diff --git a/paconvert/api_mapping.json b/paconvert/api_mapping.json
index a9be417f8..6cf219935 100644
--- a/paconvert/api_mapping.json
+++ b/paconvert/api_mapping.json
@@ -6674,7 +6674,7 @@
     "Matcher": "TensorUnchangeMatcher"
   },
   "torch.nn.Module.bfloat16": {
-    "Matcher": "NnModuleTypeMatcher",
+    "Matcher": "GenericMatcher",
     "paddle_api": "paddle.nn.Layer.to"
   },
   "torch.nn.Module.buffers": {
@@ -6694,14 +6694,14 @@
   "torch.nn.Module.cpu": {},
   "torch.nn.Module.cuda": {},
   "torch.nn.Module.double": {
-    "Matcher": "NnModuleTypeMatcher",
+    "Matcher": "GenericMatcher",
     "paddle_api": "paddle.nn.Layer.to"
   },
   "torch.nn.Module.eval": {
     "Matcher": "TensorUnchangeMatcher"
   },
   "torch.nn.Module.float": {
-    "Matcher": "NnModuleTypeMatcher",
+    "Matcher": "GenericMatcher",
     "paddle_api": "paddle.nn.Layer.to"
   },
   "torch.nn.Module.get_buffer": {},
@@ -6709,7 +6709,7 @@
   "torch.nn.Module.get_parameter": {},
   "torch.nn.Module.get_submodule": {},
   "torch.nn.Module.half": {
-    "Matcher": "NnModuleTypeMatcher",
+    "Matcher": "GenericMatcher",
     "paddle_api": "paddle.nn.Layer.to"
   },
   "torch.nn.Module.ipu": {},
@@ -6867,7 +6867,7 @@
     "paddle_api": "paddle.nn.Layer.train"
   },
   "torch.nn.Module.type": {
-    "Matcher": "NnModuleTypeMatcher",
+    "Matcher": "GenericMatcher",
     "paddle_api": "paddle.nn.Layer.to"
   },
   "torch.nn.Module.xpu": {},
diff --git a/paconvert/api_matcher.py b/paconvert/api_matcher.py
index e09f230de..a7ec1bac8 100644
--- a/paconvert/api_matcher.py
+++ b/paconvert/api_matcher.py
@@ -3651,15 +3651,6 @@ def get_paddle_nodes(self, args, kwargs):
         return node
 
 
-class NnModuleToMatcher(BaseMatcher):
-    def generate_code(self, kwargs):
-        kwargs = self.parse_kwargs(kwargs)
-        if "non_blocking" in kwargs:
-            kwargs["blocking"] = not kwargs["non_blocking"]
-            del kwargs["non_blocking"]
-        return GenericMatcher.generate_code(self, kwargs)
-
-
 class SizeAverageMatcher(BaseMatcher):
     def generate_code(self, kwargs):
         process_reduce_and_size_average(kwargs)