| 7 | namespace { |
| 8 | |
| 9 | bool reset_input(const Args& args) { |
| 10 | std::string network_path = args.model_path; |
| 11 | std::string input_path = args.input_path; |
| 12 | lite::Config config; |
| 13 | |
| 14 | //! create and load the network |
| 15 | std::shared_ptr<Network> network = std::make_shared<Network>(config); |
| 16 | network->load_model(network_path); |
| 17 | |
| 18 | //! set input data to input tensor |
| 19 | std::shared_ptr<Tensor> input_tensor = network->get_input_tensor(0); |
| 20 | auto layout = input_tensor->get_layout(); |
| 21 | |
| 22 | auto src_tensor = parse_npy(input_path); |
| 23 | void* src = src_tensor->get_memory_ptr(); |
| 24 | input_tensor->reset(src, layout); |
| 25 | |
| 26 | //! forward |
| 27 | network->forward(); |
| 28 | network->wait(); |
| 29 | |
| 30 | //! 6. get the output data or read tensor set in network_in |
| 31 | std::shared_ptr<Tensor> output_tensor = network->get_output_tensor(0); |
| 32 | void* out_data = output_tensor->get_memory_ptr(); |
| 33 | size_t out_length = output_tensor->get_tensor_total_size_in_byte() / |
| 34 | output_tensor->get_layout().get_elem_size(); |
| 35 | float max = -1.0f; |
| 36 | float sum = 0.0f; |
| 37 | for (size_t i = 0; i < out_length; i++) { |
| 38 | float data = static_cast<float*>(out_data)[i]; |
| 39 | sum += data; |
| 40 | if (max < data) |
| 41 | max = data; |
| 42 | } |
| 43 | printf("max=%e, sum=%e\n", max, sum); |
| 44 | return true; |
| 45 | } |
| 46 | |
| 47 | bool reset_input_output(const Args& args) { |
| 48 | std::string network_path = args.model_path; |
nothing calls this directly
no test coverage detected