add dtype shape and value in __str__ and __repr__ of Parameter

mindspore/common/parameter.py

@@ -201,10 +201,11 @@ class Parameter(Tensor_):
         return (Tensor, data)
 
     def __str__(self):
-        return f'Parameter (name={self._param_info.name})'
+        return f'Parameter (name={self.name}, shape={self.shape}, dtype={self.dtype}, ' \
+               f'requires_grad={self.requires_grad})'
 
     def __repr__(self):
-        return f'Parameter (name={self._param_info.name})'
+        return self.__str__()
 
     def __parameter__(self):
         """For parse check."""
@@ -242,7 +243,6 @@ class Parameter(Tensor_):
         """
         return self._inited_param
 
-
     @property
     def name(self):
         """Get the name of the parameter."""
@@ -501,10 +501,8 @@ class Parameter(Tensor_):
             Parameter, the `Parameter` after initializing data. If current `Parameter` was already initialized before,
             returns the same initialized `Parameter`.
         """
-        if self.is_default_input_init:
-            is_current_in_parallel = _is_in_parallel_mode()
-            if self.is_in_parallel != is_current_in_parallel:
-                raise RuntimeError("Must set or change parallel mode before any Tensor created.")
+        if self.is_default_input_init and self.is_in_parallel != _is_in_parallel_mode():
+            raise RuntimeError("Must set or change parallel mode before any Tensor created.")
         if self.init_mode is None:
             return self
         if self.inited_param is not None:
@@ -512,29 +510,21 @@ class Parameter(Tensor_):
         if _is_role_worker() and self.cache_enable:
             global_seed, op_seed = _get_global_and_op_seed()
             _insert_weight_init_info(self.name, global_seed, op_seed)
+
+        init_data_args = ()
         if layout is not None:
             if not isinstance(layout, tuple):
-                raise TypeError("The layout should be tuple! layout is {}.".format(layout))
+                raise TypeError("The layout should be tuple, but got layout is {}.".format(layout))
             if len(layout) < 3:
-                raise ValueError("The length of layout must be larger than 3! layout is {}.".format(layout))
+                raise ValueError("The length of layout must be larger than 2, but got layout is {}.".format(layout))
             slice_index = int(_get_slice_index(layout[0], layout[1]))
-            if (self.init_in_server and self.is_param_ps and isinstance(self.init_mode, Tensor)
-                    and self.init_mode.init is not None):
-                if _is_role_worker() or _is_role_sched():
-                    data = self.init_mode.init_data(0, [1])
-                else:
-                    data = self.init_mode.init_data(slice_index, layout[2], layout[5])
-            else:
-                data = self.init_mode.init_data(slice_index, layout[2], layout[5])
+            init_data_args += (slice_index, layout[2], layout[5])
+
+        if self.init_in_server and self.is_param_ps and isinstance(self.init_mode, Tensor) and \
+           self.init_mode.init is not None and (_is_role_worker() or _is_role_sched()):
+            data = self.init_mode.init_data(0, [1])
         else:
-            if (self.init_in_server and self.is_param_ps and isinstance(self.init_mode, Tensor)
-                    and self.init_mode.init is not None):
-                if _is_role_worker() or _is_role_sched():
-                    data = self.init_mode.init_data(0, [1])
-                else:
-                    data = self.init_mode.init_data()
-            else:
-                data = self.init_mode.init_data()
+            data = self.init_mode.init_data(*init_data_args)
 
         obj = self._update_tensor_data(data)
         if id(obj) != id(self):

tests/ut/python/pipeline/parse/test_outermost_net_pass_non_tensor_inputs.py

@@ -93,7 +93,8 @@ def test_outermost_net_pass_parameter():
     assert "The inputs types of the outermost network support bool, int, float, tensor, " \
            "mstype.Number(mstype.bool, mstype.int, mstype.float, mstype.uint), " \
            "and tuple or list containing only these types, and dict whose values are these types, " \
-           "but got 1th arg is Parameter (name=weight)" in str(err.value)
+           "but got 1th arg is Parameter (name=weight, shape=(2, 2), dtype=Float32, requires_grad=True)" \
+           in str(err.value)
 
 
 def test_outermost_net_pass_tuple_including_parameter():