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
action_dim: int64
action_horizon: int64
all_model_parameters_trainable: bool
complete: bool
data_schema: string
dataset: struct<codebase_version: string, fps: int64, robot_type: string, total_episodes: int64>
child 0, codebase_version: string
child 1, fps: int64
child 2, robot_type: string
child 3, total_episodes: int64
dataset_root: string
dataset_task: string
dataset_task_index: int64
discrete_state_input: bool
fastwam_modified: bool
fingerprint: string
gcabench_task_id: string
global_step: int64
image_contract: string
input_assets: struct<norm_stats: struct<mtime_ns: int64, path: string, sha256: string, size_bytes: int64>, tokeniz (... 77 chars omitted)
child 0, norm_stats: struct<mtime_ns: int64, path: string, sha256: string, size_bytes: int64>
child 0, mtime_ns: int64
child 1, path: string
child 2, sha256: string
child 3, size_bytes: int64
child 1, tokenizer: struct<mtime_ns: int64, path: string, sha256: string, size_bytes: int64>
child 0, mtime_ns: int64
child 1, path: string
child 2, sha256: string
child 3, size_bytes: int64
instruction: string
loss: string
max_token_len: int64
native_config: string
native_params_files: list<item: struct<path: string, size_bytes: int64>>
child 0, item: struct<path: string, size_bytes: int64>
child 0, path: string
child 1, size_bytes: int64
norm_stats_sha256: string
normalization: string
optimizer_state_saved: bool
options: struct<batch_size: int64, ema_decay: dou
...
ecay: double
child 2, fsdp_devices: int64
child 3, learning_rate: double
child 4, max_grad_norm: double
child 5, resume_state_every: int64
child 6, seed: int64
child 7, steps: int64
pretrained_checkpoint: string
qwam_modified: bool
runtime: struct<cpu_affinity_count: int64, xla_flags: string>
child 0, cpu_affinity_count: int64
child 1, xla_flags: string
schema: string
smoke: bool
tokenizer_sha256: string
train_metrics: string
training_kind: string
upstream_revision: string
weights: string
norm_stats: struct<actions: struct<mean: list<item: double>, q01: list<item: double>, q99: list<item: double>, s (... 140 chars omitted)
child 0, actions: struct<mean: list<item: double>, q01: list<item: double>, q99: list<item: double>, std: list<item: d (... 7 chars omitted)
child 0, mean: list<item: double>
child 0, item: double
child 1, q01: list<item: double>
child 0, item: double
child 2, q99: list<item: double>
child 0, item: double
child 3, std: list<item: double>
child 0, item: double
child 1, state: struct<mean: list<item: double>, q01: list<item: double>, q99: list<item: double>, std: list<item: d (... 7 chars omitted)
child 0, mean: list<item: double>
child 0, item: double
child 1, q01: list<item: double>
child 0, item: double
child 2, q99: list<item: double>
child 0, item: double
child 3, std: list<item: double>
child 0, item: double
to
{'norm_stats': {'actions': {'mean': List(Value('float64')), 'q01': List(Value('float64')), 'q99': List(Value('float64')), 'std': List(Value('float64'))}, 'state': {'mean': List(Value('float64')), 'q01': List(Value('float64')), 'q99': List(Value('float64')), 'std': List(Value('float64'))}}}
because column names don't match
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 147, 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 127, 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 483, 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 2951, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2461, in __iter__
for key, pa_table in self._iter_arrow():
~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2486, 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 547, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 430, 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 2378, in table_cast
return cast_table_to_schema(table, schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2306, in cast_table_to_schema
raise CastError(
...<3 lines>...
)
datasets.table.CastError: Couldn't cast
action_dim: int64
action_horizon: int64
all_model_parameters_trainable: bool
complete: bool
data_schema: string
dataset: struct<codebase_version: string, fps: int64, robot_type: string, total_episodes: int64>
child 0, codebase_version: string
child 1, fps: int64
child 2, robot_type: string
child 3, total_episodes: int64
dataset_root: string
dataset_task: string
dataset_task_index: int64
discrete_state_input: bool
fastwam_modified: bool
fingerprint: string
gcabench_task_id: string
global_step: int64
image_contract: string
input_assets: struct<norm_stats: struct<mtime_ns: int64, path: string, sha256: string, size_bytes: int64>, tokeniz (... 77 chars omitted)
child 0, norm_stats: struct<mtime_ns: int64, path: string, sha256: string, size_bytes: int64>
child 0, mtime_ns: int64
child 1, path: string
child 2, sha256: string
child 3, size_bytes: int64
child 1, tokenizer: struct<mtime_ns: int64, path: string, sha256: string, size_bytes: int64>
child 0, mtime_ns: int64
child 1, path: string
child 2, sha256: string
child 3, size_bytes: int64
instruction: string
loss: string
max_token_len: int64
native_config: string
native_params_files: list<item: struct<path: string, size_bytes: int64>>
child 0, item: struct<path: string, size_bytes: int64>
child 0, path: string
child 1, size_bytes: int64
norm_stats_sha256: string
normalization: string
optimizer_state_saved: bool
options: struct<batch_size: int64, ema_decay: dou
...
ecay: double
child 2, fsdp_devices: int64
child 3, learning_rate: double
child 4, max_grad_norm: double
child 5, resume_state_every: int64
child 6, seed: int64
child 7, steps: int64
pretrained_checkpoint: string
qwam_modified: bool
runtime: struct<cpu_affinity_count: int64, xla_flags: string>
child 0, cpu_affinity_count: int64
child 1, xla_flags: string
schema: string
smoke: bool
tokenizer_sha256: string
train_metrics: string
training_kind: string
upstream_revision: string
weights: string
norm_stats: struct<actions: struct<mean: list<item: double>, q01: list<item: double>, q99: list<item: double>, s (... 140 chars omitted)
child 0, actions: struct<mean: list<item: double>, q01: list<item: double>, q99: list<item: double>, std: list<item: d (... 7 chars omitted)
child 0, mean: list<item: double>
child 0, item: double
child 1, q01: list<item: double>
child 0, item: double
child 2, q99: list<item: double>
child 0, item: double
child 3, std: list<item: double>
child 0, item: double
child 1, state: struct<mean: list<item: double>, q01: list<item: double>, q99: list<item: double>, std: list<item: d (... 7 chars omitted)
child 0, mean: list<item: double>
child 0, item: double
child 1, q01: list<item: double>
child 0, item: double
child 2, q99: list<item: double>
child 0, item: double
child 3, std: list<item: double>
child 0, item: double
to
{'norm_stats': {'actions': {'mean': List(Value('float64')), 'q01': List(Value('float64')), 'q99': List(Value('float64')), 'std': List(Value('float64'))}, 'state': {'mean': List(Value('float64')), 'q01': List(Value('float64')), 'q99': List(Value('float64')), 'std': List(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.
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