From 57caf1d028e5302db7f2e00d1fb7d156ea370c9c Mon Sep 17 00:00:00 2001
From: YWMditto <ditto@YWMdittodeMacBook-Pro.local>
Date: Tue, 12 Apr 2022 11:43:26 +0800
Subject: [PATCH] =?UTF-8?q?checkpoint=20callback=20=E5=8A=A0=E5=85=A5?=
 =?UTF-8?q?=E4=BA=86=20on=5Fafter=5Ftrainer=5Finitialized=20=E7=9A=84?=
 =?UTF-8?q?=E9=80=BB=E8=BE=91?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 fastNLP/core/callbacks/checkpoint_callback.py | 18 ++++++++++++++++--
 1 file changed, 16 insertions(+), 2 deletions(-)

diff --git a/fastNLP/core/callbacks/checkpoint_callback.py b/fastNLP/core/callbacks/checkpoint_callback.py
index d3a3b52d..12b6a9e6 100644
--- a/fastNLP/core/callbacks/checkpoint_callback.py
+++ b/fastNLP/core/callbacks/checkpoint_callback.py
@@ -48,8 +48,9 @@ class CheckpointCallback(Callback):
             model_save_fn: Optional[Callable] = None,
             **kwargs,
     ):
-        if monitor is None and save_topk is not None:
-            raise ValueError("Parameter `monitor` must be set when you want to use 'save_topk'.")
+        # 我们新加了逻辑，如果 checkpoint callback 自己没有设置 monitor 和 larger_better，那么我们会将其在 trainer 中的设置赋值给它们；
+        # if monitor is None and save_topk is not None:
+        #     raise ValueError("Parameter `monitor` must be set when you want to use 'save_topk'.")
 
         if monitor is not None and not isinstance(monitor, str):
             raise ValueError("Parameter `monitor` should be of 'str' type.")
@@ -119,6 +120,19 @@ class CheckpointCallback(Callback):
         # 我们只需要保证这个创建文件夹的操作只在进程 0 上进行即可；因为后续的实际的保存操作，其它进程实际并不会去执行；
         synchronize_mkdir(self.timestamp_path)
 
+    def on_after_trainer_initialized(self, trainer, driver):
+        if self.monitor is None:
+            if trainer.monitor is not None:
+                self.monitor = trainer.monitor
+                self.larger_better = trainer.larger_better
+            elif self.save_topk is not None:
+                raise RuntimeError("You are using `topk` mode, but you have not set the `monitor` value either in this"
+                                   "callback or in trainer.")
+            else:
+                self.monitor = None
+        if self.save_topk is not None and trainer.evaluator is None:
+            raise RuntimeError("You are using `topk` mode, but there is no `evaluator` in trainer.")
+
     def on_validate_end(self, trainer, validate_res):
         self._save_topk(trainer, validate_res)