From eba9b550c31393a4bee2794ffdff31d455a120ea Mon Sep 17 00:00:00 2001
From: lijialin03 <lijialin03@baidu.com>
Date: Tue, 17 Dec 2024 02:27:05 +0000
Subject: [PATCH] update code and add regularizer for nn

---
 deepxde/nn/paddle/nn.py                 |  1 +
 deepxde/optimizers/paddle/optimizers.py | 16 +++++++---------
 2 files changed, 8 insertions(+), 9 deletions(-)

diff --git a/deepxde/nn/paddle/nn.py b/deepxde/nn/paddle/nn.py
index 6609027dc..74e6e5723 100644
--- a/deepxde/nn/paddle/nn.py
+++ b/deepxde/nn/paddle/nn.py
@@ -6,6 +6,7 @@ class NN(paddle.nn.Layer):
 
     def __init__(self):
         super().__init__()
+        self.regularizer = None
         self._input_transform = None
         self._output_transform = None
 
diff --git a/deepxde/optimizers/paddle/optimizers.py b/deepxde/optimizers/paddle/optimizers.py
index 1a12f9f5c..edb2ad7d8 100644
--- a/deepxde/optimizers/paddle/optimizers.py
+++ b/deepxde/optimizers/paddle/optimizers.py
@@ -62,13 +62,11 @@ def get(params, optimizer, learning_rate=None, decay=None, weight_decay=None):
             weight_decay=weight_decay,
         )
     if optimizer == "adamw":
-        if isinstance(weight_decay, paddle.regularizer.L2Decay):
-            if weight_decay._coeff == 0:
-                raise ValueError("AdamW optimizer requires non-zero weight decay")
-            return paddle.optimizer.AdamW(
-                learning_rate=learning_rate,
-                parameters=params,
-                weight_decay=weight_decay._coeff,
-            )
-        raise ValueError("AdamW optimizer requires l2 regularizer")
+        if not isinstance(weight_decay, paddle.regularizer.L2Decay) or weight_decay._coeff == 0:
+            raise ValueError("AdamW optimizer requires L2 regularizer and non-zero weight decay")
+        return paddle.optimizer.AdamW(
+            learning_rate=learning_rate,
+            parameters=params,
+            weight_decay=weight_decay._coeff,
+        )
     raise NotImplementedError(f"{optimizer} to be implemented for backend Paddle.")