Rename QffedAvg to QFedAvg

doc/source/changelog.rst

@@ -14,6 +14,10 @@ Incompatible changes:
 
   Prior behaviour was to perform a final round of distributed evaluation on all connected clients, which is often not required (e.g., when using server-side evaluation). The prior behaviour can be enabled by passing :code:`force_final_distributed_eval=True` to :code:`start_server`.
 
+* **Renamed q-FedAvg strategy** (`#802 <https://github.com/adap/flower/pull/802>`_)
+
+  The strategy named :code:`QffedAvg` was renamed to `QFedAvg` to better reflect the notation given in the original paper (q-FFL is the optimization objective, q-FedAvg is the proposed solver). Note the the original (now deprecated) :code:`QffedAvg` class is still available for compatibility reasons (it will be removed in a future release).
+
 
 v0.16.0 (2021-05-11)
 --------------------

src/py/flwr/server/strategy/__init__.py

@@ -22,7 +22,8 @@
 from .fedavg import FedAvg as FedAvg
 from .fedfs_v0 import FedFSv0 as FedFSv0
 from .fedfs_v1 import FedFSv1 as FedFSv1
-from .qffedavg import QffedAvg as QffedAvg
+from .qfedavg import QFedAvg as QFedAvg
+from .qfedavg import QffedAvg as QffedAvg  # Deprecated
 from .strategy import Strategy as Strategy
 
 __all__ = [
@@ -33,6 +34,7 @@
     "FedAvg",
     "FedFSv0",
     "FedFSv1",
-    "QffedAvg",
+    "QFedAvg",
+    "QffedAvg",  # Deprecated
     "Strategy",
 ]

src/py/flwr/server/strategy/qffedavg.py → src/py/flwr/server/strategy/qfedavg.py

@@ -40,8 +40,8 @@
 from .fedavg import FedAvg
 
 
-class QffedAvg(FedAvg):
-    """Configurable QffedAvg strategy implementation."""
+class QFedAvg(FedAvg):
+    """Configurable QFedAvg strategy implementation."""
 
     # pylint: disable=too-many-arguments,too-many-instance-attributes
     def __init__(
@@ -236,3 +236,54 @@ def aggregate_evaluate(
             ),
             {},
         )
+
+
+DEPRECATION_WARNING_QFFEDAVG = """
+DEPRECATION WARNING: Deprecated strategy
+
+    QffedAvg
+
+use
+
+    QFedAvg
+
+instead.
+"""
+
+
+class QffedAvg(QFedAvg):
+    """Configurable QFedAvg strategy implementation."""
+
+    # pylint: disable=too-many-arguments,too-many-instance-attributes
+    def __init__(
+        self,
+        q_param: float = 0.2,
+        qffl_learning_rate: float = 0.1,
+        fraction_fit: float = 0.1,
+        fraction_eval: float = 0.1,
+        min_fit_clients: int = 1,
+        min_eval_clients: int = 1,
+        min_available_clients: int = 1,
+        eval_fn: Optional[
+            Callable[[Weights], Optional[Tuple[float, Dict[str, Scalar]]]]
+        ] = None,
+        on_fit_config_fn: Optional[Callable[[int], Dict[str, Scalar]]] = None,
+        on_evaluate_config_fn: Optional[Callable[[int], Dict[str, Scalar]]] = None,
+        accept_failures: bool = True,
+        initial_parameters: Optional[Parameters] = None,
+    ) -> None:
+        super().__init__(
+            q_param=q_param,
+            qffl_learning_rate=qffl_learning_rate,
+            fraction_fit=fraction_fit,
+            fraction_eval=fraction_eval,
+            min_fit_clients=min_fit_clients,
+            min_eval_clients=min_eval_clients,
+            min_available_clients=min_available_clients,
+            eval_fn=eval_fn,
+            on_fit_config_fn=on_fit_config_fn,
+            on_evaluate_config_fn=on_evaluate_config_fn,
+            accept_failures=accept_failures,
+            initial_parameters=initial_parameters,
+        )
+        print(DEPRECATION_WARNING_QFFEDAVG)

src/py/flwr_experimental/baseline/tf_fashion_mnist/server.py

@@ -149,7 +149,7 @@ def main() -> None:
         )
 
     if server_setting.strategy == "qffedavg":
-        strategy = fl.server.strategy.QffedAvg(
+        strategy = fl.server.strategy.QFedAvg(
             q_param=0.2,
             qffl_learning_rate=0.1,
             fraction_fit=server_setting.sample_fraction,

src/py/flwr_experimental/baseline/tf_hotkey/server.py

@@ -128,7 +128,7 @@ def main() -> None:
         )
 
     if server_setting.strategy == "qffedavg":
-        strategy = fl.server.strategy.QffedAvg(
+        strategy = fl.server.strategy.QFedAvg(
             q_param=0.2,
             qffl_learning_rate=0.1,
             fraction_fit=server_setting.sample_fraction,