[API Compatibility] change prefix matcher for 4 distributed apis -part

paconvert/api_mapping.json

@@ -3783,6 +3783,9 @@
       "tag"
     ]
   },
+  "torch.distributed.ProcessGroup": {
+    "Matcher": "ChangePrefixMatcher"
+  },
   "torch.distributed.ReduceOp": {
     "Matcher": "ChangePrefixMatcher"
   },
@@ -3813,14 +3816,7 @@
     }
   },
   "torch.distributed.all_gather_object": {
-    "Matcher": "AllGatherObjectMatcher",
-    "paddle_api": "paddle.distributed.all_gather_object",
-    "args_list": [
-      "object_list",
-      "obj",
-      "group"
-    ],
-    "min_input_args": 2
+    "Matcher": "ChangePrefixMatcher"
   },
   "torch.distributed.all_reduce": {
     "Matcher": "ReverseAsyncOpMatcher",
@@ -3934,29 +3930,7 @@
     "Matcher": "ChangePrefixMatcher"
   },
   "torch.distributed.init_process_group": {
-    "Matcher": "GenericMatcher",
-    "paddle_api": "paddle.distributed.init_parallel_env",
-    "args_list": [
-      "backend",
-      "init_method",
-      "timeout",
-      "world_size",
-      "rank",
-      "store",
-      "group_name",
-      "pg_options"
-    ],
-    "kwargs_change": {
-      "backend": "",
-      "init_method": "",
-      "timeout": "",
-      "world_size": "",
-      "rank": "",
-      "store": "",
-      "group_name": "",
-      "pg_options": ""
-    },
-    "min_input_args": 0
+    "Matcher": "ChangePrefixMatcher"
   },
   "torch.distributed.irecv": {
     "Matcher": "GenericMatcher",

paconvert/api_matcher.py

@@ -4710,27 +4710,6 @@ def generate_code(self, kwargs):
         return code
 
 
-class AllGatherObjectMatcher(BaseMatcher):
-    def generate_code(self, kwargs):
-        if "group" not in kwargs:
-            kwargs["group"] = None
-
-        API_TEMPLATE = textwrap.dedent(
-            """
-                {}=[]
-                {}(object_list={}, obj={}, group={})
-            """
-        )
-        return API_TEMPLATE.format(
-            kwargs["object_list"],
-            self.get_paddle_api(),
-            kwargs["object_list"],
-            kwargs["obj"],
-            kwargs["group"],
-            self.kwargs_to_str(kwargs),
-        )
-
-
 class SetUpMatcher(BaseMatcher):
     def generate_code(self, kwargs):
         is_torch_cpp_extension = False

paconvert/attribute_mapping.json

@@ -145,6 +145,9 @@
   "torch.distributed.ReduceOp.SUM": {
     "Matcher": "ChangePrefixMatcher"
   },
+  "torch.distributed.group.WORLD": {
+    "Matcher": "ChangePrefixMatcher"
+  },
   "torch.distributions.Distribution.batch_shape": {},
   "torch.distributions.Distribution.event_shape": {},
   "torch.distributions.Distribution.mean": {},

tests/distributed/ProcessGroup.py

@@ -0,0 +1,34 @@
+# Copyright (c) 2026 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import os
+
+import torch
+import torch.distributed as dist
+
+dist.init_process_group(backend="nccl")
+rank = dist.get_rank()
+torch.cuda.set_device(rank)
+
+pg = dist.group.WORLD
+if rank == 0:
+    data = torch.tensor([4, 5, 6]).cuda()
+else:
+    data = torch.tensor([1, 2, 3]).cuda()
+dist.all_reduce(data, group=pg)
+result = data
+# [5, 7, 9] (2 GPUs)
+if rank == 0:
+    print(result)
+    torch.save(result.cpu(), os.environ["DUMP_FILE"])

tests/distributed/group_WORLD.py

@@ -0,0 +1,34 @@
+# Copyright (c) 2026 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import os
+
+import torch
+import torch.distributed as dist
+
+dist.init_process_group(backend="nccl")
+rank = dist.get_rank()
+torch.cuda.set_device(rank)
+
+group = dist.group.WORLD
+if rank == 0:
+    data = torch.tensor([4, 5, 6]).cuda()
+else:
+    data = torch.tensor([1, 2, 3]).cuda()
+dist.all_reduce(data, group=group)
+result = data
+# [5, 7, 9] (2 GPUs)
+if rank == 0:
+    print(result)
+    torch.save(result.cpu(), os.environ["DUMP_FILE"])

tests/distributed/init_process_group.py

@@ -21,8 +21,6 @@
 rank = dist.get_rank()
 torch.cuda.set_device(rank)
 
-result = dist.is_initialized()
-
 if rank == 0:
-    print(result)
-    torch.save(result, os.environ["DUMP_FILE"])
+    print(rank)
+    torch.save(rank, os.environ["DUMP_FILE"])