[Feature] Support MiniMax-H3 Turbo LoRA with DLO (#6550)

Signed-off-by: mglyn <1203789601@qq.com>
Co-authored-by: Hongsheng Liu <liuhongsheng4@huawei.com>

tests/diffusion/models/minimax_h3/test_minimax_h3_lora.py

@@ -197,7 +197,6 @@ def test_h3_turbo_rejects_wrong_alpha_and_ref2va(tmp_path):
     [
         "model-level CPU offload (--enable-cpu-offload)",
         "layerwise offload (--enable-layerwise-offload)",
-        "distributed layerwise offload (--enable-distributed-layerwise-offload)",
     ],
 )
 def test_h3_turbo_rejects_offload_modes(tmp_path, offload_mode):
@@ -214,6 +213,38 @@ def test_h3_turbo_rejects_offload_modes(tmp_path, offload_mode):
         )
 
 
+def test_h3_turbo_allows_distributed_layerwise_offload(monkeypatch):
+    from vllm_omni.diffusion.models.minimax_h3 import MiniMaxH3Pipeline
+    from vllm_omni.diffusion.models.minimax_h3 import (
+        pipeline_minimax_h3 as pipeline_module,
+    )
+
+    pipeline = object.__new__(MiniMaxH3Pipeline)
+    torch.nn.Module.__init__(pipeline)
+    pipeline.partition = "fl2va"
+    pipeline._turbo_lora_adapter_ids = set()
+    pipeline.od_config = SimpleNamespace(
+        enable_cpu_offload=False,
+        enable_layerwise_offload=False,
+        enable_distributed_layerwise_offload=True,
+    )
+    captured = {}
+
+    def load_turbo(**kwargs):
+        captured.update(kwargs)
+        return object(), object()
+
+    monkeypatch.setattr(pipeline_module, "load_minimax_h3_turbo_lora", load_turbo)
+    loaded = pipeline._load_diffusion_lora_adapter(
+        lora_request=_request("turbo"),
+        lora_path="turbo",
+        dtype=torch.bfloat16,
+    )
+
+    assert loaded is not None
+    assert captured["unsupported_offload_mode"] is None
+
+
 def test_h3_turbo_accepts_only_the_declared_v1_artifact(tmp_path):
     unsupported = tmp_path / "minimax_h3_fl2v_turbo_8step_v1.0_bf16.safetensors"
     _write_tiny_turbo(unsupported)