diff --git a/mmrazor/models/observers/torch_observers.py b/mmrazor/models/observers/torch_observers.py
index 0de628a9a..996314d27 100644
--- a/mmrazor/models/observers/torch_observers.py
+++ b/mmrazor/models/observers/torch_observers.py
@@ -12,7 +12,7 @@
 except ImportError:
     from mmrazor.utils import get_package_placeholder
     torch_observer_src = get_package_placeholder('torch>=1.13')
-    UniformQuantizationObserverBase = get_package_placeholder('torch>=1.13')
+    PerChannelMinMaxObserver = get_package_placeholder('torch>=1.13')
 
 
 @torch.jit.export
diff --git a/tests/test_runners/test_quantization_loop.py b/tests/test_runners/test_quantization_loop.py
index 7a15a5ccb..bc46e0cca 100644
--- a/tests/test_runners/test_quantization_loop.py
+++ b/tests/test_runners/test_quantization_loop.py
@@ -15,6 +15,7 @@
 from mmengine.optim import OptimWrapper
 from mmengine.registry import DATASETS, HOOKS, METRICS, MODELS, OPTIM_WRAPPERS
 from mmengine.runner import Runner
+from torch.ao.nn.quantized import FloatFunctional, FXFloatFunctional
 from torch.nn.intrinsic.qat import ConvBnReLU2d
 from torch.utils.data import Dataset
 
@@ -71,14 +72,14 @@ def swap_ff_with_fxff(self, model):
 
         modules_to_swap = []
         for name, module in model.named_children():
-            if isinstance(module, torch.ao.nn.quantized.FloatFunctional):
+            if isinstance(module, FloatFunctional):
                 modules_to_swap.append(name)
             else:
                 self.swap_ff_with_fxff(module)
 
         for name in modules_to_swap:
             del model._modules[name]
-            model._modules[name] = torch.ao.nn.quantized.FXFloatFunctional()
+            model._modules[name] = FXFloatFunctional()
 
     def sync_qparams(self, src_mode):
         pass