refactor(examples) Update package versions

examples/advanced-pytorch/pyproject.toml

@@ -9,9 +9,9 @@ description = "Federated Learning with PyTorch and Flower (Advanced Example)"
 license = "Apache-2.0"
 dependencies = [
     "flwr[simulation]>=1.15.0",
-    "flwr-datasets[vision]>=0.3.0",
-    "torch==2.2.1",
-    "torchvision==0.17.1",
+    "flwr-datasets[vision]>=0.5.0",
+    "torch==2.5.1",
+    "torchvision==0.20.1",
     "wandb==0.17.8",
 ]
 

examples/advanced-tensorflow/pyproject.toml

@@ -9,7 +9,7 @@ description = "Federated Learning with Tensorflow/Keras and Flower (Advanced Exa
 license = "Apache-2.0"
 dependencies = [
     "flwr[simulation]>=1.15.0",
-    "flwr-datasets[vision]>=0.3.0",
+    "flwr-datasets[vision]>=0.5.0",
     "tensorflow-cpu>=2.9.1, != 2.11.1 ; platform_machine == \"x86_64\"",
     "tensorflow-macos>=2.9.1, != 2.11.1 ; sys_platform == \"darwin\" and platform_machine == \"arm64\"",
     "wandb==0.17.8",

examples/custom-metrics/pyproject.toml

@@ -13,10 +13,10 @@ description = "Federated Learning with Flower and Custom Metrics"
 license = "Apache-2.0"
 dependencies = [
     "flwr[simulation]>=1.15.0",
-    "flwr-datasets[vision]>=0.3.0",
-    "scikit-learn>=1.2.2",
-    "tensorflow==2.12.1; sys_platform != 'darwin'",
-    "tensorflow-macos==2.12.0; sys_platform == 'darwin'",
+    "flwr-datasets[vision]>=0.5.0",
+    "scikit-learn>=1.6.0",
+    "tensorflow>=2.12.1; (platform_machine == \"x86_64\" or platform_machine == \"aarch64\")",
+    "tensorflow-macos>=2.12.1; sys_platform == \"darwin\" and platform_machine == \"arm64\"",
 ]
 
 [tool.hatch.build.targets.wheel]

examples/embedded-devices/embeddedexample/task.py

@@ -84,6 +84,8 @@ def train(net, trainloader, valloader, epochs, learning_rate, device):
 
 def test(net, testloader, device):
     """Validate the model on the test set."""
+    net.to(device)  # move model to GPU if available
+    net.eval()
     criterion = torch.nn.CrossEntropyLoss()
     correct, loss = 0, 0.0
     with torch.no_grad():

examples/embedded-devices/pyproject.toml

@@ -8,10 +8,10 @@ version = "1.0.0"
 description = "Federated AI with Embedded Devices using Flower"
 license = "Apache-2.0"
 dependencies = [
-    "flwr>=1.14.0",
-    "flwr-datasets[vision]>=0.3.0",
-    "torch==2.2.1",
-    "torchvision==0.17.1",
+    "flwr>=1.15.0",
+    "flwr-datasets[vision]>=0.5.0",
+    "torch==2.5.1",
+    "torchvision==0.20.1",
 ]
 
 [tool.hatch.build]
@@ -41,5 +41,5 @@ batch-size = 32
 default = "embedded-federation"
 
 [tool.flwr.federations.embedded-federation]
-address = "49.12.200.204:9093"
+address = "127.0.0.1:9093"
 insecure = true

examples/federated-kaplan-meier-fitter/pyproject.toml

@@ -9,7 +9,7 @@ description = "Federated Kaplan Meier Fitter with Flower"
 license = "Apache-2.0"
 dependencies = [
     "flwr[simulation]>=1.15.0",
-    "flwr-datasets>=0.3.0",
+    "flwr-datasets>=0.5.0",
     "numpy>=1.23.2",
     "pandas>=2.0.0",
     "lifelines>=0.28.0",

examples/fl-dp-sa/pyproject.toml

@@ -9,9 +9,9 @@ description = "Central Differential Privacy and Secure Aggregation in Flower"
 license = "Apache-2.0"
 dependencies = [
     "flwr[simulation]>=1.15.0",
-    "flwr-datasets[vision]>=0.3.0",
-    "torch==2.2.1",
-    "torchvision==0.17.1",
+    "flwr-datasets[vision]>=0.5.0",
+    "torch==2.5.1",
+    "torchvision==0.20.1",
 ]
 
 [tool.hatch.build.targets.wheel]

examples/fl-tabular/pyproject.toml

@@ -9,9 +9,9 @@ description = "Adult Census Income Tabular Dataset and Federated Learning in Flo
 license = "Apache-2.0"
 dependencies = [
     "flwr[simulation]>=1.15.0",
-    "flwr-datasets>=0.3.0",
+    "flwr-datasets>=0.5.0",
     "torch==2.5.1",
-    "scikit-learn==1.5.0",
+    "scikit-learn==1.6.1",
 ]
 
 [tool.hatch.build.targets.wheel]

examples/flower-authentication/pyproject.toml

@@ -8,8 +8,8 @@ version = "1.0.0"
 description = "Federated Learning with PyTorch and authenticated Flower "
 license = "Apache-2.0"
 dependencies = [
-    "flwr>=1.14.0",
-    "flwr-datasets[vision]>=0.4.0",
+    "flwr>=1.15.0",
+    "flwr-datasets[vision]>=0.5.0",
     "torch>=2.5.0,<3.0.0",
     "torchvision>=0.20.1,<0.21.0",
 ]

examples/flower-secure-aggregation/pyproject.toml

@@ -9,9 +9,9 @@ description = "Secure Aggregation in Flower"
 license = "Apache-2.0"
 dependencies = [
     "flwr[simulation]>=1.15.0",
-    "flwr-datasets[vision]>=0.3.0",
-    "torch==2.2.1",
-    "torchvision==0.17.1",
+    "flwr-datasets[vision]>=0.5.0",
+    "torch==2.5.1",
+    "torchvision==0.20.1",
 ]
 
 [tool.hatch.build.targets.wheel]

examples/flower-simulation-step-by-step-pytorch/my-awesome-app/pyproject.toml

@@ -8,10 +8,10 @@ version = "1.0.0"
 description = ""
 license = "Apache-2.0"
 dependencies = [
-    "flwr[simulation]>=1.14.0",
-    "flwr-datasets[vision]>=0.4.0",
-    "torch==2.2.1",
-    "torchvision==0.17.1",
+    "flwr[simulation]>=1.15.0",
+    "flwr-datasets[vision]>=0.5.0",
+    "torch==2.5.1",
+    "torchvision==0.20.1",
     "wandb",
 ]
 

examples/flowertune-llm/pyproject.toml

@@ -8,14 +8,15 @@ version = "1.0.0"
 description = "FlowerTune LLM: Federated LLM Fine-tuning with Flower"
 license = "Apache-2.0"
 dependencies = [
-    "flwr[simulation]==1.12.0",
-    "flwr-datasets>=0.3.0",
+    "flwr[simulation]==1.15.0",
+    "flwr-datasets>=0.5.0",
+    "torch==2.3.1",
     "trl==0.8.1",
-    "bitsandbytes==0.43.0",
+    "bitsandbytes==0.45.0",
     "scipy==1.13.0",
     "peft==0.6.2",
     "fschat[model_worker,webui]==0.2.35",
-    "transformers==4.39.3",
+    "transformers==4.47.0",
     "sentencepiece==0.2.0",
     "omegaconf==2.3.0",
     "hf_transfer==0.1.8",

examples/flowertune-vit/pyproject.toml

@@ -8,10 +8,10 @@ version = "1.0.0"
 description = "Federated Finetuning of a Vision Transformer with Flower"
 license = "Apache-2.0"
 dependencies = [
-    "flwr[simulation]==1.12.0",
-    "flwr-datasets[vision]>=0.3.0",
-    "torch==2.2.1",
-    "torchvision==0.17.1",
+    "flwr[simulation]>=1.15.0",
+    "flwr-datasets[vision]>=0.5.0",
+    "torch==2.5.1",
+    "torchvision==0.20.1",
 ]
 
 [tool.hatch.build.targets.wheel]

examples/opacus/pyproject.toml

@@ -9,9 +9,9 @@ description = "Sample-level Differential Privacy with Opacus in Flower"
 
 dependencies = [
     "flwr[simulation]>=1.15.0",
-    "flwr-datasets[vision]>=0.3.0",
-    "torch==2.1.1",
-    "torchvision==0.16.1",
+    "flwr-datasets[vision]>=0.5.0",
+    "torch==2.5.1",
+    "torchvision==0.20.1",
     "opacus==v1.4.1",
 ]
 

examples/pytorch-federated-variational-autoencoder/pyproject.toml

@@ -9,9 +9,9 @@ description = "Federated Variational Autoencoder Example with PyTorch and Flower
 license = "Apache-2.0"
 dependencies = [
     "flwr[simulation]>=1.15.0",
-    "flwr-datasets[vision]>=0.3.0",
-    "torch==2.2.1",
-    "torchvision==0.17.1",
+    "flwr-datasets[vision]>=0.5.0",
+    "torch==2.5.1",
+    "torchvision==0.20.1",
 ]
 
 [tool.hatch.build.targets.wheel]

examples/quickstart-fastai/pyproject.toml

@@ -9,10 +9,10 @@ description = "Federated Learning with Fastai and Flower (Quickstart Example)"
 license = "Apache-2.0"
 dependencies = [
     "flwr[simulation]>=1.15.0",
-    "flwr-datasets[vision]>=0.3.0",
-    "fastai==2.7.14",
-    "torch==2.2.0",
-    "torchvision==0.17.0",
+    "flwr-datasets[vision]>=0.5.0",
+    "fastai==2.7.18",
+    "torch==2.5.1",
+    "torchvision==0.20.1",
 ]
 
 [tool.hatch.build.targets.wheel]

examples/quickstart-huggingface/pyproject.toml

@@ -13,7 +13,7 @@ authors = [
 ]
 dependencies = [
     "flwr[simulation]>=1.15.0",
-    "flwr-datasets>=0.3.0",
+    "flwr-datasets>=0.5.0",
     "torch==2.4.0",
     "transformers>=4.30.0,<5.0",
     "evaluate>=0.4.0,<1.0",

examples/quickstart-jax/pyproject.toml

@@ -9,7 +9,7 @@ description = ""
 license = "Apache-2.0"
 dependencies = [
     "flwr[simulation]>=1.15.0",
-    "flwr-datasets[vision]>=0.4.0",
+    "flwr-datasets[vision]>=0.5.0",
     "datasets>=2.21.0",
     "jax==0.4.31",
     "jaxlib==0.4.31",

examples/quickstart-lerobot/pyproject.toml

@@ -16,7 +16,7 @@ authors = [
 ]
 
 dependencies = [
-    "flwr[simulation]==1.14.0",
+    "flwr[simulation]==1.15.0",
     "transformers>=4.30.0,<5.0",
     "lerobot[pusht] @ git+https://github.com/huggingface/lerobot.git@96c7052777aca85d4e55dfba8f81586103ba8f61",
     "flwr-datasets>=0.5.0",

examples/quickstart-mlx/pyproject.toml

@@ -9,7 +9,7 @@ description = "Federated Learning with MLX and Flower (Quickstart Example)"
 license = "Apache-2.0"
 dependencies = [
     "flwr[simulation]>=1.15.0",
-    "flwr-datasets[vision]>=0.3.0",
+    "flwr-datasets[vision]>=0.5.0",
     "mlx==0.21.1",
 ]
 

examples/quickstart-monai/pyproject.toml

@@ -9,9 +9,10 @@ description = "Federated Learning with MONAI and Flower (Quickstart Example)"
 license = "Apache-2.0"
 dependencies = [
     "flwr[simulation]>=1.15.0",
-    "flwr-datasets[vision]>=0.3.0",
+    "flwr-datasets[vision]>=0.5.0",
     "monai==1.3.2",
     "filelock==3.15.4",
+    "numpy<2.0.0",
 ]
 
 [tool.hatch.build.targets.wheel]

examples/quickstart-pandas/pyproject.toml

@@ -13,9 +13,9 @@ authors = [
 ]
 dependencies = [
     "flwr[simulation]>=1.15.0",
-    "flwr-datasets[vision]>=0.3.0",
-    "numpy>=1.26.0",
-    "pandas==2.0.0",
+    "flwr-datasets[vision]>=0.5.0",
+    "numpy>=2.0.2",
+    "pandas==2.2.3",
 ]
 
 [tool.hatch.build.targets.wheel]

examples/quickstart-pytorch-lightning/pyproject.toml

@@ -9,7 +9,7 @@ description = "Federated Learning with PyTorch Lightning and Flower (Quickstart
 license = "Apache-2.0"
 dependencies = [
     "flwr[simulation]>=1.15.0",
-    "flwr-datasets[vision]>=0.3.0",
+    "flwr-datasets[vision]>=0.5.0",
     "pytorch-lightning<2.0.0; sys_platform == 'darwin'",
     "pytorch-lightning==1.6.0; sys_platform != 'darwin'",
     "torch==2.5.1",

examples/quickstart-pytorch/pyproject.toml

@@ -9,9 +9,9 @@ description = "Federated Learning with PyTorch and Flower (Quickstart Example)"
 license = "Apache-2.0"
 dependencies = [
     "flwr[simulation]>=1.15.0",
-    "flwr-datasets[vision]>=0.3.0",
-    "torch==2.2.1",
-    "torchvision==0.17.1",
+    "flwr-datasets[vision]>=0.5.0",
+    "torch==2.5.1",
+    "torchvision==0.20.1",
 ]
 
 [tool.hatch.build.targets.wheel]

examples/quickstart-sklearn-tabular/pyproject.toml

@@ -9,8 +9,8 @@ description = "Federated Learning with scikit-learn and Flower (Quickstart Examp
 license = "Apache-2.0"
 dependencies = [
     "flwr[simulation]>=1.15.0",
-    "flwr-datasets[vision]>=0.3.0",
-    "scikit-learn>=1.3.0",
+    "flwr-datasets[vision]>=0.5.0",
+    "scikit-learn>=1.6.1",
 ]
 
 [tool.hatch.build.targets.wheel]

examples/quickstart-tensorflow/pyproject.toml

@@ -9,7 +9,7 @@ description = "Federated Learning with Tensorflow/Keras and Flower (Quickstart E
 license = "Apache-2.0"
 dependencies = [
     "flwr[simulation]>=1.15.0",
-    "flwr-datasets[vision]>=0.3.0",
+    "flwr-datasets[vision]>=0.5.0",
     "tensorflow>=2.9.1, != 2.11.1 ; (platform_machine == \"x86_64\" or platform_machine == \"aarch64\")",
     "tensorflow-macos>=2.9.1, != 2.11.1 ; sys_platform == \"darwin\" and platform_machine == \"arm64\"",
 ]

examples/sklearn-logreg-mnist/pyproject.toml

@@ -13,9 +13,9 @@ authors = [
 ]
 dependencies = [
     "flwr[simulation]>=1.15.0",
-    "flwr-datasets[vision]>=0.3.0",
+    "flwr-datasets[vision]>=0.5.0",
     "numpy>=2.0.0",
-    "scikit-learn~=1.2.2",
+    "scikit-learn>=1.6.1",
 ]
 
 [tool.hatch.build.targets.wheel]

examples/tensorflow-privacy/pyproject.toml

@@ -8,7 +8,7 @@ version = "1.0.0"
 description = "Sample-level Differential Privacy with Tensorflow-Privacy in Flower"
 dependencies = [
     "flwr[simulation]>=1.15.0",
-    "flwr-datasets[vision]>=0.3.0",
+    "flwr-datasets[vision]>=0.5.0",
     "tensorflow-estimator~=2.4",
     "tensorflow-probability~=0.22.0",
     "tensorflow>=2.4.0,<=2.15.0",

examples/vertical-fl/pyproject.toml

@@ -9,7 +9,7 @@ description = "PyTorch Vertical FL with Flower"
 license = "Apache-2.0"
 dependencies = [
     "flwr[simulation]>=1.15.0",
-    "flwr-datasets>=0.3.0",
+    "flwr-datasets>=0.5.0",
     "pandas==2.2.3",
     "numpy>=1.26.0",
     "scikit-learn==1.5.0",

examples/vertical-fl/vertical_fl/task.py

@@ -23,7 +23,7 @@ def _bin_age(age_series):
 
 
 def _extract_title(name_series):
-    titles = name_series.str.extract(" ([A-Za-z]+)\.", expand=False)
+    titles = name_series.str.extract(r" ([A-Za-z]+)\.", expand=False)
     rare_titles = {
         "Lady",
         "Countess",

examples/xgboost-comprehensive/pyproject.toml

@@ -9,7 +9,7 @@ description = "Federated Learning with XGBoost and Flower (Comprehensive Example
 license = "Apache-2.0"
 dependencies = [
     "flwr[simulation]>=1.15.0",
-    "flwr-datasets>=0.3.0",
+    "flwr-datasets>=0.5.0",
     "xgboost>=2.0.0",
 ]
 

examples/xgboost-quickstart/pyproject.toml

@@ -9,7 +9,7 @@ description = "Federated Learning with XGBoost and Flower (Quickstart Example)"
 license = "Apache-2.0"
 dependencies = [
     "flwr[simulation]>=1.15.0",
-    "flwr-datasets>=0.4.0",
+    "flwr-datasets>=0.5.0",
     "xgboost>=2.0.0",
 ]