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privateboss
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Continuous_MarsLander_Gusty_Wind

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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', 'worst_p1', 'stoch_zone_rate', 'robust_zone_lo', 'stoch_crash_rate', 'det_crash_rate', 'rank', 'mean'}) and 10 missing columns ({'landed', 'timeout', 'td_speed', 'in_zone', 'reward', 'mode', 'y', 'x', 'steps', 'seed'}).

This happened while the csv dataset builder was generating data using

hf://datasets/privateboss/Continuous_MarsLander_Gusty_Wind/marsLander_GustyMars_v2/robust_eval/ranking_final.csv (at revision 84b9589f59e88f0151b66c79b8ed981c88c8dbda), ['hf://datasets/privateboss/Continuous_MarsLander_Gusty_Wind@84b9589f59e88f0151b66c79b8ed981c88c8dbda/marsLander_GustyMars_v2/robust_eval/episodes_final.csv', 'hf://datasets/privateboss/Continuous_MarsLander_Gusty_Wind@84b9589f59e88f0151b66c79b8ed981c88c8dbda/marsLander_GustyMars_v2/robust_eval/episodes_screen.csv', 'hf://datasets/privateboss/Continuous_MarsLander_Gusty_Wind@84b9589f59e88f0151b66c79b8ed981c88c8dbda/marsLander_GustyMars_v2/robust_eval/ranking_final.csv', 'hf://datasets/privateboss/Continuous_MarsLander_Gusty_Wind@84b9589f59e88f0151b66c79b8ed981c88c8dbda/marsLander_GustyMars_v2/robust_eval/ranking_screen.csv', 'hf://datasets/privateboss/Continuous_MarsLander_Gusty_Wind@84b9589f59e88f0151b66c79b8ed981c88c8dbda/marsLander_GustyMars_v2/robust_eval/summary_final.csv', 'hf://datasets/privateboss/Continuous_MarsLander_Gusty_Wind@84b9589f59e88f0151b66c79b8ed981c88c8dbda/marsLander_GustyMars_v2/robust_eval/summary_screen.csv', 'hf://datasets/privateboss/Continuous_MarsLander_Gusty_Wind@84b9589f59e88f0151b66c79b8ed981c88c8dbda/marsLander_GustyMars_v2/robust_eval/worst_final.csv', 'hf://datasets/privateboss/Continuous_MarsLander_Gusty_Wind@84b9589f59e88f0151b66c79b8ed981c88c8dbda/marsLander_GustyMars_v2/robust_eval/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 1856, in _prepare_split_single
                  writer.write_table(table)
                  ~~~~~~~~~~~~~~~~~~^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 811, 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 822, in _write_table
                  pa_table = table_cast(pa_table, self._schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2381, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2309, 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 1379, 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 956, 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 1702, 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 1858, 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', 'worst_p1', 'stoch_zone_rate', 'robust_zone_lo', 'stoch_crash_rate', 'det_crash_rate', 'rank', 'mean'}) and 10 missing columns ({'landed', 'timeout', 'td_speed', 'in_zone', 'reward', 'mode', 'y', 'x', 'steps', 'seed'}).
              
              This happened while the csv dataset builder was generating data using
              
              hf://datasets/privateboss/Continuous_MarsLander_Gusty_Wind/marsLander_GustyMars_v2/robust_eval/ranking_final.csv (at revision 84b9589f59e88f0151b66c79b8ed981c88c8dbda), ['hf://datasets/privateboss/Continuous_MarsLander_Gusty_Wind@84b9589f59e88f0151b66c79b8ed981c88c8dbda/marsLander_GustyMars_v2/robust_eval/episodes_final.csv', 'hf://datasets/privateboss/Continuous_MarsLander_Gusty_Wind@84b9589f59e88f0151b66c79b8ed981c88c8dbda/marsLander_GustyMars_v2/robust_eval/episodes_screen.csv', 'hf://datasets/privateboss/Continuous_MarsLander_Gusty_Wind@84b9589f59e88f0151b66c79b8ed981c88c8dbda/marsLander_GustyMars_v2/robust_eval/ranking_final.csv', 'hf://datasets/privateboss/Continuous_MarsLander_Gusty_Wind@84b9589f59e88f0151b66c79b8ed981c88c8dbda/marsLander_GustyMars_v2/robust_eval/ranking_screen.csv', 'hf://datasets/privateboss/Continuous_MarsLander_Gusty_Wind@84b9589f59e88f0151b66c79b8ed981c88c8dbda/marsLander_GustyMars_v2/robust_eval/summary_final.csv', 'hf://datasets/privateboss/Continuous_MarsLander_Gusty_Wind@84b9589f59e88f0151b66c79b8ed981c88c8dbda/marsLander_GustyMars_v2/robust_eval/summary_screen.csv', 'hf://datasets/privateboss/Continuous_MarsLander_Gusty_Wind@84b9589f59e88f0151b66c79b8ed981c88c8dbda/marsLander_GustyMars_v2/robust_eval/worst_final.csv', 'hf://datasets/privateboss/Continuous_MarsLander_Gusty_Wind@84b9589f59e88f0151b66c79b8ed981c88c8dbda/marsLander_GustyMars_v2/robust_eval/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_7300	det	10,100,149	251.811103	true	true	-0.010929	-0.000925	0.170024	327	false
era_iter_7300	stoch	10,100,149	261.472695	true	true	0.054066	-0.000576	0.317642	292	false
era_iter_7200	det	10,100,149	252.141688	true	true	-0.008487	-0.000743	0.167841	328	false
era_iter_7200	stoch	10,100,149	261.039094	true	true	0.053161	-0.000861	0.346429	292	false
era_iter_7000	det	10,100,150	250.135775	true	true	0.117695	0.000746	0.30742	267	false
era_iter_7000	stoch	10,100,150	254.787399	true	true	0.070297	-0.000573	0.481515	251	false
era_iter_7300	det	10,100,150	251.276572	true	true	0.082752	0.00013	0.305668	280	false
era_iter_7300	stoch	10,100,150	267.477577	true	true	0.018932	-0.001234	0.458403	244	false
era_iter_7200	det	10,100,150	241.927752	true	true	0.094045	-0.00073	0.341668	281	false
era_iter_7200	stoch	10,100,150	267.686741	true	true	0.023854	-0.00084	0.469581	247	false
era_iter_7000	det	10,100,151	214.238315	true	true	0.17639	-0.020406	0.131352	556	false
era_iter_7000	stoch	10,100,151	251.368359	true	true	0.109661	-0.001362	0.01524	238	false
era_iter_7300	det	10,100,151	190.112278	true	false	0.230185	-0.039164	0.130065	559	false
era_iter_7300	stoch	10,100,151	225.25802	true	true	0.14433	-0.010394	0.071707	1,021	false
era_iter_7200	det	10,100,151	203.224034	true	true	0.162667	-0.016342	0.133862	1,069	false
era_iter_7200	stoch	10,100,151	235.149135	true	true	0.148586	-0.011846	0.069843	348	false
era_iter_7000	det	10,100,152	255.851019	true	true	-0.032582	-0.000786	0.208456	337	false
era_iter_7000	stoch	10,100,152	267.001077	true	true	0.033709	-0.000313	0.218319	288	false
era_iter_7300	det	10,100,152	255.690481	true	true	-0.0258	-0.001101	0.187437	340	false
era_iter_7300	stoch	10,100,152	265.313874	true	true	0.057086	-0.000527	0.235005	259	false
era_iter_7200	det	10,100,152	255.316845	true	true	-0.036456	-0.001164	0.209641	342	false
era_iter_7200	stoch	10,100,152	265.301779	true	true	0.052884	-0.000937	0.167301	259	false
era_iter_7000	det	10,100,153	210.223948	true	true	0.124676	-0.002478	0.167299	315	false
era_iter_7000	stoch	10,100,153	225.73177	true	true	0.107812	-0.000824	0.260589	234	false
era_iter_7300	det	10,100,153	211.183401	true	true	0.115842	-0.000834	0.17856	311	false
era_iter_7300	stoch	10,100,153	219.518046	true	true	0.132628	-0.003186	0.267053	253	false
era_iter_7200	det	10,100,153	210.385974	true	true	0.122262	-0.00175	0.158233	310	false
era_iter_7200	stoch	10,100,153	219.644419	true	true	0.136709	-0.004006	0.296514	291	false
era_iter_7000	det	10,100,154	264.945356	true	true	0.014278	0.000522	0.109994	459	false
era_iter_7000	stoch	10,100,154	118.53417	false	false	-0.202914	-0.010194	0.714908	1,200	true
era_iter_7300	det	10,100,154	264.768332	true	true	-0.000083	-0.00059	0.024483	471	false
era_iter_7300	stoch	10,100,154	210.197902	true	false	-0.44744	-0.023722	0.727307	388	false
era_iter_7200	det	10,100,218	252.926137	true	true	0.034026	-0.000805	0.101049	337	false
era_iter_7200	stoch	10,100,218	243.577405	true	true	0.095981	-0.000479	0.425216	317	false
era_iter_7000	det	10,100,219	255.823641	true	true	0.087536	-0.000328	0.175933	280	false
era_iter_7000	stoch	10,100,219	274.036794	true	true	0.105566	0.000279	0.349685	210	false
era_iter_7300	det	10,100,219	242.662032	true	true	0.112828	-0.00049	0.176974	270	false
era_iter_7300	stoch	10,100,219	273.08381	true	true	0.103302	-0.000642	0.331066	210	false
era_iter_7200	det	10,100,219	244.556282	true	true	0.134388	-0.006796	0.155128	597	false
era_iter_7200	stoch	10,100,219	271.75693	true	true	0.109989	-0.000595	0.333891	210	false
era_iter_7000	det	10,100,220	233.837942	true	true	0.172397	0.014416	0.216332	290	false
era_iter_7000	stoch	10,100,220	274.514107	true	true	0.076827	-0.000737	0.182708	190	false
era_iter_7300	det	10,100,220	237.415778	true	true	0.161213	0.011848	0.249626	299	false
era_iter_7300	stoch	10,100,220	271.885237	true	true	0.101105	-0.001017	0.132762	182	false
era_iter_7200	det	10,100,220	223.162586	true	false	0.202952	0.021348	0.207762	327	false
era_iter_7200	stoch	10,100,220	271.978381	true	true	0.098701	-0.000614	0.133672	246	false
era_iter_7000	det	10,100,221	272.544379	true	true	-0.048751	-0.000935	0.127109	245	false
era_iter_7000	stoch	10,100,221	274.140906	true	true	0.071593	-0.00014	0.240084	232	false
era_iter_7300	det	10,100,221	268.191002	true	true	-0.065127	-0.000186	0.128199	264	false
era_iter_7300	stoch	10,100,221	279.783123	true	true	-0.007117	-0.001118	0.130339	222	false
era_iter_7200	det	10,100,221	268.063843	true	true	-0.069961	-0.0009	0.122508	256	false
era_iter_7200	stoch	10,100,221	279.243499	true	true	-0.010466	0.000227	0.161441	230	false
era_iter_7000	det	10,100,222	263.797063	true	true	-0.028095	0.000952	0.299333	317	false
era_iter_7000	stoch	10,100,222	268.821139	true	true	-0.071937	-0.000643	0.163417	264	false
era_iter_7300	det	10,100,222	257.228988	true	true	-0.059068	-0.000376	0.31309	324	false
era_iter_7300	stoch	10,100,222	265.749807	true	true	-0.067531	-0.000538	0.195875	289	false
era_iter_7200	det	10,100,222	245.989073	true	true	-0.055895	0.000235	0.313363	330	false
era_iter_7200	stoch	10,100,222	264.427668	true	true	-0.084246	-0.000774	0.193591	300	false
era_iter_7000	det	10,100,223	243.235731	true	true	0.07421	-0.000632	0.248745	288	false
era_iter_7000	stoch	10,100,223	271.596614	true	true	0.099105	-0.000025	0.328284	202	false
era_iter_7300	det	10,100,223	241.946737	true	true	0.07741	-0.000429	0.263094	300	false
era_iter_7300	stoch	10,100,223	260.281824	true	true	0.109079	-0.000779	0.422933	375	false
era_iter_7200	det	10,100,223	241.035764	true	true	0.095644	-0.001159	0.237642	293	false
era_iter_7200	stoch	10,100,223	257.251134	true	true	0.108411	-0.000737	0.38119	522	false
era_iter_7000	det	10,100,192	273.134826	true	true	0.031277	-0.001106	0.080568	356	false
era_iter_7000	stoch	10,100,192	285.740389	true	true	0.002122	0.000138	0.37065	343	false
era_iter_7300	det	10,100,192	271.188912	true	true	0.044469	-0.000669	0.075939	341	false
era_iter_7300	stoch	10,100,192	283.322795	true	true	0.037854	-0.000568	0.370541	307	false
era_iter_7200	det	10,100,192	273.268627	true	true	0.027034	-0.001065	0.073086	342	false
era_iter_7200	stoch	10,100,192	283.716329	true	true	0.023782	-0.000634	0.358345	310	false
era_iter_7000	det	10,100,193	269.1725	true	true	0.084729	-0.000883	0.157659	253	false
era_iter_7000	stoch	10,100,193	285.415904	true	true	0.032899	-0.000313	0.180879	206	false
era_iter_7300	det	10,100,193	258.565478	true	true	0.086805	-0.000421	0.135203	252	false
era_iter_7300	stoch	10,100,193	283.704589	true	true	0.046751	-0.000629	0.202405	203	false
era_iter_7200	det	10,100,193	270.15449	true	true	0.077695	-0.001294	0.142196	245	false
era_iter_7200	stoch	10,100,193	286.073487	true	true	0.050687	-0.000545	0.24272	197	false
era_iter_7000	det	10,100,194	265.227849	true	true	0.108086	-0.001195	0.261575	281	false
era_iter_7000	stoch	10,100,194	298.33698	true	true	-0.00303	-0.000125	0.340566	216	false
era_iter_7300	det	10,100,194	264.650659	true	true	0.102301	-0.000778	0.250906	279	false
era_iter_7300	stoch	10,100,194	296.355622	true	true	0.02864	-0.000959	0.314829	214	false
era_iter_7200	det	10,100,194	266.977992	true	true	0.090622	-0.000549	0.265229	275	false
era_iter_7200	stoch	10,100,194	296.652053	true	true	0.027321	-0.000754	0.290065	213	false
era_iter_7000	det	10,100,195	248.222678	true	true	0.090115	-0.00075	0.381879	387	false
era_iter_7000	stoch	10,100,195	278.070439	true	true	-0.064264	-0.000367	0.241293	288	false
era_iter_7300	det	10,100,195	257.332406	true	true	0.071473	-0.000217	0.372469	397	false
era_iter_7300	stoch	10,100,195	274.440426	true	true	-0.084252	-0.000867	0.212867	313	false
era_iter_7200	det	10,100,195	258.858373	true	true	0.062879	0.000099	0.392005	396	false
era_iter_7200	stoch	10,100,195	265.096259	true	true	-0.076631	-0.000762	0.207725	313	false
era_iter_7000	det	10,100,196	263.370035	true	true	-0.131695	0.009172	0.250551	316	false
era_iter_7000	stoch	10,100,196	292.900094	true	true	-0.037703	-0.000663	0.464449	291	false
era_iter_7300	det	10,100,196	263.158706	true	true	-0.105554	-0.000748	0.139071	367	false
era_iter_7300	stoch	10,100,196	289.651496	true	true	-0.071935	-0.000624	0.484415	287	false
era_iter_7200	det	10,100,196	264.478947	true	true	-0.105915	-0.000837	0.083158	353	false
era_iter_7200	stoch	10,100,196	284.083261	true	true	-0.025651	-0.000554	0.550813	297	false
era_iter_7000	det	10,100,197	253.200121	true	true	-0.042349	-0.000335	0.349063	357	false
era_iter_7000	stoch	10,100,197	247.050147	true	true	-0.096214	-0.00049	0.324706	322	false
era_iter_7000	det	10,100,112	272.251205	true	true	-0.000422	-0.001113	0.412214	404	false
era_iter_7000	stoch	10,100,112	274.104719	true	true	0.174777	-0.000641	0.304719	277	false
era_iter_7300	det	10,100,112	272.050615	true	true	0.001193	-0.001118	0.395581	409	false
era_iter_7300	stoch	10,100,112	273.262767	true	true	0.176762	-0.000384	0.28413	340	false

End of preview.

By granting the agent adequate lateral control authority (SIDE_ENGINE_POWER = 0.30), the policy now has the mechanical muscle required to counteract heavy wind vectors

(WIND_POWER = 5.0, TURBULENCE_POWER = 2.0) right above touchdown, turning gusty Martian winds from an unpredictable hazard into a solved environment within a Total timestep of 65536000

And the voices that I'm hearing won't stop, They keep moving, they won't stay in one spot And the voices that I'm hearing won't stop, They keep moving, they won't stay in one spot

One man came slowly so I watched and saw him lift his head, The song that I was working on was in his hands and ripped to shreds That's when I got mad and asked him, "Dude, what do you want from me?" Right then is when he repeated the words that had been haunting me This time I could hear what he was reciting with clarity, He spoke the words in different octaves, each had a disparity Yet all of them sounded familiar, what was this man trying to do?, I inquired about his identity, he said, "I am you." And he was, but he was weary and translucent, He said he was who I'd be if I start to slack with my music And I finally understood the contents of his statement, All the while he was saying, "I am the ghost of your greatness."

#End #TheVoice

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