[ME] Optimize the error message of the operator module

mindspore/ccsrc/frontend/operator/composite/do_signature.cc

@@ -347,11 +347,10 @@ FuncGraphPtr DoSignatureMetaFuncGraph::GenerateFuncGraph(const AbstractBasePtrLi
 
 void RaiseExceptionForConvertRefDtype(const std::string &func_name, const std::string &ref_type,
                                       const std::string &target_type) {
-  MS_LOG(EXCEPTION) << "For '" << func_name << "' operator, "
-                    << "the type of writable argument is '" << ref_type << "', "
-                    << "but the largest type in the same SignatureEnumDType is '" << target_type
-                    << "'. The writable arg type is not equal to the largest type, "
-                    << "so can not cast automatically.";
+  MS_LOG(EXCEPTION) << "Data type conversion of parameter is not supported, so data type " << ref_type
+                    << " cannot be converted to data type " << target_type << " by inserting cast automatically.\n"
+                    << "For more details, please refer at "
+                    << "https://www.mindspore.cn/docs/note/zh-CN/master/operator_list_implicit.html.";
 }
 void RaiseExceptionForCheckParameter(const std::string &func_name, size_t i, const std::string &source_type) {
   MS_EXCEPTION(TypeError) << "Function " << func_name << "'s input " << i << " should be a Parameter, but "

tests/syntax/simple_expression/test_map.py

@@ -165,7 +165,6 @@ def test_map_param_cast():
     input_me_x = Tensor(np.random.randn(2, 3, 4, 5).astype(np.float64))
 
     net = MapNet()
-    with pytest.raises(Exception, match="For 'S-Prim-Assign' operator, "
-                                        "the type of writable argument is 'float32'"):
+    with pytest.raises(Exception, match="Data type conversion of parameter is not supported"):
         ret = net(input_me_x)
         print("ret:", ret)

tests/ut/python/pynative_mode/test_implicit_conversion.py

@@ -132,9 +132,6 @@ def test_float_tensor_and_list_add():
 
 def test_float_tensor_and_bool_tensors_add_grad():
     class Net(nn.Cell):
-        def __init__(self):
-            super(Net, self).__init__()
-
         def construct(self, x, y):
             return x + y
 
@@ -160,9 +157,6 @@ def test_float_tensor_and_bool_tensors_add_grad():
 
 def test_float_tensor_and_int_tensors_sub_grad():
     class Net(nn.Cell):
-        def __init__(self):
-            super(Net, self).__init__()
-
         def construct(self, x, y):
             return x - y
 
@@ -188,9 +182,6 @@ def test_float_tensor_and_int_tensors_sub_grad():
 
 def test_float16_tensor_and_float32_tensors_sub_grad():
     class Net(nn.Cell):
-        def __init__(self):
-            super(Net, self).__init__()
-
         def construct(self, x, y):
             return x - y
 
@@ -216,9 +207,6 @@ def test_float16_tensor_and_float32_tensors_sub_grad():
 
 def test_float_tensor_and_int_add_grad():
     class Net(nn.Cell):
-        def __init__(self):
-            super(Net, self).__init__()
-
         def construct(self, x):
             return x + 2
 
@@ -241,9 +229,6 @@ def test_float_tensor_and_int_add_grad():
 
 def test_int8_tensor_and_uint8_tensors_add_grad():
     class Net(nn.Cell):
-        def __init__(self):
-            super(Net, self).__init__()
-
         def construct(self, x, y):
             return x + y
 
@@ -266,6 +251,7 @@ def test_int8_tensor_and_uint8_tensors_add_grad():
     assert (ret[0].asnumpy() == sens.asnumpy()).all()
     assert (ret[1].asnumpy() == sens.asnumpy()).all()
 
+
 class AssignCheck(nn.Cell):
     """ NetWithNDarray definition """
 
@@ -285,4 +271,4 @@ def test_assign_check_in_sig():
     y = Tensor(3, ms.uint8)
     with pytest.raises(RuntimeError) as e:
         net(x, y)
-    assert "can not cast automatically" in e.value.args[0]
+    assert "Data type conversion of parameter is not supported" in e.value.args[0]