Datasets:

---

codemaivanngu

/

shortcut-models-b200-runtime

Like 0

Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
status: string
same_device_independent_processes: struct<status: string, groups: list<item: struct<group: string, relative_l2: double, max_scaled: dou (... 65 chars omitted)
  child 0, status: string
  child 1, groups: list<item: struct<group: string, relative_l2: double, max_scaled: double, passed: bool>>
      child 0, item: struct<group: string, relative_l2: double, max_scaled: double, passed: bool>
          child 0, group: string
          child 1, relative_l2: double
          child 2, max_scaled: double
          child 3, passed: bool
  child 2, historical_tpu_parity: bool
  child 3, efficacy: bool
negative_gradient_control: string
fixture_sha256: string
contract_sha256: string
efficacy: bool
source_commit: string
reference_generation: string
adamw: struct<learning_rate: double, b1: double, b2: double, weight_decay: double>
  child 0, learning_rate: double
  child 1, b1: double
  child 2, b2: double
  child 3, weight_decay: double
model: struct<patch_size: int64, hidden_size: int64, depth: int64, num_heads: int64, mlp_ratio: int64, out_ (... 81 chars omitted)
  child 0, patch_size: int64
  child 1, hidden_size: int64
  child 2, depth: int64
  child 3, num_heads: int64
  child 4, mlp_ratio: int64
  child 5, out_channels: int64
  child 6, num_classes: int64
  child 7, class_dropout_prob: double
  child 8, ignore_dt: bool
rationale: string
steps: int64
thresholds: struct<target: struct<rel_l2: double, max_scaled: double, atol: double>, loss: struct<rel_l2: double (... 100 chars omitted)
  child 0, target: struct<rel_l2: double, max_scaled: double, atol: double>
      child 0, rel_l2: double
      child 1, max_scaled: double
      child 2, atol: double
  child 1, loss: struct<rel_l2: double, max_scaled: double, atol: double>
      child 0, rel_l2: double
      child 1, max_scaled: double
      child 2, atol: double
  child 2, bf16: struct<rel_l2: double, max_scaled: double, atol: double>
      child 0, rel_l2: double
      child 1, max_scaled: double
      child 2, atol: double
shape: list<item: int64>
  child 0, item: int64
schema: int64
scope: string
historical_tpu_parity: bool
flags: struct<class_dropout_prob: double, num_classes: int64, denoise_timesteps: int64, gmm_router_topk: in (... 196 chars omitted)
  child 0, class_dropout_prob: double
  child 1, num_classes: int64
  child 2, denoise_timesteps: int64
  child 3, gmm_router_topk: int64
  child 4, gmm_router_temperature: double
  child 5, gmm_router_gradient_mode: string
  child 6, gmm_router_gumbel_tau: double
  child 7, gmm_router_source_mode: string
  child 8, gmm_source_shift_mean: int64
  child 9, gmm_source_center_scale: double
batch: int64
ema_decay: double
to
{'schema': Value('int64'), 'scope': Value('string'), 'efficacy': Value('bool'), 'historical_tpu_parity': Value('bool'), 'batch': Value('int64'), 'shape': List(Value('int64')), 'model': {'patch_size': Value('int64'), 'hidden_size': Value('int64'), 'depth': Value('int64'), 'num_heads': Value('int64'), 'mlp_ratio': Value('int64'), 'out_channels': Value('int64'), 'num_classes': Value('int64'), 'class_dropout_prob': Value('float64'), 'ignore_dt': Value('bool')}, 'flags': {'class_dropout_prob': Value('float64'), 'num_classes': Value('int64'), 'denoise_timesteps': Value('int64'), 'gmm_router_topk': Value('int64'), 'gmm_router_temperature': Value('float64'), 'gmm_router_gradient_mode': Value('string'), 'gmm_router_gumbel_tau': Value('float64'), 'gmm_router_source_mode': Value('string'), 'gmm_source_shift_mean': Value('int64'), 'gmm_source_center_scale': Value('float64')}, 'steps': Value('int64'), 'ema_decay': Value('float64'), 'adamw': {'learning_rate': Value('float64'), 'b1': Value('float64'), 'b2': Value('float64'), 'weight_decay': Value('float64')}, 'thresholds': {'target': {'rel_l2': Value('float64'), 'max_scaled': Value('float64'), 'atol': Value('float64')}, 'loss': {'rel_l2': Value('float64'), 'max_scaled': Value('float64'), 'atol': Value('float64')}, 'bf16': {'rel_l2': Value('float64'), 'max_scaled': Value('float64'), 'atol': Value('float64')}}, 'rationale': 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 544, 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 3052, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2559, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2584, 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 558, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 440, 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 361, 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 2381, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2309, in cast_table_to_schema
                  raise CastError(
                  ...<3 lines>...
                  )
              datasets.table.CastError: Couldn't cast
              status: string
              same_device_independent_processes: struct<status: string, groups: list<item: struct<group: string, relative_l2: double, max_scaled: dou (... 65 chars omitted)
                child 0, status: string
                child 1, groups: list<item: struct<group: string, relative_l2: double, max_scaled: double, passed: bool>>
                    child 0, item: struct<group: string, relative_l2: double, max_scaled: double, passed: bool>
                        child 0, group: string
                        child 1, relative_l2: double
                        child 2, max_scaled: double
                        child 3, passed: bool
                child 2, historical_tpu_parity: bool
                child 3, efficacy: bool
              negative_gradient_control: string
              fixture_sha256: string
              contract_sha256: string
              efficacy: bool
              source_commit: string
              reference_generation: string
              adamw: struct<learning_rate: double, b1: double, b2: double, weight_decay: double>
                child 0, learning_rate: double
                child 1, b1: double
                child 2, b2: double
                child 3, weight_decay: double
              model: struct<patch_size: int64, hidden_size: int64, depth: int64, num_heads: int64, mlp_ratio: int64, out_ (... 81 chars omitted)
                child 0, patch_size: int64
                child 1, hidden_size: int64
                child 2, depth: int64
                child 3, num_heads: int64
                child 4, mlp_ratio: int64
                child 5, out_channels: int64
                child 6, num_classes: int64
                child 7, class_dropout_prob: double
                child 8, ignore_dt: bool
              rationale: string
              steps: int64
              thresholds: struct<target: struct<rel_l2: double, max_scaled: double, atol: double>, loss: struct<rel_l2: double (... 100 chars omitted)
                child 0, target: struct<rel_l2: double, max_scaled: double, atol: double>
                    child 0, rel_l2: double
                    child 1, max_scaled: double
                    child 2, atol: double
                child 1, loss: struct<rel_l2: double, max_scaled: double, atol: double>
                    child 0, rel_l2: double
                    child 1, max_scaled: double
                    child 2, atol: double
                child 2, bf16: struct<rel_l2: double, max_scaled: double, atol: double>
                    child 0, rel_l2: double
                    child 1, max_scaled: double
                    child 2, atol: double
              shape: list<item: int64>
                child 0, item: int64
              schema: int64
              scope: string
              historical_tpu_parity: bool
              flags: struct<class_dropout_prob: double, num_classes: int64, denoise_timesteps: int64, gmm_router_topk: in (... 196 chars omitted)
                child 0, class_dropout_prob: double
                child 1, num_classes: int64
                child 2, denoise_timesteps: int64
                child 3, gmm_router_topk: int64
                child 4, gmm_router_temperature: double
                child 5, gmm_router_gradient_mode: string
                child 6, gmm_router_gumbel_tau: double
                child 7, gmm_router_source_mode: string
                child 8, gmm_source_shift_mean: int64
                child 9, gmm_source_center_scale: double
              batch: int64
              ema_decay: double
              to
              {'schema': Value('int64'), 'scope': Value('string'), 'efficacy': Value('bool'), 'historical_tpu_parity': Value('bool'), 'batch': Value('int64'), 'shape': List(Value('int64')), 'model': {'patch_size': Value('int64'), 'hidden_size': Value('int64'), 'depth': Value('int64'), 'num_heads': Value('int64'), 'mlp_ratio': Value('int64'), 'out_channels': Value('int64'), 'num_classes': Value('int64'), 'class_dropout_prob': Value('float64'), 'ignore_dt': Value('bool')}, 'flags': {'class_dropout_prob': Value('float64'), 'num_classes': Value('int64'), 'denoise_timesteps': Value('int64'), 'gmm_router_topk': Value('int64'), 'gmm_router_temperature': Value('float64'), 'gmm_router_gradient_mode': Value('string'), 'gmm_router_gumbel_tau': Value('float64'), 'gmm_router_source_mode': Value('string'), 'gmm_source_shift_mean': Value('int64'), 'gmm_source_center_scale': Value('float64')}, 'steps': Value('int64'), 'ema_decay': Value('float64'), 'adamw': {'learning_rate': Value('float64'), 'b1': Value('float64'), 'b2': Value('float64'), 'weight_decay': Value('float64')}, 'thresholds': {'target': {'rel_l2': Value('float64'), 'max_scaled': Value('float64'), 'atol': Value('float64')}, 'loss': {'rel_l2': Value('float64'), 'max_scaled': Value('float64'), 'atol': Value('float64')}, 'bf16': {'rel_l2': Value('float64'), 'max_scaled': Value('float64'), 'atol': Value('float64')}}, 'rationale': Value('string')}
              because column names don't match