[Model] Add base class for LoRA-supported models (#5018)

vllm/model_executor/models/interfaces.py

@@ -0,0 +1,130 @@
+from typing import (ClassVar, Dict, List, Literal, Optional, Protocol, Type,
+                    Union, overload, runtime_checkable)
+
+from typing_extensions import TypeGuard
+
+from vllm.config import LoRAConfig, VisionLanguageConfig
+from vllm.logger import init_logger
+
+logger = init_logger(__name__)
+
+
+@runtime_checkable
+class SupportsVision(Protocol):
+    """The interface required for all vision language models (VLMs)."""
+
+    supports_vision: ClassVar[Literal[True]]
+
+    def __init__(self, *, vlm_config: VisionLanguageConfig) -> None:
+        ...
+
+
+# We can't use runtime_checkable with ClassVar for issubclass checks
+# so we need to treat the class as an instance and use isinstance instead
+@runtime_checkable
+class _SupportsVisionType(Protocol):
+    supports_vision: Literal[True]
+
+    def __call__(self, *, vlm_config: VisionLanguageConfig) -> None:
+        ...
+
+
+@overload
+def supports_vision(model: Type[object]) -> TypeGuard[Type[SupportsVision]]:
+    ...
+
+
+@overload
+def supports_vision(model: object) -> TypeGuard[SupportsVision]:
+    ...
+
+
+def supports_vision(
+    model: Union[Type[object], object],
+) -> Union[TypeGuard[Type[SupportsVision]], TypeGuard[SupportsVision]]:
+    if isinstance(model, type):
+        return isinstance(model, _SupportsVisionType)
+
+    return isinstance(model, SupportsVision)
+
+
+@runtime_checkable
+class SupportsLoRA(Protocol):
+    """The interface required for all models that support LoRA."""
+
+    supports_lora: ClassVar[Literal[True]]
+
+    packed_modules_mapping: ClassVar[Dict[str, List[str]]]
+    supported_lora_modules: ClassVar[List[str]]
+    embedding_modules: ClassVar[Dict[str, str]]
+    embedding_padding_modules: ClassVar[List[str]]
+
+    # lora_config is None when LoRA is not enabled
+    def __init__(self, *, lora_config: Optional[LoRAConfig] = None) -> None:
+        ...
+
+
+# We can't use runtime_checkable with ClassVar for issubclass checks
+# so we need to treat the class as an instance and use isinstance instead
+@runtime_checkable
+class _SupportsLoRAType(Protocol):
+    supports_lora: Literal[True]
+
+    packed_modules_mapping: Dict[str, List[str]]
+    supported_lora_modules: List[str]
+    embedding_modules: Dict[str, str]
+    embedding_padding_modules: List[str]
+
+    def __call__(self, *, lora_config: Optional[LoRAConfig] = None) -> None:
+        ...
+
+
+@overload
+def supports_lora(model: Type[object]) -> TypeGuard[Type[SupportsLoRA]]:
+    ...
+
+
+@overload
+def supports_lora(model: object) -> TypeGuard[SupportsLoRA]:
+    ...
+
+
+def supports_lora(
+    model: Union[Type[object], object],
+) -> Union[TypeGuard[Type[SupportsLoRA]], TypeGuard[SupportsLoRA]]:
+    result = _supports_lora(model)
+
+    if not result:
+        lora_attrs = (
+            "packed_modules_mapping",
+            "supported_lora_modules",
+            "embedding_modules",
+            "embedding_padding_modules",
+        )
+        missing_attrs = tuple(attr for attr in lora_attrs
+                              if not hasattr(model, attr))
+
+        if getattr(model, "supports_lora", False):
+            if missing_attrs:
+                logger.warning(
+                    "The model (%s) sets `supports_lora=True`, "
+                    "but is missing LoRA-specific attributes: %s",
+                    model,
+                    missing_attrs,
+                )
+        else:
+            if not missing_attrs:
+                logger.warning(
+                    "The model (%s) contains all LoRA-specific attributes, "
+                    "but does not set `supports_lora=True`.", model)
+
+    return result
+
+
+def _supports_lora(
+    model: Union[Type[object], object],
+) -> Union[TypeGuard[Type[SupportsLoRA]], TypeGuard[SupportsLoRA]]:
+    if isinstance(model, type):
+        return isinstance(model, _SupportsLoRAType)
+
+    return isinstance(model, SupportsLoRA)