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Datasets:
gdelatournelle
/
laya-onnx-bench

Tasks:
Text Classification
Languages:
English
Tags:
decision-model
calibration
onnx
laya
License:
Dataset card Files
xet
 Community
Dataset Viewer
Duplicate
The dataset viewer is not available for this split.
Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
id: string
state: string
questions: struct<department: struct<type: string, instructions: string, criteria: struct<billing: string, tech (... 239 chars omitted)
  child 0, department: struct<type: string, instructions: string, criteria: struct<billing: string, technical: string, sale (... 26 chars omitted)
      child 0, type: string
      child 1, instructions: string
      child 2, criteria: struct<billing: string, technical: string, sales: string, other: string>
          child 0, billing: string
          child 1, technical: string
          child 2, sales: string
          child 3, other: string
  child 1, refund: struct<type: string, instructions: string>
      child 0, type: string
      child 1, instructions: string
  child 2, system_error: struct<type: string, instructions: string>
      child 0, type: string
      child 1, instructions: string
  child 3, urgency: struct<type: string, instructions: string, criteria: list<item: string>>
      child 0, type: string
      child 1, instructions: string
      child 2, criteria: list<item: string>
          child 0, item: string
gold: struct<department: string, refund: bool, system_error: bool, urgency: int64>
  child 0, department: string
  child 1, refund: bool
  child 2, system_error: bool
  child 3, urgency: int64
algorithm: string
repo: string
source: string
revision: string
files: struct<laya.onnx: struct<size: int64, sha256: string>, laya.onnx.data: struct<size: int64, sha256: s (... 195 chars omitted)
  child 0, laya.onnx: struct<size: int64, sha256: string>
      child 0, size: int64
      child 1, sha256: string
  child 1, laya.onnx.data: struct<size: int64, sha256: string>
      child 0, size: int64
      child 1, sha256: string
  child 2, laya_config.json: struct<size: int64, sha256: string>
      child 0, size: int64
      child 1, sha256: string
  child 3, tokenizer/tokenizer.json: struct<size: int64, sha256: string>
      child 0, size: int64
      child 1, sha256: string
  child 4, tokenizer/tokenizer_config.json: struct<size: int64, sha256: string>
      child 0, size: int64
      child 1, sha256: string
to
{'repo': Value('string'), 'revision': Value('string'), 'source': Value('string'), 'algorithm': Value('string'), 'files': {'laya.onnx': {'size': Value('int64'), 'sha256': Value('string')}, 'laya.onnx.data': {'size': Value('int64'), 'sha256': Value('string')}, 'laya_config.json': {'size': Value('int64'), 'sha256': Value('string')}, 'tokenizer/tokenizer.json': {'size': Value('int64'), 'sha256': Value('string')}, 'tokenizer/tokenizer_config.json': {'size': Value('int64'), 'sha256': 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 2840, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2373, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2398, 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 536, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 419, 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
              id: string
              state: string
              questions: struct<department: struct<type: string, instructions: string, criteria: struct<billing: string, tech (... 239 chars omitted)
                child 0, department: struct<type: string, instructions: string, criteria: struct<billing: string, technical: string, sale (... 26 chars omitted)
                    child 0, type: string
                    child 1, instructions: string
                    child 2, criteria: struct<billing: string, technical: string, sales: string, other: string>
                        child 0, billing: string
                        child 1, technical: string
                        child 2, sales: string
                        child 3, other: string
                child 1, refund: struct<type: string, instructions: string>
                    child 0, type: string
                    child 1, instructions: string
                child 2, system_error: struct<type: string, instructions: string>
                    child 0, type: string
                    child 1, instructions: string
                child 3, urgency: struct<type: string, instructions: string, criteria: list<item: string>>
                    child 0, type: string
                    child 1, instructions: string
                    child 2, criteria: list<item: string>
                        child 0, item: string
              gold: struct<department: string, refund: bool, system_error: bool, urgency: int64>
                child 0, department: string
                child 1, refund: bool
                child 2, system_error: bool
                child 3, urgency: int64
              algorithm: string
              repo: string
              source: string
              revision: string
              files: struct<laya.onnx: struct<size: int64, sha256: string>, laya.onnx.data: struct<size: int64, sha256: s (... 195 chars omitted)
                child 0, laya.onnx: struct<size: int64, sha256: string>
                    child 0, size: int64
                    child 1, sha256: string
                child 1, laya.onnx.data: struct<size: int64, sha256: string>
                    child 0, size: int64
                    child 1, sha256: string
                child 2, laya_config.json: struct<size: int64, sha256: string>
                    child 0, size: int64
                    child 1, sha256: string
                child 3, tokenizer/tokenizer.json: struct<size: int64, sha256: string>
                    child 0, size: int64
                    child 1, sha256: string
                child 4, tokenizer/tokenizer_config.json: struct<size: int64, sha256: string>
                    child 0, size: int64
                    child 1, sha256: string
              to
              {'repo': Value('string'), 'revision': Value('string'), 'source': Value('string'), 'algorithm': Value('string'), 'files': {'laya.onnx': {'size': Value('int64'), 'sha256': Value('string')}, 'laya.onnx.data': {'size': Value('int64'), 'sha256': Value('string')}, 'laya_config.json': {'size': Value('int64'), 'sha256': Value('string')}, 'tokenizer/tokenizer.json': {'size': Value('int64'), 'sha256': Value('string')}, 'tokenizer/tokenizer_config.json': {'size': Value('int64'), 'sha256': Value('string')}}}
              because column names don't match

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laya-onnx decision eval

A small, reproducible self-check for laya-onnx — an ONNX Runtime backend for Laya typed System-1 decisions (choice / score / noul, no generated tokens).

Files

file what
decisions.jsonl 8 labeled states / 10 questions with gold answers
results.json raw published results (accuracy, MAE, ECE, latency)
results.md method + published numbers
checksums.json SHA-256 manifest of the receptron/laya-onnx bundle

Published result

CPU run (Windows 11, Intel i7-1255U, onnxruntime), bundle receptron/laya-onnx @ 68f27dfe:

question type n accuracy MAE ECE
choice 4 1.00 – 0.456
noul 4 1.00 – 0.129
score 2 0.50 0.530 0.112
overall 10 0.90 – 0.256

Latency per predict() call: mean 2808 ms / p50 1760 ms / p95 7418 ms.

This is a reproducibility self-check, not a leaderboard — the sample is tiny and the intervals are wide.

Use 

git clone https://github.com/Geoking2104/laya-onnx && cd laya-onnx
python benchmarks/evaluate.py receptron/laya-onnx --eval decisions.jsonl

License

Apache-2.0.
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