Fix code formatting: apply black formatter

Author: Dayuxiaoshui

graph_net/torch/dtype_gen_passes/dtype_generalization_pass.py

@@ -134,18 +134,20 @@ def _is_float32_tensor(self, node: fx.Node) -> bool:
             # Check type annotation if available
             if node.type is not None:
                 type_str = str(node.type).lower()
-                
+
                 # Explicitly check for integer types - these should NOT be converted
                 integer_types = ["long", "int", "short", "byte", "bool"]
                 if any(int_type in type_str for int_type in integer_types):
                     return False
-                
+
                 # Only return True if explicitly a floating point tensor
                 # Check for explicit float types: FloatTensor, float32, float16, etc.
                 float_indicators = ["float", "double", "half", "bfloat"]
-                if any(float_indicator in type_str for float_indicator in float_indicators):
+                if any(
+                    float_indicator in type_str for float_indicator in float_indicators
+                ):
                     return True
-                
+
                 # For generic "Tensor" without explicit dtype, be conservative
                 # Don't assume it's float32 - it might be integer
                 return False

graph_net/torch/dtype_generalizer.py

@@ -82,7 +82,7 @@ def __call__(self, model_path: str) -> None:
         # Apply model_path_prefix if provided
         if self.model_path_prefix:
             model_path = str(Path(self.model_path_prefix) / model_path)
-        
+
         # Parse the computation graph
         traced_model = parse_immutable_model_path_into_sole_graph_module(model_path)
 
@@ -186,7 +186,9 @@ def _save_dtype_pass_names(
             model_path: Path to model directory
         """
         graph_net_json_path = Path(model_path) / "graph_net.json"
-        update_json(graph_net_json_path, {kDataTypeGeneralizationPasses: dtype_pass_names})
+        update_json(
+            graph_net_json_path, {kDataTypeGeneralizationPasses: dtype_pass_names}
+        )
 
 
 class ApplyDataTypeGeneralizationPasses:
@@ -211,17 +213,16 @@ def __init__(self, config: Dict[str, Any]):
         self.output_dir = config.get("output_dir")
         if not self.output_dir:
             raise ValueError("output_dir is required in config")
-        
+
         self.model_path_prefix = config.get("model_path_prefix", "")
-        
+
         # model_runnable_predicator is required to ensure generated code is runnable
         if "model_runnable_predicator_filepath" not in config:
             raise ValueError(
                 "model_runnable_predicator_filepath is required in config. "
                 "Generated code must be validated."
             )
         self.model_runnable_predicator = self._make_model_runnable_predicator(config)
-    
     def _make_model_runnable_predicator(self, config: Dict[str, Any]):
         """Create model runnable predicator from config."""
         module = load_module(config["model_runnable_predicator_filepath"])
@@ -245,7 +246,7 @@ def __call__(self, model_path: str) -> List[str]:
         # Apply model_path_prefix if provided
         if self.model_path_prefix:
             model_path = str(Path(self.model_path_prefix) / model_path)
-        
+
         # Read pass names from graph_net.json
         dtype_pass_names = self._read_dtype_pass_names(model_path)