Minor refine.

Author: Xreki

graph_net/subgraph_decompose_and_evaluation_step.py

@@ -143,7 +143,7 @@ def get_model_name_with_subgraph_tag(model_path):
     return f"{fields[-2]}_{fields[-1]}" if re.match(pattern, fields[-1]) else fields[-1]
 
 
-def run_decomposer(
+def run_naive_decomposer(
     framework: str,
     model_path: str,
     output_dir: str,
@@ -170,8 +170,8 @@ def run_decomposer(
         json.dumps(decorator_config).encode()
     ).decode()
 
-    print(f"[Decomposing] model_path: {model_path}")
-    print(f"[Decomposing] split_positions: {split_positions}")
+    print(f"[Decomposition] model_path: {model_path}")
+    print(f"[Decomposition] split_positions: {split_positions}")
 
     cmd = [
         sys.executable,
@@ -215,8 +215,8 @@ def run_evaluation(
         for item in (f"--{key}", str(value))
     ]
 
-    print(f"[Batch Testing] Logging to: {log_path}")
-    print(f"[Command] {' '.join(cmd)}")
+    print(f"[Evaluation] Logging to: {log_path}")
+    print(f"[Evaluation] command: {' '.join(cmd)}")
 
     os.makedirs(os.path.dirname(log_path), exist_ok=True)
     with open(log_path, "w") as f:
@@ -286,7 +286,7 @@ def generate_refined_tasks(base_output_dir, current_pass_id):
     prev_max_subgraph_size = prev_config.get("max_subgraph_size")
     max_subgraph_size = prev_max_subgraph_size // 2
 
-    if not prev_incorrect_subgraphs or prev_max_subgraph_size <= 1:
+    if not prev_incorrect_subgraphs:
         return {}, {}, max_subgraph_size
 
     print("[Analysis] Refining splits based on previous incorrect models ...")
@@ -338,7 +338,7 @@ def execute_decomposition_phase(max_subgraph_size, tasks_map, framework, pass_wo
             print(f"decomposed_samples_dir: {decomposed_samples_dir}")
 
         for model_name, task_info in tasks_map.items():
-            print(f"[Decomposing] max_subgraph_size: {max_subgraph_size}")
+            print(f"[Decomposition] max_subgraph_size: {max_subgraph_size}")
             original_path = task_info["original_path"]
             split_positions = calculate_split_positions_for_subgraph(
                 task_info["subgraph_size"], max_subgraph_size
@@ -350,15 +350,15 @@ def execute_decomposition_phase(max_subgraph_size, tasks_map, framework, pass_wo
                 rectified_model_path
             ), f"{rectified_model_path} does not exist."
 
-            success = run_decomposer(
+            success = run_naive_decomposer(
                 framework, rectified_model_path, decomposed_samples_dir, split_positions
             )
             if not success:
                 failed_decomposition.append(rectified_model_path)
 
         num_decomposed_samples = count_samples(decomposed_samples_dir)
         print(
-            f"[Decomposing] number of graphs: {len(tasks_map)} -> {num_decomposed_samples}",
+            f"[Decomposition] number of graphs: {len(tasks_map)} -> {num_decomposed_samples}",
             flush=True,
         )
         if (
@@ -455,15 +455,15 @@ def main(args):
     # --- Step 4: Testing ---
     pass_log_path = os.path.join(pass_work_dir, "batch_test_result.log")
     if task_controller.task_scheduler["run_evaluation"]:
-        print("\n--- Phase 2: Batch Testing ---")
+        print("\n--- Phase 2: Evaluation ---")
         run_evaluation(args.framework, args.test_config, pass_work_dir, pass_log_path)
 
     # --- Step 5: Analysis ---
     next_round_models = set()
     if task_controller.task_scheduler["post_analysis"]:
         print("\n--- Phase 3: Analysis ---")
         next_round_models = get_incorrect_models(args.tolerance, pass_log_path)
-        print(f"[Result] Found {len(next_round_models)} incorrect subgraphs.")
+        print(f"[Analysis] Found {len(next_round_models)} incorrect subgraphs.\n")
 
     # --- Step 6: Save State ---
     save_decompose_config(