fix kl js loss

configs/det/ch_PP-OCRv3/ch_PP-OCRv3_det_dml.yml

@@ -60,7 +60,7 @@ Loss:
       - ["Student", "Student2"]
       maps_name: "thrink_maps"
       weight: 1.0
-      act: "softmax"
+      # act: None
       model_name_pairs: ["Student", "Student2"]
       key: maps
   - DistillationDBLoss:

ppocr/losses/basic_loss.py

@@ -57,17 +57,24 @@ class CELoss(nn.Layer):
 class KLJSLoss(object):
     def __init__(self, mode='kl'):
         assert mode in ['kl', 'js', 'KL', 'JS'
-                        ], "mode can only be one of ['kl', 'js', 'KL', 'JS']"
+                        ], "mode can only be one of ['kl', 'KL', 'js', 'JS']"
         self.mode = mode
 
     def __call__(self, p1, p2, reduction="mean"):
 
-        loss = paddle.multiply(p2, paddle.log((p2 + 1e-5) / (p1 + 1e-5) + 1e-5))
-
-        if self.mode.lower() == "js":
+        if self.mode.lower() == 'kl':
+            loss = paddle.multiply(p2, paddle.log((p2 + 1e-5) / (p1 + 1e-5) + 1e-5))
+            loss += paddle.multiply(
+                    p1, paddle.log((p1 + 1e-5) / (p2 + 1e-5) + 1e-5))
+            loss *= 0.5
+        elif self.mode.lower() == "js":
+            loss = paddle.multiply(p2, paddle.log((2*p2 + 1e-5) / (p1 + p2 + 1e-5) + 1e-5))
             loss += paddle.multiply(
-                p1, paddle.log((p1 + 1e-5) / (p2 + 1e-5) + 1e-5))
+                    p1, paddle.log((2*p1 + 1e-5) / (p1 + p2 + 1e-5) + 1e-5))
             loss *= 0.5
+        else:
+            raise ValueError("The mode.lower() if KLJSLoss should be one of ['kl', 'js']")
+            
         if reduction == "mean":
             loss = paddle.mean(loss, axis=[1, 2])
         elif reduction == "none" or reduction is None:
@@ -95,7 +102,7 @@ class DMLLoss(nn.Layer):
             self.act = None
 
         self.use_log = use_log
-        self.jskl_loss = KLJSLoss(mode="js")
+        self.jskl_loss = KLJSLoss(mode="kl")
 
     def _kldiv(self, x, target):
         eps = 1.0e-10