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chore: import upstream snapshot with attribution
2026-07-13 12:41:19 +08:00

48 lines
1.5 KiB
Python

# Copyright (c) ONNX Project Contributors
# SPDX-License-Identifier: Apache-2.0
from __future__ import annotations
import inspect
from collections import defaultdict
from textwrap import dedent
from typing import Any, ClassVar
import numpy as np
def process_snippet(op_name: str, name: str, export: Any) -> tuple[str, str]:
snippet_name = name[len("export_") :] or op_name.lower()
source_code = dedent(inspect.getsource(export))
# remove the function signature line
lines = source_code.splitlines()
assert lines[0] == "@staticmethod"
assert lines[1].startswith("def export")
return snippet_name, dedent("\n".join(lines[2:]))
Snippets: dict[str, list[tuple[str, str]]] = defaultdict(list)
class _Exporter(type):
exports: ClassVar[dict[str, list[tuple[str, str]]]] = defaultdict(list)
def __init__(
cls, name: str, bases: tuple[type[Any], ...], dct: dict[str, Any]
) -> None:
for k, v in dct.items():
if k.startswith("export"):
if not isinstance(v, staticmethod):
raise ValueError("Only staticmethods could be named as export.*")
export = getattr(cls, k)
Snippets[name].append(process_snippet(name, k, export))
# export functions should call expect and so populate
# TestCases
np.random.seed(seed=0)
export()
super().__init__(name, bases, dct)
class Base(metaclass=_Exporter):
pass