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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 9 new columns ({'ds_consensus_mean', 'ds_consensus_std', 'iteration', 'row_gradient_mean', 'row_gradient_std', 'row_consensus_std', 'ds_gradient_std', 'row_consensus_mean', 'ds_gradient_mean'}) and 6 missing columns ({'row_weighted_norm', 'step', 'row_rho_power', 'ds_weighted_norm', 'ds_penalty_ratio', 'ds_rho_power'}).
This happened while the csv dataset builder was generating data using
hf://datasets/SabaPivot/icml166-row-stochastic-reproduction/claim2_quadratic.csv (at revision a428adf0901e4e38b8da911101a8ff5993446dc8), ['hf://datasets/SabaPivot/icml166-row-stochastic-reproduction@a428adf0901e4e38b8da911101a8ff5993446dc8/claim1_transient.csv', 'hf://datasets/SabaPivot/icml166-row-stochastic-reproduction@a428adf0901e4e38b8da911101a8ff5993446dc8/claim2_quadratic.csv', 'hf://datasets/SabaPivot/icml166-row-stochastic-reproduction@a428adf0901e4e38b8da911101a8ff5993446dc8/claim3_conditions.csv', 'hf://datasets/SabaPivot/icml166-row-stochastic-reproduction@a428adf0901e4e38b8da911101a8ff5993446dc8/claim4_loewner_eigenvalues.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 1837, in _prepare_split_single
writer.write_table(table)
~~~~~~~~~~~~~~~~~~^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 765, 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 773, in _write_table
pa_table = table_cast(pa_table, self._schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2369, in table_cast
return cast_table_to_schema(table, schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2297, in cast_table_to_schema
raise CastError(
...<3 lines>...
)
datasets.table.CastError: Couldn't cast
iteration: int64
row_gradient_mean: double
row_gradient_std: double
ds_gradient_mean: double
ds_gradient_std: double
row_consensus_mean: double
row_consensus_std: double
ds_consensus_mean: double
ds_consensus_std: double
-- schema metadata --
pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 1466
to
{'step': Value('int64'), 'row_weighted_norm': Value('float64'), 'row_rho_power': Value('float64'), 'ds_weighted_norm': Value('float64'), 'ds_rho_power': Value('float64'), 'ds_penalty_ratio': 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 1683, 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 1839, 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 9 new columns ({'ds_consensus_mean', 'ds_consensus_std', 'iteration', 'row_gradient_mean', 'row_gradient_std', 'row_consensus_std', 'ds_gradient_std', 'row_consensus_mean', 'ds_gradient_mean'}) and 6 missing columns ({'row_weighted_norm', 'step', 'row_rho_power', 'ds_weighted_norm', 'ds_penalty_ratio', 'ds_rho_power'}).
This happened while the csv dataset builder was generating data using
hf://datasets/SabaPivot/icml166-row-stochastic-reproduction/claim2_quadratic.csv (at revision a428adf0901e4e38b8da911101a8ff5993446dc8), ['hf://datasets/SabaPivot/icml166-row-stochastic-reproduction@a428adf0901e4e38b8da911101a8ff5993446dc8/claim1_transient.csv', 'hf://datasets/SabaPivot/icml166-row-stochastic-reproduction@a428adf0901e4e38b8da911101a8ff5993446dc8/claim2_quadratic.csv', 'hf://datasets/SabaPivot/icml166-row-stochastic-reproduction@a428adf0901e4e38b8da911101a8ff5993446dc8/claim3_conditions.csv', 'hf://datasets/SabaPivot/icml166-row-stochastic-reproduction@a428adf0901e4e38b8da911101a8ff5993446dc8/claim4_loewner_eigenvalues.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.
step int64 | row_weighted_norm float64 | row_rho_power float64 | ds_weighted_norm float64 | ds_rho_power float64 | ds_penalty_ratio float64 |
|---|---|---|---|---|---|
1 | 0.90134 | 0.90134 | 1.823089 | 0.794975 | 2.293266 |
2 | 0.812413 | 0.812413 | 1.099217 | 0.631985 | 1.739309 |
3 | 0.732261 | 0.732261 | 0.974855 | 0.502412 | 1.94035 |
4 | 0.660016 | 0.660016 | 0.756721 | 0.399405 | 1.894621 |
5 | 0.594898 | 0.594898 | 0.613213 | 0.317517 | 1.931277 |
6 | 0.536206 | 0.536206 | 0.484883 | 0.252418 | 1.920953 |
7 | 0.483303 | 0.483303 | 0.387042 | 0.200666 | 1.928787 |
8 | 0.435621 | 0.435621 | 0.307242 | 0.159524 | 1.925988 |
9 | 0.392642 | 0.392642 | 0.24448 | 0.126818 | 1.927803 |
10 | 0.353904 | 0.353904 | 0.194279 | 0.100817 | 1.927051 |
11 | 0.318988 | 0.318988 | 0.154482 | 0.080147 | 1.927489 |
12 | 0.287516 | 0.287516 | 0.122797 | 0.063715 | 1.927292 |
13 | 0.25915 | 0.25915 | 0.097626 | 0.050652 | 1.9274 |
14 | 0.233582 | 0.233582 | 0.077608 | 0.040267 | 1.927349 |
15 | 0.210537 | 0.210537 | 0.061697 | 0.032011 | 1.927376 |
16 | 0.189765 | 0.189765 | 0.049047 | 0.025448 | 1.927363 |
17 | 0.171043 | 0.171043 | 0.038992 | 0.020231 | 1.927369 |
18 | 0.154168 | 0.154168 | 0.030997 | 0.016083 | 1.927366 |
19 | 0.138958 | 0.138958 | 0.024642 | 0.012785 | 1.927368 |
20 | 0.125248 | 0.125248 | 0.01959 | 0.010164 | 1.927367 |
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End of preview.
ICML 2026 paper #166 numerical audit
Code and raw outputs for an independent reproduction of Row-Stochastic Matrices Can Provably Outperform Doubly Stochastic Matrices in Decentralized Learning (OpenReview GAQE4Wr53f, arXiv 2511.19513).
reproduce.py: float64 matrix, theorem, topology, and 100-seed local quadratic audit.gpu_experiment.py: batched PyTorch GPU audit of the paper's 16-nodelambda_Bring setup.results.jsonand CSV files: local numerical results and plotted raw data.
The paper did not provide an official code repository in the arXiv source inspected for this reproduction.
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