diff --git a/testdata/dnn/onnx/data/input_reduce_max_axis_0.npy b/testdata/dnn/onnx/data/input_reduce_max_axis_0.npy
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index 000000000..9469ba8fb
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diff --git a/testdata/dnn/onnx/data/input_reduce_max_axis_1.npy b/testdata/dnn/onnx/data/input_reduce_max_axis_1.npy
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index 000000000..9469ba8fb
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diff --git a/testdata/dnn/onnx/data/output_reduce_max_axis_0.npy b/testdata/dnn/onnx/data/output_reduce_max_axis_0.npy
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index 000000000..42b704542
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diff --git a/testdata/dnn/onnx/data/output_reduce_max_axis_1.npy b/testdata/dnn/onnx/data/output_reduce_max_axis_1.npy
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index 000000000..034e23a74
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diff --git a/testdata/dnn/onnx/generate_onnx_models.py b/testdata/dnn/onnx/generate_onnx_models.py
index 9b6f45604..9ca637ce0 100644
--- a/testdata/dnn/onnx/generate_onnx_models.py
+++ b/testdata/dnn/onnx/generate_onnx_models.py
@@ -944,15 +944,33 @@ def forward(self, x):
 model = Power(2)
 save_data_and_model("pow2", x, model)
 
-class ReduceMax(nn.Module):
+class ReduceMaxGlobal(nn.Module):
   def forward(self, x):
     out = torch.max(x)
     return torch.unsqueeze(out, 0)
 
 x = Variable(torch.randn(1, 3, 2, 2))
-model = ReduceMax()
+model = ReduceMaxGlobal()
 save_data_and_model("reduce_max", x, model)
 
+class ReduceMax(nn.Module):
+      def __init__(self, axes):
+    super(ReduceMax, self).__init__()
+    self.axes = axes
+
+  def forward(self, x):
+    # torch.return_types.max(values, indices)
+    out = torch.max(x, dim=self.axes, keepdim=False)[0]
+    return out
+
+x = Variable(torch.randn(1, 3, 2, 2))
+
+model = ReduceMax(axes=0)
+save_data_and_model("reduce_max_axis_0", x, model)
+
+model = ReduceMax(axes=1)
+save_data_and_model("reduce_max_axis_1", x, model)
+
 class ResizeConv(nn.Module):
     def __init__(
             self,
diff --git a/testdata/dnn/onnx/models/reduce_max_axis_0.onnx b/testdata/dnn/onnx/models/reduce_max_axis_0.onnx
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index 000000000..f844fd016
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diff --git a/testdata/dnn/onnx/models/reduce_max_axis_1.onnx b/testdata/dnn/onnx/models/reduce_max_axis_1.onnx
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index 000000000..0c34b9fef
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