[Misc] Remove redundant ClassRegistry (#29681)

Signed-off-by: DarkLight1337 <tlleungac@connect.ust.hk>
Signed-off-by: Cyrus Leung <cyrus.tl.leung@gmail.com>
Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com>

tests/models/multimodal/processing/test_common.py

@@ -233,7 +233,7 @@ def _test_processing_correctness(
     )
 
     model_cls = MULTIMODAL_REGISTRY._get_model_cls(model_config)
-    factories = MULTIMODAL_REGISTRY._processor_factories[model_cls]
+    factories = model_cls._processor_factory
     ctx = InputProcessingContext(
         model_config,
         tokenizer=cached_tokenizer_from_config(model_config),

tests/models/multimodal/processing/test_tensor_schema.py

@@ -193,7 +193,7 @@ def test_model_tensor_schema(model_id: str):
     model_cls = MULTIMODAL_REGISTRY._get_model_cls(model_config)
     assert supports_multimodal(model_cls)
 
-    factories = MULTIMODAL_REGISTRY._processor_factories[model_cls]
+    factories = model_cls._processor_factory
 
     inputs_parse_methods = []
     for attr_name in dir(model_cls):

vllm/model_executor/models/interfaces.py

@@ -32,11 +32,13 @@ if TYPE_CHECKING:
     from vllm.config import VllmConfig
     from vllm.model_executor.models.utils import WeightsMapper
     from vllm.multimodal.inputs import MultiModalFeatureSpec
+    from vllm.multimodal.registry import _ProcessorFactories
     from vllm.sequence import IntermediateTensors
 else:
     VllmConfig = object
     WeightsMapper = object
     MultiModalFeatureSpec = object
+    _ProcessorFactories = object
     IntermediateTensors = object
 
 logger = init_logger(__name__)
@@ -87,6 +89,11 @@ class SupportsMultiModal(Protocol):
     A set indicating CPU-only multimodal fields.
     """
 
+    _processor_factory: ClassVar[_ProcessorFactories]
+    """
+    Set internally by `MultiModalRegistry.register_processor`.
+    """
+
     @classmethod
     def get_placeholder_str(cls, modality: str, i: int) -> str | None:
         """

vllm/multimodal/registry.py

@@ -2,14 +2,11 @@
 # SPDX-FileCopyrightText: Copyright contributors to the vLLM project
 from collections.abc import Mapping
 from dataclasses import dataclass
-from typing import TYPE_CHECKING, Generic, Protocol, TypeVar
+from typing import TYPE_CHECKING, Generic, Protocol, TypeVar, cast
-
-import torch.nn as nn
 
 from vllm.config.multimodal import BaseDummyOptions
 from vllm.logger import init_logger
 from vllm.transformers_utils.tokenizer import AnyTokenizer, cached_tokenizer_from_config
-from vllm.utils.collection_utils import ClassRegistry
 
 from .cache import BaseMultiModalProcessorCache
 from .processing import (
@@ -26,10 +23,11 @@ from .profiling import (
 
 if TYPE_CHECKING:
     from vllm.config import ModelConfig
+    from vllm.model_executor.models.interfaces import SupportsMultiModal
 
 logger = init_logger(__name__)
 
-N = TypeVar("N", bound=type[nn.Module])
+N = TypeVar("N", bound=type["SupportsMultiModal"])
 _I = TypeVar("_I", bound=BaseProcessingInfo)
 _I_co = TypeVar("_I_co", bound=BaseProcessingInfo, covariant=True)
 
@@ -95,9 +93,6 @@ class MultiModalRegistry:
     A registry that dispatches data processing according to the model.
     """
 
-    def __init__(self) -> None:
-        self._processor_factories = ClassRegistry[nn.Module, _ProcessorFactories]()
-
     def _extract_mm_options(
         self,
         model_config: "ModelConfig",
@@ -207,7 +202,7 @@ class MultiModalRegistry:
         """
 
         def wrapper(model_cls: N) -> N:
-            if self._processor_factories.contains(model_cls, strict=True):
+            if "_processor_factory" in model_cls.__dict__:
                 logger.warning(
                     "Model class %s already has a multi-modal processor "
                     "registered to %s. It is overwritten by the new one.",
@@ -215,7 +210,7 @@ class MultiModalRegistry:
                     self,
                 )
 
-            self._processor_factories[model_cls] = _ProcessorFactories(
+            model_cls._processor_factory = _ProcessorFactories(
                 info=info,
                 dummy_inputs=dummy_inputs,
                 processor=processor,
@@ -225,12 +220,13 @@ class MultiModalRegistry:
 
         return wrapper
 
-    def _get_model_cls(self, model_config: "ModelConfig"):
+    def _get_model_cls(self, model_config: "ModelConfig") -> "SupportsMultiModal":
         # Avoid circular import
         from vllm.model_executor.model_loader import get_model_architecture
 
         model_cls, _ = get_model_architecture(model_config)
-        return model_cls
+        assert hasattr(model_cls, "_processor_factory")
+        return cast("SupportsMultiModal", model_cls)
 
     def _create_processing_ctx(
         self,
@@ -248,7 +244,7 @@ class MultiModalRegistry:
         tokenizer: AnyTokenizer | None = None,
     ) -> BaseProcessingInfo:
         model_cls = self._get_model_cls(model_config)
-        factories = self._processor_factories[model_cls]
+        factories = model_cls._processor_factory
         ctx = self._create_processing_ctx(model_config, tokenizer)
         return factories.info(ctx)
 
@@ -266,7 +262,7 @@ class MultiModalRegistry:
             raise ValueError(f"{model_config.model} is not a multimodal model")
 
         model_cls = self._get_model_cls(model_config)
-        factories = self._processor_factories[model_cls]
+        factories = model_cls._processor_factory
 
         ctx = self._create_processing_ctx(model_config, tokenizer)
 

vllm/utils/collection_utils.py

@@ -6,64 +6,37 @@ Contains helpers that are applied to collections.
 This is similar in concept to the `collections` module.
 """
 
-from collections import UserDict, defaultdict
+from collections import defaultdict
 from collections.abc import Callable, Generator, Hashable, Iterable, Mapping
 from typing import Generic, Literal, TypeVar
 
 from typing_extensions import TypeIs, assert_never
 
 T = TypeVar("T")
-U = TypeVar("U")
 
 _K = TypeVar("_K", bound=Hashable)
 _V = TypeVar("_V")
 
 
-class ClassRegistry(UserDict[type[T], _V]):
+class LazyDict(Mapping[str, _V], Generic[_V]):
-    """
-    A registry that acts like a dictionary but searches for other classes
-    in the MRO if the original class is not found.
-    """
-
-    def __getitem__(self, key: type[T]) -> _V:
-        for cls in key.mro():
-            if cls in self.data:
-                return self.data[cls]
-
-        raise KeyError(key)
-
-    def __contains__(self, key: object) -> bool:
-        return self.contains(key)
-
-    def contains(self, key: object, *, strict: bool = False) -> bool:
-        if not isinstance(key, type):
-            return False
-
-        if strict:
-            return key in self.data
-
-        return any(cls in self.data for cls in key.mro())
-
-
-class LazyDict(Mapping[str, T], Generic[T]):
     """
     Evaluates dictionary items only when they are accessed.
 
     Adapted from: https://stackoverflow.com/a/47212782/5082708
     """
 
-    def __init__(self, factory: dict[str, Callable[[], T]]):
+    def __init__(self, factory: dict[str, Callable[[], _V]]):
         self._factory = factory
-        self._dict: dict[str, T] = {}
+        self._dict: dict[str, _V] = {}
 
-    def __getitem__(self, key: str) -> T:
+    def __getitem__(self, key: str) -> _V:
         if key not in self._dict:
             if key not in self._factory:
                 raise KeyError(key)
             self._dict[key] = self._factory[key]()
         return self._dict[key]
 
-    def __setitem__(self, key: str, value: Callable[[], T]):
+    def __setitem__(self, key: str, value: Callable[[], _V]):
         self._factory[key] = value
 
     def __iter__(self):