I had done this test:
1, write a mlp Symbol;

2,,before saving paramters, I write these:
/////////////////////////////////////////////////////////////
std::map<std::string, NDArray> args_map;
args_map["data"] = NDArray(Shape(batch_size, 1, 10, 10), ctx_dev, false);
args_map["data_label"] = NDArray(Shape(batch_size), ctx_dev, false);
testSymbol.InferArgsMap(ctx_dev, &args_map, args_map);
/////////////////////////////////than I define function base charRNN.cpp//////////////
void SaveParams(const string filepath, Executor* exe)
{
map<string, NDArray> params;
for (auto iter : exe->arg_dict())
if (iter.first.find("init") == string::npos
&& iter.first.rfind("data") != iter.first.length() - 4
&& iter.first.rfind("label") != iter.first.length() - 5)
params.insert({ "arg:" + iter.first, iter.second });
for (auto iter : exe->aux_dict())
params.insert({ "aux:" + iter.first, iter.second });
NDArray::Save(filepath, params);
}
/////////////////////////after train,I save parameters like this.////////////////////////
string save_path_param = "./test.params";
SaveParams(save_path_param, exe);

3,load paramters like this:
/////////////////////////////////////////////////////////////////////////////////////////
SymbolHandle testSymbolhandle;
MXSymbolCreateFromFile("test.json", &testSymbolhandle);
Symbol testSymbol(testSymbolhandle);
map<string, NDArray> args_map;
Context ctx_dev(DeviceType::kGPU, 0);
args_map["data"] = NDArray(Shape(1, 1, 10, 10), ctx_dev, false);
args_map["data_label"] = NDArray(Shape(1), ctx_dev, false);
Executor* exe = testSymbol.SimpleBind(ctx_dev, args_map);
LoadToMapFromFile("test.params", exe, ctx_dev);
/////////////////////////////////than I define function base charRNN.cpp//////////////
void LoadToMapFromFile(const string filepath, Executor* exe, Context ctx_dev)
{
/map<std::string, NDArray> params = NDArray::LoadToMap(filepath);
for (auto iter : params)
{//also error.
string type = iter.first.substr(0, 4);
string name = iter.first.substr(4);
NDArray target;
if (type == "arg:")
target = exe->arg_dict()[name];
else if (type == "aux:")
target = exe->aux_dict()[name];
else
continue;
iter.second.CopyTo(&target);
}/

map<string, NDArray> paramters;
NDArray::Load(filepath, 0, &paramters);
for (const auto &k : paramters) 
{
	if (k.first.substr(0, 4) == "aux:") 
	{
		auto name = k.first.substr(4, k.first.size() - 4);
		exe->arg_dict()[name] = k.second.Copy(ctx_dev);
	}
	if (k.first.substr(0, 4) == "arg:") 
	{
		auto name = k.first.substr(4, k.first.size() - 4);
		exe->arg_dict()[name] = k.second.Copy(ctx_dev);
	}
}
/*WaitAll is need when we copy data between GPU and the main memory*/
NDArray::WaitAll();

}

4,error like these:
[21:55:46]d:\xxxx\dmlc/logging.h:300: [21:55:46] d:\xxx\ndarray.cc:687:check failed:dshape.Size()==(100 vs. 400) Memory size do not match

I sure that: json for net frame,have no error;but weight parameters don't work well .I didn't know what happen.
now,can you tell me how to do?if I had error? thank you very much!

saving/loading models #75

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