fix conv bn fusion isssue

Signed-off-by: Xin He <[email protected]>

Author: xin3he

neural_compressor/experimental/export/torch2onnx.py

@@ -127,10 +127,15 @@ def check_data(op_type, data, module_dict):
         for name, value in module_dict.items():
             if value.shape == data.shape:
                 if (value == data).all():
+                    module_dict.pop(name)
                     return name
-                # Convolution weight data mismatch.
-                elif op_type == 'Conv' and np.allclose(value, data):
-                    return name
+                elif op_type == 'Conv':
+                    # Convolution weight data have fluction and BN fusion will insert scale.
+                    # We use the weight scale of the first output channel to check.
+                    weight_scale = value[0] / data[0]
+                    if np.allclose(weight_scale - np.mean(weight_scale), 0, atol=1.e-5):
+                        module_dict.pop(name)
+                        return name
         return None
 
     module_dict = {}