fix bug in checkpoint when save scaler

mindspore/nn/wrap/cell_wrapper.py

@@ -344,5 +344,5 @@ class ParameterUpdate(Cell):
         self._param = param
 
     def construct(self, x):
-        self._param = x
+        F.assign(self._param, x)
         return x

mindspore/train/serialization.py

@@ -408,10 +408,11 @@ def _fill_param_into_net(net, parameter_list):
     for each_param in parameter_list:
         param_name = each_param["name"]
         np_val = each_param["data"].asnumpy()
-        if np_val.shape == (1,):  # to scalar
-            parameter_dict[param_name] = Parameter(np_val[0], name=param_name)
+        if np_val.shape == (1,):
+            parameter_dict[param_name] = Parameter(np_val, name=param_name)
         elif np_val.shape == ():
-            parameter_dict[param_name] = Parameter(np_val.tolist(), name=param_name)
+            parameter_dict[param_name] = Parameter(Tensor(np_val.tolist(), mstype.pytype_to_dtype(np_val.dtype)),
+                                                   name=param_name)
         else:
             parameter_dict[param_name] = Parameter(Tensor(np_val), name=param_name)
 

tests/ut/python/nn/test_parameter.py

@@ -52,12 +52,69 @@ def test_parameter_tuple_illegal():
 
 
 def test_parameter_init_illegal():
+    import numpy as np
+    dat = np.array([[1, 2, 3], [2, 3, 4]])
+    tensor = Tensor(dat)
+    data_none = None
     data_bool = True
     data_str = "nicai"
+    data_int = 3
+    data_list = [1, "2", True]
+    data_tuple = (1, 2, 3)
+
+    # test data
+    Parameter(tensor, name=data_str)
+    Parameter(data_int, name=data_str)
+    Parameter(dat, name=data_str)
     with pytest.raises(ValueError):
         Parameter(data_bool, name=data_str)
 
+    # test name
+    Parameter(tensor, name=data_none)
+    with pytest.raises(ValueError):
+        Parameter(tensor, name=dat)
+    with pytest.raises(ValueError):
+        Parameter(tensor, name=tensor)
+    with pytest.raises(ValueError):
+        Parameter(tensor, name=data_bool)
+    with pytest.raises(ValueError):
+        Parameter(tensor, name=data_int)
+    with pytest.raises(ValueError):
+        Parameter(tensor, name=data_list)
+    with pytest.raises(ValueError):
+        Parameter(tensor, name=data_tuple)
+
+    Parameter(tensor, name=data_str, requires_grad=data_bool)
+    with pytest.raises(TypeError):
+        Parameter(tensor, name=data_str, requires_grad=data_none)
+    with pytest.raises(TypeError):
+        Parameter(tensor, name=data_str, requires_grad=dat)
+    with pytest.raises(TypeError):
+        Parameter(tensor, name=data_str, requires_grad=tensor)
+    with pytest.raises(TypeError):
+        Parameter(tensor, name=data_str, requires_grad=data_str)
+    with pytest.raises(TypeError):
+        Parameter(tensor, name=data_str, requires_grad=data_int)
+    with pytest.raises(TypeError):
+        Parameter(tensor, name=data_str, requires_grad=data_list)
+    with pytest.raises(TypeError):
+        Parameter(tensor, name=data_str, requires_grad=data_tuple)
 
+    Parameter(tensor, name=data_str, requires_grad=data_bool,layerwise_parallel=data_bool)
+    with pytest.raises(TypeError):
+        Parameter(tensor, name=data_str, requires_grad=data_bool,layerwise_parallel=dat)
+    with pytest.raises(TypeError):
+        Parameter(tensor, name=data_str, requires_grad=data_bool,layerwise_parallel=tensor)
+    with pytest.raises(TypeError):
+        Parameter(tensor, name=data_str, requires_grad=data_bool,layerwise_parallel=data_none)
+    with pytest.raises(TypeError):
+        Parameter(tensor, name=data_str, requires_grad=data_bool,layerwise_parallel=data_str)
+    with pytest.raises(TypeError):
+        Parameter(tensor, name=data_str, requires_grad=data_bool,layerwise_parallel=data_int)
+    with pytest.raises(TypeError):
+        Parameter(tensor, name=data_str, requires_grad=data_bool,layerwise_parallel=data_list)
+    with pytest.raises(TypeError):
+        Parameter(tensor, name=data_str, requires_grad=data_bool,layerwise_parallel=data_tuple)
 
 
 def test_check_str_by_regular():