Add initial nnx/optax test

.github/workflows/test.yaml

@@ -0,0 +1,43 @@
+name: Test
+
+on:
+  # Trigger the workflow on push or pull request, but only on main branch
+  push:
+    branches:
+      - main
+  pull_request:
+    branches:
+      - main
+
+permissions:
+  contents: read  # to fetch code
+
+jobs:
+  build:
+    name: ${{ matrix.os }} Python ${{ matrix.python-version }}
+    runs-on: ${{ matrix.os }}
+    strategy:
+      matrix:
+        os: ["ubuntu-latest"]
+        python-version: ["3.9", "3.10", "3.11", "3.12"]
+        include:
+        - os: macOS-11
+          python-version: "3.11"
+        - os: windows-2019
+          python-version: "3.11"
+
+    steps:
+    - uses: actions/checkout@b4ffde65f46336ab88eb53be808477a3936bae11 # ratchet:actions/checkout@v4
+      with:
+        submodules: true
+    - name: Set up Python ${{ matrix.python-version }}
+      uses: actions/setup-python@39cd14951b08e74b54015e9e001cdefcf80e669f # ratchet:actions/setup-python@v5
+      with:
+        python-version: ${{ matrix.python-version }}
+    - name: Install dependencies
+      run: |
+        python -m pip install --upgrade pip
+        pip install .[dev]
+    - name: Run tests
+      run: |
+        pytest -n auto jax_ml_stack

jax_ml_stack/tests/test_nnx_with_optax.py

@@ -0,0 +1,53 @@
+# Copyright 2024 The JAX Authors.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     https://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import unittest
+import jax
+import jax.numpy as jnp
+from flax import nnx
+import optax
+
+
+class SimpleModel(nnx.Module):
+
+  def __init__(self, rngs):
+    self.layer1 = nnx.Linear(2, 5, rngs=rngs)
+    self.layer2 = nnx.Linear(5, 3, rngs=rngs)
+
+  def __call__(self, x):
+    for layer in [self.layer1, self.layer2]:
+      x = layer(x)
+    return x
+
+
+class NNXOptaxTest(unittest.TestCase):
+
+  def test_nnx_optax(self):
+    key = jax.random.key(1701)
+    x = jax.random.normal(key, (1, 2))
+    y = jnp.ones((1, 3))
+
+    model = SimpleModel(nnx.Rngs(0))
+    optimizer = optax.adam(learning_rate=1e-3)
+    state = nnx.Optimizer(model, optimizer)
+
+    def loss(model, x=x, y=y):
+      return jnp.mean((model(x) - y) ** 2)
+
+    initial_loss = loss(model)
+    grads = nnx.grad(loss, wrt=nnx.Param)(state.model)
+    state.update(grads)
+    final_loss = loss(model)
+
+    self.assertNotAlmostEqual(initial_loss, final_loss)

pyproject.toml

@@ -16,6 +16,8 @@ keywords = []
 # pip dependencies of the project
 dependencies = [
     "jax",
+    "flax",
+    "optax",
 ]
 
 [project.urls]
@@ -29,8 +31,6 @@ repository = "https://github.com/jax-ml/jax_ml_stack"
 dev = [
     "pytest",
     "pytest-xdist",
-    "pylint>=2.6.0",
-    "pyink",
 ]
 
 [tool.pyink]