| 369 | } |
| 370 | |
| 371 | void loadModelFromStream(std::istream& jsonStream) |
| 372 | { |
| 373 | #ifndef QUICK_BUILD_TESTING |
| 374 | int input_size; |
| 375 | int input_skip; |
| 376 | float input_gain; |
| 377 | float output_gain; |
| 378 | nlohmann::json model_json; |
| 379 | |
| 380 | jsonStream >> model_json; |
| 381 | |
| 382 | /* Understand which model type to load */ |
| 383 | input_size = model_json["in_shape"].back().get<int>(); |
| 384 | if (input_size > MAX_INPUT_SIZE) { |
| 385 | throw std::invalid_argument("Value for input_size not supported"); |
| 386 | } |
| 387 | |
| 388 | if (model_json["in_skip"].is_number()) { |
| 389 | input_skip = model_json["in_skip"].get<int>(); |
| 390 | if (input_skip > 1) |
| 391 | throw std::invalid_argument("Values for in_skip > 1 are not supported"); |
| 392 | } |
| 393 | else { |
| 394 | input_skip = 0; |
| 395 | } |
| 396 | |
| 397 | if (model_json["in_gain"].is_number()) { |
| 398 | input_gain = DB_CO(model_json["in_gain"].get<float>()); |
| 399 | } |
| 400 | else { |
| 401 | input_gain = 1.0f; |
| 402 | } |
| 403 | |
| 404 | if (model_json["out_gain"].is_number()) { |
| 405 | output_gain = DB_CO(model_json["out_gain"].get<float>()); |
| 406 | } |
| 407 | else { |
| 408 | output_gain = 1.0f; |
| 409 | } |
| 410 | |
| 411 | std::unique_ptr<DynamicModel> newmodel = std::make_unique<DynamicModel>(); |
| 412 | |
| 413 | if (! custom_model_creator(model_json, newmodel->variant)) |
| 414 | throw std::runtime_error("Unable to identify a known model architecture!"); |
| 415 | |
| 416 | std::visit ( |
| 417 | [&model_json] (auto&& custom_model) |
| 418 | { |
| 419 | using ModelType = std::decay_t<decltype (custom_model)>; |
| 420 | if constexpr (! std::is_same_v<ModelType, NullModel>) |
| 421 | { |
| 422 | custom_model.parseJson (model_json, true); |
| 423 | custom_model.reset(); |
| 424 | } |
| 425 | }, |
| 426 | newmodel->variant); |
| 427 | |
| 428 | // save extra info |
nothing calls this directly
no test coverage detected