Datasets:

---

ksshumab

/

hf_ckpt

like 0

Error code:   FeaturesError
Exception:    ArrowInvalid
Message:      Schema at index 1 was different: 
os: string
python: string
heartbeatAt: string
startedAt: string
docker: null
cuda: null
args: list<item: string>
state: string
program: string
codePath: string
git: struct<remote: string, commit: string>
email: string
root: string
host: string
username: string
executable: string
cpu_count: int64
cpu_count_logical: int64
cpu_freq: struct<current: double, min: double, max: double>
cpu_freq_per_core: list<item: struct<current: double, min: double, max: double>>
disk: struct<total: double, used: double>
gpu: string
gpu_count: int64
gpu_devices: list<item: struct<name: string, memory_total: int64>>
memory: struct<total: double>
vs
runtime/iteration_time: double
runtime/tflops_per_sec_per_gpu: double
runtime/tflops_per_sec: double
runtime/samples_per_sec_per_gpu: double
runtime/tokens_per_sec_per_gpu: double
train/loss: double
train/learning_rate: double
train/global_step: int64
train vs tokens/loss: double
train vs tokens/learning_rate: double
train vs tokens/consumed_train_tokens: int64
train/total_grad_norm: double
_timestamp: double
_runtime: double
_step: int64
_wandb: struct<runtime: int64>
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 231, in compute_first_rows_from_streaming_response
                  iterable_dataset = iterable_dataset._resolve_features()
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 3335, in _resolve_features
                  features = _infer_features_from_batch(self.with_format(None)._head())
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 2096, in _head
                  return next(iter(self.iter(batch_size=n)))
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 2296, in iter
                  for key, example in iterator:
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 1856, in __iter__
                  for key, pa_table in self._iter_arrow():
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 1878, in _iter_arrow
                  yield from self.ex_iterable._iter_arrow()
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 504, in _iter_arrow
                  yield new_key, pa.Table.from_batches(chunks_buffer)
                File "pyarrow/table.pxi", line 4116, in pyarrow.lib.Table.from_batches
                File "pyarrow/error.pxi", line 154, in pyarrow.lib.pyarrow_internal_check_status
                File "pyarrow/error.pxi", line 91, in pyarrow.lib.check_status
              pyarrow.lib.ArrowInvalid: Schema at index 1 was different: 
              os: string
              python: string
              heartbeatAt: string
              startedAt: string
              docker: null
              cuda: null
              args: list<item: string>
              state: string
              program: string
              codePath: string
              git: struct<remote: string, commit: string>
              email: string
              root: string
              host: string
              username: string
              executable: string
              cpu_count: int64
              cpu_count_logical: int64
              cpu_freq: struct<current: double, min: double, max: double>
              cpu_freq_per_core: list<item: struct<current: double, min: double, max: double>>
              disk: struct<total: double, used: double>
              gpu: string
              gpu_count: int64
              gpu_devices: list<item: struct<name: string, memory_total: int64>>
              memory: struct<total: double>
              vs
              runtime/iteration_time: double
              runtime/tflops_per_sec_per_gpu: double
              runtime/tflops_per_sec: double
              runtime/samples_per_sec_per_gpu: double
              runtime/tokens_per_sec_per_gpu: double
              train/loss: double
              train/learning_rate: double
              train/global_step: int64
              train vs tokens/loss: double
              train vs tokens/learning_rate: double
              train vs tokens/consumed_train_tokens: int64
              train/total_grad_norm: double
              _timestamp: double
              _runtime: double
              _step: int64
              _wandb: struct<runtime: int64>