feat(framework) Upgrade Flower NumPy version to 2.0

.github/workflows/e2e.yml

@@ -347,3 +347,59 @@ jobs:
           cd tmp-${{ matrix.framework }}
           flwr build
           flwr install *.fab
+
+  numpy:
+    runs-on: ubuntu-22.04
+    timeout-minutes: 10
+    needs: wheel
+    strategy:
+      fail-fast: false
+      matrix:
+        numpy-version: ["1.26"]
+        python-version: ["3.11"]
+        directory: [e2e-bare-auth]
+        connection: [insecure]
+        engine: [deployment-engine, simulation-engine]
+        authentication: [no-auth]
+    name: |
+      NumPy ${{ matrix.numpy-version }} / 
+      Python ${{ matrix.python-version }} /
+      ${{ matrix.connection }} / 
+      ${{ matrix.authentication }} / 
+      ${{ matrix.engine }} 
+    defaults:
+      run:
+        working-directory: e2e/${{ matrix.directory }}
+    steps:
+      - uses: actions/checkout@v4
+      - name: Bootstrap
+        uses: ./.github/actions/bootstrap
+        with:
+          python-version: ${{ matrix.python-version }}
+          poetry-skip: 'true'
+      - name: Install Flower from repo
+        if: ${{ github.repository != 'adap/flower' || github.event.pull_request.head.repo.fork || github.actor == 'dependabot[bot]' }}
+        working-directory: ./
+        run: |
+          if [[ "${{ matrix.engine }}" == "simulation-engine" ]]; then
+            python -m pip install ".[simulation]" "numpy>=${{ matrix.numpy-version }},<2.0"
+          else
+            python -m pip install . "numpy>=${{ matrix.numpy-version }},<2.0"
+          fi
+      - name: Download and install Flower wheel from artifact store
+        if: ${{ github.repository == 'adap/flower' && !github.event.pull_request.head.repo.fork && github.actor != 'dependabot[bot]' }}
+        run: |
+          # Define base URL for wheel file
+          WHEEL_URL="https://${{ env.ARTIFACT_BUCKET }}/py/${{ needs.wheel.outputs.dir }}/${{ needs.wheel.outputs.short_sha }}/${{ needs.wheel.outputs.whl_path }}"
+          if [[ "${{ matrix.engine }}" == "simulation-engine" ]]; then
+            python -m pip install "flwr[simulation] @ ${WHEEL_URL}" "numpy>=${{ matrix.numpy-version }},<2.0"
+          else
+            python -m pip install "${WHEEL_URL}" "numpy>=${{ matrix.numpy-version }},<2.0"
+          fi
+      - name: >
+          Run Flower - NumPy 1.26 test / 
+          ${{ matrix.connection }} / 
+          ${{ matrix.authentication }} / 
+          ${{ matrix.engine }} 
+        working-directory: e2e/${{ matrix.directory }}
+        run: ./../test_exec_api.sh "${{ matrix.connection }}" "${{ matrix.authentication}}" "${{ matrix.engine }}"

datasets/flwr_datasets/common/typing.py

@@ -22,5 +22,5 @@
 
 NDArray = npt.NDArray[Any]
 NDArrayInt = npt.NDArray[np.int_]
-NDArrayFloat = npt.NDArray[np.float_]
+NDArrayFloat = npt.NDArray[np.float64]
 NDArrays = list[NDArray]

datasets/flwr_datasets/partitioner/dirichlet_partitioner_test.py

@@ -29,7 +29,7 @@
 
 def _dummy_setup(
     num_partitions: int,
-    alpha: Union[float, NDArray[np.float_]],
+    alpha: Union[float, NDArray[np.float64]],
     num_rows: int,
     partition_by: str,
     self_balancing: bool = True,

datasets/pyproject.toml

@@ -52,7 +52,7 @@ exclude = [
 
 [tool.poetry.dependencies]
 python = "^3.9"
-numpy = "^1.21.0"
+numpy = ">=1.26.0,<3.0.0"
 datasets = ">=2.14.6 <=3.1.0"
 pillow = { version = ">=6.2.1", optional = true }
 soundfile = { version = ">=0.12.1", optional = true }

e2e/e2e-pandas/pyproject.toml

@@ -11,7 +11,7 @@ authors = [{ name = "Ragy Haddad", email = "ragy202@gmail.com" }]
 maintainers = [{ name = "The Flower Authors", email = "hello@flower.ai" }]
 dependencies = [
     "flwr[simulation] @ {root:parent:parent:uri}",
-    "numpy>=1.21.0,<2.0.0",
+    "numpy>=2.0.0",
     "pandas>=2.0.0,<3.0.0",
     "scikit-learn>=1.1.1,<2.0.0",
 ]

e2e/e2e-pytorch-lightning/pyproject.toml

@@ -9,8 +9,8 @@ description = "Federated Learning E2E test with Flower and PyTorch Lightning"
 license = "Apache-2.0"
 dependencies = [
     "flwr[simulation] @ {root:parent:parent:uri}",
-    "pytorch-lightning==2.2.4",
-    "torchvision==0.14.1",
+    "pytorch-lightning==2.4.0",
+    "torchvision>=0.20.1,<0.21.0",
 ]
 
 [tool.hatch.build.targets.wheel]

e2e/e2e-pytorch/pyproject.toml

@@ -9,8 +9,8 @@ description = "PyTorch Federated Learning E2E test with Flower"
 license = "Apache-2.0"
 dependencies = [
     "flwr[simulation] @ {root:parent:parent:uri}",
-    "torch>=1.12.0,<2.0.0",
-    "torchvision>=0.14.1,<0.15.0",
+    "torch>=2.5.0,<3.0.0",
+    "torchvision>=0.20.1,<0.21.0",
     "tqdm>=4.63.0,<5.0.0",
 ]
 

e2e/e2e-scikit-learn/pyproject.toml

@@ -15,6 +15,7 @@ dependencies = [
     "flwr[simulation,rest] @ {root:parent:parent:uri}",
     "scikit-learn>=1.1.1,<2.0.0",
     "openml>=0.14.0,<0.15.0",
+    "numpy<2.0.0",
 ]
 
 [tool.hatch.build.targets.wheel]

examples/custom-mods/pyproject.toml

@@ -11,7 +11,7 @@ authors = ["The Flower Authors <hello@flower.ai>"]
 [tool.poetry.dependencies]
 python = ">=3.9,<3.11"
 flwr = { path = "../../", develop = true, extras = ["simulation"] }
-tensorboard = "2.16.2"
+tensorboard = "2.18.0"
 torch = "1.13.1"
 torchvision = "0.14.1"
 tqdm = "4.65.0"

examples/sklearn-logreg-mnist/pyproject.toml

@@ -14,7 +14,7 @@ authors = [
 dependencies = [
     "flwr[simulation]>=1.12.0",
     "flwr-datasets[vision]>=0.3.0",
-    "numpy<2.0.0",
+    "numpy>=2.0.0",
     "scikit-learn~=1.2.2",
 ]
 

pyproject.toml

@@ -64,7 +64,7 @@ flower-client-app = "flwr.client.supernode:run_client_app" # Deprecated
 [tool.poetry.dependencies]
 python = "^3.9"
 # Mandatory dependencies
-numpy = "^1.21.0"
+numpy = ">=1.26.0,<3.0.0"
 grpcio = "^1.60.0,!=1.64.2,!=1.65.1,!=1.65.2,!=1.65.4,!=1.65.5,!=1.66.0,!=1.66.1"
 protobuf = "^4.25.2"
 cryptography = "^42.0.4"

src/py/flwr/common/typing.py

@@ -24,7 +24,7 @@
 
 NDArray = npt.NDArray[Any]
 NDArrayInt = npt.NDArray[np.int_]
-NDArrayFloat = npt.NDArray[np.float_]
+NDArrayFloat = npt.NDArray[np.float64]
 NDArrays = list[NDArray]
 
 # The following union type contains Python types corresponding to ProtoBuf types that

src/py/flwr/server/strategy/aggregate.py

@@ -48,12 +48,12 @@ def aggregate_inplace(results: list[tuple[ClientProxy, FitRes]]) -> NDArrays:
     num_examples_total = sum(fit_res.num_examples for (_, fit_res) in results)
 
     # Compute scaling factors for each result
-    scaling_factors = [
-        fit_res.num_examples / num_examples_total for _, fit_res in results
-    ]
+    scaling_factors = np.asarray(
+        [fit_res.num_examples / num_examples_total for _, fit_res in results]
+    )
 
     def _try_inplace(
-        x: NDArray, y: Union[NDArray, float], np_binary_op: np.ufunc
+        x: NDArray, y: Union[NDArray, np.float64], np_binary_op: np.ufunc
     ) -> NDArray:
         return (  # type: ignore[no-any-return]
             np_binary_op(x, y, out=x)