Dataset Viewer
The dataset viewer is not available for this split.
Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code: StreamingRowsError
Exception: CastError
Message: Couldn't cast
args: struct<algorithm: string, checkpoint_freq: null, data_dir: string, dataset: string, holdout_fraction (... 243 chars omitted)
child 0, algorithm: string
child 1, checkpoint_freq: null
child 2, data_dir: string
child 3, dataset: string
child 4, holdout_fraction: double
child 5, hparams: string
child 6, hparams_seed: int64
child 7, output_dir: string
child 8, save_model_every_checkpoint: bool
child 9, seed: int64
child 10, skip_model_save: bool
child 11, steps: null
child 12, task: string
child 13, test_envs: list<item: int64>
child 0, item: int64
child 14, trial_seed: int64
child 15, uda_holdout_fraction: int64
ce: double
env0_in_acc: double
env0_out_acc: double
env1_in_acc: double
env1_out_acc: double
env2_in_acc: double
env2_out_acc: double
env3_in_acc: double
env3_out_acc: double
epoch: double
hparams: struct<batch_size: int64, class_balanced: bool, data_augmentation: bool, dinov2: bool, freeze_bn: bo (... 456 chars omitted)
child 0, batch_size: int64
child 1, class_balanced: bool
child 2, data_augmentation: bool
child 3, dinov2: bool
child 4, freeze_bn: bool
child 5, lars: bool
child 6, linear_steps: int64
child 7, lr: double
child 8, nonlinear_classifier: bool
child 9, rdi_alpha: double
child 10, rdi_beta: double
child 11, rdi_ema: double
child 12, rdi_gamma: double
child 13, rdi_k: int64
child 14, rdi_lambda_geo: double
child 15, rdi_lambda_rec: double
child 16, rdi_proj_dropout: double
child 17, rdi_proj_hidden: int64
child 18, rdi_proj_out: int64
child 19, rdi_tau: double
child 20, rdi_warmup: int64
child 21, resnet18: bool
child 22, resnet50_augmix: bool
child 23, resnet_dropout: double
child 24, vit: bool
child 25, vit_attn_tune: bool
child 26, vit_dropout: double
child 27, weight_decay: double
loss: double
mem_gb: double
step: int64
step_time: double
geo: double
rate: double
rec: double
to
{'args': {'algorithm': Value('string'), 'checkpoint_freq': Value('null'), 'data_dir': Value('string'), 'dataset': Value('string'), 'holdout_fraction': Value('float64'), 'hparams': Value('string'), 'hparams_seed': Value('int64'), 'output_dir': Value('string'), 'save_model_every_checkpoint': Value('bool'), 'seed': Value('int64'), 'skip_model_save': Value('bool'), 'steps': Value('null'), 'task': Value('string'), 'test_envs': List(Value('int64')), 'trial_seed': Value('int64'), 'uda_holdout_fraction': Value('int64')}, 'env0_in_acc': Value('float64'), 'env0_out_acc': Value('float64'), 'env1_in_acc': Value('float64'), 'env1_out_acc': Value('float64'), 'env2_in_acc': Value('float64'), 'env2_out_acc': Value('float64'), 'env3_in_acc': Value('float64'), 'env3_out_acc': Value('float64'), 'epoch': Value('float64'), 'hparams': {'batch_size': Value('int64'), 'class_balanced': Value('bool'), 'data_augmentation': Value('bool'), 'dinov2': Value('bool'), 'freeze_bn': Value('bool'), 'lars': Value('bool'), 'linear_steps': Value('int64'), 'lr': Value('float64'), 'nonlinear_classifier': Value('bool'), 'resnet18': Value('bool'), 'resnet50_augmix': Value('bool'), 'resnet_dropout': Value('float64'), 'vit': Value('bool'), 'vit_attn_tune': Value('bool'), 'vit_dropout': Value('float64'), 'weight_decay': Value('float64')}, 'loss': Value('float64'), 'mem_gb': Value('float64'), 'step': Value('int64'), 'step_time': Value('float64')}
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
args: struct<algorithm: string, checkpoint_freq: null, data_dir: string, dataset: string, holdout_fraction (... 243 chars omitted)
child 0, algorithm: string
child 1, checkpoint_freq: null
child 2, data_dir: string
child 3, dataset: string
child 4, holdout_fraction: double
child 5, hparams: string
child 6, hparams_seed: int64
child 7, output_dir: string
child 8, save_model_every_checkpoint: bool
child 9, seed: int64
child 10, skip_model_save: bool
child 11, steps: null
child 12, task: string
child 13, test_envs: list<item: int64>
child 0, item: int64
child 14, trial_seed: int64
child 15, uda_holdout_fraction: int64
ce: double
env0_in_acc: double
env0_out_acc: double
env1_in_acc: double
env1_out_acc: double
env2_in_acc: double
env2_out_acc: double
env3_in_acc: double
env3_out_acc: double
epoch: double
hparams: struct<batch_size: int64, class_balanced: bool, data_augmentation: bool, dinov2: bool, freeze_bn: bo (... 456 chars omitted)
child 0, batch_size: int64
child 1, class_balanced: bool
child 2, data_augmentation: bool
child 3, dinov2: bool
child 4, freeze_bn: bool
child 5, lars: bool
child 6, linear_steps: int64
child 7, lr: double
child 8, nonlinear_classifier: bool
child 9, rdi_alpha: double
child 10, rdi_beta: double
child 11, rdi_ema: double
child 12, rdi_gamma: double
child 13, rdi_k: int64
child 14, rdi_lambda_geo: double
child 15, rdi_lambda_rec: double
child 16, rdi_proj_dropout: double
child 17, rdi_proj_hidden: int64
child 18, rdi_proj_out: int64
child 19, rdi_tau: double
child 20, rdi_warmup: int64
child 21, resnet18: bool
child 22, resnet50_augmix: bool
child 23, resnet_dropout: double
child 24, vit: bool
child 25, vit_attn_tune: bool
child 26, vit_dropout: double
child 27, weight_decay: double
loss: double
mem_gb: double
step: int64
step_time: double
geo: double
rate: double
rec: double
to
{'args': {'algorithm': Value('string'), 'checkpoint_freq': Value('null'), 'data_dir': Value('string'), 'dataset': Value('string'), 'holdout_fraction': Value('float64'), 'hparams': Value('string'), 'hparams_seed': Value('int64'), 'output_dir': Value('string'), 'save_model_every_checkpoint': Value('bool'), 'seed': Value('int64'), 'skip_model_save': Value('bool'), 'steps': Value('null'), 'task': Value('string'), 'test_envs': List(Value('int64')), 'trial_seed': Value('int64'), 'uda_holdout_fraction': Value('int64')}, 'env0_in_acc': Value('float64'), 'env0_out_acc': Value('float64'), 'env1_in_acc': Value('float64'), 'env1_out_acc': Value('float64'), 'env2_in_acc': Value('float64'), 'env2_out_acc': Value('float64'), 'env3_in_acc': Value('float64'), 'env3_out_acc': Value('float64'), 'epoch': Value('float64'), 'hparams': {'batch_size': Value('int64'), 'class_balanced': Value('bool'), 'data_augmentation': Value('bool'), 'dinov2': Value('bool'), 'freeze_bn': Value('bool'), 'lars': Value('bool'), 'linear_steps': Value('int64'), 'lr': Value('float64'), 'nonlinear_classifier': Value('bool'), 'resnet18': Value('bool'), 'resnet50_augmix': Value('bool'), 'resnet_dropout': Value('float64'), 'vit': Value('bool'), 'vit_attn_tune': Value('bool'), 'vit_dropout': Value('float64'), 'weight_decay': Value('float64')}, 'loss': Value('float64'), 'mem_gb': Value('float64'), 'step': Value('int64'), 'step_time': Value('float64')}
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.
RDI reproduction — run logs & audit outputs
Per-run DomainBed logs (results.jsonl, out.txt), collected results
(results/summary.csv), Claim-1 figures, and Claim-2 theory-audit scripts +
CSV outputs for the reproduction of ICML 2026 #11252 (RDI). Companion model
repo: kaustubh/rdi-repro-pacs-resnet50.
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