Operator Splitting with Hamilton-Jacobi-based Proximals
Paper • 2601.22370 • Published
Dataset Viewer
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Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code: StreamingRowsError
Exception: CastError
Message: Couldn't cast
schema_version: string
platform: struct<operating_system: string, architecture: string>
child 0, operating_system: string
child 1, architecture: string
python: struct<implementation: string, version: string>
child 0, implementation: string
child 1, version: string
packages: struct<numpy: string, provsleuth: string, torch: string>
child 0, numpy: string
child 1, provsleuth: string
child 2, torch: string
requirements: struct<path: string, sha256: string>
child 0, path: string
child 1, sha256: string
provsleuth_wheel: struct<path: string, sha256: string>
child 0, path: string
child 1, sha256: string
direct_child: struct<executable: string, executable_sha256: string, isolated_mode: bool, site_packages: string, bo (... 16 chars omitted)
child 0, executable: string
child 1, executable_sha256: string
child 2, isolated_mode: bool
child 3, site_packages: string
child 4, bootstrap: string
execution: struct<device: string, torch_dtype: string, analytical_dtype: string, blas_threads: int64, torch_thr (... 80 chars omitted)
child 0, device: string
child 1, torch_dtype: string
child 2, analytical_dtype: string
child 3, blas_threads: int64
child 4, torch_threads: int64
child 5, torch_interop_threads: int64
child 6, torch_deterministic_algorithms: bool
source_environment_boundary: struct<notebook_kernel_python: string, local_python_matches_notebook_metadata: bool, notebook_depend (... 109 chars omitted)
child 0, notebook_kernel_python: string
child 1, local_python_matches_notebook_metadata: bool
child 2, notebook_dependency_versions_available: bool
child 3, source_imports_scipy: bool
child 4, local_uses_numpy_norm_instead: bool
child 5, note: string
attestation_boundary: string
portability_boundary: string
installation: struct<requirements_command: string, provsleuth_command: string>
child 0, requirements_command: string
child 1, provsleuth_command: string
scope: string
replay_constraint: string
to
{'schema_version': Value('string'), 'scope': Value('string'), 'platform': {'operating_system': Value('string'), 'architecture': Value('string')}, 'python': {'implementation': Value('string'), 'version': Value('string')}, 'packages': {'numpy': Value('string'), 'provsleuth': Value('string'), 'torch': Value('string')}, 'requirements': {'path': Value('string'), 'sha256': Value('string')}, 'provsleuth_wheel': {'path': Value('string'), 'sha256': Value('string')}, 'installation': {'requirements_command': Value('string'), 'provsleuth_command': Value('string')}, 'direct_child': {'executable': Value('string'), 'executable_sha256': Value('string'), 'isolated_mode': Value('bool'), 'site_packages': Value('string'), 'bootstrap': Value('string')}, 'replay_constraint': Value('string'), 'attestation_boundary': Value('string'), 'portability_boundary': Value('string')}
because column names don't match
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 149, in get_rows_or_raise
return get_rows(
dataset=dataset,
...<4 lines>...
column_names=column_names,
)
File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
return func(*args, **kwargs)
File "/src/services/worker/src/worker/utils.py", line 129, in get_rows
rows_plus_one = list(itertools.islice(safe_iter(ds, dataset=dataset), rows_max_number + 1))
File "/src/services/worker/src/worker/utils.py", line 489, in safe_iter
yield from ds.decode(False) if ds.features else ds
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2818, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2355, in __iter__
for key, pa_table in self._iter_arrow():
~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2380, in _iter_arrow
for key, pa_table in self.ex_iterable._iter_arrow():
~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 536, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 419, in _iter_arrow
for key, pa_table in self.generate_tables_fn(**gen_kwags):
~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 343, in _generate_tables
self._cast_table(pa_table, json_field_paths=json_field_paths),
~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 132, in _cast_table
pa_table = table_cast(pa_table, self.info.features.arrow_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
schema_version: string
platform: struct<operating_system: string, architecture: string>
child 0, operating_system: string
child 1, architecture: string
python: struct<implementation: string, version: string>
child 0, implementation: string
child 1, version: string
packages: struct<numpy: string, provsleuth: string, torch: string>
child 0, numpy: string
child 1, provsleuth: string
child 2, torch: string
requirements: struct<path: string, sha256: string>
child 0, path: string
child 1, sha256: string
provsleuth_wheel: struct<path: string, sha256: string>
child 0, path: string
child 1, sha256: string
direct_child: struct<executable: string, executable_sha256: string, isolated_mode: bool, site_packages: string, bo (... 16 chars omitted)
child 0, executable: string
child 1, executable_sha256: string
child 2, isolated_mode: bool
child 3, site_packages: string
child 4, bootstrap: string
execution: struct<device: string, torch_dtype: string, analytical_dtype: string, blas_threads: int64, torch_thr (... 80 chars omitted)
child 0, device: string
child 1, torch_dtype: string
child 2, analytical_dtype: string
child 3, blas_threads: int64
child 4, torch_threads: int64
child 5, torch_interop_threads: int64
child 6, torch_deterministic_algorithms: bool
source_environment_boundary: struct<notebook_kernel_python: string, local_python_matches_notebook_metadata: bool, notebook_depend (... 109 chars omitted)
child 0, notebook_kernel_python: string
child 1, local_python_matches_notebook_metadata: bool
child 2, notebook_dependency_versions_available: bool
child 3, source_imports_scipy: bool
child 4, local_uses_numpy_norm_instead: bool
child 5, note: string
attestation_boundary: string
portability_boundary: string
installation: struct<requirements_command: string, provsleuth_command: string>
child 0, requirements_command: string
child 1, provsleuth_command: string
scope: string
replay_constraint: string
to
{'schema_version': Value('string'), 'scope': Value('string'), 'platform': {'operating_system': Value('string'), 'architecture': Value('string')}, 'python': {'implementation': Value('string'), 'version': Value('string')}, 'packages': {'numpy': Value('string'), 'provsleuth': Value('string'), 'torch': Value('string')}, 'requirements': {'path': Value('string'), 'sha256': Value('string')}, 'provsleuth_wheel': {'path': Value('string'), 'sha256': Value('string')}, 'installation': {'requirements_command': Value('string'), 'provsleuth_command': Value('string')}, 'direct_child': {'executable': Value('string'), 'executable_sha256': Value('string'), 'isolated_mode': Value('bool'), 'site_packages': Value('string'), 'bootstrap': Value('string')}, 'replay_constraint': Value('string'), 'attestation_boundary': Value('string'), 'portability_boundary': Value('string')}
because column names don't matchNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
HJ-Splitting reproduction bundle (arXiv:2601.22370v4)
Scripts and locked inputs for the full-scale seed sweeps of Operator Splitting with Hamilton-Jacobi-based Proximals.
repro/run_sparse_group_full.py— Figure 1 sparse-group panel, 10,000 updatesrepro/run_nonnegative_full.py— Figure 4 non-negative panel, 10,000 updatessources/upstream/*.source-lock.json— SHA-256 pins of the upstream notebooksenvironment/*.json— the locked local CPU runtime these were validated against
The HJ arms are stochastic: the pinned upstream notebooks do not seed Torch. Seeds are therefore declared varying parameters, and results must be reported as a spread across seeds rather than as a single endpoint.
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