tpu

pytorch_lightning/accelerators/tpu.py

@@ -19,8 +19,8 @@ class TPUAccelerator(Accelerator):
     def setup(self, trainer, model):
         if isinstance(self.precision_plugin, MixedPrecisionPlugin):
             raise MisconfigurationException(
-                "amp + tpu is not supported. "
-                "Only bfloats are supported on TPU. Consider using TPUHalfPrecisionPlugin"
+                "amp + tpu is not supported."
+                " Only bfloats are supported on TPU. Consider using TPUHalfPrecisionPlugin"
             )
 
         if not isinstance(self.training_type_plugin, (SingleTPUPlugin, TPUSpawnPlugin)):

tests/accelerators/test_tpu.py

@@ -0,0 +1,32 @@
+from unittest.mock import Mock
+
+import pytest
+
+from pytorch_lightning.accelerators import TPUAccelerator
+from pytorch_lightning.plugins import SingleTPUPlugin, DDPPlugin, PrecisionPlugin
+from pytorch_lightning.plugins.precision import MixedPrecisionPlugin
+from pytorch_lightning.utilities.exceptions import MisconfigurationException
+
+
+def test_unsupported_precision_plugins():
+    """ Test error messages are raised for unsupported precision plugins with TPU. """
+    trainer = Mock()
+    model = Mock()
+    accelerator = TPUAccelerator(
+        training_type_plugin=SingleTPUPlugin(device=Mock()),
+        precision_plugin=MixedPrecisionPlugin(),
+    )
+    with pytest.raises(MisconfigurationException, match=r"amp \+ tpu is not supported."):
+        accelerator.setup(trainer=trainer, model=model)
+
+
+def test_unsupported_training_type_plugins():
+    """ Test error messages are raised for unsupported training type with TPU. """
+    trainer = Mock()
+    model = Mock()
+    accelerator = TPUAccelerator(
+        training_type_plugin=DDPPlugin(),
+        precision_plugin=PrecisionPlugin(),
+    )
+    with pytest.raises(MisconfigurationException, match="TPUs only support a single tpu core or tpu spawn training"):
+        accelerator.setup(trainer=trainer, model=model)