-
Notifications
You must be signed in to change notification settings - Fork 2
Commit
This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository.
- Loading branch information
1 parent
e17706a
commit 3c0deb5
Showing
6 changed files
with
320 additions
and
554 deletions.
There are no files selected for viewing
This file was deleted.
Oops, something went wrong.
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,13 @@ | ||
| attacks: | ||
| FastGradientMethod: FGM | ||
| defences: | ||
| Control: Control | ||
| FeatureSqueezing: FSQ | ||
| params: | ||
| FGM: attack.init.eps | ||
| Control: model.trainer.nb_epoch | ||
| FSQ: model.art.pipeline.preprocessor.bit_depth | ||
| fillna: | ||
| FGM: 0.0 | ||
| Control: 20 | ||
| FSQ: 32 |
This file was deleted.
Oops, something went wrong.
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,241 @@ | ||
| _target_: deckard.base.experiment.Experiment | ||
| attack: | ||
| _target_: deckard.base.attack.Attack | ||
| attack_size: 10 | ||
| data: | ||
| _target_: deckard.base.data.Data | ||
| generate: | ||
| _target_: deckard.base.data.generator.DataGenerator | ||
| name: torch_mnist | ||
| sample: | ||
| _target_: deckard.base.data.sampler.SklearnDataSampler | ||
| random_state: 0 | ||
| stratify: true | ||
| sklearn_pipeline: | ||
| _target_: deckard.base.data.sklearn_pipeline.SklearnDataPipeline | ||
| preprocessor: | ||
| name: sklearn.preprocessing.StandardScaler | ||
| with_mean: true | ||
| with_std: true | ||
| init: | ||
| _target_: deckard.base.attack.AttackInitializer | ||
| batch_size: 1024 | ||
| eps: 0.99 | ||
| minimal: true | ||
| model: | ||
| _target_: deckard.base.model.Model | ||
| art: | ||
| _target_: deckard.base.model.art_pipeline.ArtPipeline | ||
| data: | ||
| _target_: deckard.base.data.Data | ||
| generate: | ||
| _target_: deckard.base.data.generator.DataGenerator | ||
| name: torch_mnist | ||
| sample: | ||
| _target_: deckard.base.data.sampler.SklearnDataSampler | ||
| random_state: 0 | ||
| stratify: true | ||
| sklearn_pipeline: | ||
| _target_: deckard.base.data.sklearn_pipeline.SklearnDataPipeline | ||
| preprocessor: | ||
| name: sklearn.preprocessing.StandardScaler | ||
| with_mean: true | ||
| with_std: true | ||
| initialize: | ||
| clip_values: | ||
| - 0 | ||
| - 255 | ||
| criterion: | ||
| name: torch.nn.CrossEntropyLoss | ||
| optimizer: | ||
| lr: 0.01 | ||
| momentum: 0.9 | ||
| name: torch.optim.SGD | ||
| library: pytorch | ||
| data: | ||
| _target_: deckard.base.data.Data | ||
| generate: | ||
| _target_: deckard.base.data.generator.DataGenerator | ||
| name: torch_mnist | ||
| sample: | ||
| _target_: deckard.base.data.sampler.SklearnDataSampler | ||
| random_state: 0 | ||
| stratify: true | ||
| sklearn_pipeline: | ||
| _target_: deckard.base.data.sklearn_pipeline.SklearnDataPipeline | ||
| preprocessor: | ||
| name: sklearn.preprocessing.StandardScaler | ||
| with_mean: true | ||
| with_std: true | ||
| init: | ||
| _target_: deckard.base.model.ModelInitializer | ||
| name: torch_example.ResNet18 | ||
| num_channels: 1 | ||
| library: pytorch | ||
| trainer: | ||
| batch_size: 1024 | ||
| nb_epoch: 1 | ||
| name: art.attacks.evasion.FastGradientMethod | ||
| targeted: false | ||
| method: evasion | ||
| model: | ||
| _target_: deckard.base.model.Model | ||
| art: | ||
| _target_: deckard.base.model.art_pipeline.ArtPipeline | ||
| data: | ||
| _target_: deckard.base.data.Data | ||
| generate: | ||
| _target_: deckard.base.data.generator.DataGenerator | ||
| name: torch_mnist | ||
| sample: | ||
| _target_: deckard.base.data.sampler.SklearnDataSampler | ||
| random_state: 0 | ||
| stratify: true | ||
| sklearn_pipeline: | ||
| _target_: deckard.base.data.sklearn_pipeline.SklearnDataPipeline | ||
| preprocessor: | ||
| name: sklearn.preprocessing.StandardScaler | ||
| with_mean: true | ||
| with_std: true | ||
| initialize: | ||
| clip_values: | ||
| - 0 | ||
| - 255 | ||
| criterion: | ||
| name: torch.nn.CrossEntropyLoss | ||
| optimizer: | ||
| lr: 0.01 | ||
| momentum: 0.9 | ||
| name: torch.optim.SGD | ||
| library: pytorch | ||
| data: | ||
| _target_: deckard.base.data.Data | ||
| generate: | ||
| _target_: deckard.base.data.generator.DataGenerator | ||
| name: torch_mnist | ||
| sample: | ||
| _target_: deckard.base.data.sampler.SklearnDataSampler | ||
| random_state: 0 | ||
| stratify: true | ||
| sklearn_pipeline: | ||
| _target_: deckard.base.data.sklearn_pipeline.SklearnDataPipeline | ||
| preprocessor: | ||
| name: sklearn.preprocessing.StandardScaler | ||
| with_mean: true | ||
| with_std: true | ||
| init: | ||
| _target_: deckard.base.model.ModelInitializer | ||
| name: torch_example.ResNet18 | ||
| num_channels: 1 | ||
| library: pytorch | ||
| trainer: | ||
| batch_size: 1024 | ||
| nb_epoch: 1 | ||
| data: | ||
| _target_: deckard.base.data.Data | ||
| generate: | ||
| _target_: deckard.base.data.generator.DataGenerator | ||
| name: torch_mnist | ||
| sample: | ||
| _target_: deckard.base.data.sampler.SklearnDataSampler | ||
| random_state: 0 | ||
| stratify: true | ||
| sklearn_pipeline: | ||
| _target_: deckard.base.data.sklearn_pipeline.SklearnDataPipeline | ||
| preprocessor: | ||
| name: sklearn.preprocessing.StandardScaler | ||
| with_mean: true | ||
| with_std: true | ||
| device_id: cpu | ||
| direction: | ||
| - maximize | ||
| - minimize | ||
| - minimize | ||
| - minimize | ||
| files: | ||
| _target_: deckard.base.files.FileConfig | ||
| adv_predictions_file: adv_predictions.json | ||
| attack_dir: attacks | ||
| attack_file: attack | ||
| attack_type: .pkl | ||
| data_dir: data | ||
| data_file: data | ||
| data_type: .pkl | ||
| directory: /result/mnist/ | ||
| model_dir: null | ||
| model_file: null | ||
| model_type: null | ||
| name: default | ||
| params_file: params.yaml | ||
| predictions_file: predictions.json | ||
| reports: reports | ||
| score_dict_file: score_dict.json | ||
| model: | ||
| _target_: deckard.base.model.Model | ||
| art: | ||
| _target_: deckard.base.model.art_pipeline.ArtPipeline | ||
| data: | ||
| _target_: deckard.base.data.Data | ||
| generate: | ||
| _target_: deckard.base.data.generator.DataGenerator | ||
| name: torch_mnist | ||
| sample: | ||
| _target_: deckard.base.data.sampler.SklearnDataSampler | ||
| random_state: 0 | ||
| stratify: true | ||
| sklearn_pipeline: | ||
| _target_: deckard.base.data.sklearn_pipeline.SklearnDataPipeline | ||
| preprocessor: | ||
| name: sklearn.preprocessing.StandardScaler | ||
| with_mean: true | ||
| with_std: true | ||
| initialize: | ||
| clip_values: | ||
| - 0 | ||
| - 255 | ||
| criterion: | ||
| name: torch.nn.CrossEntropyLoss | ||
| optimizer: | ||
| lr: 0.01 | ||
| momentum: 0.9 | ||
| name: torch.optim.SGD | ||
| library: pytorch | ||
| data: | ||
| _target_: deckard.base.data.Data | ||
| generate: | ||
| _target_: deckard.base.data.generator.DataGenerator | ||
| name: torch_mnist | ||
| sample: | ||
| _target_: deckard.base.data.sampler.SklearnDataSampler | ||
| random_state: 0 | ||
| stratify: true | ||
| sklearn_pipeline: | ||
| _target_: deckard.base.data.sklearn_pipeline.SklearnDataPipeline | ||
| preprocessor: | ||
| name: sklearn.preprocessing.StandardScaler | ||
| with_mean: true | ||
| with_std: true | ||
| init: | ||
| _target_: deckard.base.model.ModelInitializer | ||
| name: torch_example.ResNet18 | ||
| num_channels: 1 | ||
| library: pytorch | ||
| trainer: | ||
| batch_size: 1024 | ||
| nb_epoch: 1 | ||
| optimizers: | ||
| - accuracy | ||
| - train_time | ||
| - adv_accuracy | ||
| - adv_fit_time | ||
| scorers: | ||
| _target_: deckard.base.scorer.ScorerDict | ||
| accuracy: | ||
| _target_: deckard.base.scorer.ScorerConfig | ||
| direction: maximize | ||
| name: sklearn.metrics.accuracy_score | ||
| log_loss: | ||
| _target_: deckard.base.scorer.ScorerConfig | ||
| direction: minimize | ||
| name: sklearn.metrics.log_loss | ||
| stage: ??? |
Oops, something went wrong.