Address review comments

Author: aobolensk

src/nncf/experimental/torch/fx/quantization/quantize_model.py

@@ -38,6 +38,7 @@
 from nncf.parameters import TargetDevice
 from nncf.quantization.advanced_parameters import AdvancedCompressionParameters
 from nncf.quantization.advanced_parameters import AdvancedQuantizationParameters
+from nncf.quantization.advanced_parameters import is_weight_compression_needed
 from nncf.quantization.algorithms.post_training.algorithm import PostTrainingQuantization
 from nncf.quantization.algorithms.weight_compression.algorithm import WeightCompression
 from nncf.scopes import IgnoredScope
@@ -92,7 +93,7 @@ def quantize_impl(
     nncf_graph = NNCFGraphFactory.create(copied_model)
     quantized_model = quantization_algorithm.apply(copied_model, nncf_graph, dataset=calibration_dataset)
 
-    if advanced_parameters is None or advanced_parameters.is_weight_compression_needed():
+    if is_weight_compression_needed(advanced_parameters):
         compress_post_quantize_transformation(quantized_model)
     else:
         fq_weights_transformation(quantized_model)

src/nncf/openvino/quantization/quantize_model.py

@@ -41,6 +41,7 @@
 from nncf.quantization.advanced_parameters import AdvancedCompressionParameters
 from nncf.quantization.advanced_parameters import AdvancedQuantizationParameters
 from nncf.quantization.advanced_parameters import convert_to_dict_recursively
+from nncf.quantization.advanced_parameters import is_weight_compression_needed
 from nncf.quantization.algorithms.accuracy_control.algorithm import QuantizationAccuracyRestorer
 from nncf.quantization.algorithms.accuracy_control.algorithm import calculate_accuracy_drop
 from nncf.quantization.algorithms.accuracy_control.evaluator import Evaluator
@@ -121,7 +122,7 @@ def _extract_all_subgraphs(model: ov.Model, current_id: str) -> None:
         quantization_algorithm, model, graphs, main_model_graph_id, calibration_dataset, subset_size, 1
     )
 
-    if advanced_parameters is None or advanced_parameters.is_weight_compression_needed():
+    if is_weight_compression_needed(advanced_parameters):
         compress_quantize_weights_transformation(quantized_model)
 
     dump_parameters(
@@ -168,7 +169,7 @@ def native_quantize_impl(
     warning_model_no_batchwise_support(graph, advanced_parameters, model_type, OPERATIONS_OUTPUT_HAS_NO_BATCH_AXIS)
     quantized_model = quantization_algorithm.apply(model, graph, dataset=calibration_dataset)
 
-    if advanced_parameters is None or advanced_parameters.is_weight_compression_needed():
+    if is_weight_compression_needed(advanced_parameters):
         compress_quantize_weights_transformation(quantized_model)
 
     dump_parameters(
@@ -214,7 +215,7 @@ def quantize_with_accuracy_control_impl(
     else:
         copied_parameters = deepcopy(advanced_quantization_parameters)
 
-    compress_weights = copied_parameters.is_weight_compression_needed()
+    compress_weights = is_weight_compression_needed(copied_parameters)
     copied_parameters.backend_params[AdvancedQuantizationParameters.COMPRESS_WEIGHTS] = False
 
     quantized_model = quantize_impl(

src/nncf/quantization/advanced_parameters.py

@@ -256,6 +256,10 @@ class AdvancedQuantizationParameters:
     :type smooth_quant_alpha: float
     :param backend_params: Backend-specific parameters.
     :type backend_params: dict[str, Any]
+    :param COMPRESS_WEIGHTS: A key in the `backend_params` dictionary that indicates whether
+        weight compression should be applied. If set to False, weight compression is disabled.
+        By default, weight compression is enabled (True).
+    :type COMPRESS_WEIGHTS: str
     """
 
     # General parameters
@@ -289,18 +293,19 @@ class AdvancedQuantizationParameters:
     # Backend parameter names
     COMPRESS_WEIGHTS = "compress_weights"
 
-    def is_weight_compression_needed(self) -> bool:
-        """
-        Determine whether weight compression is needed based on advanced quantization parameters.
 
-        If `advanced_parameters` or its `backend_params` are not provided, defaults to True.
+def is_weight_compression_needed(advanced_parameters: Optional[AdvancedQuantizationParameters]) -> bool:
+    """
+    Determine whether weight compression is needed based on advanced quantization parameters.
+
+    If `advanced_parameters` or its `backend_params` are not provided, defaults to True.
 
-        :param advanced_parameters: Advanced quantization parameters.
-        :return: True if weight compression is needed, False otherwise.
-        """
-        if self.backend_params is not None:
-            return bool(self.backend_params.get(AdvancedQuantizationParameters.COMPRESS_WEIGHTS, True))
-        return True
+    :param advanced_parameters: Advanced quantization parameters.
+    :return: True if weight compression is needed, False otherwise.
+    """
+    if advanced_parameters.backend_params is not None:
+        return bool(advanced_parameters.backend_params.get(AdvancedQuantizationParameters.COMPRESS_WEIGHTS, True))
+    return True
 
 
 @api()