use DefaultWeightsLoader in skip modules

Signed-off-by: jiqing-feng <jiqing.feng@intel.com>

server/text_generation_server/layers/gptq/__init__.py

@@ -10,7 +10,7 @@
     Weight,
     Weights,
     WeightsLoader,
-    UnquantizedWeight,
+    DefaultWeightsLoader,
 )
 
 if SYSTEM == "ipex":
@@ -95,7 +95,7 @@ def __init__(
         quant_method: str,
         quantize: str,
         sym: bool,
-        modules_to_not_convert: Optional[List[str]],
+        modules_to_not_convert: List[str],
     ):
         self.bits = bits
         self.desc_act = desc_act
@@ -117,8 +117,7 @@ def get_weights(self, weights: Weights, prefix: str):
             use_exllama = False
 
         if self.is_layer_skipped_quantization(prefix, self.modules_to_not_convert):
-            w = weights.get_tensor(f"{prefix}.weight")
-            return UnquantizedWeight(w)
+            return DefaultWeightsLoader.get_weights(weights, prefix)
 
         try:
             qweight = weights.get_tensor(f"{prefix}.qweight")
@@ -200,10 +199,9 @@ def get_weights_col_packed(
         block_sizes: Union[int, List[int]],
     ):
         if self.is_layer_skipped_quantization(prefix, self.modules_to_not_convert):
-            w = weights.get_packed_sharded(
-                f"{prefix}.weight", dim=0, block_sizes=block_sizes
+            return DefaultWeightsLoader.get_weights_col_packed(
+                weights, prefix, block_sizes
             )
-            return UnquantizedWeight(w)
         try:
             qweight = weights.get_packed_sharded(
                 f"{prefix}.qweight", dim=1, block_sizes=block_sizes
@@ -256,10 +254,7 @@ def get_weights_col_packed(
 
     def get_multi_weights_col(self, weights: Weights, prefixes: List[str], dim: int):
         if self.is_layer_skipped_quantization(prefixes[0], self.modules_to_not_convert):
-            w = torch.cat(
-                [weights.get_sharded(f"{p}.weight", dim=0) for p in prefixes], dim=dim
-            )
-            return UnquantizedWeight(w)
+            return DefaultWeightsLoader.get_multi_weights_col(weights, prefixes, dim)
         try:
             qweight = torch.cat(
                 [weights.get_sharded(f"{p}.qweight", dim=1) for p in prefixes], dim=1
@@ -339,8 +334,7 @@ def get_weights_row(self, weights: Weights, prefix: str):
             use_exllama = False
 
         if self.is_layer_skipped_quantization(prefix, self.modules_to_not_convert):
-            w = weights.get_sharded(f"{prefix}.weight", dim=1)
-            return UnquantizedWeight(w)
+            return DefaultWeightsLoader.get_weights_row(weights, prefix)
         try:
             qweight = weights.get_sharded(f"{prefix}.qweight", dim=0)
         except RuntimeError:

server/text_generation_server/utils/quantization.py

@@ -77,7 +77,7 @@ def _get_quantizer_config(model_id, revision):
         checkpoint_format = data["quantization_config"].get("checkpoint_format")
         desc_act = data["quantization_config"].get("desc_act", False)
         modules_to_not_convert = data["quantization_config"].get(
-            "modules_to_not_convert", None
+            "modules_to_not_convert", []
         )
     except Exception:
         filename = "quantize_config.json"