[quant][be] Add a test for per channel quant for groupwise conv (#115224)

Summary:
just making sure this works

Test Plan:
python test/test_quantization.py -k test_groupwise_per_channel_quant

Reviewers:

Subscribers:

Tasks:

Tags:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/115224
Approved by: https://github.com/andrewor14

test/quantization/pt2e/test_quantize_pt2e.py

@@ -1752,3 +1752,13 @@ class TestQuantizePT2E(PT2EQuantizationTestCase):
         self.checkGraphModuleNodes(
             m, expected_node_occurrence=node_occurrence, expected_node_list=node_list
         )
+
+    def test_groupwise_per_channel_quant(self):
+        m = TestHelperModules.GroupwiseConv2d()
+        quantizer = XNNPACKQuantizer()
+        operator_config = get_symmetric_quantization_config(is_per_channel=True)
+        quantizer.set_global(operator_config)
+        example_inputs = m.example_inputs()
+        m = self._quantize(m, quantizer, example_inputs)
+        # make sure it runs
+        m(*example_inputs)

torch/testing/_internal/common_quantization.py

@@ -2667,3 +2667,14 @@ class TestHelperModules:
             permute_out = torch.permute(x, (0, 2, 3, 1))
             linear_out = self.linear(permute_out)
             return linear_out
+
+    class GroupwiseConv2d(torch.nn.Module):
+        def __init__(self):
+            super().__init__()
+            self.conv = torch.nn.Conv2d(4, 4, 3, groups=2)
+
+        def forward(self, x):
+            return self.conv(x)
+
+        def example_inputs(self):
+            return (torch.randn(2, 4, 10, 10),)