10,100,237 | 290.082843 | true | true | -0.010285 | -0.000509 | 0.30157 | 248 | false |
era_iter_1300 | stoch | 10,100,237 | 288.263618 | true | true | -0.019887 | -0.000356 | 0.358378 | 258 | false |
era_iter_2200 | det | 10,100,237 | 289.599933 | true | true | -0.023607 | -0.000775 | 0.317209 | 262 | false |
era_iter_2200 | stoch | 10,100,237 | 290.232559 | true | true | -0.018889 | -0.000207 | 0.365325 | 262 | false |
era_iter_1900 | det | 10,100,237 | 288.482087 | true | true | -0.027192 | -0.000746 | 0.374727 | 263 | false |
era_iter_1900 | stoch | 10,100,237 | 288.919106 | true | true | -0.023957 | -0.000536 | 0.377514 | 265 | false |
era_iter_1300 | det | 10,100,238 | 283.350897 | true | true | 0.015615 | -0.000644 | 0.325067 | 331 | false |
era_iter_1300 | stoch | 10,100,238 | 282.886091 | true | true | 0.021659 | -0.000509 | 0.30125 | 324 | false |
era_iter_2200 | det | 10,100,238 | 283.74961 | true | true | 0.024073 | -0.000746 | 0.365235 | 335 | false |
era_iter_2200 | stoch | 10,100,238 | 281.978678 | true | true | 0.036061 | -0.000332 | 0.391681 | 323 | false |
era_iter_1900 | det | 10,100,238 | 283.421537 | true | true | 0.025314 | -0.000611 | 0.343433 | 340 | false |
era_iter_1900 | stoch | 10,100,238 | 282.515664 | true | true | 0.035867 | -0.000289 | 0.356748 | 327 | false |
era_iter_1300 | det | 10,100,239 | 260.763461 | true | true | 0.016066 | -0.001044 | 0.277471 | 216 | false |
era_iter_1300 | stoch | 10,100,239 | 260.211665 | true | true | 0.012858 | -0.000425 | 0.282963 | 214 | false |
era_iter_2200 | det | 10,100,239 | 261.921129 | true | true | 0.019135 | -0.000775 | 0.28086 | 227 | false |
era_iter_2200 | stoch | 10,100,239 | 261.708949 | true | true | 0.021272 | -0.000008 | 0.310988 | 222 | false |
era_iter_1900 | det | 10,100,239 | 260.761861 | true | true | 0.028827 | -0.001198 | 0.296742 | 219 | false |
era_iter_1900 | stoch | 10,100,239 | 261.699101 | true | true | 0.020902 | -0.000952 | 0.281256 | 222 | false |
era_iter_1900 | det | 10,100,026 | 265.358604 | true | true | -0.196721 | -0.028563 | 0.250741 | 245 | false |
era_iter_1900 | stoch | 10,100,026 | 41.233333 | false | false | -0.221881 | -0.049544 | 0.437749 | 134 | false |
era_iter_1300 | det | 10,100,027 | 270.234055 | true | true | 0.035363 | -0.001214 | 0.27199 | 217 | false |
era_iter_1300 | stoch | 10,100,027 | 269.60177 | true | true | 0.045003 | -0.00086 | 0.26866 | 215 | false |
End of preview.
-Continuous Mars Lander with gravity utilizing PPO (Proximal Policy Optimization) with a total timestep of 21299200.
-The evaluate_robust.py does a large sample test for the agents to determine robustness and safety across the two available modes which are deterministic and stochastic.
-All the 26 eras where tested in two phases. The first phase completed 156000 episode tests across 26 eras with two modes for each era which equals 6k episodes per era or -3k episodes per era mode (deterministic- which evaluates the policy itself OR stochastic- which includes exploration noise)
-The second Phase takes the best 3 eras and evaluates them across 20000 episodes each to determine final robustness or safety ranking depending on what is more important.
The trade-off
-Deterministic Safety: pick it if the policy runs strictly without noise and avoiding crashes is the main goal.
-Robustness pick it as the general default, since it has the best reward, the smallest drop under noise, and the cleanest worst cases.
-I walk through fire. I slept in the cold.I buried the weak. I hardened my soul. No hand reached down. No God pulled me through. I bled in the dark, became something new. -Hear that silence. That's the sound of the end. No banners left. No bloodline to defended. The Throne was empty. I sat down. No voice above me. No king, no crown. -Built from the ashes, forged in the pain, I didn't inherit. I took the reign. The throne was empty, Now it's mine. Crowned from the dark, baptized in fire. -No hand chose me, no faith, no sign. I rose alone. Now I define.
-They prayed for mercy. I pray for strength. They begged for life. I embrace the length of every scar.Every wound I kept. That's the price of the throne that they never could steal. -No crown,No king, no chosen line, no fate, no end.This will is mine. If the world leaves nothing, then I become everything.
-The throne was empty. I took my place. No fear behind me. No past to chase. Built from the ashes, I wear the flame. No one alive can take my name. -The throne was empty. Now it's sealed. Forged in the wounds that never heal. No hand chose me. No fate, no sign.I rose alone. And now I reign.
#TheThroneWasEmpty
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