Backend paddle: add regularizer

Author: lijialin03

deepxde/backend/backend.py

@@ -502,3 +502,12 @@ def sparse_dense_matmul(x, y):
     Returns:
         Tensor: The multiplication result.
     """
+
+def l1_decay(x):
+    """Implement the L1 weight decay regularization."""
+
+def l2_decay(x):
+    """Implement the L2 weight decay regularization."""
+
+def l1_l2_decay(x,y):
+    """Implement the L1 and L2 weight decay regularization."""

deepxde/backend/paddle/tensor.py

@@ -229,3 +229,9 @@ def matmul(x, y):
 
 def sparse_dense_matmul(x, y):
     return paddle.sparse.matmul(x, y)
+
+def l1_decay(x):
+    return paddle.regularizer.L1Decay(coeff=x)
+
+def l2_decay(x):
+    return paddle.regularizer.L2Decay(coeff=x)

deepxde/backend/tensorflow_compat_v1/tensor.py

@@ -245,3 +245,12 @@ def matmul(x, y):
 
 def sparse_dense_matmul(x, y):
     return tf.sparse.sparse_dense_matmul(x, y)
+
+def l1_decay(x):
+    return tf.keras.regularizers.L1(l1=x)
+
+def l2_decay(x):
+    return tf.keras.regularizers.L2(l2=x)
+
+def l1_l2_decay(x,y):
+    return tf.keras.regularizers.L1L2(l1=x, l2=y)

deepxde/nn/regularizers.py

@@ -1,4 +1,5 @@
-from ..backend import tf
+from .. import backend as bkd
+from ..backend import backend_name
 
 
 def get(identifier):
@@ -22,12 +23,15 @@ def get(identifier):
     if not factor:
         raise ValueError("Regularization factor must be provided.")
 
-    if name == "l1":
-        return tf.keras.regularizers.L1(l1=factor[0])
-    if name == "l2":
-        return tf.keras.regularizers.L2(l2=factor[0])
-    if name in ("l1l2", "l1+l2"):
-        if len(factor) < 2:
-            raise ValueError("L1L2 regularizer requires both L1/L2 penalties.")
-        return tf.keras.regularizers.L1L2(l1=factor[0], l2=factor[1])
+    try:
+        if name == "l1":
+            return bkd.l1_decay(factor[0])
+        if name == "l2":
+            return bkd.l2_decay(factor[0])
+        if name in ("l1l2", "l1+l2"):
+            # TODO: only supported by 'tensorflow.compat.v1' now.
+            if len(factor) < 2:
+                return bkd.l1_l2_decay(factor[0], factor[1])
+    except Exception:
+        print(f"{name} regularization to be implemented for backend {backend_name} now.")
     raise ValueError(f"Unknown regularizer name: {name}")