!45064 [AutoParallel] fix parameter clone bug

Merge pull request !45064 from lichen/fix_parameter_clone_bug

mindspore/ccsrc/frontend/parallel/parameter_manager.cc

@@ -432,7 +432,7 @@ void InitOptimizerState(const FuncGraphPtr &root) {
     auto graph_executor = pipeline::GraphExecutorPy::GetInstance();
     MS_EXCEPTION_IF_NULL(graph_executor);
     auto phase = graph_executor->phase();
-    auto py_obj = GetPyParameterObj(param_info, CLONED_OBJ);
+    auto py_obj = GetPyParameterObj(param_info, OBJ);
     if (py::isinstance<py::none>(py_obj)) {
       MS_LOG(WARNING) << "Parameter: " << parameter->DebugString() << " can't find python obj.";
       continue;

mindspore/python/mindspore/common/parameter.py

@@ -491,7 +491,7 @@ class Parameter(Tensor_):
         else:
             info.cloned_obj = [x]
         self.param_info = info
-        param_info_clone.cloned_obj = x
+        param_info_clone.obj = x
         x.param_info = param_info_clone
         x.is_init = False
         x.init = self.init

tests/ut/python/parallel/test_parameter_clone.py

@@ -0,0 +1,41 @@
+# Copyright 2022 Huawei Technologies Co., Ltd
+#
+# 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.
+
+from mindspore import Tensor
+from mindspore import Parameter
+from mindspore.common.initializer import Normal
+import mindspore as ms
+
+
+def test_parameter_clone():
+    """
+    Feature: test parameter clone api
+    Description: assert data and repr
+    Expectation: success
+    """
+    tensor = Tensor(input_data=None, shape=(16, 32), dtype=ms.float32, init=Normal())
+    param = Parameter(tensor, requires_grad=False)
+    param2 = param.clone()
+
+    data1 = param.asnumpy()
+    data2 = param2.asnumpy()
+    repr1 = repr(param2)
+    assert (data1 == data2).all()
+    assert "requires_grad=False" in repr1
+    assert "shape=(16, 32)" in repr1
+    param3 = param2.clone()
+    data3 = param3.asnumpy()
+    repr2 = repr(param3)
+    assert (data1 == data3).all()
+    assert repr1 == repr2