Fix trailing whitespace and end-of-file newlines

openfl-tutorials/experimental/workflow/Global_DP/Workflow_Interface_Mnist_Implementation_1.py

@@ -38,13 +38,15 @@
 
 # Fixing the seed for result repeatation: remove below to stop repeatable runs
 # ----------------------------------
+# Fixing the seed for result reproducibility
 random_seed = 5495300300540669060
-g_device = torch.Generator(device="cuda")
-# Uncomment the line below to use g_cpu if not using cuda
-# g_device = torch.Generator() # noqa: E800
-# NOTE: remove below to stop repeatable runs
+# Determine the device to use (CUDA if available, otherwise CPU)
+device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+# Create a generator for the specified device
+g_device = torch.Generator(device=device)
+# Set the seed for the generator
 g_device.manual_seed(random_seed)
-print(f"\n\nWe are using seed: {random_seed}")
+print(f"\n\nWe are using seed: {random_seed} on device: {device}")
 # ----------------------------------
 
 # Loading torchvision MNIST datasets
@@ -152,6 +154,11 @@ def FedAvg(models, previous_global_model=None, dp_params=None):  # NOQA: N802
             state_dict[key] = np.sum(
                 np.array([state[key] for state in state_dicts], dtype=object), axis=0
             ) / len(models)
+            # Convert numpy arrays to torch tensors
+            if isinstance(state_dict[key], np.ndarray):
+                if state_dict[key].dtype == np.object_:
+                    state_dict[key] = state_dict[key].astype(np.float32)
+                state_dict[key] = torch.tensor(state_dict[key])
     new_model.load_state_dict(state_dict)
     return new_model
 
@@ -619,7 +626,7 @@ def end(self):
 
     # Setup participants
     # Set `num_gpus=0.09` to `num_gpus=0.0` in order to run this tutorial on CPU
-    aggregator = Aggregator(num_gpus=0.09)
+    aggregator = Aggregator(num_gpus=0.0)
 
     # Collaborator names
     collaborator_names = [
@@ -662,7 +669,7 @@ def callable_to_initialize_collaborator_private_attributes(
                 private_attributes_callable=callable_to_initialize_collaborator_private_attributes,
                 # Set `num_gpus=0.09` to `num_gpus=0.0` in order to run this tutorial on CPU
                 num_cpus=0.0,
-                num_gpus=0.09,  # Assuming GPU(s) is available in the machine
+                num_gpus=0.0,  # Assuming GPU(s) is available in the machine
                 index=idx,
                 n_collaborators=len(collaborator_names),
                 batch_size=batch_size_train,

openfl-tutorials/experimental/workflow/Global_DP/Workflow_Interface_Mnist_Implementation_2.py

@@ -644,7 +644,7 @@ def end(self):
 
     # Initialize the aggregator with the callable
     # Set `num_gpus=0.09` to `num_gpus=0.0` in order to run this tutorial on CPU
-    
+
     def callable_to_initialize_aggregator_private_attributes():
         # Load the configuration file to get dp_params
         with open(args.config_path, "rb") as _file:
@@ -657,7 +657,7 @@ def callable_to_initialize_aggregator_private_attributes():
             collaborator_names=collaborator_names,
             dp_params=dp_params
         )}
-    
+
     aggregator = Aggregator(
         name="agg",
         private_attributes_callable= callable_to_initialize_aggregator_private_attributes,
@@ -719,4 +719,4 @@ def callable_to_initialize_collaborator_private_attributes(
         clip_test=args.clip_test,
     )
     flflow.runtime = local_runtime
-    flflow.run()
+    flflow.run()