Hi, I trained and traced a Model in Python. Now I want to predict outpouts with c++. I read the tutorial code and was fine with it. the problem was the batch size of one. To fix this, I created a cutsom dataset and made data loader. How do I push the data from the dataloader to the network? I tried it as follows, but run into errors.
int main() {
	string modelPath = "C:\\..\\myModel.pt";
	shared_ptr<torch::jit::script::Module> module = torch::jit::load(modelPath);
	module->eval();

	int batch_size = 10;

	auto dataset = CustomDataset("C:\\..\\labels.csv").map(torch::data::transforms::Stack<>()); 
	auto data_loader = torch::data::make_data_loader(std::move(dataset), torch::data::DataLoaderOptions().batch_size(batch_size).workers(1))

	//Input Values
	std::vector<torch::jit::IValue> input;
for (torch::data::Example<>& batch : *data_loader) {
		
		input.push_back(batch.data);
		torch::Tensor outputs = module->forward(input).toTensor();
		input.clear();
		cout << outputs;

		//Execute model
		//at::Tensor output = module->forward(inputs).toTensor();
		//std::cout << output.slice(/*dim=*/1, /*start=*/0, /*end=*/5) << '\n';
	};
};