diff --git a/paddleformers/trainer/training_args.py b/paddleformers/trainer/training_args.py
index 44bac91563..5f0dd96388 100644
--- a/paddleformers/trainer/training_args.py
+++ b/paddleformers/trainer/training_args.py
@@ -305,7 +305,8 @@ class TrainingArguments:
         refined_recompute (`str`, *optional*, defaults to `""`):
             The refined recompute parameter is designed to optimize the balance between GPU memory usage and computational speed.
             An example configuration could be: `attention_column_ln:-1,attention_row_ln:-1,flash_attn:-1,mlp_column_ln:5,mlp_row_ln:-1`.
-            The supported parameters for refining recompute are `attention_column_ln`, `attention_row_ln`, `flash_attn`, `mlp_column_ln`, and `mlp_row_ln`.
+            The supported parameters for refining recompute are `attention_column_ln`, `attention_row_ln`, `flash_attn`, `mlp_column_ln`, `mlp_row_ln`, and `global`.
+                -`global`: global configuration that applies to ALL operators.
             The associated number, `skip_num`, determines how many times to bypass recomputation for the specified operation.
             A `skip_num` of `-1` indicates no recomputation across all stages, maximizing memory usage;
             A `skip_num` of `0` enforces recomputation at every stage, minimizing memory usage.
@@ -2029,6 +2030,7 @@ def is_context_parallel_supported():
                 "attention_column_ln": 0,
                 "mlp_column_ln": 0,
                 "flash_attn": 0,
+                "global": 0,
             }
             ops = self.refined_recompute.split(",")
             enable_rr = False