Merge branch 'main' into intro-abc-conn

.github/workflows/e2e.yml

@@ -150,9 +150,6 @@ jobs:
 
           - directory: e2e-pytorch-lightning
             e2e: e2e_pytorch_lightning
-            dataset: |
-              from torchvision.datasets import MNIST
-              MNIST('./data', download=True)
 
           - directory: e2e-scikit-learn
             e2e: e2e_scikit_learn

baselines/dasha/pyproject.toml

@@ -40,7 +40,7 @@ classifiers = [
 python = ">=3.10.0, <3.11.0"  # don't change this
 flwr = { extras = ["simulation"], version = "1.5.0" }
 hydra-core = "1.3.2" # don't change this
-scikit-learn = "1.3.0"
+scikit-learn = "1.5.0"
 matplotlib = "3.7.1"
 # Installing Torch. TODO: Fix and install the relevant version of Torch based on the current system.
 torch = [{ url = "https://download.pytorch.org/whl/cu118/torch-2.0.0%2Bcu118-cp310-cp310-linux_x86_64.whl", markers="sys_platform == 'linux'"},
@@ -59,7 +59,7 @@ pytest = "==6.2.4"
 pytest-watch = "==4.2.0"
 types-requests = "==2.27.7"
 py-spy = "==0.3.14"
-ruff = "==0.0.272"
+ruff = "==0.4.5"
 virtualenv = "==20.21.0"
 
 [tool.isort]

baselines/depthfl/depthfl/client.py

@@ -123,7 +123,7 @@ def gen_client_fn(  # pylint: disable=too-many-arguments
     learning_rate: float,
     learning_rate_decay: float,
     models: List[DictConfig],
-) -> Callable[[str], FlowerClient]:
+) -> Callable[[str], fl.client.Client]:
     """Generate the client function that creates the Flower Clients.
 
     Parameters
@@ -150,7 +150,7 @@ def gen_client_fn(  # pylint: disable=too-many-arguments
         client function that creates Flower Clients
     """
 
-    def client_fn(cid: str) -> FlowerClient:
+    def client_fn(cid: str) -> fl.client.Client:
         """Create a Flower client representing a single organization."""
         # Load model
         device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
@@ -176,6 +176,6 @@ def client_fn(cid: str) -> FlowerClient:
             learning_rate_decay,
             prev_grads,
             int(cid),
-        )
+        ).to_client()
 
     return client_fn

baselines/depthfl/depthfl/server.py

@@ -180,6 +180,7 @@ def fit_round(
             client_instructions=client_instructions,
             max_workers=self.max_workers,
             timeout=timeout,
+            group_id=server_round,
         )
         log(
             DEBUG,

baselines/depthfl/pyproject.toml

@@ -22,10 +22,7 @@ classifiers = [
     "Programming Language :: Python",
     "Programming Language :: Python :: 3",
     "Programming Language :: Python :: 3 :: Only",
-    "Programming Language :: Python :: 3.8",
-    "Programming Language :: Python :: 3.9",
     "Programming Language :: Python :: 3.10",
-    "Programming Language :: Python :: 3.11",
     "Programming Language :: Python :: Implementation :: CPython",
     "Topic :: Scientific/Engineering",
     "Topic :: Scientific/Engineering :: Artificial Intelligence",
@@ -38,7 +35,7 @@ classifiers = [
 
 [tool.poetry.dependencies]
 python = ">=3.10.0, <3.11.0"
-flwr = { extras = ["simulation"], version = "1.5.0" }
+flwr = { extras = ["simulation"], version = "1.9.0" }
 hydra-core = "1.3.2" # don't change this
 matplotlib = "3.7.1"
 torch = { url = "https://download.pytorch.org/whl/cu116/torch-1.13.1%2Bcu116-cp310-cp310-linux_x86_64.whl" }
@@ -53,9 +50,8 @@ pylint = "==2.8.2"
 flake8 = "==3.9.2"
 pytest = "==6.2.4"
 pytest-watch = "==4.2.0"
-ruff = "==0.0.272"
+ruff = "==0.4.5"
 types-requests = "==2.27.7"
-virtualenv = "==20.21.0"
 
 [tool.isort]
 line_length = 88
@@ -108,11 +104,8 @@ wrap-summaries = 88
 wrap-descriptions = 88
 
 [tool.ruff]
-target-version = "py38"
+target-version = "py39"
 line-length = 88
-select = ["D", "E", "F", "W", "B", "ISC", "C4"]
-fixable = ["D", "E", "F", "W", "B", "ISC", "C4"]
-ignore = ["B024", "B027"]
 exclude = [
     ".bzr",
     ".direnv",
@@ -137,5 +130,10 @@ exclude = [
     "proto",
 ]
 
+[tool.ruff.lint]
+select = ["D", "E", "F", "W", "B", "ISC", "C4"]
+fixable = ["D", "E", "F", "W", "B", "ISC", "C4"]
+ignore = ["B024", "B027"]
+
 [tool.ruff.pydocstyle]
 convention = "numpy"

baselines/fedmeta/pyproject.toml

@@ -41,7 +41,7 @@ python = ">=3.10.0, <3.11.0"
 flwr = { extras = ["simulation"], version = "1.5.0" }
 hydra-core = "1.3.2" # don't change this
 matplotlib = "3.7.1"
-scikit-learn = "1.3.1"
+scikit-learn = "1.5.0"
 torch = { url = "https://download.pytorch.org/whl/cu117/torch-2.0.1%2Bcu117-cp310-cp310-linux_x86_64.whl" }
 torchvision = { url = "https://download.pytorch.org/whl/cu117/torchvision-0.15.2%2Bcu117-cp310-cp310-linux_x86_64.whl" }
 

baselines/fednova/fednova/client.py

@@ -120,10 +120,10 @@ def gen_clients_fednova(  # pylint: disable=too-many-arguments
     data_sizes: List,
     model: DictConfig,
     exp_config: DictConfig,
-) -> Callable[[str], FedNovaClient]:
+) -> Callable[[str], fl.client.Client]:
     """Return a generator function to create a FedNova client."""
 
-    def client_fn(cid: str) -> FedNovaClient:
+    def client_fn(cid: str) -> fl.client.Client:
         """Create a Flower client representing a single organization."""
         # Load model
         device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
@@ -144,6 +144,6 @@ def client_fn(cid: str) -> FedNovaClient:
             num_epochs,
             client_dataset_ratio,
             exp_config,
-        )
+        ).to_client()
 
     return client_fn

baselines/fednova/pyproject.toml

@@ -22,10 +22,7 @@ classifiers = [
     "Programming Language :: Python",
     "Programming Language :: Python :: 3",
     "Programming Language :: Python :: 3 :: Only",
-    "Programming Language :: Python :: 3.8",
-    "Programming Language :: Python :: 3.9",
     "Programming Language :: Python :: 3.10",
-    "Programming Language :: Python :: 3.11",
     "Programming Language :: Python :: Implementation :: CPython",
     "Topic :: Scientific/Engineering",
     "Topic :: Scientific/Engineering :: Artificial Intelligence",
@@ -39,11 +36,11 @@ classifiers = [
 [tool.poetry.dependencies]
 # tested with python == 3.10.11
 python = ">=3.10.0, <3.11.0"
-flwr = { extras = ["simulation"], version = "1.5.0" }
+flwr = { extras = ["simulation"], version = "1.9.0" }
 hydra-core = "1.3.2" # don't change this
 torch = { url = "https://download.pytorch.org/whl/cu117/torch-2.0.1%2Bcu117-cp310-cp310-linux_x86_64.whl" }
 torchvision = { url = "https://download.pytorch.org/whl/cu117/torchvision-0.15.2%2Bcu117-cp310-cp310-linux_x86_64.whl" }
-numpy = "1.21.6"
+numpy = "1.22.0"
 matplotlib = "3.5.3"
 pandas = "1.3.5"
 
@@ -56,9 +53,8 @@ pylint = "==2.8.2"
 flake8 = "==3.9.2"
 pytest = "==6.2.4"
 pytest-watch = "==4.2.0"
-ruff = "==0.0.272"
+ruff = "==0.4.5"
 types-requests = "==2.27.7"
-virtualenv = "20.21.0"
 
 [tool.isort]
 line_length = 88
@@ -111,11 +107,8 @@ wrap-summaries = 88
 wrap-descriptions = 88
 
 [tool.ruff]
-target-version = "py38"
+target-version = "py39"
 line-length = 88
-select = ["D", "E", "F", "W", "B", "ISC", "C4"]
-fixable = ["D", "E", "F", "W", "B", "ISC", "C4"]
-ignore = ["B024", "B027"]
 exclude = [
     ".bzr",
     ".direnv",
@@ -140,5 +133,10 @@ exclude = [
     "proto",
 ]
 
+[tool.ruff.lint]
+select = ["D", "E", "F", "W", "B", "ISC", "C4"]
+fixable = ["D", "E", "F", "W", "B", "ISC", "C4"]
+ignore = ["B024", "B027"]
+
 [tool.ruff.pydocstyle]
 convention = "numpy"

baselines/fedpara/fedpara/client.py

@@ -167,10 +167,10 @@ def gen_client_fn(
     args: Dict,
     test_loader: Optional[List[DataLoader]] = None,
     state_path: Optional[str] = None,
-) -> Callable[[str], fl.client.NumPyClient]:
+) -> Callable[[str], fl.client.Client]:
     """Return a function which creates a new FlowerClient for a given cid."""
 
-    def client_fn(cid: str) -> fl.client.NumPyClient:
+    def client_fn(cid: str) -> fl.client.Client:
         """Create a new FlowerClient for a given cid."""
         cid_ = int(cid)
         device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
@@ -185,13 +185,13 @@ def client_fn(cid: str) -> fl.client.NumPyClient:
                 state_path=cl_path,
                 algorithm=args["algorithm"].lower(),
                 device=device,
-            )
+            ).to_client()
         return FlowerClient(
             cid=cid_,
             net=instantiate(model).to(device),
             train_loader=train_loaders[cid_],
             num_epochs=num_epochs,
             device=device,
-        )
+        ).to_client()
 
     return client_fn

baselines/fedpara/pyproject.toml

@@ -22,8 +22,6 @@ classifiers = [
     "Programming Language :: Python",
     "Programming Language :: Python :: 3",
     "Programming Language :: Python :: 3 :: Only",
-    "Programming Language :: Python :: 3.8",
-    "Programming Language :: Python :: 3.9",
     "Programming Language :: Python :: 3.10",
     "Programming Language :: Python :: 3.11",
     "Programming Language :: Python :: Implementation :: CPython",
@@ -38,7 +36,7 @@ classifiers = [
 
 [tool.poetry.dependencies]
 python = ">=3.10, <3.12.0"  # don't change this
-flwr = { extras = ["simulation"], version = "1.5.0" }
+flwr = { extras = ["simulation"], version = "1.9.0" }
 hydra-core = "1.3.2" # don't change this
 matplotlib = "^3.7.2"
 tqdm = "^4.66.1"
@@ -54,9 +52,9 @@ pylint = "==2.8.2"
 flake8 = "==3.9.2"
 pytest = "==6.2.4"
 pytest-watch = "==4.2.0"
-ruff = "==0.0.272"
+ruff = "==0.4.5"
 types-requests = "==2.27.7"
-virtualenv = "20.21.0"
+virtualenv = "20.26.6"
 
 [tool.isort]
 line_length = 88
@@ -109,11 +107,8 @@ wrap-summaries = 88
 wrap-descriptions = 88
 
 [tool.ruff]
-target-version = "py38"
+target-version = "py39"
 line-length = 88
-select = ["D", "E", "F", "W", "B", "ISC", "C4"]
-fixable = ["D", "E", "F", "W", "B", "ISC", "C4"]
-ignore = ["B024", "B027"]
 exclude = [
     ".bzr",
     ".direnv",
@@ -138,5 +133,10 @@ exclude = [
     "proto",
 ]
 
+[tool.ruff.lint]
+select = ["D", "E", "F", "W", "B", "ISC", "C4"]
+fixable = ["D", "E", "F", "W", "B", "ISC", "C4"]
+ignore = ["B024", "B027"]
+
 [tool.ruff.pydocstyle]
 convention = "numpy"

baselines/fedper/fedper/client.py

@@ -7,7 +7,7 @@
 
 import numpy as np
 import torch
-from flwr.client import NumPyClient
+from flwr.client import Client, NumPyClient
 from flwr.common import NDArrays, Scalar
 from omegaconf import DictConfig
 from torch.utils.data import DataLoader, Subset, random_split
@@ -239,7 +239,7 @@ def set_parameters(self, parameters: List[np.ndarray], evaluate=False) -> None:
 def get_client_fn_simulation(
     config: DictConfig,
     client_state_save_path: str = "",
-) -> Callable[[str], Union[FedPerClient, BaseClient]]:
+) -> Callable[[str], Client]:
     """Generate the client function that creates the Flower Clients.
 
     Parameters
@@ -251,7 +251,7 @@ def get_client_fn_simulation(
 
     Returns
     -------
-    Tuple[Callable[[str], FlowerClient], DataLoader]
+    Tuple[Callable[[str], Client], DataLoader]
         A tuple containing the client function that creates Flower Clients and
         the DataLoader that will be used for testing
     """
@@ -288,7 +288,7 @@ def get_client_fn_simulation(
         )
         # ------------------------------------------------------------
 
-    def client_fn(cid: str) -> BaseClient:
+    def client_fn(cid: str) -> Client:
         """Create a Flower client representing a single organization."""
         cid_use = int(cid)
         if config.dataset.name.lower() == "flickr":
@@ -343,12 +343,12 @@ def client_fn(cid: str) -> BaseClient:
                 client_essentials=client_essentials,
                 config=config,
                 model_manager_class=manager,
-            )
+            ).to_client()
         return BaseClient(
             data_loaders=client_data_loaders,
             client_essentials=client_essentials,
             config=config,
             model_manager_class=manager,
-        )
+        ).to_client()
 
     return client_fn

baselines/fedper/fedper/utils.py

@@ -9,10 +9,11 @@
 
 import matplotlib.pyplot as plt
 import numpy as np
+from flwr.client import Client
 from flwr.server.history import History
 from omegaconf import DictConfig
 
-from fedper.client import BaseClient, FedPerClient, get_client_fn_simulation
+from fedper.client import get_client_fn_simulation
 from fedper.implemented_models.mobile_model import MobileNet, MobileNetModelSplit
 from fedper.implemented_models.resnet_model import ResNet, ResNetModelSplit
 
@@ -71,7 +72,7 @@ def set_client_state_save_path() -> str:
 
 def get_client_fn(
     config: DictConfig, client_state_save_path: str = ""
-) -> Callable[[str], Union[FedPerClient, BaseClient]]:
+) -> Callable[[str], Client]:
     """Get client function."""
     # Get algorithm
     algorithm = config.algorithm.lower()