rebase: adapt to vLLM v0.29 APIs

Signed-off-by: tzhouam <tzhouam@connect.ust.hk>

tests/model_executor/models/test_weight_loader.py

@@ -0,0 +1,40 @@
+# SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM-Omni project
+
+import torch
+from torch import nn
+from vllm.model_executor.models.utils import WeightsMapper
+
+from vllm_omni.model_executor.models.weight_loader import AutoWeightsLoader
+
+
+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_auto_weights_loader_preserves_removed_skip_arguments() -> None:
+    model = _TinyModel()
+    model.skipped.weight.data.zero_()
+
+    loaded = AutoWeightsLoader(
+        model,
+        skip_prefixes=["skipped."],
+        skip_substrs=["rotary_embed.inv_freq"],
+    ).load_weights(
+        [
+            ("checkpoint.kept.weight", torch.ones(1, 1)),
+            ("skipped.weight", torch.full((1, 1), 2.0)),
+            ("rotary_embed.inv_freq", torch.ones(1)),
+        ],
+        mapper=WeightsMapper(orig_to_new_prefix={"checkpoint.": ""}),
+    )
+
+    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))