[edge-infer] WIP snapshot: uncommitted M0/W1/W4/W5 edge work as of 2026-09-18

Verbatim copy of the edge/omni-edge working tree (tracked diffs + untracked
edge/local, tests/edge/local, docs/edge, pipeline files). Taken so that
vLLM-Omni v0.29.0rc1 can be merged on a branch without touching the
user's working tree. logs_edge/ and benchmark .npy outputs excluded.

Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>

tests/worker/test_forward_kwargs_filtering.py

@@ -0,0 +1,69 @@
+# SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM-Omni project
+"""Omni-only forward kwargs must not be forced on a model that cannot take them.
+
+The AR runner hands every stage ``sampling_metadata``, ``logits_index`` and
+``sampler``, which omni-native models absorb through ``**kwargs``. A model vLLM
+owns does not: ``LlamaForCausalLM.forward`` is
+``(input_ids, positions, intermediate_tensors, inputs_embeds)`` and nothing
+else, so passing the extras is a ``TypeError`` on the very first forward.
+"""
+
+from __future__ import annotations
+
+import torch
+
+from vllm_omni.worker.gpu_model_runner import OmniGPUModelRunner
+
+
+class _OmniNativeModel(torch.nn.Module):
+    def forward(self, input_ids, positions, intermediate_tensors=None, inputs_embeds=None, **kwargs):
+        return input_ids
+
+
+class _VLLMNativeModel(torch.nn.Module):
+    """The shape of vLLM's own causal LMs: no ``**kwargs``."""
+
+    def forward(self, input_ids, positions, intermediate_tensors=None, inputs_embeds=None):
+        return input_ids
+
+
+class _Probe:
+    """Just enough of a runner to exercise the helper."""
+
+    def __init__(self, model):
+        self.model = model
+
+    _accepted_forward_kwargs = OmniGPUModelRunner._accepted_forward_kwargs
+
+
+def test_a_model_taking_kwargs_is_left_alone():
+    assert _Probe(_OmniNativeModel())._accepted_forward_kwargs() is None
+
+
+def test_a_vllm_native_model_reports_exactly_its_parameters():
+    accepted = _Probe(_VLLMNativeModel())._accepted_forward_kwargs()
+    assert accepted == frozenset(
+        {"input_ids", "positions", "intermediate_tensors", "inputs_embeds"}
+    )
+    for omni_only in ("sampling_metadata", "logits_index", "sampler"):
+        assert omni_only not in accepted
+
+
+def test_the_answer_is_cached():
+    """``inspect.signature`` on every decode step would be absurd."""
+    probe = _Probe(_VLLMNativeModel())
+    first = probe._accepted_forward_kwargs()
+    probe.model = _OmniNativeModel()  # would change the answer if recomputed
+    assert probe._accepted_forward_kwargs() is first
+
+
+def test_an_uninspectable_forward_falls_back_to_passing_everything():
+    """Degrade to the previous behaviour rather than silently dropping
+    arguments a model may actually need."""
+
+    class Weird(torch.nn.Module):
+        forward = staticmethod(print)  # no usable signature for our purposes
+
+    accepted = _Probe(Weird())._accepted_forward_kwargs()
+    assert accepted is None or "sampling_metadata" not in accepted