reorg Mamba folder

bowang-lab · Feb 1, 2024 · f6aa31e · f6aa31e
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diff --git a/configs/Exphormer/cifar10.yaml b/configs/Exphormer/cifar10.yaml
@@ -3,7 +3,7 @@ metric_best: accuracy
 wandb:
   use: True
   project: GNN-Benchmark-RandomSeed-Exphormer
-  entity: tf-map
+  entity: project
 dataset:
   format: PyG-GNNBenchmarkDataset
   name: CIFAR10

diff --git a/configs/Exphormer/cluster.yaml b/configs/Exphormer/cluster.yaml
@@ -3,7 +3,7 @@ metric_best: accuracy-SBM
 wandb:
   use: True
   project: GNN-Benchmark-RandomSeed-Exphormer #flop_experiment_re #graph-mamba
-  entity: tf-map
+  entity: project
 dataset:
   format: PyG-GNNBenchmarkDataset
   name: CLUSTER

diff --git a/configs/Exphormer/malnettiny.yaml b/configs/Exphormer/malnettiny.yaml
@@ -3,7 +3,7 @@ metric_best: accuracy
 wandb:
   use: True
   project: GNN-Benchmark-RandomSeed-Exphormer
-  entity: tf-map
+  entity: project
 dataset:
   format: PyG-MalNetTiny
   name: LocalDegreeProfile

diff --git a/configs/Exphormer/mnist.yaml b/configs/Exphormer/mnist.yaml
@@ -3,7 +3,7 @@ metric_best: accuracy
 wandb:
   use: True
   project: GNN-Benchmark-RandomSeed-Exphormer #graph-mamba
-  entity: tf-map
+  entity: project
 dataset:
   format: PyG-GNNBenchmarkDataset
   name: MNIST

diff --git a/configs/Exphormer/pattern.yaml b/configs/Exphormer/pattern.yaml
@@ -3,7 +3,7 @@ metric_best: accuracy-SBM
 wandb:
   use: True
   project: GNN-Benchmark-RandomSeed-Exphormer #graph-mamba
-  entity: tf-map
+  entity: project
 dataset:
   format: PyG-GNNBenchmarkDataset
   name: PATTERN

diff --git a/configs/Exphormer_LRGB/cocosuperpixels-EX1.yaml b/configs/Exphormer_LRGB/cocosuperpixels-EX1.yaml
@@ -2,8 +2,8 @@ out_dir: results
 metric_best: f1
 wandb:
   use: True
-  project: LRGB-Benchmark-RandomSeed-Exphormer #graph-mamba #flop_experiment_re
-  entity: tf-map
+  project: LRGB-Benchmark-RandomSeed-Exphormer
+  entity: project
 dataset:
   format: PyG-COCOSuperpixels
   name: edge_wt_region_boundary

diff --git a/configs/Exphormer_LRGB/pcqm-contact-EX1.yaml b/configs/Exphormer_LRGB/pcqm-contact-EX1.yaml
@@ -3,8 +3,8 @@ metric_best: mrr
 num_workers: 4
 wandb:
   use: True
-  project: Graph-Mamba-Benchmark-GNN #LRGB-Benchmark-RandomSeed-Exphormer #flop_experiment_re #pcqm4m-contact
-  entity: tf-map
+  project: Graph-Mamba-Benchmark-GNN
+  entity: project
 dataset:
   format: OGB
   name: PCQM4Mv2Contact-shuffle

diff --git a/configs/Exphormer_LRGB/peptides-func-EX1.yaml b/configs/Exphormer_LRGB/peptides-func-EX1.yaml
@@ -2,8 +2,8 @@ out_dir: results
 metric_best: ap
 wandb:
   use: True
-  project: LRGB-Benchmark-RandomSeed-Exphormer #flop_experiment_re #graph-mamba
-  entity: tf-map
+  project: LRGB-Benchmark-RandomSeed-Exphormer
+  entity: project
 dataset:
   format: OGB
   name: peptides-functional

diff --git a/configs/Exphormer_LRGB/peptides-struct-EX.yaml b/configs/Exphormer_LRGB/peptides-struct-EX.yaml
@@ -3,8 +3,8 @@ metric_best: mae
 metric_agg: argmin
 wandb:
   use: True
-  project: LRGB-Benchmark-RandomSeed-Exphormer #graph-mamba #flop_experiment_re
-  entity: tf-map
+  project: LRGB-Benchmark-RandomSeed-Exphormer
+  entity: project
 dataset:
   format: OGB
   name: peptides-structural

diff --git a/configs/Exphormer_LRGB/vocsuperpixels-EX1.yaml b/configs/Exphormer_LRGB/vocsuperpixels-EX1.yaml
@@ -2,8 +2,8 @@ out_dir: results
 metric_best: f1
 wandb:
   use: True
-  project: LRGB-Benchmark-RandomSeed-Exphormer #graph-mamba #flop_experiment_re
-  entity: tf-map
+  project: LRGB-Benchmark-RandomSeed-Exphormer
+  entity: project
 dataset:
   format: PyG-VOCSuperpixels
   name: edge_wt_region_boundary

diff --git a/configs/GPS/cifar10-GPS.yaml b/configs/GPS/cifar10-GPS.yaml
@@ -37,7 +37,7 @@ model:
   edge_decoding: dot
   graph_pooling: mean
 gt:  # Hyperparameters optimized for ~100k budget.
-  layer_type: CustomGatedGCN+Mamba_Hybrid_Degree_Noise
+  layer_type: CustomGatedGCN+Transformer
   layers: 3
   n_heads: 4
   dim_hidden: 52  # `gt.dim_hidden` must match `gnn.dim_inner`
@@ -58,17 +58,8 @@ gnn:
 optim:
   clip_grad_norm: True
   optimizer: adamW
-  weight_decay: 0.01
-  base_lr: 0.005
+  weight_decay: 1e-5
+  base_lr: 0.001
   max_epoch: 100
   scheduler: cosine_with_warmup
   num_warmup_epochs: 5
-seed: 0
-# optim:
-#   clip_grad_norm: True
-#   optimizer: adamW
-#   weight_decay: 1e-5
-#   base_lr: 0.001
-#   max_epoch: 100
-#   scheduler: cosine_with_warmup
-#   num_warmup_epochs: 5
diff --git a/configs/GPS/cluster-GPS.yaml b/configs/GPS/cluster-GPS.yaml
@@ -38,7 +38,7 @@ model:
   loss_fun: weighted_cross_entropy
   edge_decoding: dot
 gt:  # Hyperparameters optimized for ~500k budget.
-  layer_type: CustomGatedGCN+Mamba_Hybrid_Degree_Noise
+  layer_type: CustomGatedGCN+Transformer
   layers: 16
   n_heads: 8
   dim_hidden: 48  # `gt.dim_hidden` must match `gnn.dim_inner`
@@ -59,17 +59,8 @@ gnn:
 optim:
   clip_grad_norm: True
   optimizer: adamW
-  weight_decay: 0.0001
-  base_lr: 0.001
+  weight_decay: 1e-5
+  base_lr: 0.0005
   max_epoch: 100
   scheduler: cosine_with_warmup
   num_warmup_epochs: 5
-seed: 0
-# optim:
-#   clip_grad_norm: True
-#   optimizer: adamW
-#   weight_decay: 1e-5
-#   base_lr: 0.0005
-#   max_epoch: 100
-#   scheduler: cosine_with_warmup
-#   num_warmup_epochs: 5
diff --git a/configs/GPS/cocosuperpixels-GPS.yaml b/configs/GPS/cocosuperpixels-GPS.yaml
@@ -2,7 +2,7 @@ out_dir: results
 metric_best: f1
 wandb:
   use: True
-  project: LRGB-Benchmark-RandomSeed #flop_experiment_re
+  project: LRGB-Benchmark-RandomSeed
   entity: project
 dataset:
   format: PyG-COCOSuperpixels
@@ -36,7 +36,7 @@ model:
   type: GPSModel
   loss_fun: weighted_cross_entropy
 gt:
-  layer_type: CustomGatedGCN+Mamba_Hybrid_Degree_Noise_Bucket
+  layer_type: CustomGatedGCN+Transformer
   layers: 4
   n_heads: 8
   dim_hidden: 96  # `gt.dim_hidden` must match `gnn.dim_inner`
@@ -54,20 +54,11 @@ gnn:
   dropout: 0.0
   agg: mean
   normalize_adj: False
-# optim:
-#   clip_grad_norm: True
-#   optimizer: adamW
-#   weight_decay: 0.0
-#   base_lr: 0.0005
-#   max_epoch: 300
-#   scheduler: cosine_with_warmup
-#   num_warmup_epochs: 10
 optim:
-    clip_grad_norm: True
-    optimizer: adamW
-    weight_decay: 0.001
-    base_lr: 0.0015
-    max_epoch: 300
-    scheduler: cosine_with_warmup
-    num_warmup_epochs: 10
-seed: 0
+  clip_grad_norm: True
+  optimizer: adamW
+  weight_decay: 0.0
+  base_lr: 0.0005
+  max_epoch: 300
+  scheduler: cosine_with_warmup
+  num_warmup_epochs: 10
diff --git a/configs/GPS/malnettiny-GPS.yaml b/configs/GPS/malnettiny-GPS.yaml
@@ -2,7 +2,7 @@ out_dir: results
 metric_best: accuracy
 wandb:
   use: True
-  project: Graph-Mamba-Benchmark-GNN
+  project: GNN-Benchmark-RandomSeed
   entity: project
 dataset:
   format: PyG-MalNetTiny
@@ -26,7 +26,7 @@ model:
   edge_decoding: dot
   graph_pooling: max
 gt:
-  layer_type: CustomGatedGCN+Mamba_Hybrid_Degree_Noise_Bucket
+  layer_type: CustomGatedGCN+Transformer
   layers: 5
   n_heads: 4
   dim_hidden: 64  # `gt.dim_hidden` must match `gnn.dim_inner`
@@ -48,11 +48,10 @@ optim:
   clip_grad_norm: True
   optimizer: adamW
   weight_decay: 1e-5
-  base_lr: 0.0015
+  base_lr: 0.0005
   max_epoch: 150
   scheduler: cosine_with_warmup
   num_warmup_epochs: 10
-seed: 0
 # optim:
 #   clip_grad_norm: True
 #   optimizer: adamW

diff --git a/configs/GPS/mnist-GPS.yaml b/configs/GPS/mnist-GPS.yaml
@@ -37,7 +37,7 @@ model:
   edge_decoding: dot
   graph_pooling: mean
 gt:  # Hyperparameters optimized for ~100k budget.
-  layer_type: CustomGatedGCN+Mamba_Hybrid_Degree_Noise
+  layer_type: CustomGatedGCN+Transformer
   layers: 3
   n_heads: 4
   dim_hidden: 52  # `gt.dim_hidden` must match `gnn.dim_inner`
@@ -58,17 +58,8 @@ gnn:
 optim:
   clip_grad_norm: True
   optimizer: adamW
-  weight_decay: 0.01
-  base_lr: 0.005
+  weight_decay: 1e-5
+  base_lr: 0.001
   max_epoch: 100
   scheduler: cosine_with_warmup
-  num_warmup_epochs: 5
-seed: 0
-# optim:
-#   clip_grad_norm: True
-#   optimizer: adamW
-#   weight_decay: 1e-5
-#   base_lr: 0.001
-#   max_epoch: 100
-#   scheduler: cosine_with_warmup
-#   num_warmup_epochs: 5
+  num_warmup_epochs: 5
diff --git a/configs/GPS/pattern-GPS.yaml b/configs/GPS/pattern-GPS.yaml
@@ -38,7 +38,7 @@ model:
   loss_fun: weighted_cross_entropy
   edge_decoding: dot
 gt:  # Hyperparameters optimized for up to ~500k budget.
-  layer_type: CustomGatedGCN+Mamba_Hybrid_Degree_Noise
+  layer_type: CustomGatedGCN+Transformer
   layers: 6
   n_heads: 4
   dim_hidden: 64  # `gt.dim_hidden` must match `gnn.dim_inner`
@@ -59,17 +59,8 @@ gnn:
 optim:
   clip_grad_norm: True
   optimizer: adamW
-  weight_decay: 0.0001
-  base_lr: 0.001
+  weight_decay: 1e-5
+  base_lr: 0.0005
   max_epoch: 100
   scheduler: cosine_with_warmup
   num_warmup_epochs: 5
-seed: 0
-# optim:
-#   clip_grad_norm: True
-#   optimizer: adamW
-#   weight_decay: 1e-5
-#   base_lr: 0.0005
-#   max_epoch: 100
-#   scheduler: cosine_with_warmup
-#   num_warmup_epochs: 5
diff --git a/configs/GPS/pcqm-contact-GPS.yaml b/configs/GPS/pcqm-contact-GPS.yaml
@@ -38,7 +38,7 @@ model:
   loss_fun: cross_entropy
   edge_decoding: dot
 gt:
-  layer_type: CustomGatedGCN+Mamba_Hybrid_Degree_Noise #Mamba_Hybrid_Degree_Noise #Mamba
+  layer_type: CustomGatedGCN+Transformer #Mamba_Hybrid_Degree_Noise #Mamba
   layers: 4
   n_heads: 4
   dim_hidden: 96  # `gt.dim_hidden` must match `gnn.dim_inner`
@@ -57,27 +57,8 @@ gnn:
 optim:
   clip_grad_norm: True
   optimizer: adamW
-  weight_decay: 0.01
-  base_lr: 0.002
+  weight_decay: 0.0
+  base_lr: 0.0003
   max_epoch: 100
   scheduler: cosine_with_warmup
   num_warmup_epochs: 10
-seed: 0
-# optim:
-#   clip_grad_norm: True
-#   optimizer: adamW
-#   weight_decay: 0.0
-#   base_lr: 0.0003
-#   max_epoch: 200
-#   scheduler: cosine_with_warmup
-#   num_warmup_epochs: 10
-#optim:
-#  batch_accumulation: 1
-#  optimizer: adamW
-#  weight_decay: 0.0
-#  base_lr: 0.0003
-#  max_epoch: 200
-#  scheduler: reduce_on_plateau
-#  reduce_factor: 0.5
-#  schedule_patience: 10
-#  min_lr: 1e-5
diff --git a/configs/GPS/peptides-func-GPS.yaml b/configs/GPS/peptides-func-GPS.yaml
@@ -37,7 +37,7 @@ model:
   loss_fun: cross_entropy
   graph_pooling: mean
 gt:
-  layer_type: CustomGatedGCN+Mamba_Hybrid_Degree_Noise
+  layer_type: CustomGatedGCN+Transformer
   n_heads: 4
   dim_hidden: 96  # `gt.dim_hidden` must match `gnn.dim_inner`
   dropout: 0.0
@@ -55,18 +55,8 @@ gnn:
 optim:
   clip_grad_norm: True
   optimizer: adamW
-  weight_decay: 0.01
-  base_lr: 0.001
+  weight_decay: 0.0
+  base_lr: 0.0003
   max_epoch: 200
   scheduler: cosine_with_warmup
-  num_warmup_epochs: 10
-seed: 0
-#optim:
-#  optimizer: adamW
-#  weight_decay: 0.0
-#  base_lr: 0.0003
-#  max_epoch: 500
-#  scheduler: reduce_on_plateau
-#  reduce_factor: 0.5
-#  schedule_patience: 20
-#  min_lr: 1e-5
+  num_warmup_epochs: 10
diff --git a/configs/GPS/peptides-struct-GPS.yaml b/configs/GPS/peptides-struct-GPS.yaml
@@ -37,7 +37,7 @@ model:
   loss_fun: l1
   graph_pooling: mean
 gt:
-  layer_type: CustomGatedGCN+Mamba_Hybrid_Degree_Noise
+  layer_type: CustomGatedGCN+Transformer
   layers: 4
   n_heads: 4
   dim_hidden: 96  # `gt.dim_hidden` must match `gnn.dim_inner`
@@ -56,18 +56,8 @@ gnn:
 optim:
   clip_grad_norm: True
   optimizer: adamW
-  weight_decay: 0.01
-  base_lr: 0.001
+  weight_decay: 0.0
+  base_lr: 0.0003
   max_epoch: 200
   scheduler: cosine_with_warmup
-  num_warmup_epochs: 10
-seed: 0
-#optim:
-#  optimizer: adamW
-#  weight_decay: 0.0
-#  base_lr: 0.0003
-#  max_epoch: 500
-#  scheduler: reduce_on_plateau
-#  reduce_factor: 0.5
-#  schedule_patience: 20
-#  min_lr: 1e-5
+  num_warmup_epochs: 10