replace depreciated pydantic functions

src/compressed_tensors/compressors/model_compressors/model_compressor.py

@@ -137,7 +137,7 @@ def from_compression_config(
                 format, **sparsity_config
             )
         if quantization_config is not None:
-            quantization_config = QuantizationConfig.parse_obj(quantization_config)
+            quantization_config = QuantizationConfig.model_validate(quantization_config)
 
         return cls(
             sparsity_config=sparsity_config, quantization_config=quantization_config
@@ -193,7 +193,7 @@ def parse_sparsity_config(
 
         if is_compressed_tensors_config(compression_config):
             s_config = compression_config.sparsity_config
-            return s_config.dict() if s_config is not None else None
+            return s_config.model_dump() if s_config is not None else None
 
         return compression_config.get(SPARSITY_CONFIG_NAME, None)
 
@@ -214,7 +214,7 @@ def parse_quantization_config(
 
         if is_compressed_tensors_config(compression_config):
             q_config = compression_config.quantization_config
-            return q_config.dict() if q_config is not None else None
+            return q_config.model_dump() if q_config is not None else None
 
         quantization_config = deepcopy(compression_config)
         quantization_config.pop(SPARSITY_CONFIG_NAME, None)

src/compressed_tensors/quantization/quant_config.py

@@ -160,7 +160,7 @@ def model_post_init(self, __context):
 
     def to_dict(self):
         # for compatibility with HFQuantizer
-        return self.dict()
+        return self.model_dump()
 
     @staticmethod
     def from_pretrained(

tests/test_compressors/model_compressors/test_model_compressor.py

@@ -99,8 +99,8 @@ def test_hf_compressor_tensors_config(s_config, q_config, tmp_path):
     )
     q_config = QuantizationConfig(**q_config) if q_config is not None else None
 
-    s_config_dict = s_config.dict() if s_config is not None else None
-    q_config_dict = q_config.dict() if q_config is not None else None
+    s_config_dict = s_config.model_dump() if s_config is not None else None
+    q_config_dict = q_config.model_dump() if q_config is not None else None
 
     assert compressor.sparsity_config == s_config
     assert compressor.quantization_config == q_config

tests/test_quantization/lifecycle/test_apply.py

@@ -222,7 +222,7 @@ def get_sample_tinyllama_quant_config(status: str = "frozen"):
         },
         "ignore": ["LlamaRotaryEmbedding", "model.layers.1.mlp.down_proj"],
     }
-    return QuantizationConfig.parse_obj(config_dict)
+    return QuantizationConfig.model_validate(config_dict)
 
 
 @requires_accelerate()

tests/test_quantization/lifecycle/test_dynamic_lifecycle.py

@@ -110,4 +110,4 @@ def get_sample_dynamic_tinyllama_quant_config():
         },
         "ignore": ["LlamaRotaryEmbedding", "model.layers.1.mlp.down_proj"],
     }
-    return QuantizationConfig.parse_obj(config_dict)
+    return QuantizationConfig.model_validate(config_dict)

tests/test_quantization/test_quant_config.py

@@ -72,3 +72,10 @@ def test_load_scheme_from_preset(scheme_name: str):
     assert scheme_name in config.config_groups
     assert isinstance(config.config_groups[scheme_name], QuantizationScheme)
     assert config.config_groups[scheme_name].targets == targets
+
+
+def test_to_dict():
+    config_groups = {"group_1": QuantizationScheme(targets=[])}
+    config = QuantizationConfig(config_groups=config_groups)
+    reloaded = QuantizationConfig.model_validate(config.to_dict())
+    assert config == reloaded