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privateboss
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Continuous_MarsLander_Calm_WindAndTurbulence

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

This happened while the csv dataset builder was generating data using

hf://datasets/privateboss/Continuous_MarsLander_Calm_WindAndTurbulence/marsLander_calm/robust_eval/ranking_final.csv (at revision 3e4e5cc9708d5943e41fc3dc47cebcd69bff5aba), ['hf://datasets/privateboss/Continuous_MarsLander_Calm_WindAndTurbulence@3e4e5cc9708d5943e41fc3dc47cebcd69bff5aba/marsLander_calm/robust_eval/episodes_final.csv', 'hf://datasets/privateboss/Continuous_MarsLander_Calm_WindAndTurbulence@3e4e5cc9708d5943e41fc3dc47cebcd69bff5aba/marsLander_calm/robust_eval/episodes_screen.csv', 'hf://datasets/privateboss/Continuous_MarsLander_Calm_WindAndTurbulence@3e4e5cc9708d5943e41fc3dc47cebcd69bff5aba/marsLander_calm/robust_eval/ranking_final.csv', 'hf://datasets/privateboss/Continuous_MarsLander_Calm_WindAndTurbulence@3e4e5cc9708d5943e41fc3dc47cebcd69bff5aba/marsLander_calm/robust_eval/ranking_screen.csv', 'hf://datasets/privateboss/Continuous_MarsLander_Calm_WindAndTurbulence@3e4e5cc9708d5943e41fc3dc47cebcd69bff5aba/marsLander_calm/robust_eval/summary_final.csv', 'hf://datasets/privateboss/Continuous_MarsLander_Calm_WindAndTurbulence@3e4e5cc9708d5943e41fc3dc47cebcd69bff5aba/marsLander_calm/robust_eval/summary_screen.csv', 'hf://datasets/privateboss/Continuous_MarsLander_Calm_WindAndTurbulence@3e4e5cc9708d5943e41fc3dc47cebcd69bff5aba/marsLander_calm/robust_eval/worst_final.csv', 'hf://datasets/privateboss/Continuous_MarsLander_Calm_WindAndTurbulence@3e4e5cc9708d5943e41fc3dc47cebcd69bff5aba/marsLander_calm/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 ({'stoch_crash_rate', 'mean', 'rank', 'robust_zone_lo', 'stoch_zone_rate', 'det_crash_rate', 'worst_p1', 'det_zone_rate'}) and 10 missing columns ({'landed', 'mode', 'timeout', 'seed', 'in_zone', 'td_speed', 'steps', 'y', 'reward', 'x'}).
              
              This happened while the csv dataset builder was generating data using
              
              hf://datasets/privateboss/Continuous_MarsLander_Calm_WindAndTurbulence/marsLander_calm/robust_eval/ranking_final.csv (at revision 3e4e5cc9708d5943e41fc3dc47cebcd69bff5aba), ['hf://datasets/privateboss/Continuous_MarsLander_Calm_WindAndTurbulence@3e4e5cc9708d5943e41fc3dc47cebcd69bff5aba/marsLander_calm/robust_eval/episodes_final.csv', 'hf://datasets/privateboss/Continuous_MarsLander_Calm_WindAndTurbulence@3e4e5cc9708d5943e41fc3dc47cebcd69bff5aba/marsLander_calm/robust_eval/episodes_screen.csv', 'hf://datasets/privateboss/Continuous_MarsLander_Calm_WindAndTurbulence@3e4e5cc9708d5943e41fc3dc47cebcd69bff5aba/marsLander_calm/robust_eval/ranking_final.csv', 'hf://datasets/privateboss/Continuous_MarsLander_Calm_WindAndTurbulence@3e4e5cc9708d5943e41fc3dc47cebcd69bff5aba/marsLander_calm/robust_eval/ranking_screen.csv', 'hf://datasets/privateboss/Continuous_MarsLander_Calm_WindAndTurbulence@3e4e5cc9708d5943e41fc3dc47cebcd69bff5aba/marsLander_calm/robust_eval/summary_final.csv', 'hf://datasets/privateboss/Continuous_MarsLander_Calm_WindAndTurbulence@3e4e5cc9708d5943e41fc3dc47cebcd69bff5aba/marsLander_calm/robust_eval/summary_screen.csv', 'hf://datasets/privateboss/Continuous_MarsLander_Calm_WindAndTurbulence@3e4e5cc9708d5943e41fc3dc47cebcd69bff5aba/marsLander_calm/robust_eval/worst_final.csv', 'hf://datasets/privateboss/Continuous_MarsLander_Calm_WindAndTurbulence@3e4e5cc9708d5943e41fc3dc47cebcd69bff5aba/marsLander_calm/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_700	det	10,100,218	266.095416	true	true	-0.041559	-0.000137	0.297434	319	false
era_iter_700	stoch	10,100,218	264.0452	true	true	-0.071851	-0.001059	0.336482	312	false
era_iter_1800	det	10,100,219	286.956023	true	true	-0.01631	-0.001049	0.334256	206	false
era_iter_1800	stoch	10,100,219	287.838348	true	true	-0.021158	-0.000553	0.373368	198	false
era_iter_1500	det	10,100,219	284.425803	true	true	-0.025817	-0.001016	0.288417	187	false
era_iter_1500	stoch	10,100,219	285.01702	true	true	-0.023633	-0.000636	0.331575	197	false
era_iter_700	det	10,100,219	281.994712	true	true	-0.052466	-0.000647	0.339156	196	false
era_iter_700	stoch	10,100,219	282.362177	true	true	-0.055302	-0.000388	0.316752	190	false
era_iter_1800	det	10,100,220	279.271446	true	true	0.095479	-0.000081	0.21446	166	false
era_iter_1800	stoch	10,100,220	279.907783	true	true	0.099173	-0.000678	0.254571	177	false
era_iter_1500	det	10,100,220	278.139302	true	true	0.094433	-0.000161	0.239383	179	false
era_iter_1500	stoch	10,100,220	278.153592	true	true	0.094851	-0.000911	0.238457	174	false
era_iter_700	det	10,100,220	282.745254	true	true	0.07122	-0.001297	0.270941	165	false
era_iter_700	stoch	10,100,220	283.008717	true	true	0.065763	-0.000461	0.282713	169	false
era_iter_1800	det	10,100,221	280.192352	true	true	-0.09768	-0.001254	0.214865	211	false
era_iter_1800	stoch	10,100,221	279.109461	true	true	-0.102747	0.000041	0.217416	205	false
era_iter_1500	det	10,100,221	277.282709	true	true	-0.099617	-0.000984	0.210172	213	false
era_iter_1500	stoch	10,100,221	277.979005	true	true	-0.100462	-0.000191	0.24094	212	false
era_iter_700	det	10,100,221	268.429208	true	true	-0.133674	-0.005667	0.168283	200	false
era_iter_700	stoch	10,100,221	271.096518	true	true	-0.123117	-0.002874	0.180761	224	false
era_iter_1800	det	10,100,222	266.672577	true	true	-0.033005	-0.000707	0.267779	324	false
era_iter_1800	stoch	10,100,222	266.747039	true	true	-0.038848	-0.000726	0.260872	321	false
era_iter_1500	det	10,100,222	253.669701	true	true	-0.066901	-0.001072	0.244648	319	false
era_iter_1500	stoch	10,100,222	264.774625	true	true	-0.063234	0.000157	0.262482	320	false
era_iter_700	det	10,100,222	249.898407	true	true	-0.060791	-0.000221	0.296944	346	false
era_iter_700	stoch	10,100,222	250.382595	true	true	-0.077567	-0.00046	0.265136	353	false
era_iter_1800	det	10,100,223	275.191417	true	true	0.091887	-0.000897	0.390351	185	false
era_iter_1800	stoch	10,100,223	256.001104	true	true	0.082095	-0.000277	0.352796	205	false
era_iter_1500	det	10,100,223	272.162482	true	true	0.100149	-0.000948	0.327795	201	false
era_iter_1500	stoch	10,100,223	273.414736	true	true	0.09284	-0.000246	0.344581	176	false
era_iter_700	det	10,100,223	274.704803	true	true	0.097314	-0.000997	0.392358	196	false
era_iter_700	stoch	10,100,223	276.814538	true	true	0.075206	-0.000712	0.404699	189	false
era_iter_1800	det	10,100,144	250.321776	true	true	-0.024963	-0.001278	0.280001	226	false
era_iter_1800	stoch	10,100,144	250.298507	true	true	-0.020177	-0.000792	0.271583	218	false
era_iter_1500	det	10,100,144	248.73166	true	true	-0.037743	-0.000765	0.281716	227	false
era_iter_1500	stoch	10,100,144	249.3049	true	true	-0.034593	-0.000539	0.275087	226	false
era_iter_700	det	10,100,144	245.704665	true	true	-0.06298	-0.000344	0.282999	230	false
era_iter_700	stoch	10,100,144	245.030121	true	true	-0.059749	-0.001308	0.244033	227	false
era_iter_1800	det	10,100,145	262.434365	true	false	0.205002	-0.017364	0.18485	534	false
era_iter_1800	stoch	10,100,145	263.634057	true	false	0.208627	-0.017614	0.185732	487	false
era_iter_1500	det	10,100,145	259.039166	true	false	0.213357	-0.0192	0.204269	535	false
era_iter_1500	stoch	10,100,145	261.604513	true	false	0.219712	-0.019906	0.169597	488	false
era_iter_700	det	10,100,145	269.274084	true	true	0.19329	-0.015371	0.249077	492	false
era_iter_700	stoch	10,100,145	269.862103	true	true	0.196092	-0.015514	0.254277	464	false
era_iter_1800	det	10,100,146	246.534107	true	true	-0.020562	-0.000722	0.241643	205	false
era_iter_1800	stoch	10,100,146	246.665123	true	true	-0.020394	-0.000473	0.275468	203	false
era_iter_1500	det	10,100,146	245.178101	true	true	-0.02859	-0.000499	0.245743	197	false
era_iter_1500	stoch	10,100,146	244.729337	true	true	-0.033775	-0.000517	0.250095	194	false
era_iter_700	det	10,100,146	240.155239	true	true	-0.067858	-0.000789	0.220861	203	false
era_iter_700	stoch	10,100,146	239.301751	true	true	-0.077374	-0.000126	0.200647	202	false
era_iter_1800	det	10,100,147	273.346633	true	true	-0.109807	-0.000622	0.20875	177	false
era_iter_1800	stoch	10,100,147	264.127705	true	true	-0.105943	-0.000039	0.225138	171	false
era_iter_1500	det	10,100,147	271.335804	true	true	-0.116541	0.000307	0.165975	267	false
era_iter_1500	stoch	10,100,147	261.558412	true	true	-0.111784	0.000108	0.216375	202	false
era_iter_700	det	10,100,147	258.806443	true	true	-0.165275	0.010099	0.16427	160	false
era_iter_700	stoch	10,100,147	265.559538	true	true	-0.146127	0.006559	0.215339	181	false
era_iter_1800	det	10,100,148	270.14279	true	true	-0.001428	-0.000612	0.243378	180	false
era_iter_1800	stoch	10,100,148	270.397468	true	true	0.000129	-0.000354	0.254317	187	false
era_iter_1500	det	10,100,148	267.621164	true	true	-0.012243	-0.000067	0.22569	182	false
era_iter_1500	stoch	10,100,148	268.278518	true	true	-0.01074	-0.000327	0.263382	192	false
era_iter_700	det	10,100,148	264.893659	true	true	-0.036995	-0.000572	0.229863	189	false
era_iter_700	stoch	10,100,148	266.782073	true	true	-0.03547	-0.000238	0.238059	184	false
era_iter_1800	det	10,100,149	53.992803	false	false	0.015749	-0.032565	0.335721	195	false
era_iter_1800	stoch	10,100,149	52.882313	false	false	0.012839	-0.03246	0.33659	195	false
era_iter_1800	det	10,100,160	263.790596	true	true	-0.043719	0.000011	0.252449	247	false
era_iter_1800	stoch	10,100,160	264.957522	true	true	-0.02961	-0.001107	0.231305	257	false
era_iter_1500	det	10,100,160	261.590046	true	true	-0.059938	-0.000067	0.239738	256	false
era_iter_1500	stoch	10,100,160	261.874329	true	true	-0.057691	-0.000346	0.23532	244	false
era_iter_700	det	10,100,160	243.479483	true	true	-0.103822	-0.000673	0.142565	258	false
era_iter_700	stoch	10,100,160	253.874595	true	true	-0.097	-0.000999	0.10981	252	false
era_iter_1800	det	10,100,161	278.696748	true	true	0.038998	-0.000486	0.302025	207	false
era_iter_1800	stoch	10,100,161	278.147786	true	true	0.045801	-0.000485	0.299311	204	false
era_iter_1500	det	10,100,161	278.935529	true	true	0.038596	-0.00054	0.316452	207	false
era_iter_1500	stoch	10,100,161	278.362991	true	true	0.042097	-0.000617	0.281044	203	false
era_iter_700	det	10,100,161	283.691857	true	true	0.002199	-0.000329	0.283763	215	false
era_iter_700	stoch	10,100,161	282.504981	true	true	0.017258	-0.000744	0.311422	210	false
era_iter_1800	det	10,100,162	284.054183	true	true	-0.055058	-0.000783	0.296484	383	false
era_iter_1800	stoch	10,100,162	275.147123	true	true	-0.055138	-0.000489	0.326031	359	false
era_iter_1500	det	10,100,162	273.617479	true	true	-0.058811	-0.000682	0.328642	372	false
era_iter_1500	stoch	10,100,162	284.701602	true	true	-0.048471	-0.000345	0.331973	387	false
era_iter_700	det	10,100,162	284.439419	true	true	0.017331	0.00059	0.313379	442	false
era_iter_700	stoch	10,100,162	284.984952	true	true	0.005075	-0.000842	0.332445	432	false
era_iter_1800	det	10,100,163	284.561921	true	true	-0.028244	-0.000265	0.292093	331	false
era_iter_1800	stoch	10,100,163	284.868789	true	true	-0.033384	-0.000183	0.30345	333	false
era_iter_1500	det	10,100,163	282.957458	true	true	-0.047964	-0.000335	0.291963	321	false
era_iter_1500	stoch	10,100,163	274.959157	true	true	-0.033825	-0.000917	0.284483	331	false
era_iter_700	det	10,100,163	267.377906	true	true	-0.061379	-0.000456	0.270291	372	false
era_iter_700	stoch	10,100,163	257.068988	true	true	-0.052361	-0.000818	0.281454	457	false
era_iter_1800	det	10,100,164	279.206251	true	true	0.079321	0.000333	0.458818	310	false
era_iter_1800	stoch	10,100,164	283.473867	true	true	0.051907	-0.000154	0.483536	305	false
era_iter_1500	det	10,100,164	281.480427	true	true	0.062954	0.000072	0.437049	314	false
era_iter_1500	stoch	10,100,164	285.394021	true	true	0.028566	-0.000345	0.437486	310	false
era_iter_700	det	10,100,164	282.35032	true	true	-0.047122	-0.000687	0.336642	318	false
era_iter_700	stoch	10,100,164	278.121209	true	true	-0.09718	-0.000922	0.357916	299	false
era_iter_1800	det	10,100,165	48.6034	false	false	-0.070843	-0.033127	0.410997	112	false
era_iter_1800	stoch	10,100,165	47.101258	false	false	-0.069337	-0.033543	0.425292	110	false
era_iter_1500	det	10,100,149	271.399249	true	true	0.008954	-0.000433	0.288883	279	false
era_iter_1500	stoch	10,100,149	272.622031	true	true	-0.001678	-0.000982	0.334826	269	false
era_iter_700	det	10,100,149	271.253317	true	true	-0.020157	-0.001175	0.378208	269	false
era_iter_700	stoch	10,100,149	271.15931	true	true	-0.021284	-0.000598	0.397365	279	false

End of preview.

Agent learns to land safely and efficently which effectively solves the environment with Mars gravity and calm wind trubulence with total timestep of 24576000.

Varda skald, druma thren Njordr's breath on ice and fen Skaldin var, ulven's cry By the flame, the spirits fly

Hei-a, hei-a, runa brenn Thur's path, the gods ascend Skjold and axe, in dusk we bind Odin’s voice within the wind.

#Odin's Call

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