Error for unsupported precision types with ModelParallelStrategy (#19902

)

src/lightning/fabric/connector.py

@@ -62,6 +62,7 @@
 )
 from lightning.fabric.strategies.ddp import _DDP_FORK_ALIASES
 from lightning.fabric.strategies.fsdp import _FSDP_ALIASES, FSDPStrategy
+from lightning.fabric.strategies.model_parallel import ModelParallelStrategy
 from lightning.fabric.utilities import rank_zero_info, rank_zero_warn
 from lightning.fabric.utilities.device_parser import _determine_root_gpu_device
 from lightning.fabric.utilities.imports import _IS_INTERACTIVE
@@ -460,6 +461,12 @@ def _check_and_init_precision(self) -> Precision:
             return DeepSpeedPrecision(self._precision_input)  # type: ignore
         if isinstance(self.strategy, FSDPStrategy):
             return FSDPPrecision(precision=self._precision_input)  # type: ignore[arg-type]
+        mp_precision_supported = ("32-true", "bf16-mixed", "bf16-true", "16-true")
+        if isinstance(self.strategy, ModelParallelStrategy) and self._precision_input not in mp_precision_supported:
+            raise ValueError(
+                f"The `ModelParallelStrategy` does not support `Fabric(..., precision={self._precision_input!r})`."
+                f" Choose a different precision among: {', '.join(mp_precision_supported)}."
+            )
         if self._precision_input in ("16-true", "bf16-true"):
             return HalfPrecision(self._precision_input)  # type: ignore
         if self._precision_input == "32-true":

src/lightning/pytorch/trainer/connectors/accelerator_connector.py

@@ -529,6 +529,16 @@ def _validate_precision_choice(self) -> None:
             self.accelerator, CUDAAccelerator
         ):
             raise RuntimeError("Bitsandbytes is only supported on CUDA GPUs.")
+        mp_precision_supported = ("32-true", "bf16-mixed", "bf16-true", "16-true")
+        if (
+            isinstance(self._strategy_flag, ModelParallelStrategy)
+            and self._precision_flag not in mp_precision_supported
+        ):
+            raise ValueError(
+                f"The `ModelParallelStrategy` does not support `Fabric(..., precision={self._precision_flag!r})`."
+                f" Choose a different precision among: {', '.join(mp_precision_supported)}."
+            )
+
         if _habana_available_and_importable():
             from lightning_habana import HPUAccelerator
 

tests/tests_fabric/strategies/test_model_parallel_integration.py

@@ -241,9 +241,7 @@ def _train(fabric, model=None, optimizer=None):
 @pytest.mark.parametrize(
     "precision",
     [
-        pytest.param(
-            "16-mixed", marks=pytest.mark.xfail(reason="Precision plugin does not implement ShardedGradScaler yet")
-        ),
+        pytest.param("32-true"),
         pytest.param("bf16-mixed", marks=RunIf(bf16_cuda=True)),
     ],
 )
@@ -548,26 +546,17 @@ def _parallelize_single_linear_tp_fsdp2(model, device_mesh):
     "precision",
     [
         "32-true",
-        pytest.param("16-mixed"),
         pytest.param("bf16-mixed", marks=RunIf(bf16_cuda=True)),
     ],
 )
 @pytest.mark.parametrize(
     "clip_type",
     [
         pytest.param("norm", marks=pytest.mark.skip("Gradient clipping by norm is not correct.")),
-        pytest.param(
-            "val",
-            marks=pytest.mark.xfail(
-                raises=RecursionError, strict=False, reason="Recursion error when clipping DTensor"
-            ),
-        ),
+        "val",
     ],
 )
 def test_clip_gradients(clip_type, precision):
-    if clip_type == "norm" and precision == "16-mixed":
-        pytest.skip(reason="Clipping by norm with 16-mixed is numerically unstable.")
-
     strategy = ModelParallelStrategy(_parallelize_single_linear_tp_fsdp2)
     fabric = Fabric(accelerator="auto", devices=2, precision=precision, strategy=strategy)
     fabric.launch()

tests/tests_fabric/test_connector.py

@@ -14,6 +14,7 @@
 import inspect
 import os
 import sys
+from contextlib import nullcontext
 from typing import Any, Dict
 from unittest import mock
 from unittest.mock import Mock
@@ -53,6 +54,7 @@
     DDPStrategy,
     DeepSpeedStrategy,
     FSDPStrategy,
+    ModelParallelStrategy,
     SingleDeviceStrategy,
     SingleDeviceXLAStrategy,
     XLAFSDPStrategy,
@@ -866,6 +868,18 @@ def test_precision_selection_amp_ddp(strategy, devices, is_custom_plugin, plugin
     assert isinstance(connector.precision, plugin_cls)
 
 
+@RunIf(min_torch="2.3")
+@pytest.mark.parametrize(
+    ("precision", "raises"),
+    [("32-true", False), ("16-true", False), ("bf16-true", False), ("16-mixed", True), ("bf16-mixed", False)],
+)
+@mock.patch("lightning.fabric.accelerators.mps.MPSAccelerator.is_available", return_value=False)
+def test_precision_selection_model_parallel(_, precision, raises):
+    error_context = pytest.raises(ValueError, match=f"does not support .*{precision}") if raises else nullcontext()
+    with error_context:
+        _Connector(precision=precision, strategy=ModelParallelStrategy(lambda x, _: x))
+
+
 def test_bitsandbytes_precision_cuda_required(monkeypatch):
     monkeypatch.setattr(lightning.fabric.plugins.precision.bitsandbytes, "_BITSANDBYTES_AVAILABLE", True)
     monkeypatch.setitem(sys.modules, "bitsandbytes", Mock())

tests/tests_pytorch/trainer/connectors/test_accelerator_connector.py

@@ -14,6 +14,7 @@
 import inspect
 import os
 import sys
+from contextlib import nullcontext
 from typing import Any, Dict
 from unittest import mock
 from unittest.mock import Mock
@@ -48,6 +49,7 @@
     DDPStrategy,
     DeepSpeedStrategy,
     FSDPStrategy,
+    ModelParallelStrategy,
     SingleDeviceStrategy,
     SingleDeviceXLAStrategy,
     XLAStrategy,
@@ -1063,3 +1065,14 @@ def test_bitsandbytes_precision_cuda_required(monkeypatch):
     monkeypatch.setitem(sys.modules, "bitsandbytes", Mock())
     with pytest.raises(RuntimeError, match="Bitsandbytes is only supported on CUDA GPUs"):
         _AcceleratorConnector(accelerator="cpu", plugins=BitsandbytesPrecision(mode="int8"))
+
+
+@RunIf(min_torch="2.3")
+@pytest.mark.parametrize(
+    ("precision", "raises"),
+    [("32-true", False), ("16-true", False), ("bf16-true", False), ("16-mixed", True), ("bf16-mixed", False)],
+)
+def test_precision_selection_model_parallel(precision, raises, mps_count_0):
+    error_context = pytest.raises(ValueError, match=f"does not support .*{precision}") if raises else nullcontext()
+    with error_context:
+        _AcceleratorConnector(precision=precision, strategy=ModelParallelStrategy())