Skip to content

Fix non-deterministic cache hash for MetricGrouping tasks #1260

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Open
nuthalapativarun wants to merge 1 commit into
base: main
Choose a base branch
from
Open

Fix non-deterministic cache hash for MetricGrouping tasks #1260

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
24 changes: 14 additions & 10 deletions src/lighteval/tasks/lighteval_task.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -159,6 +159,19 @@ def __post_init__(self):
self.stop_sequence = self.stop_sequence if self.stop_sequence is not None else ()
self.full_name = f"{self.name}|{self.num_fewshots}" # todo clefourrier: this is likely incorrect

@staticmethod
def _repr_metric_value(v):
if isinstance(v, functools.partial):
func_name = getattr(v.func, "__name__", str(v.func))
return f"partial({func_name}, ...)"
if isinstance(v, dict):
return repr({key: LightevalTaskConfig._repr_metric_value(val) for key, val in v.items()})
if isinstance(v, Callable):
return getattr(v, "__name__", repr(v))
if isinstance(v, Metric.get_allowed_types_for_metrics()):
return str(v)
return repr(v)

def __str__(self, lite: bool = False): # noqa: C901
md_writer = MarkdownTableWriter()
md_writer.headers = ["Key", "Value"]
Expand All @@ -174,16 +187,7 @@ def __str__(self, lite: bool = False): # noqa: C901
if k == "metrics":
for ix, metrics in enumerate(v):
for metric_k, metric_v in metrics.items():
if isinstance(metric_v, functools.partial):
func_name = getattr(metric_v.func, "__name__", str(metric_v.func))
repr_v = f"partial({func_name}, ...)"
elif isinstance(metric_v, Callable):
repr_v = getattr(metric_v, "__name__", repr(metric_v))
elif isinstance(metric_v, Metric.get_allowed_types_for_metrics()):
repr_v = str(metric_v)
else:
repr_v = repr(metric_v)
values.append([f"{k} {ix}: {metric_k}", repr_v])
values.append([f"{k} {ix}: {metric_k}", self._repr_metric_value(metric_v)])

else:
if isinstance(v, functools.partial):
Expand Down