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1.01 kB
| using namespace neuroflow; | |
| int main() { | |
| std::cout << "Simple model test..." << std::endl; | |
| NeuroFlowModel::Config cfg; | |
| cfg.input_dim = 64; | |
| cfg.hidden_dim = 32; | |
| cfg.output_dim = 5; | |
| cfg.memory_slots = 8; | |
| cfg.memory_dim = 16; | |
| cfg.num_layers = 1; | |
| cfg.num_associations = 2; | |
| cfg.use_mla = false; // 不使用 MLA | |
| std::cout << "Creating model..." << std::endl; | |
| NeuroFlowModel model(cfg); | |
| std::cout << "Creating input tensor..." << std::endl; | |
| Tensor input({1, cfg.input_dim}); | |
| float* data = input.as_fp32(); | |
| for (size_t i = 0; i < input.numel(); ++i) { | |
| data[i] = 0.1f * i; | |
| } | |
| std::cout << "Running forward..." << std::endl; | |
| auto output = model.forward(input); | |
| std::cout << "Output shape: [" << output.output.shape_[0] << ", " << output.output.shape_[1] << "]" << std::endl; | |
| std::cout << "Success!" << std::endl; | |
| return 0; | |
| } | |