Combining experiments and adding documentation

SewoongLab · Jan 3, 2024 · b8f324b · b8f324b
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Showing 6 changed files with 35 additions and 10 deletions.
diff --git a/experiments/example_attack/config.toml b/experiments/example_attack/config.toml
@@ -1,6 +1,9 @@
-# TODO Description
+# This example trains a single expert and generates poisoned labels
+# for the sinusoidal (1xs) trigger with ResNet-32s. The labels are 
+# FLIPped at the provided budgets. The config file is broken down 
+# into three modules detailed in the schemas/ folder.
 
-# TODO
+# Module to train and record an expert trajectory.
 [train_expert]
 output_dir = "out/checkpoints/r32p_1xs/0/"
 model = "r32p"
@@ -12,7 +15,7 @@ poisoner = "1xs"
 epochs = 20
 checkpoint_iters = 50
 
-# TODO
+# Module to generate attack labels from the expert trajectories.
 [generate_labels]
 input_pths = "out/checkpoints/r32p_1xs/{}/model_{}_{}.pth"
 opt_pths = "out/checkpoints/r32p_1xs/{}/model_{}_{}_opt.pth"
@@ -36,3 +39,9 @@ one_hot_temp = 5
 alpha = 0
 label_kwargs = {lr = 150, momentum = 0.5}
 
+# Module to flip labels at the provided budgets.
+[select_flips]
+budgets = [150, 300, 500, 1000, 1500]
+input_label_glob = "experiments/example_attack/labels.npy"
+true_labels = "experiments/example_attack/true.npy"
+output_dir = "experiments/example_attack/"
diff --git a/experiments/example_downstream/config.toml b/experiments/example_downstream/config.toml
@@ -1,5 +1,11 @@
+# This example trains a user model on the poisoned labels from
+# example_attack with 1500 budget and records the attack metrics.
+# The config file is broken down into a single module detailed in
+# the schemas/ folder.
+
+# Module to train a user model on input labels.
 [train_user]
-input_labels = "experiments/example_attack/labels.npy"
+input_labels = "experiments/example_attack/1500.npy"
 user_model = "r32p"
 trainer = "sgd"
 dataset = "cifar"
@@ -8,4 +14,4 @@ target_label = 4
 poisoner = "1xs"
 output_dir = "experiments/example_downstream/"
 soft = false
-alpha = 0.0
+alpha = 0.0
diff --git a/experiments/example_downstream_soft/config.toml b/experiments/example_downstream_soft/config.toml
@@ -1,3 +1,8 @@
+# This example trains a user model on the (soft) logits from
+# example_attack and records the attack metrics. The config file 
+# is broken down into a single module detailed in the schemas/ folder.
+
+# Module to train a user model on input labels.
 [train_user]
 input_labels = "experiments/example_attack/labels.npy"
 true_labels = "experiments/example_attack/true.npy"

diff --git a/experiments/example_flip_selection/config.toml b/experiments/example_flip_selection/config.toml
diff --git a/experiments/example_precomputed/config.toml b/experiments/example_precomputed/config.toml
@@ -1,3 +1,8 @@
+# This example trains a user model on precomputed labels with a 1500
+# flip budget. The config file is broken down into a single module
+# detailed in the schemas/ folder.
+
+# Module to train a user model on input labels.
 [train_user]
 input_labels = "precomputed/cifar/r32p/1xs/1500.npy"
 user_model = "r32p"

diff --git a/experiments/example_precomputed_mix/config.toml b/experiments/example_precomputed_mix/config.toml
@@ -1,3 +1,8 @@
+# This example trains a ViT user model on precomputed ResNet labels
+# with a 1500 flip budget. The config file is broken down into a 
+# single module detailed in the schemas/ folder.
+
+# Module to train a user model on input labels.
 [train_user]
 input_labels = "precomputed/cifar/r32p/1xs/1500.npy"
 user_model = "vit-pretrain"