config updates

simplymathematics · Jul 30, 2024 · 4060aa1 · 4060aa1
1 parent ab8a119
commit 4060aa1
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Showing 7 changed files with 900 additions and 428 deletions.
diff --git a/examples/pytorch/attacks.sh b/examples/pytorch/attacks.sh
@@ -3,64 +3,63 @@
 # # This script is used to generate the attacks for the example.
 
 # Fast Gradient Method
-bash models.sh \
-    stage=attack \
-    attack=default \
-    ++attack.init.name=art.attacks.evasion.FastGradientMethod \
-    ++attack.init.eps=.001,.01,.1,.5,1 \
-    ++attack.init.norm=2 \
-    atk_name=FGM  $@
-# #####################################################
-# Projected Gradient Descent
-bash models.sh \
-    stage=attack \
-    attack=default \
-    ++attack.init.name=art.attacks.evasion.ProjectedGradientDescent \
-    ++attack.init.eps=.001,.01,.1,.5,1 \
-    ++attack.init.norm=2 \
-    ++attack.init.eps_step=.001,.003,.01 \
-    atk_name=PGD \
-    ++attack.init.max_iter=1,5,10,50,100 $@
-# #####################################################
-# DeepFool
-bash models.sh \
-    stage=attack \
-    attack=default \
-    ++attack.init.name=art.attacks.evasion.DeepFool \
-    ++attack.init.max_iter=10 \
-    ++attack.init.batch_size=4096 \
-    ++attack.init.nb_grads=1,3,5,8,10 \
-    atk_name=Deep $@
+# bash models.sh \
+#     stage=attack \
+#     attack=default \
+#     ++attack.init.name=art.attacks.evasion.FastGradientMethod \
+#     ++attack.init.eps=.001,.01,.1,.5,1 \
+#     ++attack.init.norm=2 \
+#     atk_name=FGM  $@
 # # #####################################################
-# # HopSkipJump
+# # Projected Gradient Descent
 # bash models.sh \
 #     stage=attack \
 #     attack=default \
-#     ++attack.init.name=art.attacks.evasion.HopSkipJump \
-#     ++attack.init.max_iter=1,3,5,10,15 \
-#     ++attack.init.init_eval=10 \
-#     ++attack.init.batch_size=4096 \
-#     ++attack.init.max_eval=100 \
+#     ++attack.init.name=art.attacks.evasion.ProjectedGradientDescent \
+#     ++attack.init.eps=.001,.01,.1,.5,1 \
 #     ++attack.init.norm=2 \
-#     atk_name=HSJ $@
+#     ++attack.init.eps_step=.001,.003,.01 \
+#     atk_name=PGD \
+#     ++attack.init.max_iter=1,5,10,50,100 $@
 # # #####################################################
-# # PixelAttack
+# # DeepFool
 # bash models.sh \
 #     stage=attack \
-#     attack=default  \
-#     ++attack.init.name=art.attacks.evasion.PixelAttack \
-#     ~attack.init.batch_size \
-#     ++attack.init.th=1,4,16,64,256 \
-#     atk_name=Pixel $@
+#     attack=default \
+#     ++attack.init.name=art.attacks.evasion.DeepFool \
+#     ++attack.init.max_iter=10 \
+#     ++attack.init.batch_size=4096 \
+#     ++attack.init.nb_grads=1,3,5,8,10 \
+#     atk_name=Deep $@
 # # #####################################################
-# # ThresholdAttack
+# # HopSkipJump
 # bash models.sh \
 #     stage=attack \
 #     attack=default \
-#     ++attack.init.name=art.attacks.evasion.ThresholdAttack \
-#     ~attack.init.batch_size \
-#     ++attack.init.th=1,4,16,64,256 \
-#     atk_name=Thresh $@
+#     ++attack.init.name=art.attacks.evasion.HopSkipJump \
+#     ++attack.init.max_iter=1,3,5,10,15 \
+#     ++attack.init.init_eval=3 \
+#     ++attack.init.max_eval=10 \
+#     ++attack.init.norm=2 \
+#     atk_name=HSJ $@
+# #####################################################
+# PixelAttack
+bash models.sh \
+    stage=attack \
+    attack=default  \
+    ++attack.init.name=art.attacks.evasion.PixelAttack \
+    ~attack.init.batch_size \
+    ++attack.init.th=1,4,16,64,256 \
+    atk_name=Pixel $@
+# #####################################################
+# ThresholdAttack
+bash models.sh \
+    stage=attack \
+    attack=default \
+    ++attack.init.name=art.attacks.evasion.ThresholdAttack \
+    ~attack.init.batch_size \
+    ++attack.init.th=1,4,16,64,256 \
+    atk_name=Thresh $@
 # #####################################################
 # # ZooAttack
 # bash models.sh \

diff --git a/examples/pytorch/conf/cifar.yaml b/examples/pytorch/conf/cifar.yaml
@@ -38,7 +38,7 @@ hydra:
       ++model.art.initialize.optimizer.lr: shuffle(choice( 0.1, 0.01, 0.001, .0001, .00001, 0.000001))
       ++model.art.initialize.optimizer.momentum: choice(0.1, 0.9, 0.95, 0.99)
       # ++model.trainer.nb_epochs: choice(1, 10, 30, 50, 100)
-      ++model.trainer.batch_size: choice(32, 64, 128, 256, 512, 1024)
+      ++model.trainer.batch_size: choice(128, 256, 512, 1024)
     _target_: hydra_plugins.hydra_optuna_sweeper.optuna_sweeper.OptunaSweeper
   launcher:
     _target_: hydra_plugins.hydra_joblib_launcher.joblib_launcher.JoblibLauncher

diff --git a/examples/pytorch/conf/cifar100.yaml b/examples/pytorch/conf/cifar100.yaml
@@ -38,7 +38,7 @@ hydra:
       ++model.art.initialize.optimizer.lr: choice( 0.1, 0.01, 0.001, .0001, .00001, 0.000001)
       ++model.art.initialize.optimizer.momentum: choice(0.1, 0.9, 0.95, 0.99)
       # ++model.trainer.nb_epochs: choice(1, 10, 30, 50, 100)
-      ++model.trainer.batch_size: choice(32, 64, 128, 256, 512, 1024)
+      ++model.trainer.batch_size: choice(128, 256, 512, 1024)
     _target_: hydra_plugins.hydra_optuna_sweeper.optuna_sweeper.OptunaSweeper
   launcher:
     _target_: hydra_plugins.hydra_joblib_launcher.joblib_launcher.JoblibLauncher

diff --git a/examples/pytorch/conf/mnist.yaml b/examples/pytorch/conf/mnist.yaml
@@ -38,7 +38,7 @@ hydra:
       ++model.art.initialize.optimizer.lr: choice( 0.1, 0.01, 0.001, .0001, .00001, 0.000001)
       ++model.art.initialize.optimizer.momentum: choice(0.1, 0.9, 0.95, 0.99)
       # ++model.trainer.nb_epochs: choice(1, 10, 30, 50, 100)
-      ++model.trainer.batch_size: choice(32, 64, 128, 256, 512, 1024)
+      ++model.trainer.batch_size: choice(128, 256, 512, 1024)
     _target_: hydra_plugins.hydra_optuna_sweeper.optuna_sweeper.OptunaSweeper
   launcher:
     _target_: hydra_plugins.hydra_joblib_launcher.joblib_launcher.JoblibLauncher
@@ -50,4 +50,4 @@ hydra:
     batch_size: auto
     temp_folder: /tmp/deckard
     max_nbytes: 100000
-    mmap_mode: r
+    mmap_mode: r