user property instead

Author: a-r-r-o-w

tests/quantization/bnb/test_4bit.py

@@ -866,15 +866,17 @@ def test_fp4_double_safe(self):
 
 @require_torch_version_greater("2.7.1")
 class Bnb4BitCompileTests(QuantCompileTests):
-    quantization_config = PipelineQuantizationConfig(
-        quant_backend="bitsandbytes_8bit",
-        quant_kwargs={
-            "load_in_4bit": True,
-            "bnb_4bit_quant_type": "nf4",
-            "bnb_4bit_compute_dtype": torch.bfloat16,
-        },
-        components_to_quantize=["transformer", "text_encoder_2"],
-    )
+    @property
+    def quantization_config(self):
+        return PipelineQuantizationConfig(
+            quant_backend="bitsandbytes_8bit",
+            quant_kwargs={
+                "load_in_4bit": True,
+                "bnb_4bit_quant_type": "nf4",
+                "bnb_4bit_compute_dtype": torch.bfloat16,
+            },
+            components_to_quantize=["transformer", "text_encoder_2"],
+        )
 
     def test_torch_compile(self):
         torch._dynamo.config.capture_dynamic_output_shape_ops = True

tests/quantization/bnb/test_mixed_int8.py

@@ -831,11 +831,13 @@ def test_serialization_sharded(self):
 
 @require_torch_version_greater_equal("2.6.0")
 class Bnb8BitCompileTests(QuantCompileTests):
-    quantization_config = PipelineQuantizationConfig(
-        quant_backend="bitsandbytes_8bit",
-        quant_kwargs={"load_in_8bit": True},
-        components_to_quantize=["transformer", "text_encoder_2"],
-    )
+    @property
+    def quantization_config(self):
+        return PipelineQuantizationConfig(
+            quant_backend="bitsandbytes_8bit",
+            quant_kwargs={"load_in_8bit": True},
+            components_to_quantize=["transformer", "text_encoder_2"],
+        )
 
     def test_torch_compile(self):
         torch._dynamo.config.capture_dynamic_output_shape_ops = True

tests/quantization/test_torch_compile_utils.py

@@ -24,7 +24,11 @@
 @require_torch_gpu
 @slow
 class QuantCompileTests(unittest.TestCase):
-    quantization_config = None
+    @property
+    def quantization_config(self):
+        raise NotImplementedError(
+            "This property should be implemented in the subclass to return the appropriate quantization config."
+        )
 
     def setUp(self):
         super().setUp()

tests/quantization/torchao/test_torchao.py

@@ -631,11 +631,13 @@ def test_int_a16w8_cpu(self):
 
 @require_torchao_version_greater_or_equal("0.7.0")
 class TorchAoCompileTest(QuantCompileTests):
-    quantization_config = PipelineQuantizationConfig(
-        quant_mapping={
-            "transformer": TorchAoConfig(quant_type="int8_weight_only"),
-        },
-    )
+    @property
+    def quantization_config(self):
+        return PipelineQuantizationConfig(
+            quant_mapping={
+                "transformer": TorchAoConfig(quant_type="int8_weight_only"),
+            },
+        )
 
     def test_torch_compile(self):
         super()._test_torch_compile(quantization_config=self.quantization_config)