Merge pull request #3360 from AI-Hypercomputer:xfgu-fixit

PiperOrigin-RevId: 881496802

Author: Google-ML-Automation

tests/unit/train_rl_test.py

@@ -0,0 +1,98 @@
+# Copyright 2026 Google LLC
+#
+# 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.
+
+"""Unit tests for train_rl.py."""
+
+import unittest
+from unittest import mock
+import pytest
+from types import SimpleNamespace
+import jax
+
+
+# Same as in rl_utils_test.py.
+train_rl = pytest.importorskip(
+    "maxtext.trainers.post_train.rl.train_rl",
+    reason="Tunix is not installed on the GPU image",
+)
+
+
+def _get_mock_devices(num_devices):
+  mock_devices = [mock.MagicMock() for _ in range(num_devices)]
+  for i, d in enumerate(mock_devices):
+    d.id = i
+  return mock_devices
+
+
+class TrainRLTest(unittest.TestCase):
+  """Tests for train_rl.py."""
+
+  @pytest.mark.cpu_only
+  def test_setup_configs_and_devices_pathways_split(self):
+    """Test setup_configs_and_devices with multiple VMs and Pathways."""
+    mock_devices = _get_mock_devices(8)
+
+    mock_config = SimpleNamespace(
+        num_trainer_slices=-1,
+        num_samplers_slices=-1,
+        chips_per_vm=4,
+        use_pathways=True,
+        trainer_devices_fraction=0.5,
+        sampler_devices_fraction=0.5,
+    )
+
+    # Following the pattern in distillation_checkpointing_test.py for mocking jax objects
+    with (
+        mock.patch.object(jax, "devices", return_value=mock_devices),
+        mock.patch("maxtext.trainers.post_train.rl.train_rl.pyconfig.initialize_pydantic", return_value=mock_config),
+    ):
+      trainer_config, sampler_config, trainer_devices, sampler_devices = train_rl.setup_configs_and_devices(
+          ["dummy", "dummy"]
+      )
+
+      self.assertEqual(trainer_config, mock_config)
+      self.assertEqual(sampler_config, mock_config)
+      self.assertEqual(len(trainer_devices), 4)
+      self.assertEqual(len(sampler_devices), 4)
+      self.assertEqual(trainer_devices, mock_devices[:4])
+      self.assertEqual(sampler_devices, mock_devices[4:])
+
+  @pytest.mark.cpu_only
+  def test_setup_configs_and_devices_pathways_fractional_split(self):
+    """Test setup_configs_and_devices with multiple VMs and custom fractions."""
+    mock_devices = _get_mock_devices(8)
+
+    mock_config = SimpleNamespace(
+        num_trainer_slices=-1,
+        num_samplers_slices=-1,
+        chips_per_vm=4,
+        use_pathways=True,
+        trainer_devices_fraction=0.25,
+        sampler_devices_fraction=0.75,
+    )
+
+    with (
+        mock.patch.object(jax, "devices", return_value=mock_devices),
+        mock.patch("maxtext.trainers.post_train.rl.train_rl.pyconfig.initialize_pydantic", return_value=mock_config),
+    ):
+      _, _, trainer_devices, sampler_devices = train_rl.setup_configs_and_devices(["dummy", "dummy"])
+
+      self.assertEqual(len(trainer_devices), 2)
+      self.assertEqual(len(sampler_devices), 6)
+      self.assertEqual(trainer_devices, mock_devices[:2])
+      self.assertEqual(sampler_devices, mock_devices[2:])
+
+
+if __name__ == "__main__":
+  unittest.main()