转换规则 torch.nn.parallel.DistributedDataParallel (#240)

paconvert/api_mapping.json

@@ -9403,6 +9403,37 @@
       "n": 2
     }
   },
+  "torch.nn.parallel.DistributedDataParallel": {
+    "Matcher": "GenericMatcher",
+    "paddle_api": "paddle.DataParallel",
+    "args_list": [
+      "module",
+      "device_ids",
+      "output_device",
+      "dim",
+      "broadcast_buffers",
+      "process_group",
+      "bucket_cap_mb",
+      "find_unused_parameters",
+      "check_reduction",
+      "gradient_as_bucket_view",
+      "static_graph"
+    ],
+    "kwargs_change": {
+      "module": "layers",
+      "device_ids": "",
+      "bucket_cap_mb": "comm_buffer_size",
+      "check_reduction": ""
+    },
+    "unsupport_args": [
+      "output_device",
+      "dim",
+      "broadcast_buffers",
+      "process_group",
+      "gradient_as_bucket_view",
+      "static_graph"
+    ]
+  },
   "torch.nn.utils.clip_grad_norm_": {
     "Matcher": "GenericMatcher",
     "paddle_api": "paddle.nn.utils.clip_grad_norm_",

tests/test_nn_parallel_DistributedDataParallel.py

@@ -0,0 +1,78 @@
+# Copyright (c) 2023 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 textwrap
+
+from apibase import APIBase
+
+obj = APIBase("paddle.DataParallel")
+
+
+def _test_case_1():
+    pytorch_code = textwrap.dedent(
+        """
+        import torch
+        torch.distributed.init_process_group(
+            "nccl",
+            init_method="tcp://127.0.0.1:23456",
+            rank=0,
+            world_size=1
+        )
+        model = torch.nn.Linear(1, 1, bias=False).cuda()
+        model = torch.nn.parallel.DistributedDataParallel(model)
+        result=True
+        """
+    )
+    obj.run(pytorch_code, ["result"])
+
+
+def _test_case_2():
+    pytorch_code = textwrap.dedent(
+        """
+        import torch
+        torch.distributed.init_process_group(
+            "nccl",
+            init_method="tcp://127.0.0.1:23456",
+            rank=0,
+            world_size=1
+        )
+        model = torch.nn.Linear(1, 1, bias=False).cuda()
+        model = torch.nn.parallel.DistributedDataParallel(model,device_ids=[0])
+        result=True
+        """
+    )
+    obj.run(pytorch_code, ["result"])
+
+
+def test_case_3():
+    pytorch_code = textwrap.dedent(
+        """
+        import torch
+        torch.distributed.init_process_group(
+            "nccl",
+            init_method="tcp://127.0.0.1:23456",
+            rank=0,
+            world_size=1
+        )
+        model = torch.nn.Linear(1, 1, bias=False).cuda()
+        model = torch.nn.parallel.DistributedDataParallel(model,device_ids=[0],output_device=0)
+        result=True
+        """
+    )
+    obj.run(
+        pytorch_code,
+        ["result"],
+        unsupport=True,
+        reason="paddle not support the parameter",
+    )