Datasets:

---

StarStick

/

PlanarGSExperiments

like 0

Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
scene_name: string
dataset_path: string
total_combinations: int64
timestamp: string
results: list<item: struct<combination: string, results: struct<SSIM: double, PSNR: double, LPIPS: double, tr (... 214 chars omitted)
  child 0, item: struct<combination: string, results: struct<SSIM: double, PSNR: double, LPIPS: double, training_time (... 202 chars omitted)
      child 0, combination: string
      child 1, results: struct<SSIM: double, PSNR: double, LPIPS: double, training_time_seconds: double, num_gaussians: int6 (... 91 chars omitted)
          child 0, SSIM: double
          child 1, PSNR: double
          child 2, LPIPS: double
          child 3, training_time_seconds: double
          child 4, num_gaussians: int64
          child 5, point_cloud_size_mb: double
          child 6, combination: string
          child 7, scene_name: string
          child 8, timestamp: string
      child 2, status: string
      child 3, training_time: double
      child 4, error: string
      child 5, timestamp: string
_metadata: struct<model_path: string, selected_method: string, combination: string, scene_name: string, trainin (... 93 chars omitted)
  child 0, model_path: string
  child 1, selected_method: string
  child 2, combination: string
  child 3, scene_name: string
  child 4, training_time_seconds: double
  child 5, num_gaussians: int64
  child 6, point_cloud_size_mb: double
  child 7, timestamp: string
ours_30000: struct<SSIM: double, PSNR: double, LPIPS: double, training_time_seconds: double, num_gaussians: int6 (... 91 chars omitted)
  child 0, SSIM: double
  child 1, PSNR: double
  child 2, LPIPS: double
  child 3, training_time_seconds: double
  child 4, num_gaussians: int64
  child 5, point_cloud_size_mb: double
  child 6, combination: string
  child 7, scene_name: string
  child 8, timestamp: string
to
{'ours_30000': {'SSIM': Value('float64'), 'PSNR': Value('float64'), 'LPIPS': Value('float64'), 'training_time_seconds': Value('float64'), 'num_gaussians': Value('int64'), 'point_cloud_size_mb': Value('float64'), 'combination': Value('string'), 'scene_name': Value('string'), 'timestamp': Value('string')}, '_metadata': {'model_path': Value('string'), 'selected_method': Value('string'), 'combination': Value('string'), 'scene_name': Value('string'), 'training_time_seconds': Value('float64'), 'num_gaussians': Value('int64'), 'point_cloud_size_mb': Value('float64'), 'timestamp': Value('string')}}
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 2690, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2227, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2251, 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 494, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 384, 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 289, 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 124, 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 2272, in table_cast
                  return cast_table_to_schema(table, schema)
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2218, in cast_table_to_schema
                  raise CastError(
              datasets.table.CastError: Couldn't cast
              scene_name: string
              dataset_path: string
              total_combinations: int64
              timestamp: string
              results: list<item: struct<combination: string, results: struct<SSIM: double, PSNR: double, LPIPS: double, tr (... 214 chars omitted)
                child 0, item: struct<combination: string, results: struct<SSIM: double, PSNR: double, LPIPS: double, training_time (... 202 chars omitted)
                    child 0, combination: string
                    child 1, results: struct<SSIM: double, PSNR: double, LPIPS: double, training_time_seconds: double, num_gaussians: int6 (... 91 chars omitted)
                        child 0, SSIM: double
                        child 1, PSNR: double
                        child 2, LPIPS: double
                        child 3, training_time_seconds: double
                        child 4, num_gaussians: int64
                        child 5, point_cloud_size_mb: double
                        child 6, combination: string
                        child 7, scene_name: string
                        child 8, timestamp: string
                    child 2, status: string
                    child 3, training_time: double
                    child 4, error: string
                    child 5, timestamp: string
              _metadata: struct<model_path: string, selected_method: string, combination: string, scene_name: string, trainin (... 93 chars omitted)
                child 0, model_path: string
                child 1, selected_method: string
                child 2, combination: string
                child 3, scene_name: string
                child 4, training_time_seconds: double
                child 5, num_gaussians: int64
                child 6, point_cloud_size_mb: double
                child 7, timestamp: string
              ours_30000: struct<SSIM: double, PSNR: double, LPIPS: double, training_time_seconds: double, num_gaussians: int6 (... 91 chars omitted)
                child 0, SSIM: double
                child 1, PSNR: double
                child 2, LPIPS: double
                child 3, training_time_seconds: double
                child 4, num_gaussians: int64
                child 5, point_cloud_size_mb: double
                child 6, combination: string
                child 7, scene_name: string
                child 8, timestamp: string
              to
              {'ours_30000': {'SSIM': Value('float64'), 'PSNR': Value('float64'), 'LPIPS': Value('float64'), 'training_time_seconds': Value('float64'), 'num_gaussians': Value('int64'), 'point_cloud_size_mb': Value('float64'), 'combination': Value('string'), 'scene_name': Value('string'), 'timestamp': Value('string')}, '_metadata': {'model_path': Value('string'), 'selected_method': Value('string'), 'combination': Value('string'), 'scene_name': Value('string'), 'training_time_seconds': Value('float64'), 'num_gaussians': Value('int64'), 'point_cloud_size_mb': Value('float64'), 'timestamp': Value('string')}}
              because column names don't match