Datasets:

---

HoangTrungNguyen

/

TinyPerson_training

Like 0

Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
image_id: int64
category_id: int64
bbox: list<item: double>
  child 0, item: double
score: double
batch_size: int64
torch: string
tinybenchmark_merged: struct<AP50: double, AP75: double, mAP50-75: double, AP50_tiny: double, AP50_tiny1: double, AP50_tin (... 72 chars omitted)
  child 0, AP50: double
  child 1, AP75: double
  child 2, mAP50-75: double
  child 3, AP50_tiny: double
  child 4, AP50_tiny1: double
  child 5, AP50_tiny2: double
  child 6, AP50_tiny3: double
  child 7, AP50_small: double
  child 8, AP50_medium: double
runtime_seconds: double
pretrained_transfer: struct<total: int64, direct: int64, backbone_remapped: int64, input_conv_adapted: int64, repc2f_repa (... 35 chars omitted)
  child 0, total: int64
  child 1, direct: int64
  child 2, backbone_remapped: int64
  child 3, input_conv_adapted: int64
  child 4, repc2f_reparameterized: int64
  child 5, method: string
pretrained: string
best_checkpoint: string
case: string
metrics: struct<val: struct<bbox_mAP: double, bbox_mAP_50: double, bbox_mAP_75: double, precision: double, re (... 123 chars omitted)
  child 0, val: struct<bbox_mAP: double, bbox_mAP_50: double, bbox_mAP_75: double, precision: double, recall: double (... 1 chars omitted)
      child 0, bbox_mAP: double
      child 1, bbox_mAP_50: double
      child 2, bbox_mAP_75: double
      child 3, precision: double
      child 4, recall: double
  child 1, test: struct<bbox_mAP: double, bbox_mAP_50: double, bbox_mAP_75: double, precision: double, recall: double (... 1 chars omitted)
      child 0, bbox_mAP: double
      child 1, bbox_mAP_50: double
      child 2, bbox_mAP_75: double
      child 3, precision: double
      child 4, recall: double
gpu: string
image_size: int64
gflops: double
cuda: string
epochs: int64
parameters: int64
learned_guidance: struct<>
seed: int64
trainable_parameters: int64
to
{'case': Value('string'), 'seed': Value('int64'), 'pretrained': Value('string'), 'pretrained_transfer': {'total': Value('int64'), 'direct': Value('int64'), 'backbone_remapped': Value('int64'), 'input_conv_adapted': Value('int64'), 'repc2f_reparameterized': Value('int64'), 'method': Value('string')}, 'epochs': Value('int64'), 'image_size': Value('int64'), 'batch_size': Value('int64'), 'parameters': Value('int64'), 'trainable_parameters': Value('int64'), 'gflops': Value('float64'), 'tinybenchmark_merged': {'AP50': Value('float64'), 'AP75': Value('float64'), 'mAP50-75': Value('float64'), 'AP50_tiny': Value('float64'), 'AP50_tiny1': Value('float64'), 'AP50_tiny2': Value('float64'), 'AP50_tiny3': Value('float64'), 'AP50_small': Value('float64'), 'AP50_medium': Value('float64')}, 'runtime_seconds': Value('float64'), 'best_checkpoint': Value('string'), 'learned_guidance': {}, 'metrics': {'val': {'bbox_mAP': Value('float64'), 'bbox_mAP_50': Value('float64'), 'bbox_mAP_75': Value('float64'), 'precision': Value('float64'), 'recall': Value('float64')}, 'test': {'bbox_mAP': Value('float64'), 'bbox_mAP_50': Value('float64'), 'bbox_mAP_75': Value('float64'), 'precision': Value('float64'), 'recall': Value('float64')}}, 'torch': Value('string'), 'cuda': Value('string'), 'gpu': Value('string')}
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
              image_id: int64
              category_id: int64
              bbox: list<item: double>
                child 0, item: double
              score: double
              batch_size: int64
              torch: string
              tinybenchmark_merged: struct<AP50: double, AP75: double, mAP50-75: double, AP50_tiny: double, AP50_tiny1: double, AP50_tin (... 72 chars omitted)
                child 0, AP50: double
                child 1, AP75: double
                child 2, mAP50-75: double
                child 3, AP50_tiny: double
                child 4, AP50_tiny1: double
                child 5, AP50_tiny2: double
                child 6, AP50_tiny3: double
                child 7, AP50_small: double
                child 8, AP50_medium: double
              runtime_seconds: double
              pretrained_transfer: struct<total: int64, direct: int64, backbone_remapped: int64, input_conv_adapted: int64, repc2f_repa (... 35 chars omitted)
                child 0, total: int64
                child 1, direct: int64
                child 2, backbone_remapped: int64
                child 3, input_conv_adapted: int64
                child 4, repc2f_reparameterized: int64
                child 5, method: string
              pretrained: string
              best_checkpoint: string
              case: string
              metrics: struct<val: struct<bbox_mAP: double, bbox_mAP_50: double, bbox_mAP_75: double, precision: double, re (... 123 chars omitted)
                child 0, val: struct<bbox_mAP: double, bbox_mAP_50: double, bbox_mAP_75: double, precision: double, recall: double (... 1 chars omitted)
                    child 0, bbox_mAP: double
                    child 1, bbox_mAP_50: double
                    child 2, bbox_mAP_75: double
                    child 3, precision: double
                    child 4, recall: double
                child 1, test: struct<bbox_mAP: double, bbox_mAP_50: double, bbox_mAP_75: double, precision: double, recall: double (... 1 chars omitted)
                    child 0, bbox_mAP: double
                    child 1, bbox_mAP_50: double
                    child 2, bbox_mAP_75: double
                    child 3, precision: double
                    child 4, recall: double
              gpu: string
              image_size: int64
              gflops: double
              cuda: string
              epochs: int64
              parameters: int64
              learned_guidance: struct<>
              seed: int64
              trainable_parameters: int64
              to
              {'case': Value('string'), 'seed': Value('int64'), 'pretrained': Value('string'), 'pretrained_transfer': {'total': Value('int64'), 'direct': Value('int64'), 'backbone_remapped': Value('int64'), 'input_conv_adapted': Value('int64'), 'repc2f_reparameterized': Value('int64'), 'method': Value('string')}, 'epochs': Value('int64'), 'image_size': Value('int64'), 'batch_size': Value('int64'), 'parameters': Value('int64'), 'trainable_parameters': Value('int64'), 'gflops': Value('float64'), 'tinybenchmark_merged': {'AP50': Value('float64'), 'AP75': Value('float64'), 'mAP50-75': Value('float64'), 'AP50_tiny': Value('float64'), 'AP50_tiny1': Value('float64'), 'AP50_tiny2': Value('float64'), 'AP50_tiny3': Value('float64'), 'AP50_small': Value('float64'), 'AP50_medium': Value('float64')}, 'runtime_seconds': Value('float64'), 'best_checkpoint': Value('string'), 'learned_guidance': {}, 'metrics': {'val': {'bbox_mAP': Value('float64'), 'bbox_mAP_50': Value('float64'), 'bbox_mAP_75': Value('float64'), 'precision': Value('float64'), 'recall': Value('float64')}, 'test': {'bbox_mAP': Value('float64'), 'bbox_mAP_50': Value('float64'), 'bbox_mAP_75': Value('float64'), 'precision': Value('float64'), 'recall': Value('float64')}}, 'torch': Value('string'), 'cuda': Value('string'), 'gpu': Value('string')}
              because column names don't match