Datasets:

---

GUI-Gym

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qwen3.8-27b-android-world

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GUI-Gym 3

Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
model: string
benchmark: string
runs: int64
tasks_per_run: int64
run_success: struct<1: string, 2: string>
  child 0, 1: string
  child 1, 2: string
mean_success_rate: double
combined: string
pass_at_2: int64
time: double
served_model_name: string
serving: struct<vllm: string, instances: list<item: struct<gpus: list<item: int64>, port: int64, tensor_paral (... 133 chars omitted)
  child 0, vllm: string
  child 1, instances: list<item: struct<gpus: list<item: int64>, port: int64, tensor_parallel: int64, gpu_memory_utilizati (... 100 chars omitted)
      child 0, item: struct<gpus: list<item: int64>, port: int64, tensor_parallel: int64, gpu_memory_utilization: double, (... 88 chars omitted)
          child 0, gpus: list<item: int64>
              child 0, item: int64
          child 1, port: int64
          child 2, tensor_parallel: int64
          child 3, gpu_memory_utilization: double
          child 4, max_model_len: int64
          child 5, max_num_seqs: int64
          child 6, seed: int64
          child 7, extra_args: list<item: string>
              child 0, item: string
sampling: struct<temperature: int64, top_p: int64, max_tokens: int64, request_seed: null, thinking: bool, engi (... 15 chars omitted)
  child 0, temperature: int64
  child 1, top_p: int64
  child 2, max_tokens: int64
  child 3, request_seed: null
  child 4, thinking: bool
  child 5, engine_seed: int64
eval_tag: string
campaign: string
agent: struct<type: string, class: string, name: string, prompt_name: string, screenshot_only: bool, histor (... 84 chars omitted)
  child 0, type: string
  child 1, class: string
  child 2, name: string
  child 3, prompt_name: string
  child 4, screenshot_only: bool
  child 5, history_len: int64
  child 6, n_history_image: int64
  child 7, wait_after_action_seconds: double
  child 8, hint: bool
evaluation: struct<suite_family: string, tasks: int64, workers: int64, seeds: list<item: int64>, repeats_per_see (... 151 chars omitted)
  child 0, suite_family: string
  child 1, tasks: int64
  child 2, workers: int64
  child 3, seeds: list<item: int64>
      child 0, item: int64
  child 4, repeats_per_seed: int64
  child 5, seed_semantics: string
  child 6, step_budget: string
  child 7, entry: string
  child 8, config_name: string
  child 9, docker_image_built: string
  child 10, avd: string
  child 11, avd_volume: string
endpoint: string
to
{'model': Value('string'), 'served_model_name': Value('string'), 'serving': {'vllm': Value('string'), 'instances': List({'gpus': List(Value('int64')), 'port': Value('int64'), 'tensor_parallel': Value('int64'), 'gpu_memory_utilization': Value('float64'), 'max_model_len': Value('int64'), 'max_num_seqs': Value('int64'), 'seed': Value('int64'), 'extra_args': List(Value('string'))})}, 'agent': {'type': Value('string'), 'class': Value('string'), 'name': Value('string'), 'prompt_name': Value('string'), 'screenshot_only': Value('bool'), 'history_len': Value('int64'), 'n_history_image': Value('int64'), 'wait_after_action_seconds': Value('float64'), 'hint': Value('bool')}, 'sampling': {'temperature': Value('int64'), 'top_p': Value('int64'), 'max_tokens': Value('int64'), 'request_seed': Value('null'), 'thinking': Value('bool'), 'engine_seed': Value('int64')}, 'evaluation': {'suite_family': Value('string'), 'tasks': Value('int64'), 'workers': Value('int64'), 'seeds': List(Value('int64')), 'repeats_per_seed': Value('int64'), 'seed_semantics': Value('string'), 'step_budget': Value('string'), 'entry': Value('string'), 'config_name': Value('string'), 'docker_image_built': Value('string'), 'avd': Value('string'), 'avd_volume': Value('string')}, 'endpoint': Value('string'), 'campaign': Value('string'), 'eval_tag': Value('string'), 'time': Value('float64')}
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
              model: string
              benchmark: string
              runs: int64
              tasks_per_run: int64
              run_success: struct<1: string, 2: string>
                child 0, 1: string
                child 1, 2: string
              mean_success_rate: double
              combined: string
              pass_at_2: int64
              time: double
              served_model_name: string
              serving: struct<vllm: string, instances: list<item: struct<gpus: list<item: int64>, port: int64, tensor_paral (... 133 chars omitted)
                child 0, vllm: string
                child 1, instances: list<item: struct<gpus: list<item: int64>, port: int64, tensor_parallel: int64, gpu_memory_utilizati (... 100 chars omitted)
                    child 0, item: struct<gpus: list<item: int64>, port: int64, tensor_parallel: int64, gpu_memory_utilization: double, (... 88 chars omitted)
                        child 0, gpus: list<item: int64>
                            child 0, item: int64
                        child 1, port: int64
                        child 2, tensor_parallel: int64
                        child 3, gpu_memory_utilization: double
                        child 4, max_model_len: int64
                        child 5, max_num_seqs: int64
                        child 6, seed: int64
                        child 7, extra_args: list<item: string>
                            child 0, item: string
              sampling: struct<temperature: int64, top_p: int64, max_tokens: int64, request_seed: null, thinking: bool, engi (... 15 chars omitted)
                child 0, temperature: int64
                child 1, top_p: int64
                child 2, max_tokens: int64
                child 3, request_seed: null
                child 4, thinking: bool
                child 5, engine_seed: int64
              eval_tag: string
              campaign: string
              agent: struct<type: string, class: string, name: string, prompt_name: string, screenshot_only: bool, histor (... 84 chars omitted)
                child 0, type: string
                child 1, class: string
                child 2, name: string
                child 3, prompt_name: string
                child 4, screenshot_only: bool
                child 5, history_len: int64
                child 6, n_history_image: int64
                child 7, wait_after_action_seconds: double
                child 8, hint: bool
              evaluation: struct<suite_family: string, tasks: int64, workers: int64, seeds: list<item: int64>, repeats_per_see (... 151 chars omitted)
                child 0, suite_family: string
                child 1, tasks: int64
                child 2, workers: int64
                child 3, seeds: list<item: int64>
                    child 0, item: int64
                child 4, repeats_per_seed: int64
                child 5, seed_semantics: string
                child 6, step_budget: string
                child 7, entry: string
                child 8, config_name: string
                child 9, docker_image_built: string
                child 10, avd: string
                child 11, avd_volume: string
              endpoint: string
              to
              {'model': Value('string'), 'served_model_name': Value('string'), 'serving': {'vllm': Value('string'), 'instances': List({'gpus': List(Value('int64')), 'port': Value('int64'), 'tensor_parallel': Value('int64'), 'gpu_memory_utilization': Value('float64'), 'max_model_len': Value('int64'), 'max_num_seqs': Value('int64'), 'seed': Value('int64'), 'extra_args': List(Value('string'))})}, 'agent': {'type': Value('string'), 'class': Value('string'), 'name': Value('string'), 'prompt_name': Value('string'), 'screenshot_only': Value('bool'), 'history_len': Value('int64'), 'n_history_image': Value('int64'), 'wait_after_action_seconds': Value('float64'), 'hint': Value('bool')}, 'sampling': {'temperature': Value('int64'), 'top_p': Value('int64'), 'max_tokens': Value('int64'), 'request_seed': Value('null'), 'thinking': Value('bool'), 'engine_seed': Value('int64')}, 'evaluation': {'suite_family': Value('string'), 'tasks': Value('int64'), 'workers': Value('int64'), 'seeds': List(Value('int64')), 'repeats_per_seed': Value('int64'), 'seed_semantics': Value('string'), 'step_budget': Value('string'), 'entry': Value('string'), 'config_name': Value('string'), 'docker_image_built': Value('string'), 'avd': Value('string'), 'avd_volume': Value('string')}, 'endpoint': Value('string'), 'campaign': Value('string'), 'eval_tag': Value('string'), 'time': Value('float64')}
              because column names don't match