diff --git a/testdata/dnn/onnx/data/input_normalize_fusion.npy b/testdata/dnn/onnx/data/input_normalize_fusion.npy
new file mode 100644
index 000000000..8cdfd0bff
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diff --git a/testdata/dnn/onnx/data/output_normalize_fusion.npy b/testdata/dnn/onnx/data/output_normalize_fusion.npy
new file mode 100644
index 000000000..420aebbce
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diff --git a/testdata/dnn/onnx/generate_onnx_models.py b/testdata/dnn/onnx/generate_onnx_models.py
index 8d5cc52c3..f017ad775 100644
--- a/testdata/dnn/onnx/generate_onnx_models.py
+++ b/testdata/dnn/onnx/generate_onnx_models.py
@@ -1245,3 +1245,16 @@ def forward(self, x):
 x = Variable(torch.randn([1, 1, 3, 4]))
 model = PadCalculation()
 save_data_and_model("calc_pads", x, model, version=11)
+
+class NormalizeFusion(nn.Module):
+    def forward(self, x):
+        mul = x * x
+        sum = torch.sum(mul, dim=(1), keepdim=True)
+        maximum = torch.clamp(sum, min=1e-8)
+        sqrt = torch.sqrt(maximum)
+        reciprocal = torch.reciprocal(sqrt)
+        return x * reciprocal
+
+x = Variable(torch.randn([2, 3]))
+model = NormalizeFusion()
+save_data_and_model("normalize_fusion", x, model)
diff --git a/testdata/dnn/onnx/models/normalize_fusion.onnx b/testdata/dnn/onnx/models/normalize_fusion.onnx
new file mode 100644
index 000000000..196c6808c
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