Remove log

adap · Mar 15, 2024 · 3ffe3f5 · 3ffe3f5
1 parent 3e1a121
commit 3ffe3f5
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Showing 2 changed files with 1 addition and 5 deletions.
diff --git a/examples/fl-dp-sa/fl_dp_sa/server.py b/examples/fl-dp-sa/fl_dp_sa/server.py
@@ -39,7 +39,7 @@ def weighted_average(metrics: List[Tuple[int, Metrics]]) -> Metrics:
 parameters = ndarrays_to_parameters(ndarrays)
 
 
-# Define core strategy
+# Define strategy
 strategy = FedAvg(
     fraction_fit=0.2,
     fraction_evaluate=0.0,  # Disable evaluation for demo purpose
@@ -48,9 +48,6 @@ def weighted_average(metrics: List[Tuple[int, Metrics]]) -> Metrics:
     fit_metrics_aggregation_fn=weighted_average,
     initial_parameters=parameters,
 )
-
-
-# Wrap the core strategy
 strategy = DifferentialPrivacyClientSideFixedClipping(
     strategy, noise_multiplier=0.2, clipping_norm=10, num_sampled_clients=20
 )

diff --git a/examples/fl-dp-sa/fl_dp_sa/task.py b/examples/fl-dp-sa/fl_dp_sa/task.py
@@ -58,7 +58,6 @@ def apply_transforms(batch):
 
 def train(net, trainloader, valloader, epochs, device):
     """Train the model on the training set."""
-    log(INFO, "Starting training...")
     net.to(device)  # move model to GPU if available
     criterion = torch.nn.CrossEntropyLoss().to(device)
     optimizer = torch.optim.Adam(net.parameters())