fix style

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

Author: shanjiaz

src/llmcompressor/core/lifecycle.py

@@ -96,7 +96,7 @@ def initialize(
             recipe=recipe, target_stage=recipe_stage, override_args=recipe_args
         )
         self.modifiers = self.recipe.create_modifier()
-
+        breakpoint()
         mod_data = []
         for mod in self.modifiers:
             data = mod.initialize(state=self.state, **kwargs)

src/llmcompressor/pipelines/registry.py

@@ -42,7 +42,6 @@ def from_modifiers(
         :param user: pipeline name passed by user
         :return: CalibrationPipeline instance to be called with data (if not datafree)
         """
-
         user = standardize_lookup_name(user) if user else None
         inferred = standardize_lookup_name(cls._validate_infer_pipeline(modifiers))
         independent = standardize_lookup_name("independent")

src/llmcompressor/pipelines/sequential/helpers.py

@@ -432,6 +432,7 @@ def get_targets_from_modifiers(
     sequential_modifiers = [
         modifier for modifier in modifiers if isinstance(modifier, SEQUENTIAL_MODIFIERS)
     ]
+
     if len(sequential_modifiers) >= 2:
         types = [type(modifier) for modifier in sequential_modifiers]
         logger.warning(

src/llmcompressor/recipe/recipe.py

@@ -10,8 +10,8 @@
 from llmcompressor.recipe.utils import (
     _load_json_or_yaml_string,
     _parse_recipe_from_md,
-    get_yaml_serializable_dict,
     deep_merge_dicts,
+    get_yaml_serializable_dict,
 )
 
 __all__ = [
@@ -251,6 +251,7 @@ def create_modifier(self) -> List[Modifier]:
             if isinstance(modifier, Modifier)
             else ModifierFactory.create(
                 modifier["type"],
+                group=modifier.get("group"),
                 allow_registered=True,
                 allow_experimental=True,
                 **modifier["args"],
@@ -272,18 +273,19 @@ def yaml(
         existing_recipe_path: Optional[str] = None,
     ) -> str:
         """
-        Return a YAML string representation of the recipe, optionally merging with another YAML file.
+        Return a YAML string representation of the recipe,
+        optionally merging with another YAML file.
 
         :param file_path: Optional path to save YAML
         :param existing_recipe_path: Optional path to another recipe.yaml file
         :return: Combined YAML string
         """
         # Load the other recipe from file, if given
-        other_dict = {}
+        existing_dict = {}
         if existing_recipe_path:
             with open(existing_recipe_path, "r") as f:
                 existing_recipe_str = f.read()
-            other_dict = _load_json_or_yaml_string(existing_recipe_str)
+            existing_dict = _load_json_or_yaml_string(existing_recipe_str)
 
         # Serialize current recipe
         self_dict = get_yaml_serializable_dict(
@@ -292,7 +294,7 @@ def yaml(
         )
 
         # Deep merge — keep both recipe contents
-        merged_dict = deep_merge_dicts(other_dict, self_dict)
+        merged_dict = deep_merge_dicts(existing_dict, self_dict)
 
         # Dump YAML
         file_stream = None if file_path is None else open(file_path, "w")
@@ -304,7 +306,7 @@ def yaml(
             default_flow_style=None,
             width=88,
         )
-        
+
         if file_stream:
             file_stream.close()
 

src/llmcompressor/recipe/utils.py

@@ -97,6 +97,7 @@ def get_yaml_serializable_dict(modifiers: List[Modifier], stage: str) -> Dict[st
 
     return stage_dict
 
+
 def deep_merge_dicts(d1: dict, d2: dict) -> dict:
     """
     Recursively merge d2 into d1.

src/llmcompressor/transformers/sparsification/compressed_tensors_utils.py

@@ -293,10 +293,10 @@ def update_and_save_recipe(model_stub: str, save_directory: str):
         existing recipe
     :param save_directory: path to save combined existing recipe and current recipe
     """
- 
+
     existing_recipe = infer_recipe_from_model_path(model_stub)
 
     recipe = active_session().lifecycle.recipe
-    
+
     recipe_path = os.path.join(save_directory, RECIPE_FILE_NAME)
     recipe.yaml(file_path=recipe_path, existing_recipe_path=existing_recipe)