fix some issues

auto_round/auto_quantizer.py

@@ -599,14 +599,16 @@ def cpu_post_init(self, model):
 
         for n, layer in tqdm(layers, desc=message, total=len(layers),
                              leave=True):
-            from auto_round_extension.qbits import qbits_qlinear_classes
+            from auto_round_extension.qbits import qbits_qlinear_classes,qbits_awq_classes
             from auto_round_extension.ipex import ipex_qlinear_classes
             if isinstance(layer, qbits_qlinear_classes):
                 if dep_check:
                     layer.req_check()
                 layer.post_init()
                 dep_check = False
-            if isinstance(layer, ipex_qlinear_classes):
+            elif isinstance(layer, ipex_qlinear_classes):
+                layer.post_init()
+            elif isinstance(layer, qbits_awq_classes):
                 layer.post_init()
 
         return model

auto_round_extension/qbits/__init__.py

@@ -2,5 +2,8 @@
 from auto_round_extension.qbits.qlinear_qbits_gptq import (
     QuantLinear as QBitsGPTQQuantLinear,
 )
+from auto_round_extension.qbits.qbits_awq import  QuantLinear as QBitsAWQQuantLinear
 
 qbits_qlinear_classes = (QBitsQuantLinear, QBitsGPTQQuantLinear)
+
+qbits_awq_classes=(QBitsAWQQuantLinear)

auto_round_extension/qbits/qbits_awq.py

@@ -90,15 +90,24 @@ def __init__(self, w_bit, group_size, in_features, out_features, bias, zero_poin
         assert self.in_features % self.group_size == 0
         assert out_features % (32 // self.w_bit) == 0
         self.pack_num = 32 // self.w_bit
-
-        self.register_buffer(
-            "qzeros",
-            torch.zeros(
-                (in_features // self.group_size, out_features // self.pack_num),
-                dtype=torch.int8,
-                device=dev,
-            ) if self.zero_point else None,
-        )
+        if self.zero_point:
+            self.register_buffer(
+                "qzeros",
+                torch.zeros(
+                    (in_features // self.group_size, out_features // self.pack_num),
+                    dtype=torch.int8,
+                    device=dev,
+                )
+            )
+        else:
+            self.register_buffer(
+                "qzeros",
+                torch.ones(
+                    (in_features // self.group_size, out_features // self.pack_num),
+                    dtype=torch.int8,
+                    device=dev,
+                )*8
+            )
         self.register_buffer(
             "scales",
             torch.zeros(