Fix ReLU fusion when conv/linear has > 1 user

Differential Revision: D65989599

Pull Request resolved: #6894

Author: mcr229

backends/xnnpack/test/ops/conv2d.py

@@ -394,3 +394,26 @@ def get_inputs(self):
             quant_config=get_symmetric_quantization_config(),
             conv_count=2,
         )
+
+    def test_qs8_conv2d_relu_multi_users(self):
+        class Conv2dReluMultiUsers(torch.nn.Module):
+            def __init__(self):
+                super().__init__()
+                self.conv1 = torch.nn.Conv2d(1, 1, 1)
+                self.conv2 = torch.nn.Conv2d(1, 64, 1)
+                self.relu = torch.nn.ReLU()
+
+            def forward(self, x):
+                conv_default = self.conv1(x)
+                y = self.relu(conv_default)
+                conv_default_2 = self.conv2(y)
+                return conv_default + conv_default_2
+
+            def get_inputs(self):
+                return (torch.randn(1, 1, 1, 1),)
+
+        self._test(
+            Conv2dReluMultiUsers(),
+            quant_config=get_symmetric_quantization_config(),
+            conv_count=2,
+        )