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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,100 +1,11 @@ | ||
| // Copyright 2016, Tobias Hermann. | ||
| // https://github.com/Dobiasd/frugally-deep | ||
| // Distributed under the MIT License. | ||
| // (See accompanying LICENSE file or at | ||
| // https://opensource.org/licenses/MIT) | ||
|
|
||
| /* | ||
| CUDA_VISIBLE_DEVICES='' python3.11 ../keras_export/generate_test_models.py exhaustive test_model_exhaustive.keras | ||
| CUDA_VISIBLE_DEVICES='' python3.11 ../keras_export/convert_model.py test_model_exhaustive.keras test_model_exhaustive.json | ||
| cat test_model_exhaustive.json | jq . > test_model_exhaustive.json.formatted.json | ||
| subl test_model_exhaustive.json.formatted.json | ||
| */ | ||
| #include "fdeep/fdeep.hpp" | ||
|
|
||
| int main() | ||
| { | ||
| std::vector<std::string> model_paths = { | ||
| // "convnextbase.json", | ||
| // "convnextlarge.json", | ||
| // "convnextsmall.json", | ||
| // "convnexttiny.json", | ||
| // "convnextxlarge.json", | ||
| "densenet121.json", | ||
| "densenet169.json", | ||
| "densenet201.json", | ||
| "efficientnetb0.json", | ||
| "efficientnetb1.json", | ||
| "efficientnetb2.json", | ||
| "efficientnetb3.json", | ||
| "efficientnetb4.json", | ||
| "efficientnetb5.json", | ||
| "efficientnetb6.json", | ||
| "efficientnetb7.json", | ||
| "efficientnetv2b0.json", | ||
| "efficientnetv2b1.json", | ||
| "efficientnetv2b2.json", | ||
| "efficientnetv2b3.json", | ||
| "efficientnetv2l.json", | ||
| "efficientnetv2m.json", | ||
| "efficientnetv2s.json", | ||
| // "inceptionresnetv2.json", | ||
| "inceptionv3.json", | ||
| "mobilenet.json", | ||
| "mobilenetv2.json", | ||
| "nasnetlarge.json", | ||
| "nasnetmobile.json", | ||
| "resnet101.json", | ||
| "resnet101v2.json", | ||
| "resnet152.json", | ||
| "resnet152v2.json", | ||
| "resnet50.json", | ||
| "resnet50v2.json", | ||
| "vgg16.json", | ||
| "vgg19.json", | ||
| "xception.json" | ||
| }; | ||
|
|
||
| bool error = false; | ||
|
|
||
| for (const auto& model_path : model_paths) | ||
| { | ||
| std::cout << "----" << std::endl; | ||
| std::cout << model_path << std::endl; | ||
| #ifdef NDEBUG | ||
| try | ||
| { | ||
| const auto model = fdeep::load_model(model_path, true); | ||
| const std::size_t warm_up_runs = 3; | ||
| const std::size_t test_runs = 5; | ||
| for (std::size_t i = 0; i < warm_up_runs; ++i) | ||
| { | ||
| const double duration = model.test_speed(); | ||
| std::cout << "Forward pass took " | ||
| << duration << " s." << std::endl; | ||
| } | ||
| double duration_sum = 0; | ||
| std::cout << "Starting performance measurements." << std::endl; | ||
| for (std::size_t i = 0; i < test_runs; ++i) | ||
| { | ||
| const double duration = model.test_speed(); | ||
| duration_sum += duration; | ||
| std::cout << "Forward pass took " | ||
| << duration << " s." << std::endl; | ||
| } | ||
| const double duration_avg = | ||
| duration_sum / static_cast<double>(test_runs); | ||
| std::cout << "Forward pass took " | ||
| << duration_avg << " s on average." << std::endl; | ||
| } | ||
| catch (const std::exception& e) | ||
| { | ||
| std::cerr << "ERROR: " << e.what() << std::endl; | ||
| error = true; | ||
| } | ||
| #else | ||
| const auto model = fdeep::load_model(model_path, true); | ||
| #endif | ||
| } | ||
|
|
||
| if (error) | ||
| { | ||
| std::cout << "There were errors." << std::endl; | ||
| return 1; | ||
| } | ||
| std::cout << "All imports and test OK." << std::endl; | ||
| fdeep::load_model("test_model_exhaustive.json"); | ||
| } |