fix: Make Recipe.model_dump() output compatible with model_validate()

src/llmcompressor/recipe/recipe.py

@@ -46,7 +46,7 @@ def from_modifiers(
 
         (Note: all modifiers are wrapped into a single stage
         with the modifier_group_name as the stage name. If modifier_group_name is None,
-        the default run type is `oneshot`)
+        the default run_type is `oneshot`)
 
         Lfecycle:
         | - Validate Modifiers
@@ -524,6 +524,33 @@ def dict(self, *args, **kwargs) -> Dict[str, Any]:
 
         return dict_
 
+    def model_dump(self, *args, **kwargs) -> Dict[str, Any]:
+        """
+        Override the model_dump method to provide a dictionary representation that
+        is compatible with model_validate.
+
+        Unlike the standard model_dump, this transforms the stages list to a format
+        expected by the validation logic, ensuring round-trip compatibility with
+        model_validate.
+
+        :return: A dictionary representation of the recipe compatible with
+            model_validate
+        """
+        # Get the base dictionary from parent class
+        base_dict = super().model_dump(*args, **kwargs)
+
+        # Transform stages into the expected format
+        if "stages" in base_dict:
+            stages_dict = {}
+            for stage in base_dict["stages"]:
+                group = stage["group"]
+                if group not in stages_dict:
+                    stages_dict[group] = []
+                stages_dict[group].append(stage)
+            base_dict["stages"] = stages_dict
+
+        return base_dict
+
     def yaml(self, file_path: Optional[str] = None) -> str:
         """
         Return a yaml string representation of the recipe.

tests/recipe/test_recipe.py

@@ -0,0 +1,54 @@
+from src.llmcompressor.recipe import Recipe
+
+
+def test_recipe_model_dump():
+    """Test that model_dump produces a format compatible with model_validate."""
+    # Create a recipe with multiple stages and modifiers
+    recipe_str = """
+    version: "1.0"
+    args:
+        learning_rate: 0.001
+    train_stage:
+        pruning_modifiers:
+            ConstantPruningModifier:
+                start: 0.0
+                end: 2.0
+                targets: ['re:.*weight']
+        quantization_modifiers:
+            QuantizationModifier:
+                bits: 8
+                targets: ['re:.*weight']
+    eval_stage:
+        pruning_modifiers:
+            ConstantPruningModifier:
+                start: 2.0
+                end: 4.0
+                targets: ['re:.*weight']
+    """
+
+    # Create recipe instance
+    recipe = Recipe.create_instance(recipe_str)
+
+    # Get dictionary representation
+    recipe_dict = recipe.model_dump()
+
+    # Verify the structure is compatible with model_validate
+    # by creating a new recipe from the dictionary
+    new_recipe = Recipe.model_validate(recipe_dict)
+
+    # Verify version and args are preserved
+    assert new_recipe.version == recipe.version
+    assert new_recipe.args == recipe.args
+
+    # Verify stages are preserved
+    assert len(new_recipe.stages) == len(recipe.stages)
+
+    # Verify stage names and modifiers are preserved
+    for new_stage, orig_stage in zip(new_recipe.stages, recipe.stages):
+        assert new_stage.group == orig_stage.group
+        assert len(new_stage.modifiers) == len(orig_stage.modifiers)
+
+        # Verify modifier types and args are preserved
+        for new_mod, orig_mod in zip(new_stage.modifiers, orig_stage.modifiers):
+            assert new_mod.type == orig_mod.type
+            assert new_mod.args == orig_mod.args