Added validation logic to recipe

Signed-off-by: shanjiaz <[email protected]>

Author: shanjiaz

src/llmcompressor/modifiers/interface.py

@@ -1,15 +1,16 @@
 from abc import abstractmethod
 from typing import Optional
 
+from pydantic import BaseModel, ConfigDict
+
 from llmcompressor.core.events import Event, EventType
 from llmcompressor.core.state import State
-from llmcompressor.modifiers.interface import ModifierInterface
 from llmcompressor.modifiers.utils.hooks import HooksMixin
 
 __all__ = ["Modifier"]
 
 
-class Modifier(ModifierInterface, HooksMixin):
+class Modifier(HooksMixin, BaseModel):
     """
     A base class for all modifiers to inherit from.
     Modifiers are used to modify the training process for a model.
@@ -30,6 +31,8 @@ class Modifier(ModifierInterface, HooksMixin):
     :param update: The update step for the modifier
     """
 
+    model_config = ConfigDict(extra="forbid")
+
     index: Optional[int] = None
     group: Optional[str] = None
     start: Optional[float] = None

src/llmcompressor/modifiers/modifier.py

@@ -64,12 +64,6 @@ def _validate_infer_pipeline(modifiers: List[Modifier]) -> str:
             return "sequential"
 
         active_qmods = _get_active_quant_modifiers(modifiers)
-        if len(active_qmods) > 1:
-            raise ValueError(
-                f"Recipe contains more than one active quantization config "
-                f"({active_qmods}). These configs may be conflicting, Please modify "
-                "your recipe to use at most one quantization config"
-            )
 
         if len(active_qmods) == 1:
             quant_modifier = active_qmods[0]

src/llmcompressor/pipelines/registry.py

@@ -8,6 +8,7 @@
 
 from llmcompressor.modifiers import Modifier, ModifierFactory
 from llmcompressor.recipe.utils import (
+    _get_active_quant_modifiers,
     _load_json_or_yaml_string,
     _parse_recipe_from_md,
     deep_merge_dicts,
@@ -161,6 +162,16 @@ def create_instance(
 
             return Recipe.model_validate(filter_dict(obj, target_stage=target_stage))
 
+    @classmethod
+    def validate_pipeline(self) -> str:
+        active_qmods = _get_active_quant_modifiers(self.modifiers)
+        if len(active_qmods) > 1:
+            raise ValueError(
+                f"Recipe contains more than one active quantization config "
+                f"({active_qmods}). These configs may be conflicting. Please modify "
+                "your recipe to use at most one quantization config"
+            )
+
     @model_validator(mode="before")
     @classmethod
     def parse_from_dict(cls, values: Dict[str, Any]) -> Dict[str, Any]:
@@ -226,6 +237,7 @@ def create_modifier(self) -> List[Modifier]:
             )
             for modifier in self.modifiers
         ]
+        self.validate_pipeline()
         return self.modifiers
 
     def dict(self, *args, **kwargs) -> Dict[str, Any]:

src/llmcompressor/recipe/recipe.py

@@ -139,3 +139,7 @@ def deep_merge_dicts(d1: dict, d2: dict) -> dict:
                     i += 1
                 result[f"{base_key}_{i}"] = val
     return result
+
+
+def _get_active_quant_modifiers(modifiers: List[Modifier]) -> List[Modifier]:
+    return [m for m in modifiers if m.__class__.__name__ == "QuantizationModifier"]