Update default NNCF configurations (#824)

* Add configs from 143530

* Fix wrong AWQ option

* Apply comment

* Add test

* Add missed configuration

* Apply comment

Author: nikita-malininn

optimum/intel/openvino/configuration.py

@@ -32,19 +32,25 @@
 
 logger = logging.getLogger(__name__)
 
+
+class OVQuantizationMethod(str, Enum):
+    DEFAULT = "default"
+    HYBRID = "hybrid"
+    AWQ = "awq"
+
+
 _DEFAULT_4BIT_CONFIGS = {
-    "databricks/dolly-v2-3b": {"bits": 4, "sym": False, "group_size": 128, "ratio": 0.8},
+    "databricks/dolly-v2-3b": {"bits": 4, "sym": False, "group_size": 128, "scale_estimation": True},
     "EleutherAI/gpt-j-6b": {"bits": 4, "sym": False, "group_size": 64},
     "facebook/opt-6.7b": {"bits": 4, "sym": False, "group_size": 64, "ratio": 0.8},
-    "bigscience/bloomz-7b1": {"bits": 4, "sym": False, "group_size": 32, "ratio": 0.6},
     "togethercomputer/RedPajama-INCITE-7B-Instruct": {"bits": 4, "sym": False, "group_size": 128},
     "HuggingFaceH4/zephyr-7b-beta": {
         "bits": 4,
         "sym": True,
         "group_size": 128,
         "ratio": 0.8,
         "dataset": "wikitext2",
-        "awq": True,
+        "quant_method": OVQuantizationMethod.AWQ,
     },
     "meta-llama/Llama-2-7b": {"bits": 4, "sym": True, "group_size": 128, "ratio": 0.6},
     "meta-llama/Llama-2-7b-chat": {"bits": 4, "sym": True, "group_size": 128, "ratio": 0.8},
@@ -55,21 +61,21 @@
         "group_size": 64,
         "ratio": 0.8,
         "dataset": "wikitext2",
-        "awq": True,
+        "quant_method": OVQuantizationMethod.AWQ,
     },
     "stabilityai/stablelm-zephyr-3b": {
         "bits": 4,
         "sym": False,
         "group_size": 128,
         "ratio": 1.0,
         "dataset": "wikitext2",
-        "awq": True,
+        "quant_method": OVQuantizationMethod.AWQ,
     },
     "stabilityai/stable-code-3b": {"bits": 4, "sym": True, "group_size": 64, "ratio": 0.8},
     "pansophic/rocket-3B": {"bits": 4, "sym": True, "group_size": 128, "ratio": 0.8},
     "THUDM/chatglm2-6b": {"bits": 4, "sym": True, "group_size": 128, "ratio": 0.72},
     "Qwen/Qwen-7B-Chat": {"bits": 4, "sym": True, "group_size": 128, "ratio": 0.6},
-    "openlm-research/open_llama_3b": {"bits": 4, "sym": True, "group_size": 64, "all_layers": True},
+    "openlm-research/open_llama_3b": {"bits": 4, "sym": False, "group_size": 64, "all_layers": True},
     "openlm-research/open_llama_3b_v2": {"bits": 4, "sym": True, "group_size": 64, "all_layers": True},
     "tiiuae/falcon-7b-instruct": {"bits": 4, "sym": True, "group_size": 64, "all_layers": True},
     "psmathur/orca_mini_3b": {
@@ -78,19 +84,24 @@
         "group_size": 64,
         "all_layers": True,
         "dataset": "wikitext2",
-        "awq": True,
+        "quant_method": OVQuantizationMethod.AWQ,
     },
     "bigscience/bloomz-560m": {
         "bits": 4,
         "sym": True,
         "group_size": 64,
         "ratio": 0.8,
         "dataset": "wikitext2",
-        "awq": True,
+        "quant_method": OVQuantizationMethod.AWQ,
     },
     "mistralai/Mixtral-8x7B-v0.1": {"bits": 4, "sym": True, "group_size": 128, "ratio": 0.8},
     "facebook/opt-2.7b": {"bits": 4, "sym": True, "group_size": 128, "ratio": 0.7},
-    "togethercomputer/RedPajama-INCITE-Chat-3B-v1": {"bits": 4, "sym": False, "group_size": 128, "ratio": 0.8},
+    "togethercomputer/RedPajama-INCITE-Chat-3B-v1": {
+        "bits": 4,
+        "sym": False,
+        "group_size": 128,
+        "scale_estimation": True,
+    },
     "lmsys/vicuna-7b-v1.5": {"bits": 4, "sym": False, "group_size": 128, "ratio": 1.0},
     "stabilityai/stablelm-tuned-alpha-3b": {"bits": 4, "sym": False, "group_size": 128, "ratio": 0.8},
     "mistralai/Mistral-7B-v0.1": {"bits": 4, "sym": True, "group_size": 128, "ratio": 0.9},
@@ -100,8 +111,20 @@
         "group_size": 128,
         "ratio": 0.8,
         "dataset": "wikitext2",
-        "awq": True,
+        "quant_method": OVQuantizationMethod.AWQ,
     },
+    "openai-community/gpt2": {"bits": 4, "sym": False, "group_size": 128, "ratio": 0.5, "scale_estimation": True},
+    "lmsys/longchat-7b-16k": {"bits": 4, "sym": False, "group_size": 128, "ratio": 0.9},
+    "bigcode/starcoder2-3b": {"bits": 4, "sym": False, "group_size": 128, "ratio": 0.9},
+    "TinyLlama/TinyLlama-1.1B-Chat-v1.0": {"bits": 4, "sym": False, "group_size": 128, "ratio": 0.8},
+    "stabilityai/stablelm-tuned-alpha-7b": {
+        "bits": 4,
+        "sym": False,
+        "group_size": 128,
+        "ratio": 0.6,
+        "scale_estimation": True,
+    },
+    "microsoft/phi-2": {"bits": 4, "sym": False, "group_size": 128, "ratio": 0.9},
 }
 
 _DEFAULT_4BIT_CONFIG = {
@@ -113,12 +136,6 @@
 }
 
 
-class OVQuantizationMethod(str, Enum):
-    DEFAULT = "default"
-    HYBRID = "hybrid"
-    AWQ = "awq"
-
-
 @dataclass
 class OVQuantizationConfigBase(QuantizationConfigMixin):
     """

tests/openvino/test_quantization.py

@@ -61,7 +61,13 @@
     OVWeightQuantizationConfig,
     OVDynamicQuantizationConfig,
 )
-from optimum.intel.openvino.configuration import OVQuantizationMethod, OVQuantizationConfigBase
+from optimum.intel.openvino.configuration import (
+    OVQuantizationMethod,
+    OVQuantizationConfigBase,
+    _DEFAULT_4BIT_CONFIGS,
+    _DEFAULT_4BIT_CONFIG,
+)
+from copy import deepcopy
 
 from optimum.intel.openvino.quantization import InferRequestWrapper
 from optimum.intel.utils.import_utils import is_openvino_version, is_transformers_version
@@ -820,6 +826,13 @@ class OVQuantizationConfigTest(unittest.TestCase):
         (dict(bits=8, fast_bias_correction=True, weight_only=False), OVQuantizationConfig, None),
     )
 
+    def get_default_configurations() -> dict:
+        default_configurations = deepcopy(_DEFAULT_4BIT_CONFIGS)
+        default_configurations.update({"default": _DEFAULT_4BIT_CONFIG})
+        return default_configurations
+
+    DEFAULT_CONFIGURATIONS = get_default_configurations()
+
     @parameterized.expand(QUANTIZATION_CONFIGS)
     def test_config_serialization(self, quantization_config: OVQuantizationConfigBase):
         ov_config = OVConfig(quantization_config=quantization_config)
@@ -849,6 +862,14 @@ def test_config_from_dict(self, quantization_config: dict, config_type: type, wa
             if hasattr(ov_config.quantization_config, k):
                 self.assertEqual(getattr(ov_config.quantization_config, k), v)
 
+    @parameterized.expand(DEFAULT_CONFIGURATIONS)
+    def test_named_default_configurations(self, config_id: str):
+        custom_configuration = self.DEFAULT_CONFIGURATIONS[config_id]
+        prepared_config = OVModelForCausalLM._prepare_weight_quantization_config(custom_configuration)
+        for field_name, reference_value in custom_configuration.items():
+            value = prepared_config.__getattribute__(field_name)
+            self.assertEqual(value, reference_value)
+
 
 class InferRequestWrapperTest(unittest.TestCase):
     MODEL_ID = ("openai/whisper-tiny.en",)