Modify Tensorflow regularizers

deepxde/nn/regularizers.py

@@ -2,16 +2,32 @@
 
 
 def get(identifier):
+    """Retrieves a TensorFlow regularizer instance based on the given identifier.
+
+    Args:
+        identifier (list/tuple): Specifies the type and factor(s) of the regularizer.
+            The first element should be one of "l1", "l2", or "l1l2" ("l1+l2").
+            For "l1" and "l2", a single regularization factor is expected.
+            For "l1l2", provide both "l1" and "l2" factors.
+    """
+
     # TODO: other backends
-    if identifier is None:
+    if identifier is None or not identifier:
         return None
-    name, scales = identifier[0].lower(), identifier[1:]
-    return (
-        tf.keras.regularizers.L1(l1=scales[0])
-        if name == "l1"
-        else tf.keras.regularizers.L2(l2=scales[0])
-        if name == "l2"
-        else tf.keras.regularizers.L1L2(l1=scales[0], l2=scales[1])
-        if name in ("l1+l2", "l1l2")
-        else None
-    )
+    if not isinstance(identifier, (list, tuple)):
+        raise ValueError("Identifier must be a list or a tuple.")
+
+    name = identifier[0].lower()
+    factor = identifier[1:]
+    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])
+    raise ValueError(f"Unknown regularizer name: {name}")