diff --git a/testdata/dnn/onnx/data/input_PReLU_slope.npy b/testdata/dnn/onnx/data/input_PReLU_slope.npy
new file mode 100644
index 0000000000000000000000000000000000000000..b850fc49b46072258df1fea0d724391acb6e02ab
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diff --git a/testdata/dnn/onnx/data/output_PReLU_slope.npy b/testdata/dnn/onnx/data/output_PReLU_slope.npy
new file mode 100644
index 0000000000000000000000000000000000000000..e8d0d5d207dbcf9efef4a2e6e6e3ebf93f0a69e3
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diff --git a/testdata/dnn/onnx/generate_onnx_models.py b/testdata/dnn/onnx/generate_onnx_models.py
index ab31636aa8ee8f516117d3e9ba4f0cb5e4e45384..8f69df725bd8bb49c7fac6b25a57af8135cef372 100644
--- a/testdata/dnn/onnx/generate_onnx_models.py
+++ b/testdata/dnn/onnx/generate_onnx_models.py
@@ -136,6 +136,18 @@ input = Variable(torch.randn(1, 2, 10, 10))
 relu = nn.ReLU(inplace=True)
 save_data_and_model("ReLU", input, relu)
 
+class PReLU_slope(nn.Module):
+    def __init__(self, *args, **kwargs):
+        super(PReLU_slope, self).__init__()
+
+    def forward(self, x):
+        return nn.PReLU()(x)
+
+model = PReLU_slope()
+input_ = Variable(torch.randn(1, 1, 5, 5, dtype=torch.float32))
+save_data_and_model("PReLU_slope", input_, model, export_params=True)
+simplify('models/PReLU_slope.onnx', False)
+
 
 input = Variable(torch.randn(2, 3))
 dropout = nn.Dropout()
diff --git a/testdata/dnn/onnx/models/PReLU_slope.onnx b/testdata/dnn/onnx/models/PReLU_slope.onnx
new file mode 100644
index 0000000000000000000000000000000000000000..b0d72218b8b7d1f5fbced9a2d4a29c2203a39d57
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