refactor: optimize MultiDtypeGenerator code style and reduce nesting

- Refactor _modify_weight_meta to use single-pass traversal
- Extract _should_keep_weight_float32 helper method
- Simplify _ensure_autocast_import to reduce duplicate file writes
- Clean up unused variables in _validate_sample
- Apply black code formatting

Author: Dayuxiaoshui

graph_net/torch/multi_dtype_generate.py

@@ -16,59 +16,60 @@
 
 def main():
     parser = argparse.ArgumentParser(
-        description='Generate low-precision samples from existing float32 samples'
+        description="Generate low-precision samples from existing float32 samples"
     )
     parser.add_argument(
-        '--source-sample-path',
+        "--source-sample-path",
         type=str,
         required=True,
-        help='Path to the source sample directory'
+        help="Path to the source sample directory",
     )
     parser.add_argument(
-        '--output-base-path',
+        "--output-base-path",
         type=str,
         required=True,
-        help='Base path for output samples'
+        help="Base path for output samples",
     )
     parser.add_argument(
-        '--dtype-list',
+        "--dtype-list",
         type=str,
-        nargs='+',
-        default=['float16', 'bfloat16'],
-        choices=['float16', 'bfloat16', 'float8'],
-        help='List of target dtypes to generate (default: float16 bfloat16)'
+        nargs="+",
+        default=["float16", "bfloat16"],
+        choices=["float16", "bfloat16", "float8"],
+        help="List of target dtypes to generate (default: float16 bfloat16)",
     )
     parser.add_argument(
-        '--filter-config',
+        "--filter-config",
         type=str,
         default=None,
-        help='Path to filter configuration file (JSON format)'
+        help="Path to filter configuration file (JSON format)",
     )
-    
+
     args = parser.parse_args()
-    
+
     # Load filter config if provided
     filter_config = {}
     if args.filter_config:
         import json
-        with open(args.filter_config, 'r') as f:
+
+        with open(args.filter_config, "r") as f:
             filter_config = json.load(f)
-    
+
     # Create generator
     generator = MultiDtypeGenerator(
         source_sample_path=args.source_sample_path,
         output_base_path=args.output_base_path,
         dtype_list=args.dtype_list,
         filter_config=filter_config,
     )
-    
+
     # Generate samples
     print(f"Generating samples from: {args.source_sample_path}")
     print(f"Output base path: {args.output_base_path}")
     print(f"Target dtypes: {args.dtype_list}")
-    
+
     generated_paths = generator.generate()
-    
+
     if generated_paths:
         print(f"\nSuccessfully generated {len(generated_paths)} sample(s):")
         for path in generated_paths:
@@ -79,6 +80,5 @@ def main():
         return 1
 
 
-if __name__ == '__main__':
+if __name__ == "__main__":
     sys.exit(main())
-