renaming rest

Author: jerryzh168

test/quantization/test_quant_api.py

@@ -946,7 +946,7 @@ def test_workflow_e2e_numerics(self, config):
         assert sqnr >= 16.5, f"SQNR {sqnr} is too low"
 
     @unittest.skipIf(not torch.cuda.is_available(), "Need CUDA available")
-    def test_ao_per_module_config_default(self):
+    def test_module_fqn_to_config_default(self):
         config1 = Int4WeightOnlyConfig(group_size=32)
         config2 = Int8WeightOnlyConfig()
         config = ModuleFqnToConfig({"_default": config1, "linear2": config2})
@@ -960,7 +960,7 @@ def test_ao_per_module_config_default(self):
         assert isinstance(model.linear2.weight._layout, PlainLayout)
 
     @unittest.skipIf(not torch.cuda.is_available(), "Need CUDA available")
-    def test_ao_per_module_config_module_name(self):
+    def test_module_fqn_to_config_module_name(self):
         config1 = Int4WeightOnlyConfig(group_size=32)
         config2 = Int8WeightOnlyConfig()
         config = ModuleFqnToConfig({"linear1": config1, "linear2": config2})
@@ -974,7 +974,7 @@ def test_ao_per_module_config_module_name(self):
         assert isinstance(model.linear2.weight._layout, PlainLayout)
 
     @unittest.skipIf(not TORCH_VERSION_AT_LEAST_2_6, "Need torch 2.6+")
-    def test_ao_per_module_config_embedding_linear(self):
+    def test_module_fqn_to_config_embedding_linear(self):
         weight_dtype = torch.int8
         granularity = PerGroup(8)
         mapping_type = MappingType.SYMMETRIC
@@ -1006,7 +1006,7 @@ def test_ao_per_module_config_embedding_linear(self):
         assert isinstance(model.linear.weight, LinearActivationQuantizedTensor)
 
     @unittest.skipIf(not torch.cuda.is_available(), "Need CUDA available")
-    def test_ao_per_module_config_skip(self):
+    def test_module_fqn_to_config_skip(self):
         config1 = Int4WeightOnlyConfig(group_size=32)
         config = ModuleFqnToConfig({"_default": config1, "linear2": None})
         model = ToyLinearModel().cuda().to(dtype=torch.bfloat16)

torchao/quantization/quant_api.py

@@ -599,7 +599,7 @@ def quantize_(
     if isinstance(config, ModuleFqnToConfig):
         _replace_with_custom_fn_if_matches_filter_with_name(
             model,
-            _ao_per_module_config_handler,
+            _module_fqn_to_config_handler,
             filter_fn,
             device=device,
             extra_args=(config,),
@@ -2024,7 +2024,7 @@ class ModuleFqnToConfig(AOBaseConfig):
     )
 
 
-def _ao_per_module_config_handler(
+def _module_fqn_to_config_handler(
     module: torch.nn.Module, module_fqn: str, config: ModuleFqnToConfig
 ):
     c = None