[Model] FP8 Support For Boogu-Image (#6925)

Signed-off-by: Dmaner <2663515256@qq.com>

tests/diffusion/quantization/test_torchao_config.py

@@ -0,0 +1,58 @@
+# SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM-Omni project
+
+import pytest
+import torch
+
+from vllm_omni.quantization import build_quant_config
+from vllm_omni.quantization.component_config import ComponentQuantizationConfig
+
+pytestmark = [pytest.mark.core_model, pytest.mark.cpu, pytest.mark.diffusion]
+
+
+@pytest.mark.parametrize(
+    "transformer_spec",
+    [
+        {
+            "method": "torchao",
+            "quant_type": {
+                "default": {
+                    "_type": "Float8WeightOnlyConfig",
+                    "_version": 2,
+                    "_data": {
+                        "weight_dtype": {
+                            "_type": "torch.dtype",
+                            "_data": "float8_e4m3fn",
+                        },
+                        "set_inductor_config": False,
+                    },
+                }
+            },
+        },
+        {"method": "torchao_float8_weight_only"},
+    ],
+    ids=["serialized-json", "checkpoint-shorthand"],
+)
+def test_build_quant_config_torchao_checkpoint(transformer_spec):
+    quantization = pytest.importorskip("torchao.quantization")
+    result = build_quant_config({"transformer": transformer_spec})
+
+    assert isinstance(result, ComponentQuantizationConfig)
+    transformer = result.resolve("transformer")
+    assert transformer.get_name() == "torchao"
+    assert transformer.is_checkpoint_torchao_serialized is True
+    assert isinstance(transformer.torchao_config, quantization.Float8WeightOnlyConfig)
+    assert transformer.torchao_config.version == 2
+    assert transformer.torchao_config.weight_dtype is torch.float8_e4m3fn
+    assert transformer.torchao_config.set_inductor_config is False
+
+
+def test_build_quant_config_torchao_runtime():
+    from vllm.model_executor.layers.quantization.torchao import TorchAOConfig
+
+    torchao_config = object()
+    result = build_quant_config("torchao", torchao_config=torchao_config)
+
+    assert isinstance(result, TorchAOConfig)
+    assert result.torchao_config is torchao_config
+    assert result.is_checkpoint_torchao_serialized is False