Meta-Eval/EvalHarness
3
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

Few-shot split loading goes through cached materialization

Browse Source 
Was: raw load_raw_records() hit the hub on EVERY run -- offline machines
stalled in 5x HF retries then silently degraded to 0-shot (changing the
benchmark's default contract, e.g. gsm8k 4-shot). Now the few-shot split
is a proper Dataset entry: first use downloads+cache, every later run is
a pure cache hit (verified: second run with HF_HUB_OFFLINE=1 loads
4-shot from cache, zero network lines, acc unchanged).

Co-Authored-By: Claude <noreply@anthropic.com>
This commit is contained in:
sora 2026-09-10 07:47:48 +00:00
parent 9991c15816
commit 2dfb60cdf2
1 changed files with 11 additions and 5 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

16
evalharness/model/runner.py
View File

@ -606,10 +606,16 @@ async def run_eval(
fs_spec = dataclasses.replace(spec, split=fs_split) if spec is not None else None fs_spec = dataclasses.replace(spec, split=fs_split) if spec is not None else None
if fs_spec is not None: if fs_spec is not None:
from ..data.loader import load_raw_records # go through the CACHED materialization path (not raw hub
# loads): a cached few-shot split never touches the
# network; first use downloads and caches it for offline
# runs afterwards
from ..data.dataset import Dataset
fn = prov.resolve_record_fn() fn = prov.resolve_record_fn()
fs_raw = load_raw_records(fs_spec) fs_ds = Dataset(fs_spec, fn)
fs_ds.materialize()
fs_samples_all = list(fs_ds)
# keep the WHOLE dev split when samples carry a category: # keep the WHOLE dev split when samples carry a category:
# es selects domain-MATCHED exemplars per subject (mmlu # es selects domain-MATCHED exemplars per subject (mmlu
# biology questions get biology exemplars), we do the same # biology questions get biology exemplars), we do the same
@ -617,16 +623,16 @@ async def run_eval(
def _lv_of(md): def _lv_of(md):
return (md or {}).get('category') or (md or {}).get('level') return (md or {}).get('category') or (md or {}).get('level')
cats = {_lv_of(fn(r).metadata) for r in fs_raw[:200]} cats = {_lv_of(s.metadata) for s in fs_samples_all[:200]}
style_is = getattr(spec, 'prompt_style', '') if spec is not None else '' style_is = getattr(spec, 'prompt_style', '') if spec is not None else ''
if len(cats) > 1 and spec is not None and \ if len(cats) > 1 and spec is not None and \
(style_is.startswith('cot_letter') or style_is == 'imo_es'): (style_is.startswith('cot_letter') or style_is == 'imo_es'):
# mmlu-style per-subject OR math per-Level exemplars: # mmlu-style per-subject OR math per-Level exemplars:
# load the WHOLE few-shot split; assemble-time picks # load the WHOLE few-shot split; assemble-time picks
# domain-matched first-N (es reformat_subset semantics) # domain-matched first-N (es reformat_subset semantics)
few_shot_samples = [fn(r) for r in fs_raw] few_shot_samples = fs_samples_all
else: else:
few_shot_samples = [fn(r) for r in fs_raw[:few_shot_num]] few_shot_samples = fs_samples_all[:few_shot_num]
except Exception as e: except Exception as e:
print(f'few-shot: could not load {fs_split} split ({type(e).__name__}: ' print(f'few-shot: could not load {fs_split} split ({type(e).__name__}: '
f'{str(e)[:80]}); continuing 0-shot', flush=True) f'{str(e)[:80]}); continuing 0-shot', flush=True)