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Zhou TaichangandClaude Opus 5 aff7d64948 [Rebase] Rebase to vLLM 0.29.0 (#7230)
Signed-off-by: tzhouam <tzhouam@connect.ust.hk>
Signed-off-by: Zhou Taichang <tzhouam@connect.ust.hk>
Co-authored-by: Claude Opus 5 <noreply@anthropic.com>
2026-09-10 12:08:28 +08:00

39 lines
1.4 KiB
Python

# SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM-Omni project
import pytest
import torch
from torch import nn
from vllm.model_executor.models.utils import AutoWeightsLoader, WeightsMapper
pytestmark = [pytest.mark.core_model, pytest.mark.cpu]
class _TinyModel(nn.Module):
def __init__(self) -> None:
super().__init__()
self.kept = nn.Linear(1, 1, bias=False)
self.skipped = nn.Linear(1, 1, bias=False)
self.rotary_embed = nn.Module()
self.rotary_embed.register_parameter("inv_freq", nn.Parameter(torch.zeros(1)))
def test_upstream_mapper_preserves_stage_exclusions_after_renaming() -> None:
model = _TinyModel()
model.skipped.weight.data.zero_()
loaded = AutoWeightsLoader(model).load_weights(
[
("checkpoint.kept.weight", torch.ones(1, 1)),
("checkpoint.skipped.weight", torch.full((1, 1), 2.0)),
("rotary_embed.inv_freq", torch.ones(1)),
],
mapper=WeightsMapper(orig_to_new_prefix={"checkpoint.": ""})
| WeightsMapper(orig_to_new_prefix={"skipped.": None}, orig_to_new_substr={"rotary_embed.inv_freq": None}),
)
assert loaded == {"kept.weight"}
torch.testing.assert_close(model.kept.weight, torch.ones(1, 1))
torch.testing.assert_close(model.skipped.weight, torch.zeros(1, 1))
torch.testing.assert_close(model.rotary_embed.inv_freq, torch.zeros(1))