refactor: mark use_sequential deprecated/frozen instead of key-rename validator

Per reviewer feedback on #1251, re-introduce use_sequential as a real field
marked deprecated and frozen. Pydantic emits DeprecationWarning on use and
blocks post-construction reassignment; a model_validator(mode='after')
copies the legacy value into layerwise when layerwise was not set.
Replaces the mode='before' key-rename validator added in b4c6a03.

Signed-off-by: realAsma <akuriparambi@nvidia.com>

Author: realAsma

modelopt/torch/quantization/config.py

@@ -154,7 +154,7 @@
 import warnings
 from typing import Any, Literal, cast
 
-from pydantic import ValidationInfo, field_validator, model_validator
+from pydantic import Field, ValidationInfo, field_validator, model_validator
 from typing_extensions import Required, TypedDict
 
 from modelopt.torch.opt.config import ModeloptBaseConfig, ModeloptField
@@ -1227,6 +1227,12 @@ class QuantizeAlgorithmConfig(ModeloptBaseConfig):
         ),
     )
 
+    use_sequential: bool | None = Field(
+        default=None,
+        deprecated="Use 'layerwise' instead.",
+        frozen=True,
+    )
+
     layerwise_checkpoint_dir: str | None = ModeloptField(
         default=None,
         title="Checkpoint directory for layerwise calibration.",
@@ -1237,20 +1243,11 @@ class QuantizeAlgorithmConfig(ModeloptBaseConfig):
         ),
     )
 
-    @model_validator(mode="before")
-    @classmethod
-    def _rename_legacy_fields(cls, values):
-        """Rewrite renamed fields to their current names for backward compatibility.
-
-        Preserves the stored value so checkpoints saved before a field was renamed
-        continue to load. Explicit values on the new name take precedence.
-        """
-        legacy_to_current = {"use_sequential": "layerwise"}
-        if isinstance(values, dict):
-            for legacy, current in legacy_to_current.items():
-                if legacy in values:
-                    values.setdefault(current, values.pop(legacy))
-        return values
+    @model_validator(mode="after")
+    def _migrate_use_sequential(self):
+        if self.use_sequential is not None and not self.layerwise:
+            object.__setattr__(self, "layerwise", self.use_sequential)
+        return self
 
     @model_validator(mode="after")
     def validate_layerwise_checkpoint_dir(self):

tests/unit/torch/quantization/test_config_validation.py

@@ -532,13 +532,21 @@ class TestLegacyFieldRename:
     """Old PTQ checkpoints saved the field as ``use_sequential`` before #1251."""
 
     def test_legacy_use_sequential_true_maps_to_layerwise(self):
-        cfg = MaxCalibConfig(use_sequential=True)
+        with pytest.warns(DeprecationWarning):
+            cfg = MaxCalibConfig(use_sequential=True)
         assert cfg.layerwise is True
 
     def test_legacy_use_sequential_false_maps_to_layerwise(self):
-        cfg = MaxCalibConfig(use_sequential=False)
+        with pytest.warns(DeprecationWarning):
+            cfg = MaxCalibConfig(use_sequential=False)
         assert cfg.layerwise is False
 
     def test_explicit_layerwise_wins_over_legacy(self):
-        cfg = MaxCalibConfig(use_sequential=False, layerwise=True)
+        with pytest.warns(DeprecationWarning):
+            cfg = MaxCalibConfig(use_sequential=False, layerwise=True)
         assert cfg.layerwise is True
+
+    def test_use_sequential_is_frozen(self):
+        cfg = MaxCalibConfig()
+        with pytest.raises(ValidationError):
+            cfg.use_sequential = True