FIX: Broken repr of TorchAoConfig (#34560)

FIX Broken repr of TorchAoConfig

The __repr__ method references a non-existent self.kwargs. This is now
fixed.

There does not appear to be a uniform way of defining __repr__ for
quantization configs. I copied the method as implemented for HQQ:

https://github.com/huggingface/transformers/blob/e2ac16b28a0b8b900e136750309ca40c49d975c5/src/transformers/utils/quantization_config.py#L285-L287

src/transformers/utils/quantization_config.py

@@ -1309,7 +1309,8 @@ def get_apply_tensor_subclass(self):
         return _STR_TO_METHOD[self.quant_type](**self.quant_type_kwargs)
 
     def __repr__(self):
-        return f"{self.quant_type}({', '.join(str(k) + '=' + str(v) for k, v in self.kwargs.items())})"
+        config_dict = self.to_dict()
+        return f"{self.__class__.__name__} {json.dumps(config_dict, indent=2, sort_keys=True)}\n"
 
 
 @dataclass

tests/quantization/torchao_integration/test_torchao.py

@@ -74,6 +74,13 @@ def test_post_init_check(self):
         with self.assertRaisesRegex(ValueError, "Unexpected keyword arg"):
             _ = TorchAoConfig("int4_weight_only", group_size1=32)
 
+    def test_repr(self):
+        """
+        Check that there is no error in the repr
+        """
+        quantization_config = TorchAoConfig("int4_weight_only", modules_to_not_convert=["conv"], group_size=8)
+        repr(quantization_config)
+
 
 @require_torch_gpu
 @require_torchao