inference-kernels / scripts /task_acceptance.py
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"""Evaluate one output using the task's explicit, unchanged acceptance policy."""
def compare_output(actual, expected, tolerance):
import torch
if (
actual.shape != expected.shape
or actual.dtype != expected.dtype
or actual.device != expected.device
):
raise AssertionError("Output shape, dtype or device differs")
if not actual.is_floating_point():
if not torch.equal(actual, expected):
raise AssertionError("Integer output differs")
return {"exact": True}
if not bool(torch.isfinite(actual).all()) or not bool(
torch.isfinite(expected).all()
):
raise AssertionError("Nonfinite output")
error = (actual.float() - expected.float()).abs()
if tolerance.get("comparison") == "absolute_or_relative":
close = (error <= tolerance["atol"]) | (
error / (expected.float().abs() + 1e-8) <= tolerance["rtol"]
)
else:
close = error <= tolerance["atol"] + tolerance["rtol"] * expected.float().abs()
# Count in integer arithmetic; a floating-point mean can round below 1
# even when every element passes.
matched = int(close.sum())
ratio = matched / close.numel() if close.numel() else 1.0
required = tolerance.get("required_matched_ratio")
if ratio < (1.0 if required is None else required):
raise AssertionError(
f"Matched {matched}/{close.numel()} output elements ({ratio})"
)
return {
"max_absolute_error": error.max().item() if error.numel() else 0.0,
"matched_ratio": ratio,
"mismatched_elements": close.numel() - matched,
}