batch scoring in cpp

首先使用 ResNet 符号文件和参数文件重现 issue 中的两条路径，然后跟踪每种方法所使用的 C++ NDArray::Load、Symbol::SimpleBind 和 executor 设置调用。比较得到的参数映射和批处理方式，并将完成定义为：确定 segmentation fault 的原因，并记录哪种 batch-scoring 方法有效以及原因。

I am trying to load a pre-built model and do batch scoring, I tried the following two ways, the first one can produce some results, and the second one compiles successfully but runs with segmentation fault. Could you please let me know which way I should follow, and why the second way doesn't work? Thanks!
method 1:

/* Image size and channels */
int width = 224;
int height = 224;
int channels = 3;
int batch_size = 5;

Context ctx_dev(DeviceType::kCPU, 0);
map<string, NDArray> args_map;
map<string, NDArray> aux_map;
map<string, NDArray> parameters;

NDArray::Load("../Resnet/resnet-152-0000.params", 0, &parameters);

for (const auto &k : parameters) {
  if (k.first.substr(0, 4) == "aux:") {
    auto name = k.first.substr(4, k.first.size() - 4);
    aux_map[name] = k.second.Copy(ctx_dev);
  }
  if (k.first.substr(0, 4) == "arg:") {
    auto name = k.first.substr(4, k.first.size() - 4);
    args_map[name] = k.second.Copy(ctx_dev);
  }
}

auto net = Symbol::Load("../Resnet/resnet-152-symbol.json");

auto data_iter = MXDataIter("ImageRecordIter")
.SetParam("path_imglist","../caltech_256/caltech-256-60-train.lst")
.SetParam("path_imgrec","../caltech_256/caltech-256-60-train.rec")
.SetParam("data_shape", Shape(3, 224, 224))
.SetParam("batch_size", batch_size)
.SetParam("shuffle", 1)
.CreateDataIter();

while(data_iter.Next()){
auto batch = data_iter.GetData();
args_map["data"] = batch;
auto *exec = net.SimpleBind(ctx_dev, args_map);
exec->Forward(false);
auto outputs = exec->outputs[0].Copy(Context(kCPU, 0));
NDArray::WaitAll();
for (int i = 0; i <2; i++) {
cout << outputs.At(0, i) <<",";
}
cout << endl;
}
MXNotifyShutdown();

method 2:

int width = 224;
int height = 224;
int channels = 3;
int batch_size = 5;

Context ctx_dev(DeviceType::kCPU, 0);

map<string, NDArray> args_map;
map<string, NDArray> aux_map;

args_map["data"] = NDArray(Shape(batch_size, channels, width, height), ctx_dev);
args_map["label"] = NDArray(Shape(batch_size), ctx_dev);

auto net = Symbol::Load("../Resnet/resnet-152-symbol.json");

auto *exec = net.SimpleBind(ctx_dev, args_map);

NDArray::Load("../Resnet/resnet-152-0000.params", 0, &args_map);

auto data_iter = MXDataIter("ImageRecordIter")
  .SetParam("path_imglist","../caltech_256/caltech-256-60-train.lst")
  .SetParam("path_imgrec","../caltech_256/caltech-256-60-train.rec")
  .SetParam("data_shape", Shape(3, 224, 224))
  .SetParam("batch_size", batch_size)
  .SetParam("shuffle", 1)
  .CreateDataIter();

while(data_iter.Next()){
auto batch = data_iter.GetDataBatch();
batch.data.CopyTo(&args_map["data"]);
batch.label.CopyTo(&args_map["label"]);
exec->Forward(false);
NDArray::WaitAll();
}

delete exec;
MXNotifyShutdown();