O1: slight cleanup
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1 changed files with 2 additions and 15 deletions
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@ -596,25 +596,12 @@ def train_convnet(hp, train_dl, test_dl):
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criterion = nn.CrossEntropyLoss()
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optimizer = optim.Adam(model.parameters(), lr=1e-3)
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#if hp['epochs'] <= 10:
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# optimizer = optim.Adam(model.parameters(), lr=lr)
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#elif hp['epochs'] > 10 and hp['epochs'] <= 25:
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# optimizer = optim.Adam(model.parameters(), lr=(lr/10))
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#else:
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# optimizer = optim.Adam(model.parameters(), lr=(lr/50))
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scheduler = MultiStepLR(optimizer, milestones=[10, 25], gamma=0.1)
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# scheduler = MultiStepLR(
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# optimizer,
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# milestones=[int(i * hp['epochs']) for i in [0.3, 0.6, 0.8]],
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# gamma=0.2
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# )
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print(f"Training with {hp['epochs']} epochs")
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if hp['epsilon'] is not None:
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privacy_engine = opacus.PrivacyEngine()
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privacy_engine = opacus.PrivacyEngine(accountant='rdp')
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model, optimizer, train_loader = privacy_engine.make_private_with_epsilon(
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module=model,
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optimizer=optimizer,
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@ -764,7 +751,7 @@ def main():
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"wrn_depth": 16,
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"wrn_width": 1,
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"epsilon": args.epsilon,
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"delta": 1e-5,
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"delta": 1e-6,
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"norm": args.norm,
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"batch_size": 50 if args.convnet else 4096,
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"epochs": args.epochs,
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