| 24 | } |
| 25 | |
| 26 | int process(void* model_buf, const void* input_data, int input_size, |
| 27 | void** output_data, int* output_size) { |
| 28 | auto model = static_cast<tensorflow::processor::Model*>(model_buf); |
| 29 | if (input_size == 0) { |
| 30 | auto model_str = model->DebugString(); |
| 31 | *output_data = strndup(model_str.c_str(), model_str.length()); |
| 32 | *output_size = model_str.length(); |
| 33 | return 200; |
| 34 | } |
| 35 | |
| 36 | auto status = model->Predict(input_data, input_size, |
| 37 | output_data, output_size); |
| 38 | if (!status.ok()) { |
| 39 | std::string errmsg = tensorflow::strings::StrCat( |
| 40 | "[TensorFlow] Processor predict failed: ", |
| 41 | status.error_message()); |
| 42 | *output_data = strndup(errmsg.c_str(), strlen(errmsg.c_str())); |
| 43 | *output_size = strlen(errmsg.c_str()); |
| 44 | LOG(ERROR) << errmsg; |
| 45 | return 500; |
| 46 | } |
| 47 | return 200; |
| 48 | } |
| 49 | |
| 50 | int batch_process(void* model_buf, const void* input_data[], int* input_size, |
| 51 | void* output_data[], int* output_size) { |