Cherry pick 012 distilbert qat fixes (#726)

* fix QATWrapper not properly overwritting qconfig properties for symmetric activations (#724)

* re-add fix symmetric zero points for unit8 quantization (#604) (#725)

src/sparseml/pytorch/sparsification/quantization/helpers.py

@@ -119,41 +119,37 @@ class QConfigProperties:
         Default is torch.qint8.
     :param activation_bits: number of bits for activations. Default is 8.
     :param weight_bits: number of bits for weights. Default is 8.
+    :param tensorrt: if True sets quantization configuration for compatibility with
+       explict quantization as supported by TensorRT 8.2.
     """
 
-    _symmetric_activations: Optional[bool] = None
-    _symmetric_weights: Optional[bool] = None
+    _symmetric_activations: bool = False
+    _symmetric_weights: bool = True
     reduce_range: bool = False
     activation_dtype: torch.dtype = torch.quint8
     weight_dtype: torch.dtype = torch.qint8
     activation_bits: int = 8
     weight_bits: int = 8
     activation_qconfig_kwargs: Dict[str, Any] = field(default_factory=dict)
     weight_qconfig_kwargs: Dict[str, Any] = field(default_factory=dict)
+    tensorrt: bool = False
 
     @property
     def symmetric_activations(self) -> bool:
-        if self._symmetric_activations:
-            return self._symmetric_activations
-        else:
-            return False
+        # always use symmetric activations in tensorrt mode
+        return self.tensorrt or self._symmetric_activations
 
     @symmetric_activations.setter
     def symmetric_activations(self, value: bool):
-        if self._symmetric_activations is None:
-            self._symmetric_activations = value
+        self._symmetric_activations = value
 
     @property
     def symmetric_weights(self) -> bool:
-        if self._symmetric_weights:
-            return self._symmetric_weights
-        else:
-            return True
+        return self.tensorrt or self._symmetric_weights
 
     @symmetric_weights.setter
     def symmetric_weights(self, value: bool):
-        if self._symmetric_weights is None:
-            self._symmetric_weights = value
+        self._symmetric_weights = value
 
 
 class QATWrapper(Module):
@@ -365,9 +361,10 @@ def _load_qconfigs(
                     f"Found string with value {qconfig} in {name}"
                 )
 
-            qproperties.symmetric_activations = qconfig == "symmetric"
+            qproperties_idx = deepcopy(qproperties)
+            qproperties_idx.symmetric_activations = qconfig == "symmetric"
 
-            qconfigs[idx] = get_qat_qconfig(qproperties)
+            qconfigs[idx] = get_qat_qconfig(qproperties_idx)
 
         return qconfigs
 
@@ -578,6 +575,11 @@ def fix_observer_quant_range(module: Module):
             fake_quantize.quant_min is None
             or fake_quantize.quant_max is None
             or (observer.quant_min is not None or observer.quant_max is not None)
+            or (  # do not propagate default uint8 symmetric range
+                observer.qscheme == torch.per_tensor_symmetric
+                and fake_quantize.quant_min == 0
+                and fake_quantize.quant_max == 255
+            )
         ):
             continue
         observer.quant_min = fake_quantize.quant_min

src/sparseml/pytorch/sparsification/quantization/modifier_quantization.py

@@ -615,9 +615,8 @@ def _enable_module_qat(self, module: Module):
                 "Overriding quantization scheme to symmetric int8 "
                 "for both weights and activations because tensorrt flag is True."
             )
-            qproperties.symmetric_activations = True
+            qproperties.tensorrt = True
             qproperties.activation_dtype = torch.qint8
-            qproperties.symmetric_weights = True
             qproperties.weight_dtype = torch.qint8
 
         qconfig = get_qat_qconfig(qproperties)