first commit after paper revision

.gitignore

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+/log
+/out
+/data
+**/__pycache__

args/citeseer.yaml

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+num_clients: 5
+hidden_dim: 64
+dropout: 0.1
+lr: 0.01
+step_size: 16
+gamma: 0.9
+patience: 16

args/cora.yaml

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+num_clients: 5
+hidden_dim: 64
+dropout: 0.0
+lr: 0.005
+step_size: 4
+gamma: 0.9
+patience: 16

args/cora_1.yaml

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+num_clients: 1
+hidden_dim: 64
+dropout: 0.0
+lr: 0.05
+step_size: 1
+gamma: 0.9
+patience: 16

args/cora_10.yaml

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+num_clients: 10
+hidden_dim: 64
+dropout: 0.0
+lr: 0.005
+step_size: 8
+gamma: 0.9
+patience: 16

args/cora_20.yaml

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+num_clients: 20
+hidden_dim: 64
+dropout: 0.0
+lr: 0.005
+step_size: 4
+gamma: 0.9
+patience: 16

args/cora_30.yaml

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+num_clients: 30
+hidden_dim: 64
+dropout: 0.0
+lr: 0.01
+step_size: 1
+gamma: 0.9
+patience: 16

args/cora_5.yaml

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+num_clients: 5
+hidden_dim: 64
+dropout: 0.0
+lr: 0.005
+step_size: 4
+gamma: 0.9
+patience: 16

args/cora_50.yaml

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+num_clients: 50
+hidden_dim: 64
+dropout: 0.0
+lr: 0.01
+step_size: 1
+gamma: 0.9
+patience: 16

args/dblp_conf.yaml

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+num_clients: 20
+hidden_dim: 64
+dropout: 0.1
+lr: 0.03
+step_size: 8
+gamma: 0.9
+patience: 16

args/dblp_org.yaml

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+num_clients: 8
+hidden_dim: 64
+dropout: 0.0
+lr: 0.1
+step_size: 4
+gamma: 0.9
+patience: 16

args/pubmed.yaml

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+num_clients: 5
+hidden_dim: 128
+dropout: 0.0
+lr: 0.1
+step_size: 8
+gamma: 0.9
+patience: 16

code/args.py

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+from typing import *
+import argparse
+import pytorch_lightning as pl
+import yaml
+import os
+
+
+def parse_global_args():
+    parser = argparse.ArgumentParser()
+    parser = pl.Trainer.add_argparse_args(parser)
+
+    parser.add_argument('--root', type=str, default='/home/guozhuoning/projects/hierarchical_fed_graph/')
+    parser.add_argument('--data_folder', type=str, default='data')
+    parser.add_argument('--args_folder', type=str, default='args')
+    parser.add_argument('-D', '--dataset_name', type=str)
+    parser.add_argument('-E', '--epochs', type=int, default=1024, help='epoch size')
+    parser.add_argument('--train_batch_size', type=int, default=1, help='train batch size.')
+    parser.add_argument('--val_batch_size', type=int, default=1, help='validation batch size.')
+    parser.add_argument('--test_batch_size', type=int, default=1, help='test batch size.')
+    parser.add_argument('--monitor', type=str, default='ACC', help='training monitor')
+    parser.add_argument('--cross_client', type=bool, default=True, help='whether the graph remains the cross-client edges')
+    parser.add_argument('--num_layers', type=int, default=2, help='number of gnn layers')
+
+    global_args, _ = parser.parse_known_args()
+    return parser, global_args
+
+
+def parse_dataset_specific_args(parent_args: argparse.Namespace):
+    with open(os.path.join(parent_args.root, parent_args.args_folder, f'{parent_args.dataset_name}.yaml'), 'r') as f:
+        dataset_specific_args = yaml.load(f, Loader=yaml.FullLoader)
+    parent_args.__dict__.update(**dataset_specific_args)
+    return parent_args