diff --git a/auto_gptq/modeling/_base.py b/auto_gptq/modeling/_base.py
index 34e69d2..c656420 100644
--- a/auto_gptq/modeling/_base.py
+++ b/auto_gptq/modeling/_base.py
@@ -227,7 +227,8 @@ class BaseGPTQForCausalLM(nn.Module, PushToHubMixin):
                             break
                 layer_inputs.append(move_to_device(inp, self.data_device))
                 attention_masks.append(kwargs["attention_mask"].to(self.data_device))
-                if (pos_ids := kwargs.get("position_ids", None)) is not None:
+                pos_ids = kwargs.get("position_ids", None)
+                if pos_ids is not None:
                     position_ids.append(move_to_device(pos_ids, self.data_device))
                 one_kwargs = dict()
                 for k, v in kwargs.items():  # make sure other arguments also be captured
@@ -328,10 +329,8 @@ class BaseGPTQForCausalLM(nn.Module, PushToHubMixin):
                     additional_layer_inputs = {
                         "attention_mask": layer_attention_mask
                     }
-                    if (
-                        layer_position_ids := None if not position_ids
-                        else move_to_device(position_ids[j], cur_layer_device)
-                    ) is not None:
+                    layer_position_ids = None if not position_ids else move_to_device(position_ids[j], cur_layer_device)
+                    if layer_position_ids is not None:
                         additional_layer_inputs["position_ids"] = layer_position_ids
                     for k, v in layer_input_kwargs[j].items():
                         if isinstance(v, torch.Tensor):
@@ -363,10 +362,8 @@ class BaseGPTQForCausalLM(nn.Module, PushToHubMixin):
                 additional_layer_inputs = {
                     "attention_mask": layer_attention_mask
                 }
-                if (
-                    layer_position_ids := None if not position_ids
-                    else move_to_device(position_ids[j], cur_layer_device)
-                ) is not None:
+                layer_position_ids = None if not position_ids else move_to_device(position_ids[j], cur_layer_device)
+                if layer_position_ids is not None:
                     additional_layer_inputs["position_ids"] = layer_position_ids
                 for k, v in layer_input_kwargs[j].items():
                     if isinstance(v, torch.Tensor):