From 136114bfe9077407882edac471307064f5615d45 Mon Sep 17 00:00:00 2001 From: David Emerson <43939939+emersodb@users.noreply.github.com> Date: Thu, 5 Jun 2025 10:56:24 -0400 Subject: [PATCH 1/4] Creating FedBN client and adding test --- examples/fedbn_example/client.py | 10 +-- fl4health/clients/fedbn_client.py | 27 ++++++++ fl4health/strategies/fedpm.py | 2 +- tests/clients/test_fedbn_client.py | 66 +++++++++++++++++++ tests/mixins/personalized/test_ditto.py | 4 +- tests/mixins/personalized/test_utils.py | 4 +- .../mixins/test_adaptive_drift_constrained.py | 4 +- 7 files changed, 102 insertions(+), 15 deletions(-) create mode 100644 fl4health/clients/fedbn_client.py create mode 100644 tests/clients/test_fedbn_client.py diff --git a/examples/fedbn_example/client.py b/examples/fedbn_example/client.py index 464faba98..28c7c2c67 100644 --- a/examples/fedbn_example/client.py +++ b/examples/fedbn_example/client.py @@ -13,7 +13,7 @@ from torch.utils.data import DataLoader from examples.models.cnn_model import MnistNetWithBnAndFrozen, SkinCancerNet -from fl4health.clients.basic_client import BasicClient +from fl4health.clients.fedbn_client import FedBnClient from fl4health.datasets.skin_cancer.load_data import load_skin_cancer_data from fl4health.metrics import Accuracy from fl4health.metrics.base_metrics import Metric @@ -24,7 +24,7 @@ from fl4health.utils.sampler import DirichletLabelBasedSampler -class MnistFedBNClient(BasicClient): +class MnistFedBnClient(FedBnClient): def get_data_loaders(self, config: Config) -> tuple[DataLoader, DataLoader]: batch_size = narrow_dict_type(config, "batch_size", int) sampler = DirichletLabelBasedSampler(list(range(10)), sample_percentage=0.75, beta=1) @@ -45,7 +45,7 @@ def get_parameter_exchanger(self, config: Config) -> ParameterExchanger: return LayerExchangerWithExclusions(self.model, {nn.BatchNorm2d}) -class SkinCancerFedBNClient(BasicClient): +class SkinCancerFedBNClient(FedBnClient): def __init__(self, data_path: Path, metrics: Sequence[Metric], device: torch.device, dataset_name: str): super().__init__(data_path, metrics, device) self.dataset_name = dataset_name @@ -95,9 +95,9 @@ def get_parameter_exchanger(self, config: Config) -> ParameterExchanger: log(INFO, f"Server Address: {args.server_address}") if args.dataset_name in ["Barcelona", "Rosendahl", "Vienna", "UFES", "Canada"]: - client: BasicClient = SkinCancerFedBNClient(data_path, [Accuracy()], device, args.dataset_name) + client: FedBnClient = SkinCancerFedBNClient(data_path, [Accuracy()], device, args.dataset_name) elif args.dataset_name == "mnist": - client = MnistFedBNClient(data_path, [Accuracy()], device) + client = MnistFedBnClient(data_path, [Accuracy()], device) else: raise ValueError( "Unsupported dataset name. Please choose from 'Barcelona', 'Rosendahl', \ diff --git a/fl4health/clients/fedbn_client.py b/fl4health/clients/fedbn_client.py new file mode 100644 index 000000000..562c8e82b --- /dev/null +++ b/fl4health/clients/fedbn_client.py @@ -0,0 +1,27 @@ +from flwr.common.typing import Config + +from fl4health.clients.basic_client import BasicClient +from fl4health.parameter_exchange.layer_exchanger import LayerExchangerWithExclusions + + +class FedBnClient(BasicClient): + """ + This class serves as a sparse interface for clients aiming to leverage the FedBN method + (https://arxiv.org/abs/2102.07623) or any other approach that excludes specific types of model layers during + parameter exchange. This class simply ensures that the user has overridden the `get_parameter_exchanger` properly. + + For example, in FedBN, batch normalization layers are excluded from exchange with the server + but all other layers flow through and are aggregated via whatever strategy the server is implementing. An example + of this where one wants to exclude 2D batch normalization layers during exchange is + `LayerExchangerWithExclusions(self.model, {nn.BatchNorm2d})`, where the model is provided so that the exchanger + can identify the appropriate layers to leave out. + """ + + def setup_client(self, config: Config) -> None: + super().setup_client(config=config) + assert isinstance(self.parameter_exchanger, LayerExchangerWithExclusions), ( + "For FedBnClients the parameter exchanger must be of type LayerExchangerWithExclusions " + f"but got {type(self.parameter_exchanger)}. If you haven't already, override the get_parameter_exchanger " + "function in your class." + ) + return super().setup_client(config) diff --git a/fl4health/strategies/fedpm.py b/fl4health/strategies/fedpm.py index 889e38601..32bb6d35e 100644 --- a/fl4health/strategies/fedpm.py +++ b/fl4health/strategies/fedpm.py @@ -110,7 +110,7 @@ def aggregate_bayesian(self, results: list[tuple[NDArrays, int]]) -> dict[str, N In this case, the updates performed are: - .. code:: python + .. code-block:: python alpha_new = alpha + M diff --git a/tests/clients/test_fedbn_client.py b/tests/clients/test_fedbn_client.py new file mode 100644 index 000000000..7f02660a2 --- /dev/null +++ b/tests/clients/test_fedbn_client.py @@ -0,0 +1,66 @@ +from pathlib import Path + +import pytest +import torch +import torch.nn as nn +from flwr.common.typing import Config +from torch.nn.modules.loss import _Loss +from torch.optim import Optimizer +from torch.utils.data import DataLoader +from torch.utils.data.dataset import TensorDataset + +from fl4health.clients.fedbn_client import FedBnClient +from fl4health.metrics import Accuracy +from fl4health.parameter_exchange.full_exchanger import FullParameterExchanger +from fl4health.parameter_exchange.layer_exchanger import LayerExchangerWithExclusions +from fl4health.parameter_exchange.parameter_exchanger_base import ParameterExchanger +from tests.test_utils.models_for_test import ToyConvNet + + +class GoodClientForTest(FedBnClient): + def get_parameter_exchanger(self, config: Config) -> ParameterExchanger: + return LayerExchangerWithExclusions(ToyConvNet(include_bn=True), {nn.BatchNorm1d}) + + def get_data_loaders(self, config: Config) -> tuple[DataLoader, DataLoader]: + train_loader = DataLoader(TensorDataset(torch.ones((4, 4)), torch.ones((4)))) + val_loader = DataLoader(TensorDataset(torch.ones((4, 4)), torch.ones((4)))) + return train_loader, val_loader + + def get_criterion(self, config: Config) -> _Loss: + return torch.nn.CrossEntropyLoss() + + def get_optimizer(self, config: Config) -> Optimizer: + return torch.optim.SGD(self.model.parameters(), lr=0.001, momentum=0.9) + + def get_model(self, config: Config) -> nn.Module: + return ToyConvNet().to(self.device) + + +class BadClientForTest(FedBnClient): + def get_parameter_exchanger(self, config: Config) -> ParameterExchanger: + return FullParameterExchanger() + + def get_data_loaders(self, config: Config) -> tuple[DataLoader, DataLoader]: + train_loader = DataLoader(TensorDataset(torch.ones((4, 4)), torch.ones((4)))) + val_loader = DataLoader(TensorDataset(torch.ones((4, 4)), torch.ones((4)))) + return train_loader, val_loader + + def get_criterion(self, config: Config) -> _Loss: + return torch.nn.CrossEntropyLoss() + + def get_optimizer(self, config: Config) -> Optimizer: + return torch.optim.SGD(self.model.parameters(), lr=0.001, momentum=0.9) + + def get_model(self, config: Config) -> nn.Module: + return ToyConvNet().to(self.device) + + +def test_instance_level_client_with_changes() -> None: + # Creating client in the right way shouldn't throw an error + good_client = GoodClientForTest(data_path=Path(""), metrics=[Accuracy()], device=torch.device("cpu")) + good_client.setup_client({}) + # We should throw an assertion error here because we're trying to use a FedBnClient with the wrong kind of + # parameter exchanger. + with pytest.raises(AssertionError): + bad_client = BadClientForTest(data_path=Path(""), metrics=[Accuracy()], device=torch.device("cpu")) + bad_client.setup_client({}) diff --git a/tests/mixins/personalized/test_ditto.py b/tests/mixins/personalized/test_ditto.py index e4b464ca9..5e1f082d8 100644 --- a/tests/mixins/personalized/test_ditto.py +++ b/tests/mixins/personalized/test_ditto.py @@ -24,9 +24,7 @@ make_it_personal, ) from fl4health.parameter_exchange.packing_exchanger import FullParameterExchangerWithPacking -from fl4health.parameter_exchange.parameter_packer import ( - ParameterPackerAdaptiveConstraint, -) +from fl4health.parameter_exchange.parameter_packer import ParameterPackerAdaptiveConstraint from fl4health.utils.losses import TrainingLosses from fl4health.utils.typing import TorchFeatureType, TorchInputType, TorchPredType diff --git a/tests/mixins/personalized/test_utils.py b/tests/mixins/personalized/test_utils.py index 9b7ec2cf6..938a914d9 100644 --- a/tests/mixins/personalized/test_utils.py +++ b/tests/mixins/personalized/test_utils.py @@ -13,9 +13,7 @@ from fl4health.metrics import Accuracy from fl4health.mixins.personalized.utils import ensure_protocol_compliance from fl4health.parameter_exchange.packing_exchanger import FullParameterExchangerWithPacking -from fl4health.parameter_exchange.parameter_packer import ( - ParameterPackerAdaptiveConstraint, -) +from fl4health.parameter_exchange.parameter_packer import ParameterPackerAdaptiveConstraint def test_ensure_protocol_compliance_does_not_raise() -> None: diff --git a/tests/mixins/test_adaptive_drift_constrained.py b/tests/mixins/test_adaptive_drift_constrained.py index 11ae5d4c6..b00792994 100644 --- a/tests/mixins/test_adaptive_drift_constrained.py +++ b/tests/mixins/test_adaptive_drift_constrained.py @@ -22,9 +22,7 @@ ) from fl4health.mixins.core_protocols import BasicClientProtocol from fl4health.parameter_exchange.packing_exchanger import FullParameterExchangerWithPacking -from fl4health.parameter_exchange.parameter_packer import ( - ParameterPackerAdaptiveConstraint, -) +from fl4health.parameter_exchange.parameter_packer import ParameterPackerAdaptiveConstraint class _TestBasicClient(BasicClient): From dac808b683aafdbb072c975e1bd6042a04827c27 Mon Sep 17 00:00:00 2001 From: David Emerson <43939939+emersodb@users.noreply.github.com> Date: Thu, 5 Jun 2025 19:23:09 -0400 Subject: [PATCH 2/4] Updating the poetry lock to address vulnerability --- poetry.lock | 2303 ++++++++++++++++++++++++++------------------------- 1 file changed, 1172 insertions(+), 1131 deletions(-) diff --git a/poetry.lock b/poetry.lock index 6d44d5f73..47eb11fd6 100644 --- a/poetry.lock +++ b/poetry.lock @@ -13,13 +13,13 @@ files = [ [[package]] name = "accelerate" -version = "1.6.0" +version = "1.7.0" description = "Accelerate" optional = false python-versions = ">=3.9.0" files = [ - {file = "accelerate-1.6.0-py3-none-any.whl", hash = "sha256:1aee717d3d3735ad6d09710a7c26990ee4652b79b4e93df46551551b5227c2aa"}, - {file = "accelerate-1.6.0.tar.gz", hash = "sha256:28c1ef1846e690944f98b68dc7b8bb6c51d032d45e85dcbb3adb0c8b99dffb32"}, + {file = "accelerate-1.7.0-py3-none-any.whl", hash = "sha256:cf57165cca28769c6cf2650812371c81b18e05743dfa3c748524b1bb4f2b272f"}, + {file = "accelerate-1.7.0.tar.gz", hash = "sha256:e8a2a5503d6237b9eee73cc8d36cf543f9c2d8dd2c6713450b322f5e6d53a610"}, ] [package.dependencies] @@ -38,6 +38,7 @@ quality = ["black (>=23.1,<24.0)", "hf-doc-builder (>=0.3.0)", "ruff (>=0.11.2,< rich = ["rich"] sagemaker = ["sagemaker"] test-dev = 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[[package]] name = "types-requests" -version = "2.32.0.20250328" +version = "2.32.0.20250602" description = "Typing stubs for requests" optional = false python-versions = ">=3.9" files = [ - {file = "types_requests-2.32.0.20250328-py3-none-any.whl", hash = "sha256:72ff80f84b15eb3aa7a8e2625fffb6a93f2ad5a0c20215fc1dcfa61117bcb2a2"}, - {file = "types_requests-2.32.0.20250328.tar.gz", hash = "sha256:c9e67228ea103bd811c96984fac36ed2ae8da87a36a633964a21f199d60baf32"}, + {file = "types_requests-2.32.0.20250602-py3-none-any.whl", hash = "sha256:f4f335f87779b47ce10b8b8597b409130299f6971ead27fead4fe7ba6ea3e726"}, + {file = "types_requests-2.32.0.20250602.tar.gz", hash = "sha256:ee603aeefec42051195ae62ca7667cd909a2f8128fdf8aad9e8a5219ecfab3bf"}, ] [package.dependencies] @@ -9759,13 +9799,13 @@ types-docutils = "*" [[package]] name = "types-six" -version = "1.17.0.20250403" +version = "1.17.0.20250515" description = "Typing stubs for six" optional = false python-versions = ">=3.9" files = [ - 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hash = "sha256:16246631db62bdfbf069b0645177d6e8a77ba950cfedbfd093acef9444e4d885"}, + {file = "uvicorn-0.34.3.tar.gz", hash = "sha256:35919a9a979d7a59334b6b10e05d77c1d0d574c50e0fc98b8b1a0f165708b55a"}, ] [package.dependencies] @@ -9877,7 +9917,7 @@ h11 = ">=0.8" typing-extensions = {version = ">=4.0", markers = "python_version < \"3.11\""} [package.extras] -standard = ["colorama (>=0.4)", "httptools (>=0.6.3)", "python-dotenv (>=0.13)", "pyyaml (>=5.1)", "uvloop (>=0.14.0,!=0.15.0,!=0.15.1)", "watchfiles (>=0.13)", "websockets (>=10.4)"] +standard = ["colorama (>=0.4)", "httptools (>=0.6.3)", "python-dotenv (>=0.13)", "pyyaml (>=5.1)", "uvloop (>=0.15.1)", "watchfiles (>=0.13)", "websockets (>=10.4)"] [[package]] name = "virtualenv" @@ -10620,13 +10660,13 @@ propcache = ">=0.2.1" [[package]] name = "zipp" -version = "3.21.0" +version = "3.22.0" description = "Backport of pathlib-compatible object wrapper for zip files" optional = false python-versions = ">=3.9" files = [ - {file = 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"jaraco.itertools", "jaraco.test", "more_itertools", "pytest (>=6,!=8.1.*)", "pytest-ignore-flaky"] type = ["pytest-mypy"] [metadata] lock-version = "2.0" python-versions = ">=3.10.0,<3.11" -content-hash = "bb31dd7ed4c81ea8f2a20822535b8ca18e1bdeb6eb349b0637da9dc9eb1f99a7" +content-hash = "141759837c136d298f317941aed09d28d1e371625ea4c1dbf6616bccb4d720e3" diff --git a/pyproject.toml b/pyproject.toml index e24db8acd..1ad733c76 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -34,6 +34,7 @@ acvl_utils = "0.2" # Pin as it was causing an issue with nnunet (ModuleNotFoundE scikit-learn = "1.5.0" # Pin as it was causing issues with nnunet peft = "^0.14.0" jupyter-core = "^5.8.1" +fastapi = "^0.115.12" # Problematic grpcio versions cause issues, should be fixed in next flwr update # See https://github.com/adap/flower/pull/3853