improve the recognition of Parameter object and raise error when convert keywordarg to pydata

mindspore/_extends/parse/namespace.py

@@ -118,5 +118,5 @@ class ClassMemberNamespace(Namespace):
         except ValueError:
             raise UnboundLocalError(name)
         except KeyError:
-            logger.warning(f"'{d.__class__.__name__ }' object has no attribute or method: '{name}', "
-                           f"so will return None.")
+            logger.info(f"'{d.__class__.__name__ }' object has no attribute or method: '{name}', so will return None.")
+            raise AttributeError(name)

mindspore/ccsrc/pipeline/jit/parse/resolve.cc

@@ -89,7 +89,7 @@ AnfNodePtr ResolveParameterObj(const FuncGraphPtr &func_graph, const py::object
     MS_LOG(EXCEPTION) << "Parameter object should have name attribute";
   }
 
-  std::string param_name = py::cast<std::string>(name_attr);
+  auto param_name = py::cast<std::string>(name_attr);
   auto top_graph = Parser::GetTopFuncGraph();
   // if the parameter node has been created , return it
   AnfNodePtr para_node = nullptr;
@@ -115,7 +115,7 @@ AnfNodePtr ResolveParameterObj(const FuncGraphPtr &func_graph, const py::object
 
 bool ResolveObjectToNode(const FuncGraphPtr &func_graph, const py::object &obj, AnfNodePtr *const node) {
   AnfNodePtr output = nullptr;
-  if (py::hasattr(obj, "__parameter__")) {
+  if (py::hasattr(obj, "__parameter__") && py::isinstance<tensor::MetaTensor>(obj)) {
     auto param = ResolveParameterObj(func_graph, obj);
     if (param == nullptr) {
       MS_LOG(ERROR) << "Resolve parameter object failed, got nullptr";

mindspore/ccsrc/pipeline/jit/static_analysis/prim.cc

@@ -1014,7 +1014,8 @@ class CreateInstanceEvaluator : public TransitionPrimEvaluator {
     // create class instance
     auto obj = parse::data_converter::CreatePythonObject(class_type, params);
     if (py::isinstance<py::none>(obj)) {
-      MS_LOG(EXCEPTION) << "Create python object failed, only support Cell and Primitive type";
+      MS_LOG(EXCEPTION) << "Create python object" << py::str(class_type)
+                        << " failed, only support create Cell or Primitive object.";
     }
 
     // process the object

mindspore/ccsrc/pipeline/pynative/pynative_execute.cc

@@ -1361,8 +1361,8 @@ void PynativeExecutor::EndGraphByOutId(const std::string &out_id, const py::obje
     auto params = newfg->parameters();
     auto manager = Manage({newfg}, false);
     if (args.size() > params.size()) {
-      MS_EXCEPTION(ValueError) << "The number of arguments " << args.size()
-                               << " is more than the number of parameters required, which is " << params.size();
+      MS_EXCEPTION(TypeError) << "The number of arguments " << args.size()
+                              << " is more than the number of parameters required, which is " << params.size();
     }
     for (size_t i = 0; i < args.size(); i++) {
       ValuePtr value = PyAttrValue(args[i]);

mindspore/ccsrc/utils/convert_utils_py.cc

@@ -147,7 +147,7 @@ py::object ValuePtrToPyData(const ValuePtr &value) {
   } else if (value->isa<None>()) {
     ret = py::none();
   } else {
-    MS_LOG(INFO) << "Unsupported convert value: " << value->ToString() << " to a PyData.";
+    MS_LOG(EXCEPTION) << "Unsupported convert value: " << value->ToString() << " to a PyData.";
   }
   return ret;
 }

mindspore/common/parameter.py

@@ -48,6 +48,8 @@ class Parameter(MetaTensor):
     Note:
         Each parameter of Cell is represented by Parameter class.
         A Parameter has to belong to a Cell.
+        If there is an operator in the network that requires part of the inputs to be Parameter,
+        then the Parameters as this part of the inputs are not allowed to be cast.
 
     Args:
         default_input (Union[Tensor, Initializer, Number]): Parameter data, to be set initialized.

mindspore/ops/primitive.py

@@ -22,6 +22,7 @@ from mindspore import context
 from .._c_expression import Primitive_, real_run_op, prim_type
 from . import signature as sig
 
+
 class Primitive(Primitive_):
     """
     Primitive is the base class of primitives in python.
@@ -168,7 +169,7 @@ class Primitive(Primitive_):
         return type(self)(**self.init_attrs)
 
     def __repr__(self):
-        attr = ', '.join([f'{k}={self.attrs[k]}'for k in self.attrs if not k in Primitive._repr_ignore_list])
+        attr = ', '.join([f'{k}={self.attrs[k]}' for k in self.attrs if not k in Primitive._repr_ignore_list])
         info_str = f'Prim[{self.name}]'
         if attr:
             info_str += f'<{attr}>'
@@ -425,6 +426,7 @@ def prim_attr_register(fn):
     Returns:
         function, original function.
     """
+
     def deco(self, *args, **kwargs):
         if isinstance(self, PrimitiveWithInfer):
             PrimitiveWithInfer.__init__(self, self.__class__.__name__)
@@ -442,6 +444,7 @@ def prim_attr_register(fn):
             self.add_prim_attr(name, value)
             self.init_attrs[name] = value
         fn(self, *args, **kwargs)
+
     deco.decorated_func = fn
     return deco
 
@@ -470,6 +473,7 @@ def constexpr(fn=None, get_instance=True, name=None):
         >>>     return len(x)
         >>> assert tuple_len_class()(a) == 2
     """
+
     def deco(fn):
         class CompileOp(PrimitiveWithInfer):
             def __init__(self):
@@ -479,9 +483,11 @@ def constexpr(fn=None, get_instance=True, name=None):
 
             def infer_value(self, *args):
                 return fn(*args)
+
         if get_instance:
             return CompileOp()
         return CompileOp
+
     if fn is not None:
         return deco(fn)
     return deco

tests/ut/python/train/summary/test_summary_ops_params_valid_check.py

@@ -143,6 +143,7 @@ class TestSummaryOps:
             (SummaryEnum.TENSOR.value, Tensor(0)),
             (SummaryEnum.HISTOGRAM.value, Tensor(0))
         ])
+
     def test_value_shape_invalid(self, summary_type, value):
         """Test invalid shape of every summary operators."""
         net = SummaryNet(summary_type, tag='tag', data=value)

tests/ut/python/train/summary/test_tensor_summary.py

@@ -122,7 +122,6 @@ class SummaryDemo(nn.Cell):
         self.s("y1", y)
         return z
 
-
 def test_tensor_summary_with_ge():
     """ test_tensor_summary_with_ge """
     log.debug("begin test_tensor_summary_with_ge")