Replace method

openvinotoolkit · Oct 17, 2023 · 90dc04e · 90dc04e
1 parent 19f7cb1
commit 90dc04e
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Showing 4 changed files with 33 additions and 30 deletions.
diff --git a/nncf/quantization/algorithms/post_training/algorithm.py b/nncf/quantization/algorithms/post_training/algorithm.py
@@ -90,7 +90,7 @@ def __init__(
 
         sq_params = advanced_parameters.smooth_quant_params
 
-        if model_type == ModelType.TRANSFORMER and sq_params.convolution >= 0 and sq_params.matmul >= 0:
+        if model_type == ModelType.TRANSFORMER and (sq_params.convolution >= 0 or sq_params.matmul >= 0):
             alpha_map = {"convolution": sq_params.convolution, "matmul": sq_params.matmul}
             smooth_quant_algorithm = SmoothQuant(
                 subset_size=subset_size, inplace_statistics=advanced_parameters.inplace_statistics, alpha_map=alpha_map

diff --git a/nncf/quantization/algorithms/smooth_quant/algorithm.py b/nncf/quantization/algorithms/smooth_quant/algorithm.py
@@ -74,7 +74,6 @@ def __init__(
         self._backend_entity = None
         self._algorithm_key = f"SQ_{hash(self)}"
         self._cached_multiply_names = Counter()
-        self._validate_alpha_map(alpha_map)
         self._alpha_map = alpha_map
 
     @property
@@ -97,16 +96,6 @@ def _set_backend_entity(self, model: TModel) -> None:
                 "Cannot return backend-specific entity because {} is not supported!".format(model_backend.value)
             )
 
-    def _validate_alpha_map(self, alpha_map: Dict[str, float]) -> None:
-        """
-        Validates the alpha map for case of the negative value.
-
-        :param alpha_map: Map for the validation.
-        """
-        for layer_type, alpha_value in alpha_map.items():
-            if alpha_value < 0:
-                raise RuntimeError(f"Smooth Quant algorithm does not support negative parameter for {layer_type}!")
-
     def apply(
         self,
         model: TModel,
@@ -115,7 +104,7 @@ def apply(
         dataset: Optional[Dataset] = None,
     ) -> TModel:
         self._set_backend_entity(model)
-        alpha_map = self._backend_entity.get_alpha_map(self._alpha_map)
+        alpha_map = self._get_alpha_map()
 
         nodes_to_smooth_data = self._get_nodes_to_smooth_data(graph, alpha_map.keys())
         model_transformer = ModelTransformerFactory.create(model)
@@ -238,7 +227,7 @@ def get_statistic_points(self, model: TModel, graph: NNCFGraph) -> StatisticPoin
         statistic_container = StatisticPointsContainer()
 
         self._set_backend_entity(model)
-        alpha_map = self._backend_entity.get_alpha_map(self._alpha_map)
+        alpha_map = self._get_alpha_map()
 
         nodes_to_smooth_data = self._get_nodes_to_smooth_data(graph, alpha_map.keys())
 
@@ -377,3 +366,25 @@ def _create_scale_node_name(self, source_name: str, source_port_id: int) -> str:
         unique_index = self._cached_multiply_names[scale_node_name]
         self._cached_multiply_names[scale_node_name] += 1
         return f"{scale_node_name}_{unique_index}/sq_multiply"
+
+    def _get_alpha_map(self) -> Dict[OperatorMetatype, float]:
+        """
+        Returns alpha map by metatypes.
+
+        :return: Alpha map by metatypes.
+        """
+        alpha_by_metatype_map = {}
+        name_to_metatype = {
+            "convolution": self._backend_entity.convolution_metatype,
+            "matmul": self._backend_entity.matmul_metatype,
+        }
+        for type_name, alpha_value in self._alpha_map.items():
+            if alpha_value < 0:
+                nncf_logger.debug(
+                    f"Smooth Quant algorithm does not support negative parameter for {type_name}! "
+                    "Skipping these layers."
+                )
+                continue
+            metatype = name_to_metatype[type_name]
+            alpha_by_metatype_map[metatype] = alpha_value
+        return alpha_by_metatype_map
diff --git a/nncf/quantization/algorithms/smooth_quant/backend.py b/nncf/quantization/algorithms/smooth_quant/backend.py
@@ -28,21 +28,6 @@
 
 
 class SmoothQuantAlgoBackend(ABC):
-    def get_alpha_map(self, alpha_map: Dict[str, float]) -> Dict[OperatorMetatype, float]:
-        """
-        Returns alpha map by metatypes.
-
-        :param convolution_alpha: Alpha value for Convolution layers.
-        :param matmul_alpha: Alpha value for MatMul layers.
-        :return: Alpha map by metatypes.
-        """
-        alpha_by_metatype_map = {}
-        name_to_metatype = {"convolution": self.convolution_metatype, "matmul": self.matmul_metatype}
-        for type_name, alpha_value in alpha_map.items():
-            metatype = name_to_metatype[type_name]
-            alpha_by_metatype_map[metatype] = alpha_value
-        return alpha_by_metatype_map
-
     @property
     @abstractmethod
     def convolution_metatype(self) -> OperatorMetatype:

diff --git a/tests/post_training/model_scope.py b/tests/post_training/model_scope.py
@@ -13,6 +13,8 @@
 
 from nncf import ModelType
 from nncf import QuantizationPreset
+from nncf.quantization.advanced_parameters import AdvancedQuantizationParameters
+from nncf.quantization.advanced_parameters import AdvancedSmoothQuantParameters
 from tests.post_training.pipelines.base import ALL_PTQ_BACKENDS
 from tests.post_training.pipelines.base import NNCF_PTQ_BACKENDS
 from tests.post_training.pipelines.base import BackendType
@@ -52,6 +54,9 @@
         "ptq_params": {
             "preset": QuantizationPreset.MIXED,
             "model_type": ModelType.TRANSFORMER,
+            "advanced_parameters": AdvancedQuantizationParameters(
+                smooth_quant_params=AdvancedSmoothQuantParameters(matmul=-1.0)
+            ),
         },
         "backends": [BackendType.TORCH, BackendType.ONNX, BackendType.OV, BackendType.POT],
     },
@@ -71,6 +76,9 @@
         "ptq_params": {
             "preset": QuantizationPreset.MIXED,
             "model_type": ModelType.TRANSFORMER,
+            "advanced_parameters": AdvancedQuantizationParameters(
+                smooth_quant_params=AdvancedSmoothQuantParameters(matmul=-1.0)
+            ),
         },
         "backends": ALL_PTQ_BACKENDS,
     },
@@ -143,7 +151,6 @@
         "ptq_params": {
             "preset": QuantizationPreset.MIXED,
             "model_type": ModelType.TRANSFORMER,
-            # "advanced_parameters": AdvancedQuantizationParameters(smooth_quant_alpha=0.05),
         },
         "backends": [BackendType.TORCH, BackendType.ONNX, BackendType.OV],
     },