diff --git a/test/quantization/pt2e/test_quantize_pt2e_qat.py b/test/quantization/pt2e/test_quantize_pt2e_qat.py
index dfa53550fc84f..996824c0be9fd 100644
--- a/test/quantization/pt2e/test_quantize_pt2e_qat.py
+++ b/test/quantization/pt2e/test_quantize_pt2e_qat.py
@@ -347,11 +347,18 @@ def _verify_symmetric_xnnpack_qat_graph_helper(
         self.assertEqual(eps, 1e-5)
 
 
-class BaseTestQuantizePT2EQAT_ConvBn(PT2EQATTestCase):
+class TestQuantizePT2EQAT_ConvBn_Base(PT2EQATTestCase):
     """
     Base TestCase to be used for all conv-bn[-relu] fusion patterns.
     """
 
+    def setUp(self):
+        # NB: Skip the test if this is a base class, this is to handle the test
+        # discovery logic in buck which finds and runs all tests here including
+        # the base class which we don't want to run
+        if self.id() and "_Base" in self.id():
+            self.skipTest("Skipping test running from base class")
+
     def test_qat_conv_no_bias(self):
         m1 = self._get_conv_bn_model(has_conv_bias=False, has_bn=False, has_relu=True)
         m2 = self._get_conv_bn_model(has_conv_bias=False, has_bn=False, has_relu=False)
@@ -759,7 +766,7 @@ def test_qat_per_channel_weight_custom_dtype(self):
 
 # TODO: enable this in the next PR
 @skipIfNoQNNPACK
-class TestQuantizePT2EQAT_ConvBn1d(BaseTestQuantizePT2EQAT_ConvBn):
+class TestQuantizePT2EQAT_ConvBn1d(TestQuantizePT2EQAT_ConvBn_Base):
     dim = 1
     example_inputs = (torch.randn(1, 3, 5),)
     conv_class = torch.nn.Conv1d
@@ -767,7 +774,7 @@ class TestQuantizePT2EQAT_ConvBn1d(BaseTestQuantizePT2EQAT_ConvBn):
 
 
 @skipIfNoQNNPACK
-class TestQuantizePT2EQAT_ConvBn2d(BaseTestQuantizePT2EQAT_ConvBn):
+class TestQuantizePT2EQAT_ConvBn2d(TestQuantizePT2EQAT_ConvBn_Base):
     dim = 2
     example_inputs = (torch.randn(1, 3, 5, 5),)
     conv_class = torch.nn.Conv2d