Code updates to match MICCAI21

README.md

@@ -28,40 +28,10 @@ Available at: https://arxiv.org/abs/2104.05600
 
 ## Training
 
+To reproduce all results run the following scripts:
+- `sh scripts/run-lw.sh`
+- `sh scripts/run-rn.sh`
+- `sh scripts/run-un.sh`
 
-
-To reproduce the results showed in the fig a, b, c, and d, please run the following scripts.
-
-### Fig a
-
-- `sh scripts/fig_a/LW.sh`
-- `sh scripts/fig_a/LW-PBB.sh`
-- `sh scripts/fig_a/U-Net.sh`
-- `sh scripts/fig_a/U-Net-PBB.sh`
-
-### Fig b
-
-- `sh scripts/fig_b/sigma_prior_0.001.sh`
-- `sh scripts/fig_b/sigma_prior_0.005.sh`
-- `sh scripts/fig_b/sigma_prior_0.01.sh`
-- `sh scripts/fig_b/sigma_prior_0.02.sh`
-- `sh scripts/fig_b/sigma_prior_0.03.sh`
-- `sh scripts/fig_b/sigma_prior_0.04.sh`
-- `sh scripts/fig_b/sigma_prior_0.05.sh`
-
-### Fig c
-
-- `sh scripts/fig_c/sigma_prior_0.001.sh`
-- `sh scripts/fig_c/sigma_prior_0.005.sh`
-- `sh scripts/fig_c/sigma_prior_0.01.sh`
-- `sh scripts/fig_c/sigma_prior_0.02.sh`
-- `sh scripts/fig_c/sigma_prior_0.03.sh`
-- `sh scripts/fig_c/sigma_prior_0.04.sh`
-- `sh scripts/fig_c/sigma_prior_0.05.sh`
-- `sh scripts/fig_c/sigma_prior_0.1.sh`
-- `sh scripts/fig_c/sigma_prior_0.2.sh`
-
-### Fig d
-
-- `sh scripts/fig_d/LW.sh`
-- `sh scripts/fig_d/U-Net.sh`
+To run individual experiments, please check the comments which identify each 
+subcall with the correct experiment.

scripts/run-lw.sh

@@ -0,0 +1,90 @@
+for seed in 0
+do
+    python3 -m src.main \
+        --model=light \
+        --baseline \
+        --random_seed=$seed \
+        --device=0
+        # --wandb=miccai21-rerun \
+        # --wandb_id=redo/rs$seed/fig_a/LW
+
+    python3 -m src.main \
+        --model=light \
+        --use_prefix \
+        --freeze_batchnorm \
+        --mc_samples=1000 \
+        --random_seed=$seed \
+        --device=0
+        # --wandb=miccai21-rerun \
+        # --wandb_id=redo/rs$seed/fig_a/LW-PBB
+
+    python3 -m src.main \
+        --model=light \
+        --use_prefix \
+        --freeze_batchnorm \
+        --sigma_prior=0.001 \
+        --random_seed=$seed \
+        --device=0
+        # --wandb=miccai21-rerun \
+        # --wandb_id=redo/rs$seed/fig_c/sigma_prior_0.001
+
+    python3 -m src.main \
+        --model=light \
+        --use_prefix \
+        --freeze_batchnorm \
+        --sigma_prior=0.005 \
+        --random_seed=$seed \
+        --device=0
+        # --wandb=miccai21-rerun \
+        # --wandb_id=redo/rs$seed/fig_c/sigma_prior_0.005
+
+    python3 -m src.main \
+        --model=light \
+        --use_prefix \
+        --freeze_batchnorm \
+        --sigma_prior=0.01 \
+        --random_seed=$seed \
+        --device=0
+        # --wandb=miccai21-rerun \
+        # --wandb_id=redo/rs$seed/fig_c/sigma_prior_0.01
+
+    python3 -m src.main \
+        --model=light \
+        --use_prefix \
+        --freeze_batchnorm \
+        --sigma_prior=0.02 \
+        --random_seed=$seed \
+        --device=0
+        # --wandb=miccai21-rerun \
+        # --wandb_id=redo/rs$seed/fig_c/sigma_prior_0.02
+
+    python3 -m src.main \
+        --model=light \
+        --use_prefix \
+        --freeze_batchnorm \
+        --sigma_prior=0.03 \
+        --random_seed=$seed \
+        --device=0
+        # --wandb=miccai21-rerun \
+        # --wandb_id=redo/rs$seed/fig_c/sigma_prior_0.03
+
+    python3 -m src.main \
+        --model=light \
+        --use_prefix \
+        --freeze_batchnorm \
+        --sigma_prior=0.04 \
+        --random_seed=$seed \
+        --device=0
+        # --wandb=miccai21-rerun \
+        # --wandb_id=redo/rs$seed/fig_c/sigma_prior_0.04
+
+    python3 -m src.main \
+        --model=light \
+        --use_prefix \
+        --freeze_batchnorm \
+        --sigma_prior=0.05 \
+        --random_seed=$seed \
+        --device=0
+        # --wandb=miccai21-rerun \
+        # --wandb_id=redo/rs$seed/fig_c/sigma_prior_0.05
+done

scripts/run-rn.sh

@@ -0,0 +1,117 @@
+for seed in 0
+do
+    python3 -m src.main \
+        --task=classify \
+        --model=resnet18 \
+        --init_lr=5e-1 \
+        --batch_size=64 \
+        --baseline \
+        --random_seed=$seed \
+        --device=0
+        # --wandb=miccai21-rerun \
+        # --wandb_id=rs$seed/fig_a/RN
+
+    python3 -m src.main \
+        --task=classify \
+        --model=resnet18 \
+        --init_lr=5e-1 \
+        --batch_size=64 \
+        --use_prefix \
+        --freeze_batchnorm \
+        --mc_samples=1000 \
+        --random_seed=$seed \
+        --device=0
+        # --wandb=miccai21-rerun \
+        # --wandb_id=rs$seed/fig_a/RN-PBB
+
+    python3 -m src.main \
+        --task=classify \
+        --model=resnet18 \
+        --init_lr=5e-1 \
+        --batch_size=64 \
+        --use_prefix \
+        --freeze_batchnorm \
+        --sigma_prior=0.001 \
+        --random_seed=$seed \
+        --device=0
+        # --wandb=miccai21-rerun \
+        # --wandb_id=rs$seed/fig_d/sigma_prior_0.001
+
+    python3 -m src.main \
+        --task=classify \
+        --model=resnet18 \
+        --init_lr=5e-1 \
+        --batch_size=64 \
+        --use_prefix \
+        --freeze_batchnorm \
+        --sigma_prior=0.005 \
+        --random_seed=$seed \
+        --device=0
+        # --wandb=miccai21-rerun \
+        # --wandb_id=rs$seed/fig_d/sigma_prior_0.005
+
+    python3 -m src.main \
+        --task=classify \
+        --model=resnet18 \
+        --init_lr=5e-1 \
+        --batch_size=64 \
+        --use_prefix \
+        --freeze_batchnorm \
+        --sigma_prior=0.01 \
+        --random_seed=$seed \
+        --device=0
+        # --wandb=miccai21-rerun \
+        # --wandb_id=rs$seed/fig_d/sigma_prior_0.01
+
+    python3 -m src.main \
+        --task=classify \
+        --model=resnet18 \
+        --init_lr=5e-1 \
+        --batch_size=64 \
+        --use_prefix \
+        --freeze_batchnorm \
+        --sigma_prior=0.02 \
+        --random_seed=$seed \
+        --device=0
+        # --wandb=miccai21-rerun \
+        # --wandb_id=rs$seed/fig_d/sigma_prior_0.02
+
+    python3 -m src.main \
+        --task=classify \
+        --model=resnet18 \
+        --init_lr=5e-1 \
+        --batch_size=64 \
+        --use_prefix \
+        --freeze_batchnorm \
+        --sigma_prior=0.03 \
+        --random_seed=$seed \
+        --device=0
+        # --wandb=miccai21-rerun \
+        # --wandb_id=rs$seed/fig_d/sigma_prior_0.03
+
+    python3 -m src.main \
+        --task=classify \
+        --model=resnet18 \
+        --init_lr=5e-1 \
+        --batch_size=64 \
+        --use_prefix \
+        --freeze_batchnorm \
+        --sigma_prior=0.04 \
+        --random_seed=$seed \
+        --device=0
+        # --wandb=miccai21-rerun \
+        # --wandb_id=rs$seed/fig_d/sigma_prior_0.04
+
+    python3 -m src.main \
+        --task=classify \
+        --model=resnet18 \
+        --init_lr=5e-1 \
+        --batch_size=64 \
+        --use_prefix \
+        --freeze_batchnorm \
+        --sigma_prior=0.05 \
+        --random_seed=$seed \
+        --device=0
+        # --wandb=miccai21-rerun \
+        # --wandb_id=rs$seed/fig_d/sigma_prior_0.05
+done