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
schema_version: int64
generated_at: string
window_steps: int64
min_windows_per_silo: int64
participant_count: int64
silos: list<item: struct<participant_id: string, data_source: string, data_format: string, episode_count: i (... 433 chars omitted)
child 0, item: struct<participant_id: string, data_source: string, data_format: string, episode_count: int64, windo (... 421 chars omitted)
child 0, participant_id: string
child 1, data_source: string
child 2, data_format: string
child 3, episode_count: int64
child 4, window_count: int64
child 5, dataset_root: string
child 6, dataset_commitment_schema_version: int64
child 7, hash_algorithm: string
child 8, wmcp_version: string
child 9, embodiment_ids: list<item: string>
child 0, item: string
child 10, action_spec: struct<embodiment_id: string, kind: string, dim: int64, low: list<item: double>, high: list<item: do (... 74 chars omitted)
child 0, embodiment_id: string
child 1, kind: string
child 2, dim: int64
child 3, low: list<item: double>
child 0, item: double
child 4, high: list<item: double>
child 0, item: double
child 5, num_classes: null
child 6, units: list<item: string>
child 0, item: string
child 7, wmcp_version: string
child 11, observation_shape: list<item: int64>
child 0, item: int64
child 12, action_sha
...
: string
child 3, license: string
child 4, raw_data_crosses_boundary: bool
child 5, smoke_report_sha256: string
child 6, smoke_report_uri: string
child 7, window_steps: int64
child 6, observation_contract: struct<contract_id: string, dtype: string, frame_skip: int64, shape: list<item: int64>, wmcp_version (... 9 chars omitted)
child 0, contract_id: string
child 1, dtype: string
child 2, frame_skip: int64
child 3, shape: list<item: int64>
child 0, item: int64
child 4, wmcp_version: string
child 7, participant_id: string
child 8, role: string
run_id: string
model: struct<base_checkpoint_ref: null, config_hash: null, lambda_anc: double, latent_dim: int64, model_fa (... 92 chars omitted)
child 0, base_checkpoint_ref: null
child 1, config_hash: null
child 2, lambda_anc: double
child 3, latent_dim: int64
child 4, model_family: string
child 5, num_tokens: int64
child 6, objective_target_stop_gradient: bool
child 7, wmcp_version: string
runtime: struct<dp_required: bool, dropout_retry_budget: int64, min_trainers: int64, protocol_version: string (... 91 chars omitted)
child 0, dp_required: bool
child 1, dropout_retry_budget: int64
child 2, min_trainers: int64
child 3, protocol_version: string
child 4, secure_aggregation_backend: string
child 5, secure_aggregation_required: bool
child 6, transport: string
consortium_id: string
to
{'accepted_action_contracts': List({'contract_id': Value('string'), 'dim': Value('int64'), 'embodiment_id': Value('string'), 'high': List(Value('float64')), 'kind': Value('string'), 'low': List(Value('float64')), 'num_classes': Value('null'), 'units': List(Value('string')), 'wmcp_version': Value('string')}), 'accepted_observation_contracts': List({'contract_id': Value('string'), 'dtype': Value('string'), 'frame_skip': Value('int64'), 'shape': List(Value('int64')), 'wmcp_version': Value('string')}), 'claim_boundary': Value('string'), 'consortium_id': Value('string'), 'coordinator_id': Value('string'), 'created_at': Value('timestamp[s]'), 'dp_policy': {'accountant': Value('string'), 'clip_norm': Value('float64'), 'delta': Value('float64'), 'enabled': Value('bool'), 'epsilon': Value('float64'), 'noise_multiplier': Value('float64')}, 'model': {'base_checkpoint_ref': Value('null'), 'config_hash': Value('null'), 'lambda_anc': Value('float64'), 'latent_dim': Value('int64'), 'model_family': Value('string'), 'num_tokens': Value('int64'), 'objective_target_stop_gradient': Value('bool'), 'wmcp_version': Value('string')}, 'participants': List({'accepted_probe_hash': Value('string'), 'accepted_probe_version': Value('int64'), 'action_contract': {'contract_id': Value('string'), 'dim': Value('int64'), 'embodiment_id': Value('string'), 'high': List(Value('float64')), 'kind': Value('string'), 'low': List(Value('float64')), 'num_classes': Value('null'), 'units': List(Value('string')), 'wmcp_version': Value('string')}, 'capabilities': {'dp_accountants': List(Value('string')), 'max_model_latent_dim': Value('int64'), 'network_transport': Value('bool'), 'private_data_mounts': Value('bool'), 'resumable': Value('bool'), 'secure_aggregation_backends': List(Value('string'))}, 'contact': {'contact': Value('string'), 'owner': Value('string')}, 'data': {'data_ref': Value('string'), 'format': Value('string'), 'heldout_policy': Value('string'), 'license': Value('string'), 'raw_data_crosses_boundary': Value('bool'), 'smoke_report_sha256': Value('string'), 'smoke_report_uri': Value('string'), 'window_steps': Value('int64')}, 'observation_contract': {'contract_id': Value('string'), 'dtype': Value('string'), 'frame_skip': Value('int64'), 'shape': List(Value('int64')), 'wmcp_version': Value('string')}, 'participant_id': Value('string'), 'role': Value('string')}), 'public_probe': {'content_hash': Value('string'), 'probe_id': Value('string'), 'version': Value('int64')}, 'run_id': Value('string'), 'runtime': {'dp_required': Value('bool'), 'dropout_retry_budget': Value('int64'), 'min_trainers': Value('int64'), 'protocol_version': Value('string'), 'secure_aggregation_backend': Value('string'), 'secure_aggregation_required': Value('bool'), 'transport': Value('string')}, 'schema_version': Value('int64')}
because column names don't match
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 99, in get_rows_or_raise
return get_rows(
^^^^^^^^^
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 77, in get_rows
rows_plus_one = list(itertools.islice(ds, rows_max_number + 1))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2815, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2352, in __iter__
for key, pa_table in self._iter_arrow():
^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2377, in _iter_arrow
for key, pa_table in self.ex_iterable._iter_arrow():
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 536, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.12/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/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 310, in _generate_tables
self._cast_table(pa_table, json_field_paths=json_field_paths),
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 130, in _cast_table
pa_table = table_cast(pa_table, self.info.features.arrow_schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2369, in table_cast
return cast_table_to_schema(table, schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2297, in cast_table_to_schema
raise CastError(
datasets.table.CastError: Couldn't cast
schema_version: int64
generated_at: string
window_steps: int64
min_windows_per_silo: int64
participant_count: int64
silos: list<item: struct<participant_id: string, data_source: string, data_format: string, episode_count: i (... 433 chars omitted)
child 0, item: struct<participant_id: string, data_source: string, data_format: string, episode_count: int64, windo (... 421 chars omitted)
child 0, participant_id: string
child 1, data_source: string
child 2, data_format: string
child 3, episode_count: int64
child 4, window_count: int64
child 5, dataset_root: string
child 6, dataset_commitment_schema_version: int64
child 7, hash_algorithm: string
child 8, wmcp_version: string
child 9, embodiment_ids: list<item: string>
child 0, item: string
child 10, action_spec: struct<embodiment_id: string, kind: string, dim: int64, low: list<item: double>, high: list<item: do (... 74 chars omitted)
child 0, embodiment_id: string
child 1, kind: string
child 2, dim: int64
child 3, low: list<item: double>
child 0, item: double
child 4, high: list<item: double>
child 0, item: double
child 5, num_classes: null
child 6, units: list<item: string>
child 0, item: string
child 7, wmcp_version: string
child 11, observation_shape: list<item: int64>
child 0, item: int64
child 12, action_sha
...
: string
child 3, license: string
child 4, raw_data_crosses_boundary: bool
child 5, smoke_report_sha256: string
child 6, smoke_report_uri: string
child 7, window_steps: int64
child 6, observation_contract: struct<contract_id: string, dtype: string, frame_skip: int64, shape: list<item: int64>, wmcp_version (... 9 chars omitted)
child 0, contract_id: string
child 1, dtype: string
child 2, frame_skip: int64
child 3, shape: list<item: int64>
child 0, item: int64
child 4, wmcp_version: string
child 7, participant_id: string
child 8, role: string
run_id: string
model: struct<base_checkpoint_ref: null, config_hash: null, lambda_anc: double, latent_dim: int64, model_fa (... 92 chars omitted)
child 0, base_checkpoint_ref: null
child 1, config_hash: null
child 2, lambda_anc: double
child 3, latent_dim: int64
child 4, model_family: string
child 5, num_tokens: int64
child 6, objective_target_stop_gradient: bool
child 7, wmcp_version: string
runtime: struct<dp_required: bool, dropout_retry_budget: int64, min_trainers: int64, protocol_version: string (... 91 chars omitted)
child 0, dp_required: bool
child 1, dropout_retry_budget: int64
child 2, min_trainers: int64
child 3, protocol_version: string
child 4, secure_aggregation_backend: string
child 5, secure_aggregation_required: bool
child 6, transport: string
consortium_id: string
to
{'accepted_action_contracts': List({'contract_id': Value('string'), 'dim': Value('int64'), 'embodiment_id': Value('string'), 'high': List(Value('float64')), 'kind': Value('string'), 'low': List(Value('float64')), 'num_classes': Value('null'), 'units': List(Value('string')), 'wmcp_version': Value('string')}), 'accepted_observation_contracts': List({'contract_id': Value('string'), 'dtype': Value('string'), 'frame_skip': Value('int64'), 'shape': List(Value('int64')), 'wmcp_version': Value('string')}), 'claim_boundary': Value('string'), 'consortium_id': Value('string'), 'coordinator_id': Value('string'), 'created_at': Value('timestamp[s]'), 'dp_policy': {'accountant': Value('string'), 'clip_norm': Value('float64'), 'delta': Value('float64'), 'enabled': Value('bool'), 'epsilon': Value('float64'), 'noise_multiplier': Value('float64')}, 'model': {'base_checkpoint_ref': Value('null'), 'config_hash': Value('null'), 'lambda_anc': Value('float64'), 'latent_dim': Value('int64'), 'model_family': Value('string'), 'num_tokens': Value('int64'), 'objective_target_stop_gradient': Value('bool'), 'wmcp_version': Value('string')}, 'participants': List({'accepted_probe_hash': Value('string'), 'accepted_probe_version': Value('int64'), 'action_contract': {'contract_id': Value('string'), 'dim': Value('int64'), 'embodiment_id': Value('string'), 'high': List(Value('float64')), 'kind': Value('string'), 'low': List(Value('float64')), 'num_classes': Value('null'), 'units': List(Value('string')), 'wmcp_version': Value('string')}, 'capabilities': {'dp_accountants': List(Value('string')), 'max_model_latent_dim': Value('int64'), 'network_transport': Value('bool'), 'private_data_mounts': Value('bool'), 'resumable': Value('bool'), 'secure_aggregation_backends': List(Value('string'))}, 'contact': {'contact': Value('string'), 'owner': Value('string')}, 'data': {'data_ref': Value('string'), 'format': Value('string'), 'heldout_policy': Value('string'), 'license': Value('string'), 'raw_data_crosses_boundary': Value('bool'), 'smoke_report_sha256': Value('string'), 'smoke_report_uri': Value('string'), 'window_steps': Value('int64')}, 'observation_contract': {'contract_id': Value('string'), 'dtype': Value('string'), 'frame_skip': Value('int64'), 'shape': List(Value('int64')), 'wmcp_version': Value('string')}, 'participant_id': Value('string'), 'role': Value('string')}), 'public_probe': {'content_hash': Value('string'), 'probe_id': Value('string'), 'version': Value('int64')}, 'run_id': Value('string'), 'runtime': {'dp_required': Value('bool'), 'dropout_retry_budget': Value('int64'), 'min_trainers': Value('int64'), 'protocol_version': Value('string'), 'secure_aggregation_backend': Value('string'), 'secure_aggregation_required': Value('bool'), 'transport': Value('string')}, 'schema_version': Value('int64')}
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.
Lensemble Phase 3 — SO-100 consortium silos + held-out eval split
Deterministic episode-modulo split (k % 5) of the public SO-100 pick-place set
abdelstark/so100-pickplace-lewm-ready
into four sovereign participant silos plus one disjoint held-out eval split, for the Phase 3
federated JEPA / LeWorldModel consortium run (Lensemble epic #249, issue #242).
| file | role | episodes | windows (window_steps=4) |
dataset Merkle root (sha256, prefix) |
|---|---|---|---|---|
phase3-so100-silo0.h5 |
participant phase3-so100-a |
10 | 1284 | 75889fe338dae47e |
phase3-so100-silo1.h5 |
participant phase3-so100-b |
10 | 1339 | ef9bed423ef5f2fe |
phase3-so100-silo2.h5 |
participant phase3-so100-c |
10 | 1261 | 916cfbb514ee03cd |
phase3-so100-silo3.h5 |
participant phase3-so100-d |
10 | 1259 | fdd0caf3976e9f99 |
phase3-so100-silo4.h5 |
held-out eval split phase3-so100-heldout |
10 | 1216 | b0f9b6514a33ee85 |
Frames are never duplicated across files; episode_index is remapped to local 0-based ids. Every silo
shares the lerobot-6dof continuous action spec and (5, 1, 3, 224, 224) window observation shape.
Companion artifacts
phase3_silo_split_manifest.json— the deterministic split manifest (source sha256, per-silo episode ids).phase3_dataset_smoke.json— combined residency-safe smoke report (window counts, Merkle roots, shapes; no raw arrays).smoke/phase3-so100-{a,b,c,d}.json— per-participant residency-safe smoke reports.phase3_public_probe_spec.json— the pinned public-probe spec; its content hash is reproducible from(seed, probe_points, num_frames, image_size)alone.phase3_consortium_manifest.json/phase3_long_run_dataset_registry.json— the agreed consortium manifest and the validated dataset/probe registry (all four participantspublished, zero placeholders).
Residency boundary
These are residency-safe published silos for a consortium-engineering + training demonstration. Raw trajectories never cross a participant boundary at run time; only pseudo-gradients and residency-safe metadata do. This is not a provenance ledger or a cryptographic proof of honest computation.
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