（Phase 1）Add ModelOpt FP8 auto-detect support for diffusion checkpoints #2709 (#2913)

Signed-off-by: roG0d <rodgarcas98@gmail.com>
Signed-off-by: roG0d <baonudesifeizhai@gmail.com>
Signed-off-by: baonudesifeizhai <85092850+baonudesifeizhai@users.noreply.github.com>
Co-authored-by: roG0d <rodgarcas98@gmail.com>

tests/diffusion/quantization/test_fp8_config.py

@@ -54,6 +54,25 @@ def test_build_quant_config_dict_not_mutated():
     assert original == copy
 
 
+def test_build_quant_config_modelopt_fp8_config_json():
+    from vllm.model_executor.layers.quantization.modelopt import ModelOptFp8Config
+
+    from vllm_omni.quantization import build_quant_config
+
+    config = build_quant_config(
+        {
+            "quant_method": "modelopt",
+            "quant_algo": "FP8",
+            "ignore": ["proj_out"],
+            "producer": {"name": "modelopt"},
+        }
+    )
+
+    assert isinstance(config, ModelOptFp8Config)
+    assert config.get_name() == "modelopt"
+    assert config.is_checkpoint_fp8_serialized
+
+
 def test_build_quant_config_per_component():
     from vllm_omni.quantization import ComponentQuantizationConfig, build_quant_config
 
@@ -91,7 +110,7 @@ def test_flat_dict_not_misdetected_as_per_component():
     as a per-component dict — it should raise ValueError for missing 'method'."""
     from vllm_omni.quantization import build_quant_config
 
-    with pytest.raises(ValueError, match="must have a 'method' key"):
+    with pytest.raises(ValueError, match="must have a 'method' or 'quant_method' key"):
         build_quant_config({"activation_scheme": "static"})
 
 
@@ -194,10 +213,30 @@ def test_integration_per_component():
     assert config.quantization_config.component_configs["vae"] is None
 
 
+def test_transformer_config_auto_detects_modelopt_fp8():
+    from vllm.model_executor.layers.quantization.modelopt import ModelOptFp8Config
+
+    from vllm_omni.diffusion.data import TransformerConfig
+
+    config = TransformerConfig.from_dict(
+        {
+            "_class_name": "FluxTransformer2DModel",
+            "quantization_config": {
+                "quant_method": "modelopt",
+                "quant_algo": "FP8",
+                "ignore": ["proj_out"],
+            },
+        }
+    )
+
+    assert isinstance(config.quant_config, ModelOptFp8Config)
+    assert config.quant_method == "modelopt"
+
+
 def test_supported_methods_includes_vllm():
     from vllm_omni.quantization import SUPPORTED_QUANTIZATION_METHODS
 
-    for method in ["fp8", "gguf", "awq", "gptq", "bitsandbytes", "modelopt", "modelopt_fp4"]:
+    for method in ["fp8", "gguf", "awq", "gptq", "bitsandbytes", "modelopt"]:
         assert method in SUPPORTED_QUANTIZATION_METHODS, f"{method} missing"
 
 
@@ -243,14 +282,10 @@ def test_per_component_routing_with_default():
     assert resolved.get_name() == "fp8"
 
 
-@pytest.mark.parametrize(
-    "quant_algo",
-    ["FP8", "NVFP4"],
-    ids=["modelopt_fp8", "modelopt_nvfp4"],
-)
+@pytest.mark.parametrize("quant_algo", ["FP8"], ids=["modelopt_fp8"])
 def test_omni_convertor_thinker_finds_text_config_quant(quant_algo):
     """Thinker stage should discover quantization_config from
-    thinker_config.text_config for both FP8 and NVFP4 modelopt checkpoints."""
+    thinker_config.text_config for verified modelopt FP8 checkpoints."""
     from types import SimpleNamespace
 
     from vllm_omni.config.model import OmniModelArchConfigConvertor