[ONNX] Add test case for onnx::Max scalar type (#88751)

Referenced by minimum cases
Pull Request resolved: #88751
Approved by: https://github.com/wschin, https://github.com/BowenBao

test/onnx/test_pytorch_onnx_onnxruntime.py

@@ -8728,6 +8728,28 @@ def forward(self, x, y):
         y = torch.full_like(x, True)
         self.run_test(MinimumModel(), (x, y))
 
+    @skipIfUnsupportedMinOpsetVersion(12)
+    def test_maximum_dtypes(self):
+        class MaximumModel(torch.nn.Module):
+            def forward(self, x, y):
+                return torch.maximum(x, y)
+
+        x = torch.randn((5, 5), dtype=torch.float16)
+        y = torch.randn((5, 5), dtype=torch.float)
+        self.run_test(MaximumModel(), (x, y))
+
+        x = torch.randn((5, 5), dtype=torch.float16)
+        y = torch.randint(10, (5, 5), dtype=torch.int16)
+        self.run_test(MaximumModel(), (x, y))
+
+        x = torch.randint(10, (5, 5), dtype=torch.int16)
+        y = torch.randint(10, (5, 5), dtype=torch.int32)
+        self.run_test(MaximumModel(), (x, y))
+
+        x = torch.randint(10, (5, 5), dtype=torch.int)
+        y = torch.full_like(x, True)
+        self.run_test(MaximumModel(), (x, y))
+
     @skipIfUnsupportedMinOpsetVersion(9)
     def test_any(self):
         class M(torch.nn.Module):