fix(quant): resolve hyphenated registry methods and disk-dict from_config in quant factory

_normalize_method_name canonicalizes dashes to underscores for _OVERRIDES
lookup, but vLLM's QUANTIZATION_METHODS keeps historical spellings
('compressed-tensors'), so both --quantization compressed-tensors and
checkpoint auto-detection raised 'Unknown quantization method'. Resolve
the normalized name back to the registry spelling, and fall back to
from_config for registry configs whose __init__ does not take the
serialized schema (compressed-tensors config_groups/format/ignore).

tests/quantization/test_quant_factory.py

@@ -0,0 +1,72 @@
+# SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM-Omni project
+"""Tests for the quantization config factory's method-name and disk-dict resolution."""
+
+from __future__ import annotations
+
+import pytest
+from vllm.model_executor.layers.quantization.compressed_tensors.compressed_tensors import (
+    CompressedTensorsConfig,
+)
+
+from vllm_omni.quantization import build_quant_config, resolve_component_quant_config
+from vllm_omni.quantization.component_config import (
+    ComponentQuantizationConfig,
+    resolve_encoder_quant_config,
+)
+from vllm_omni.quantization.factory import SUPPORTED_QUANTIZATION_METHODS, _build_single
+
+
+def _int8_weight_only_disk_config() -> dict:
+    """Serialized compressed-tensors int8 weight-only metadata as it appears on disk."""
+    weights = {
+        "num_bits": 8,
+        "type": "int",
+        "symmetric": True,
+        "strategy": "channel",
+        "dynamic": False,
+        "observer": "minmax",
+    }
+    return {
+        "quant_method": "compressed-tensors",
+        "format": "pack-quantized",
+        "config_groups": {"group_0": {"targets": ["Linear"], "weights": weights}},
+        "ignore": ["img_in"],
+        "quantization_status": "frozen",
+    }
+
+
+def test_hyphenated_registry_method_builds_from_str() -> None:
+    config = _build_single("compressed-tensors")
+    assert isinstance(config, CompressedTensorsConfig)
+    assert config.get_name() == "compressed-tensors"
+
+
+@pytest.mark.parametrize("spelling", ["compressed-tensors", "compressed_tensors"])
+def test_disk_dict_builds_via_from_config(spelling: str) -> None:
+    disk = _int8_weight_only_disk_config()
+    disk["quant_method"] = spelling
+    config = build_quant_config(disk)
+    assert isinstance(config, CompressedTensorsConfig)
+
+
+def test_per_component_dict_routes_transformer_only() -> None:
+    disk = {"transformer": _int8_weight_only_disk_config()}
+    config = build_quant_config(disk)
+    assert isinstance(config, ComponentQuantizationConfig)
+    assert isinstance(
+        resolve_component_quant_config(config, "transformer"), CompressedTensorsConfig
+    )
+    encoder = resolve_encoder_quant_config(
+        resolve_component_quant_config(config, "text_encoder")
+    )
+    assert encoder is None
+
+
+def test_unknown_method_still_raises() -> None:
+    with pytest.raises(ValueError, match="Unknown quantization method"):
+        _build_single("not-a-real-method")
+
+
+def test_supported_list_advertises_hyphenated_registry_names() -> None:
+    assert "compressed-tensors" in SUPPORTED_QUANTIZATION_METHODS