Setup ray cluster

README.md

@@ -92,7 +92,7 @@ bash setup_cluster.sh
 Delete the RayCluster Custom Resource:
 
 ```bash
-cd docs/examples/configs
+cd ray_cluster_configs
 kubectl delete -f ray_kubernetes_cluster.yaml
 kubectl delete -f ray_kubernetes_ingress.yaml
 ```
@@ -108,7 +108,7 @@ Finally, Delete the node first and then delete EKS Cluster:
 
 ```bash
 kubectl get nodes -o name | xargs kubectl delete
-eksctl delete cluster --region us-west-2 --name user
+eksctl delete cluster --region <YOUR_AWS_REGION> --name <CLUSTER_NAME>
 ```
 
 ## Step to Push Data to Hugging Face Hub CLI

benchmark/configs/config_FedGAT.yaml

@@ -0,0 +1,38 @@
+dual_weight: 5.e-4
+aug_lagrange_rho: 6.e-4
+model_lr: 0.06
+model_regularisation: 2.e-3
+dual_lr: 1.e-2
+num_local_iters: 1
+train_rounds: 35
+global_rounds: 35
+gamma: 0.2
+attn_func_parameter: 0.2
+# lambda x: AttnFunction(x, 0.2)
+attn_func_domain: [-5, 5, 500]
+sample_probab: 1
+hidden_dim: 8
+num_heads: 8
+max_deg: 16
+
+# dataset: ogbn-arxiv
+dataset: cora
+n_trainer: 20
+num_layers: 2
+num_hops: 2
+gpu: false
+momentum: 0.0
+iid_beta: 10000
+logdir: ./runs
+device: cpu
+optim_kind: Adam
+glob_comm: FedAvg
+optim_reset: False
+dampening: 0.0
+limit_node_degree: 150
+# method: DistributedGAT
+# method: CentralizedGAT
+method: FedGAT
+batch_size: False
+vecgen: True
+communication_grad: True

benchmark/configs/config_FedGCN.yaml

@@ -0,0 +1,11 @@
+dataset: cora
+fedtype: fedgcn
+global_rounds: 100
+local_step: 3
+learning_rate: 0.5
+n_trainer: 2
+num_layers: 2
+num_hops: 2
+gpu: false
+iid_beta: 10000
+logdir: ./runs

benchmark/configs/config_GC_FedAvg.yaml

@@ -0,0 +1,29 @@
+# general:
+  model: 'FedAvg'
+
+# dataset
+  dataset: "IMDB-BINARY"
+  is_multiple_dataset: False
+  datapath: './data'
+  convert_x: False
+  overlap: False
+
+# setup
+  device: 'cpu'
+  seed: 10
+  seed_split_data: 42
+
+# model_parameters
+  num_trainers: 2
+  num_rounds: 200
+  local_epoch: 1
+  lr: 0.001
+  weight_decay: 0.0005
+  nlayer: 3
+  hidden: 64
+  dropout: 0.5
+  batch_size: 128
+
+# output
+  outbase: './outputs'
+  save_files: False

benchmark/configs/config_GC_FedProx.yaml

@@ -0,0 +1,30 @@
+# general:
+  model: 'FedAvg'
+
+# dataset:
+  dataset: "IMDB-BINARY"
+  is_multiple_dataset: False
+  datapath: './data'
+  convert_x: False
+  overlap: False
+
+# setup:
+  device: 'cpu'
+  seed: 10
+  seed_split_data: 42
+
+# model_parameters:
+  num_trainers: 2
+  num_rounds: 200
+  local_epoch: 1
+  lr: 0.001
+  weight_decay: 0.0005
+  nlayer: 3
+  hidden: 64
+  dropout: 0.5
+  batch_size: 128
+  mu: 0.01
+
+# output:
+  outbase: './outputs'
+  save_files: False

benchmark/configs/config_GC_GCFL+.yaml

@@ -0,0 +1,33 @@
+# general:
+  model: 'GCFL'
+
+# dataset:
+  dataset: "IMDB-BINARY"
+  is_multiple_dataset: False
+  datapath: './data'
+  convert_x: False
+  overlap: False
+
+# setup:
+  device: 'cpu'
+  seed: 10
+  seed_split_data: 42
+
+# model_parameters:
+  num_trainers: 2
+  num_rounds: 200
+  local_epoch: 1
+  lr: 0.001
+  weight_decay: 0.0005
+  nlayer: 3
+  hidden: 64
+  dropout: 0.5
+  batch_size: 128
+  standardize: False
+  seq_length: 5
+  epsilon1: 0.05
+  epsilon2: 0.1
+
+# output:
+  outbase: './outputs'
+  save_files: False

benchmark/configs/config_GC_GCFL+dWs.yaml

@@ -0,0 +1,33 @@
+# general:
+  model: 'GCFL'
+
+# dataset:
+  dataset: "IMDB-BINARY"
+  is_multiple_dataset: False
+  datapath: './data'
+  convert_x: False
+  overlap: False
+
+# setup:
+  device: 'cpu'
+  seed: 10
+  seed_split_data: 42
+
+# model_parameters:
+  num_trainers: 2
+  num_rounds: 200
+  local_epoch: 1
+  lr: 0.001
+  weight_decay: 0.0005
+  nlayer: 3
+  hidden: 64
+  dropout: 0.5
+  batch_size: 128
+  standardize: False
+  seq_length: 5
+  epsilon1: 0.05
+  epsilon2: 0.1
+
+# output:
+  outbase: './outputs'
+  save_files: False

benchmark/configs/config_GC_GCFL.yaml

@@ -0,0 +1,33 @@
+# general:
+  model: 'GCFL'
+
+# dataset:
+  dataset: "IMDB-BINARY"
+  is_multiple_dataset: False
+  datapath: './data'
+  convert_x: False
+  overlap: False
+
+# setup:
+  device: 'cpu'
+  seed: 10
+  seed_split_data: 42
+
+# model_parameters:
+  num_trainers: 2
+  num_rounds: 200
+  local_epoch: 1
+  lr: 0.001
+  weight_decay: 0.0005
+  nlayer: 3
+  hidden: 64
+  dropout: 0.5
+  batch_size: 128
+  standardize: False
+  seq_length: 5
+  epsilon1: 0.05
+  epsilon2: 0.1
+
+# output:
+  outbase: './outputs'
+  save_files: False

benchmark/configs/config_GC_SelfTrain.yaml

@@ -0,0 +1,28 @@
+# general:
+  model: 'SelfTrain'
+
+# dataset
+  dataset: "IMDB-BINARY"
+  is_multiple_dataset: False
+  datapath: './data'
+  convert_x: False
+  overlap: False
+
+# setup
+  device: 'cpu'
+  seed: 10
+  seed_split_data: 42
+
+# model_parameters
+  num_trainers: 2
+  local_epoch: 1
+  lr: 0.001
+  weight_decay: 0.0005
+  nlayer: 3
+  hidden: 64
+  dropout: 0.5
+  batch_size: 128
+
+# output
+  outbase: './outputs'
+  save_files: False

benchmark/configs/config_LP.yaml

@@ -0,0 +1,24 @@
+# general:
+method: FedLink
+fedgraph_task: LP
+# dataset:
+country_codes: ["US", "BR"] # country_codes = ['US', 'BR', 'ID', 'TR', 'JP']
+dataset_path: data/LPDataset
+global_file_path: data/LPDataset/data_five_countries.txt
+traveled_file_path: data/LPDataset/traveled_users.txt
+
+# setup:
+device: gpu
+use_buffer: false
+buffer_size: 300000
+online_learning: false
+seed: 10
+
+# model_parameters:
+global_rounds: 8
+local_steps: 3
+repeat_time: 1
+hidden_channels: 64
+
+# output:
+record_results: false