Update E2E tests to follow recent conventions

e2e/bare-client-auth/client.py

@@ -1,16 +1,14 @@
-from typing import Optional
-
 import numpy as np
 
-import flwr as fl
+from flwr.client import ClientApp, NumPyClient
 from flwr.common import Context
 
 model_params = np.array([1])
 objective = 5
 
 
 # Define Flower client
-class FlowerClient(fl.client.NumPyClient):
+class FlowerClient(NumPyClient):
     def get_parameters(self, config):
         return model_params
 
@@ -30,6 +28,6 @@ def client_fn(context: Context):
     return FlowerClient().to_client()
 
 
-app = fl.client.ClientApp(
+app = ClientApp(
     client_fn=client_fn,
 )

e2e/bare-https/client.py

@@ -1,17 +1,16 @@
 from pathlib import Path
-from typing import Optional
 
 import numpy as np
 
-import flwr as fl
+from flwr.client import ClientApp, NumPyClient, start_client
 from flwr.common import Context
 
 model_params = np.array([1])
 objective = 5
 
 
 # Define Flower client
-class FlowerClient(fl.client.NumPyClient):
+class FlowerClient(NumPyClient):
     def get_parameters(self, config):
         return model_params
 
@@ -31,13 +30,13 @@ def client_fn(context: Context):
     return FlowerClient().to_client()
 
 
-app = fl.client.ClientApp(
+app = ClientApp(
     client_fn=client_fn,
 )
 
 if __name__ == "__main__":
     # Start Flower client
-    fl.client.start_client(
+    start_client(
         server_address="127.0.0.1:8080",
         client=FlowerClient().to_client(),
         root_certificates=Path("certificates/ca.crt").read_bytes(),

e2e/bare/client.py

@@ -1,9 +1,8 @@
 from datetime import datetime
-from typing import Optional
 
 import numpy as np
 
-import flwr as fl
+from flwr.client import ClientApp, NumPyClient, start_client
 from flwr.common import ConfigsRecord, Context
 
 SUBSET_SIZE = 1000
@@ -15,7 +14,7 @@
 
 
 # Define Flower client
-class FlowerClient(fl.client.NumPyClient):
+class FlowerClient(NumPyClient):
     def get_parameters(self, config):
         return model_params
 
@@ -56,12 +55,10 @@ def client_fn(context: Context):
     return FlowerClient().to_client()
 
 
-app = fl.client.ClientApp(
+app = ClientApp(
     client_fn=client_fn,
 )
 
 if __name__ == "__main__":
     # Start Flower client
-    fl.client.start_client(
-        server_address="127.0.0.1:8080", client=FlowerClient().to_client()
-    )
+    start_client(server_address="127.0.0.1:8080", client=FlowerClient().to_client())

e2e/docker/client.py

@@ -1,6 +1,5 @@
 import warnings
 from collections import OrderedDict
-from typing import Optional
 
 import torch
 import torch.nn as nn

e2e/framework-fastai/client.py

@@ -1,12 +1,11 @@
 import warnings
 from collections import OrderedDict
-from typing import Optional
 
 import numpy as np
 import torch
 from fastai.vision.all import *
 
-import flwr as fl
+from flwr.client import ClientApp, NumPyClient, start_client
 from flwr.common import Context
 
 warnings.filterwarnings("ignore", category=UserWarning)
@@ -31,7 +30,7 @@
 
 
 # Define Flower client
-class FlowerClient(fl.client.NumPyClient):
+class FlowerClient(NumPyClient):
     def get_parameters(self, config):
         return [val.cpu().numpy() for _, val in learn.model.state_dict().items()]
 
@@ -55,14 +54,14 @@ def client_fn(context: Context):
     return FlowerClient().to_client()
 
 
-app = fl.client.ClientApp(
+app = ClientApp(
     client_fn=client_fn,
 )
 
 
 if __name__ == "__main__":
     # Start Flower client
-    fl.client.start_client(
+    start_client(
         server_address="127.0.0.1:8080",
         client=FlowerClient().to_client(),
     )

e2e/framework-jax/client.py

@@ -1,12 +1,12 @@
 """Flower client example using JAX for linear regression."""
 
-from typing import Dict, List, Optional, Tuple
+from typing import Dict, List, Tuple
 
 import jax
 import jax_training
 import numpy as np
 
-import flwr as fl
+from flwr.client import ClientApp, NumPyClient, start_client
 from flwr.common import Context
 
 # Load data and determine model shape
@@ -15,7 +15,7 @@
 model_shape = train_x.shape[1:]
 
 
-class FlowerClient(fl.client.NumPyClient):
+class FlowerClient(NumPyClient):
     def __init__(self):
         self.params = jax_training.load_model(model_shape)
 
@@ -53,12 +53,10 @@ def client_fn(context: Context):
     return FlowerClient().to_client()
 
 
-app = fl.client.ClientApp(
+app = ClientApp(
     client_fn=client_fn,
 )
 
 if __name__ == "__main__":
     # Start Flower client
-    fl.client.start_client(
-        server_address="127.0.0.1:8080", client=FlowerClient().to_client()
-    )
+    start_client(server_address="127.0.0.1:8080", client=FlowerClient().to_client())

e2e/framework-opacus/client.py

@@ -1,6 +1,5 @@
 import math
 from collections import OrderedDict
-from typing import Optional
 
 import torch
 import torch.nn as nn
@@ -10,7 +9,7 @@
 from torch.utils.data import DataLoader
 from torchvision.datasets import CIFAR10
 
-import flwr as fl
+from flwr.client import ClientApp, NumPyClient, start_client
 from flwr.common import Context
 
 # Define parameters.
@@ -97,7 +96,7 @@ def load_data():
 
 
 # Define Flower client.
-class FlowerClient(fl.client.NumPyClient):
+class FlowerClient(NumPyClient):
     def __init__(self, model) -> None:
         super().__init__()
         # Create a privacy engine which will add DP and keep track of the privacy budget.
@@ -146,11 +145,11 @@ def client_fn(context: Context):
     return FlowerClient(model).to_client()
 
 
-app = fl.client.ClientApp(
+app = ClientApp(
     client_fn=client_fn,
 )
 
 if __name__ == "__main__":
-    fl.client.start_client(
+    start_client(
         server_address="127.0.0.1:8080", client=FlowerClient(model).to_client()
     )

e2e/framework-pandas/client.py

@@ -1,9 +1,9 @@
-from typing import Dict, List, Optional, Tuple
+from typing import Dict, List, Tuple
 
 import numpy as np
 import pandas as pd
 
-import flwr as fl
+from flwr.client import ClientApp, NumPyClient, start_client
 from flwr.common import Context
 
 df = pd.read_csv("./data/client.csv")
@@ -17,7 +17,7 @@ def compute_hist(df: pd.DataFrame, col_name: str) -> np.ndarray:
 
 
 # Define Flower client
-class FlowerClient(fl.client.NumPyClient):
+class FlowerClient(NumPyClient):
     def fit(
         self, parameters: List[np.ndarray], config: Dict[str, str]
     ) -> Tuple[List[np.ndarray], int, Dict]:
@@ -37,13 +37,13 @@ def client_fn(context: Context):
     return FlowerClient().to_client()
 
 
-app = fl.client.ClientApp(
+app = ClientApp(
     client_fn=client_fn,
 )
 
 if __name__ == "__main__":
     # Start Flower client
-    fl.client.start_client(
+    start_client(
         server_address="127.0.0.1:8080",
         client=FlowerClient().to_client(),
     )

e2e/framework-pytorch-lightning/client.py

@@ -1,15 +1,14 @@
 from collections import OrderedDict
-from typing import Optional
 
 import mnist
 import pytorch_lightning as pl
 import torch
 
-import flwr as fl
+from flwr.client import ClientApp, NumPyClient, start_client
 from flwr.common import Context
 
 
-class FlowerClient(fl.client.NumPyClient):
+class FlowerClient(NumPyClient):
     def __init__(self, model, train_loader, val_loader, test_loader):
         self.model = model
         self.train_loader = train_loader
@@ -61,7 +60,7 @@ def client_fn(context: Context):
     return FlowerClient(model, train_loader, val_loader, test_loader).to_client()
 
 
-app = fl.client.ClientApp(
+app = ClientApp(
     client_fn=client_fn,
 )
 
@@ -73,7 +72,7 @@ def main() -> None:
 
     # Flower client
     client = FlowerClient(model, train_loader, val_loader, test_loader).to_client()
-    fl.client.start_client(server_address="127.0.0.1:8080", client=client)
+    start_client(server_address="127.0.0.1:8080", client=client)
 
 
 if __name__ == "__main__":

e2e/framework-pytorch/client.py

@@ -1,7 +1,6 @@
 import warnings
 from collections import OrderedDict
 from datetime import datetime
-from typing import Optional
 
 import torch
 import torch.nn as nn
@@ -11,7 +10,7 @@
 from torchvision.transforms import Compose, Normalize, ToTensor
 from tqdm import tqdm
 
-import flwr as fl
+from flwr.client import ClientApp, NumPyClient, start_client
 from flwr.common import ConfigsRecord, Context
 
 # #############################################################################
@@ -90,7 +89,7 @@ def load_data():
 
 
 # Define Flower client
-class FlowerClient(fl.client.NumPyClient):
+class FlowerClient(NumPyClient):
     def get_parameters(self, config):
         return [val.cpu().numpy() for _, val in net.state_dict().items()]
 
@@ -141,14 +140,14 @@ def client_fn(context: Context):
     return FlowerClient().to_client()
 
 
-app = fl.client.ClientApp(
+app = ClientApp(
     client_fn=client_fn,
 )
 
 
 if __name__ == "__main__":
     # Start Flower client
-    fl.client.start_client(
+    start_client(
         server_address="127.0.0.1:8080",
         client=FlowerClient().to_client(),
     )

e2e/framework-scikit-learn/client.py

@@ -6,7 +6,7 @@
 from sklearn.linear_model import LogisticRegression
 from sklearn.metrics import log_loss
 
-import flwr as fl
+from flwr.client import ClientApp, NumPyClient, start_client
 from flwr.common import Context
 
 # Load MNIST dataset from https://www.openml.org/d/554
@@ -28,7 +28,7 @@
 
 
 # Define Flower client
-class FlowerClient(fl.client.NumPyClient):
+class FlowerClient(NumPyClient):
     def get_parameters(self, config):  # type: ignore
         return utils.get_model_parameters(model)
 
@@ -51,12 +51,10 @@ def client_fn(context: Context):
     return FlowerClient().to_client()
 
 
-app = fl.client.ClientApp(
+app = ClientApp(
     client_fn=client_fn,
 )
 
 if __name__ == "__main__":
     # Start Flower client
-    fl.client.start_client(
-        server_address="0.0.0.0:8080", client=FlowerClient().to_client()
-    )
+    start_client(server_address="0.0.0.0:8080", client=FlowerClient().to_client())