Simplify configs

.gitignore

@@ -1,2 +1,3 @@
 __pycache__
-*.compiled
+*.compiled
+*.optimized

cifar/gelu_4fc_100/config.yaml

@@ -2,7 +2,6 @@ general:
   root_path: ${CONFIG_PATH}  # Folder containing the csv and vnnlib files for verification.
   csv_name: instances.csv
   loss_reduction_func: min
-  sparse_alpha: false
 model:
   name: >-
     Customized("../models/gelu.py", "gelu_4fc_100")
@@ -10,14 +9,9 @@ model:
   input_shape: [-1, 3, 32, 32]
 solver:
   batch_size: 512
-  min_batch_size_ratio: 0
   alpha-crown:
     iteration: 50
   beta-crown:
     lr_alpha: 0.1
     lr_beta: 0.1
-    iteration: 50
-bab:
-  pruning_in_iteration: false   # bug
-  branching:
-    method: nonlinear
+    iteration: 50

cifar/gelu_4fc_200/config.yaml

@@ -1,7 +1,6 @@
 general:
   csv_name: instances.csv
   loss_reduction_func: min
-  sparse_alpha: false
   root_path: ${CONFIG_PATH}
 model:
   name: >-
@@ -10,14 +9,9 @@ model:
   input_shape: [-1, 3, 32, 32]
 solver:
   batch_size: 256
-  min_batch_size_ratio: 0
   alpha-crown:
     iteration: 50
   beta-crown:
     lr_alpha: 0.1
     lr_beta: 0.1
-    iteration: 50
-bab:
-  pruning_in_iteration: false   # bug
-  branching:
-    method: nonlinear
+    iteration: 50

cifar/gelu_4fc_500/config.yaml

@@ -2,22 +2,16 @@ general:
   root_path: ${CONFIG_PATH}  # Folder containing the csv and vnnlib files for verification.
   csv_name: instances.csv
   loss_reduction_func: min
-  sparse_alpha: false
 model:
   name: >-
     Customized("../models/gelu.py", "gelu_4fc_500")
   path: ${CONFIG_PATH}/model.pth
   input_shape: [-1, 3, 32, 32]
 solver:
-  min_batch_size_ratio: 0
   batch_size: 128
   alpha-crown:
     iteration: 50
   beta-crown:
     lr_alpha: 0.1
     lr_beta: 0.1
-    iteration: 50
-bab:
-  pruning_in_iteration: false   # bug
-  branching:
-    method: nonlinear
+    iteration: 50

cifar/lstm_16_32/config.yaml

@@ -1,8 +1,7 @@
 general:
   csv_name: instances.csv
   loss_reduction_func: min
-  sparse_alpha: false
-  sparse_interm: false
+  conv_mode: matrix
   root_path: ${CONFIG_PATH}
 model:
   name: >-
@@ -10,7 +9,6 @@ model:
   path: ${CONFIG_PATH}/model.pth
   input_shape: [-1, 3, 32, 32]
 solver:
-  min_batch_size_ratio: 0
   batch_size: 2048
   alpha-crown:
     iteration: 20
@@ -18,8 +16,4 @@ solver:
   beta-crown:
     lr_alpha: 0.1
     lr_beta: 0.1
-    iteration: 50
-bab:
-  pruning_in_iteration: false   # bug
-  branching:
-    method: nonlinear
+    iteration: 50

cifar/lstm_16_64/config.yaml

@@ -1,8 +1,7 @@
 general:
   csv_name: instances.csv
   loss_reduction_func: min
-  sparse_alpha: false
-  sparse_interm: false
+  conv_mode: matrix
   root_path: ${CONFIG_PATH}
 model:
   name: >-
@@ -10,7 +9,6 @@ model:
   path: ${CONFIG_PATH}/model.pth
   input_shape: [-1, 3, 32, 32]
 solver:
-  min_batch_size_ratio: 0
   batch_size: 512
   alpha-crown:
     iteration: 20
@@ -18,8 +16,4 @@ solver:
   beta-crown:
     lr_alpha: 0.1
     lr_beta: 0.1
-    iteration: 50
-bab:
-  pruning_in_iteration: false   # bug
-  branching:
-    method: nonlinear
+    iteration: 50

cifar/sigmoid_4fc_100/config.yaml

@@ -9,7 +9,6 @@ model:
   path: ${CONFIG_PATH}/model.pth
   input_shape: [-1, 3, 32, 32]
 solver:
-  min_batch_size_ratio: 0
   batch_size: 384
   alpha-crown:
     iteration: 50
@@ -18,7 +17,5 @@ solver:
     lr_beta: 0.1
     iteration: 50
 bab:
-  pruning_in_iteration: false   # bug
   branching:
-    method: nonlinear
     reduceop: mean

cifar/sigmoid_4fc_500/config.yaml

@@ -2,14 +2,12 @@ general:
   root_path: ${CONFIG_PATH}
   csv_name: instances.csv
   loss_reduction_func: min
-  sparse_alpha: false
 model:
   name: >-
     Customized("../models/sigmoid.py", "sigmoid_4fc_500")
   path: ${CONFIG_PATH}/model.pth
   input_shape: [-1, 3, 32, 32]
 solver:
-  min_batch_size_ratio: 0
   batch_size: 64
   alpha-crown:
     iteration: 50
@@ -18,7 +16,5 @@ solver:
     lr_beta: 0.1
     iteration: 50
 bab:
-  pruning_in_iteration: false   # bug
   branching:
-    method: nonlinear
     reduceop: mean

cifar/sigmoid_6fc_100/config.yaml

@@ -2,14 +2,12 @@ general:
   root_path: ${CONFIG_PATH}
   csv_name: instances.csv
   loss_reduction_func: min
-  sparse_alpha: false
 model:
   name: >-
     Customized("../models/sigmoid.py", "sigmoid_6fc_100")
   path: ${CONFIG_PATH}/model.pth
   input_shape: [-1, 3, 32, 32]
 solver:
-  min_batch_size_ratio: 0
   batch_size: 384
   alpha-crown:
     iteration: 50
@@ -18,7 +16,5 @@ solver:
     lr_beta: 0.1
     iteration: 50
 bab:
-  pruning_in_iteration: false   # bug
   branching:
-    method: nonlinear
     reduceop: mean

cifar/sigmoid_6fc_200/config.yaml

@@ -2,14 +2,12 @@ general:
   root_path: ${CONFIG_PATH}
   csv_name: instances.csv
   loss_reduction_func: min
-  sparse_alpha: false
 model:
   name: >-
     Customized("../models/sigmoid.py", "sigmoid_6fc_200")
   path: ${CONFIG_PATH}/model.pth
   input_shape: [-1, 3, 32, 32]
 solver:
-  min_batch_size_ratio: 0
   batch_size: 128
   alpha-crown:
     iteration: 50
@@ -18,7 +16,5 @@ solver:
     lr_beta: 0.1
     iteration: 50
 bab:
-  pruning_in_iteration: false   # bug
   branching:
-    method: nonlinear
     reduceop: mean

cifar/sin_4fc_100/config.yaml

@@ -2,14 +2,12 @@ general:
   root_path: ${CONFIG_PATH}
   csv_name: instances.csv
   loss_reduction_func: min
-  sparse_alpha: false
 model:
   name: >-
     Customized("../models/sin.py", "sin_4fc_100")
   path: ${CONFIG_PATH}/model.pth
   input_shape: [-1, 3, 32, 32]
 solver:
-  min_batch_size_ratio: 0
   batch_size: 800
   alpha-crown:
     iteration: 50
@@ -18,7 +16,5 @@ solver:
     lr_beta: 0.02
     iteration: 10
 bab:
-  pruning_in_iteration: false   # bug
   branching:
-    method: nonlinear
-    reduceop: mean
+    reduceop: mean

cifar/sin_4fc_200/config.yaml

@@ -2,14 +2,12 @@ general:
   root_path: ${CONFIG_PATH}
   csv_name: instances.csv
   loss_reduction_func: min
-  sparse_alpha: false
 model:
   name: >-
     Customized("../models/sin.py", "sin_4fc_200")
   path: ${CONFIG_PATH}/model.pth
   input_shape: [-1, 3, 32, 32]
 solver:
-  min_batch_size_ratio: 0
   batch_size: 400
   alpha-crown:
     iteration: 50
@@ -18,7 +16,5 @@ solver:
     lr_beta: 0.02
     iteration: 10
 bab:
-  pruning_in_iteration: false   # bug
   branching:
-    method: nonlinear
     reduceop: mean

cifar/sin_4fc_500/config.yaml

@@ -2,14 +2,12 @@ general:
   root_path: ${CONFIG_PATH}
   csv_name: instances.csv
   loss_reduction_func: min
-  sparse_alpha: false
 model:
   name: >-
     Customized("../models/sin.py", "sin_4fc_500")
   path: ${CONFIG_PATH}/model.pth
   input_shape: [-1, 3, 32, 32]
 solver:
-  min_batch_size_ratio: 0
   batch_size: 128
   alpha-crown:
     iteration: 50
@@ -18,7 +16,5 @@ solver:
     lr_beta: 0.02
     iteration: 10
 bab:
-  pruning_in_iteration: false   # bug
   branching:
-    method: nonlinear
-    reduceop: mean
+    reduceop: mean

cifar/tanh_4fc_100/config.yaml

@@ -2,14 +2,12 @@ general:
   root_path: ${CONFIG_PATH}
   csv_name: instances.csv
   loss_reduction_func: min
-  sparse_alpha: false
 model:
   name: >-
     Customized("../models/tanh.py", "tanh_4fc_100")
   path: ${CONFIG_PATH}/model.pth
   input_shape: [-1, 3, 32, 32]
 solver:
-  min_batch_size_ratio: 0
   batch_size: 384
   alpha-crown:
     iteration: 50
@@ -18,7 +16,5 @@ solver:
     lr_beta: 0.1
     iteration: 50
 bab:
-  pruning_in_iteration: false   # bug
   branching:
-    method: nonlinear
-    reduceop: mean
+    reduceop: mean

cifar/tanh_6fc_100/config.yaml

@@ -2,14 +2,12 @@ general:
   root_path: ${CONFIG_PATH}
   csv_name: instances.csv
   loss_reduction_func: min
-  sparse_alpha: false
 model:
   name: >-
     Customized("../models/tanh.py", "tanh_6fc_100")
   path: ${CONFIG_PATH}/model.pth
   input_shape: [-1, 3, 32, 32]
 solver:
-  min_batch_size_ratio: 0
   batch_size: 384
   alpha-crown:
     iteration: 50
@@ -18,7 +16,5 @@ solver:
     lr_beta: 0.1
     iteration: 50
 bab:
-  pruning_in_iteration: false   # bug
   branching:
-    method: nonlinear
-    reduceop: mean
+    reduceop: mean

cifar/vit_1_3/config.yaml

@@ -11,14 +11,9 @@ model:
   path: ${CONFIG_PATH}/model.pth
   input_shape: [-1, 3, 32, 32]
 solver:
-  min_batch_size_ratio: 0
   batch_size: 50
   alpha-crown:
     lr_alpha: 0.01
     iteration: 50
   beta-crown:
-    iteration: 50
-bab:
-  pruning_in_iteration: False
-  branching:
-    method: nonlinear
+    iteration: 50

cifar/vit_1_6/config.yaml

@@ -11,14 +11,9 @@ model:
   path: ${CONFIG_PATH}/model.pth
   input_shape: [-1, 3, 32, 32]
 solver:
-  min_batch_size_ratio: 0
   batch_size: 25
   alpha-crown:
     lr_alpha: 0.01
     iteration: 50
   beta-crown:
-    iteration: 50
-bab:
-  pruning_in_iteration: False
-  branching:
-    method: nonlinear
+    iteration: 50

cifar/vit_2_3/config.yaml

@@ -11,14 +11,9 @@ model:
   path: ${CONFIG_PATH}/model.pth
   input_shape: [-1, 3, 32, 32]
 solver:
-  min_batch_size_ratio: 0
   batch_size: 50
   alpha-crown:
     lr_alpha: 0.01
     iteration: 20
   beta-crown:
-    iteration: 20
-bab:
-  pruning_in_iteration: False
-  branching:
-    method: nonlinear
+    iteration: 20

cifar/vit_2_6/config.yaml

@@ -11,14 +11,9 @@ model:
   path: ${CONFIG_PATH}/model.pth
   input_shape: [-1, 3, 32, 32]
 solver:
-  min_batch_size_ratio: 0
   batch_size: 25
   alpha-crown:
     lr_alpha: 0.01
     iteration: 20
   beta-crown:
-    iteration: 20
-bab:
-  pruning_in_iteration: False
-  branching:
-    method: nonlinear
+    iteration: 20

eran/sigmoid_6_100/config.yaml

@@ -1,6 +1,5 @@
 general:
   loss_reduction_func: min
-  sparse_alpha: false
 model:
   onnx_path: ${CONFIG_PATH}/ffnnSIGMOID__Point_6x100.onnx
   input_shape: [-1, 1, 28, 28]
@@ -10,7 +9,6 @@ data:
 specification:
   epsilon: 0.015
 solver:
-  min_batch_size_ratio: 0
   batch_size: 2048
   alpha-crown:
     iteration: 50
@@ -20,8 +18,6 @@ solver:
     iteration: 50
 bab:
   timeout: 300
-  pruning_in_iteration: false
   branching:
-    method: nonlinear
     nonlinear_split:
       loose_tanh_threshold: 5

eran/sigmoid_6_200/config.yaml

@@ -1,6 +1,5 @@
 general:
   loss_reduction_func: min
-  sparse_alpha: false
 model:
   onnx_path: ${CONFIG_PATH}/ffnnSIGMOID__Point_6x200.onnx
   input_shape: [-1, 1, 28, 28]
@@ -10,7 +9,6 @@ data:
 specification:
   epsilon: 0.012
 solver:
-  min_batch_size_ratio: 0
   batch_size: 1024
   early_stop_patience: 100
   alpha-crown:
@@ -21,8 +19,6 @@ solver:
     iteration: 25
 bab:
   timeout: 300
-  pruning_in_iteration: false
   branching:
-    method: nonlinear
     nonlinear_split:
       loose_tanh_threshold: 5

eran/sigmoid_9_100/config.yaml

@@ -1,6 +1,5 @@
 general:
   loss_reduction_func: min
-  sparse_alpha: false
 model:
   onnx_path: ${CONFIG_PATH}/ffnnSIGMOID__Point_9x100.onnx
   input_shape: [-1, 1, 28, 28]
@@ -10,7 +9,6 @@ data:
 specification:
   epsilon: 0.015
 solver:
-  min_batch_size_ratio: 0
   batch_size: 2048
   early_stop_patience: 100
   alpha-crown:
@@ -21,8 +19,6 @@ solver:
     iteration: 25
 bab:
   timeout: 300
-  pruning_in_iteration: false
   branching:
-    method: nonlinear
     nonlinear_split:
       loose_tanh_threshold: 5

eran/sigmoid_conv_small/config.yaml

@@ -1,6 +1,5 @@
 general:
   loss_reduction_func: min
-  sparse_alpha: false
 model:
   onnx_path: ${CONFIG_PATH}/convSmallSIGMOID__Point.onnx
   input_shape: [-1, 1, 28, 28]
@@ -10,7 +9,6 @@ data:
 specification:
   epsilon: 0.014
 solver:
-  min_batch_size_ratio: 0
   batch_size: 64
   early_stop_patience: 100
   alpha-crown:
@@ -21,8 +19,6 @@ solver:
     iteration: 25
 bab:
   timeout: 300
-  pruning_in_iteration: false
   branching:
-    method: nonlinear
     nonlinear_split:
       loose_tanh_threshold: 5

eran/tanh_6_100/config.yaml

@@ -1,6 +1,5 @@
 general:
   loss_reduction_func: min
-  sparse_alpha: false
 model:
   onnx_path: ${CONFIG_PATH}/ffnnTANH__Point_6x100.onnx
   input_shape: [-1, 1, 28, 28]
@@ -10,7 +9,6 @@ data:
 specification:
   epsilon: 0.006
 solver:
-  min_batch_size_ratio: 0
   batch_size: 2048
   early_stop_patience: 100
   alpha-crown:
@@ -21,8 +19,6 @@ solver:
     iteration: 25
 bab:
   timeout: 300
-  pruning_in_iteration: false
   branching:
-    method: nonlinear
     nonlinear_split:
       loose_tanh_threshold: 2

eran/tanh_6_200/config.yaml

@@ -1,6 +1,5 @@
 general:
   loss_reduction_func: min
-  sparse_alpha: false
 model:
   onnx_path: ${CONFIG_PATH}/ffnnTANH__Point_6x200.onnx
   input_shape: [-1, 1, 28, 28]
@@ -20,8 +19,6 @@ solver:
     iteration: 25
 bab:
   timeout: 300
-  pruning_in_iteration: false
   branching:
-    method: nonlinear
     nonlinear_split:
       loose_tanh_threshold: 2

eran/tanh_9_100/config.yaml

@@ -1,6 +1,5 @@
 general:
   loss_reduction_func: min
-  sparse_alpha: false
 model:
   onnx_path: ${CONFIG_PATH}/ffnnTANH__Point_9x100.onnx
   input_shape: [-1, 1, 28, 28]
@@ -10,7 +9,6 @@ data:
 specification:
   epsilon: 0.006
 solver:
-  min_batch_size_ratio: 0
   batch_size: 2048
   early_stop_patience: 100
   alpha-crown:
@@ -21,8 +19,6 @@ solver:
     iteration: 25
 bab:
   timeout: 300
-  pruning_in_iteration: false
   branching:
-    method: nonlinear
     nonlinear_split:
       loose_tanh_threshold: 2

eran/tanh_conv_small/config.yaml

@@ -1,6 +1,5 @@
 general:
   loss_reduction_func: min
-  sparse_alpha: false
 model:
   onnx_path: ${CONFIG_PATH}/convSmallTANH__Point.onnx
   input_shape: [-1, 1, 28, 28]
@@ -10,7 +9,6 @@ data:
 specification:
   epsilon: 0.005
 solver:
-  min_batch_size_ratio: 0
   batch_size: 64
   early_stop_patience: 100
   alpha-crown:
@@ -21,8 +19,6 @@ solver:
     iteration: 25
 bab:
   timeout: 300
-  pruning_in_iteration: false
   branching:
-    method: nonlinear
     nonlinear_split:
       loose_tanh_threshold: 2

ml4acopf/config.yaml

@@ -1,8 +1,6 @@
 general:
   root_path: ${CONFIG_PATH}
   csv_name: instances.csv
-  sparse_alpha: false
-  sparse_interm: false
   verify_onnxruntime_output: True
 model:
   onnx_optimization_flags: ["remove_matmul_inplace"]
@@ -11,7 +9,6 @@ attack:
   attack_tolerance: 0.0001
 solver:
   batch_size: 128
-  min_batch_size_ratio: 0.0
   early_stop_patience: 200
   alpha-crown:
     lr_alpha: 0.2
@@ -22,9 +19,7 @@ solver:
     lr_beta: 0.5
     iteration: 50
 bab:
-  pruning_in_iteration: false
   branching:
-    method: nonlinear
     candidates: 200
     nonlinear_split:
       filter: true

prover/mnist_lstm_7_32_1/config.yaml

@@ -1,8 +1,7 @@
 general:
   csv_name: instances.csv
   loss_reduction_func: min
-  sparse_alpha: false
-  sparse_interm: false
+  conv_mode: matrix
   root_path: ${CONFIG_PATH}
 model:
   name: >-
@@ -10,7 +9,6 @@ model:
   path: ${CONFIG_PATH}/model.pth
   input_shape: [-1, 1, 28, 28]
 solver:
-  min_batch_size_ratio: 0
   batch_size: 2048
   alpha-crown:
     iteration: 20
@@ -18,8 +16,4 @@ solver:
   beta-crown:
     lr_alpha: 0.1
     lr_beta: 0.1
-    iteration: 50
-bab:
-  pruning_in_iteration: false   # bug
-  branching:
-    method: nonlinear
+    iteration: 50