diff --git a/testdata/dnn/onnx/data/input_gather_multi_output.npy b/testdata/dnn/onnx/data/input_gather_multi_output.npy
new file mode 100644
index 000000000..b88e81dd3
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diff --git a/testdata/dnn/onnx/data/output_gather_multi_output.npy b/testdata/dnn/onnx/data/output_gather_multi_output.npy
new file mode 100644
index 000000000..b92aa732b
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diff --git a/testdata/dnn/onnx/generate_onnx_models.py b/testdata/dnn/onnx/generate_onnx_models.py
index 4458f3ea6..9b6f45604 100644
--- a/testdata/dnn/onnx/generate_onnx_models.py
+++ b/testdata/dnn/onnx/generate_onnx_models.py
@@ -1023,3 +1023,20 @@ def forward(self, x, kernel, bias):
 bias = Variable(torch.randn(4))
 model = Conv1dBias()
 save_data_and_model_multy_inputs("conv1d_variable_wb", model, x, kernel, bias)
+
+class GatherMultiOutput(nn.Module):
+    def __init__(self, in_dim = 2):
+        super(GatherMultiOutput, self).__init__()
+        self.in_dim = in_dim
+        self.lin_inp = nn.Linear(in_dim, 2, bias=False)
+    def forward(self, x):
+        x_projected = self.lin_inp(x).long()
+        x_gather = x_projected[:,0,:]
+        x_float1 = x_gather.float()
+        x_float2 = x_gather.float()
+        x_float3 = x_gather.float()
+        return x_float1+x_float2+x_float3
+
+x = Variable(torch.zeros([1, 2, 2]))
+model = GatherMultiOutput()
+save_data_and_model("gather_multi_output", x, model)
diff --git a/testdata/dnn/onnx/models/gather_multi_output.onnx b/testdata/dnn/onnx/models/gather_multi_output.onnx
new file mode 100644
index 000000000..1b9195a43
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