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nncf/openvino/graph/layer_attributes.py

@@ -84,6 +84,12 @@ def get_backend_agnostic_attributes(self):
 
 
 def get_conv_weights_layout_from_node(node: NNCFNode) -> OVConvLayout:
+    """
+    Calculates weights layout for a target convolution node.
+
+    :param node: Target convolution node.
+    :return: Target convolution Node weights layout.
+    """
     layer_attributes = node.layer_attributes
     port_id = _get_port_id_from_layer_attributes(layer_attributes)
     return get_conv_weights_layout(
@@ -92,6 +98,12 @@ def get_conv_weights_layout_from_node(node: NNCFNode) -> OVConvLayout:
 
 
 def get_linear_weights_layout_from_node(node: NNCFNode) -> OVConvLayout:
+    """
+    Calculates weights layout for a target linear node.
+
+    :param node: Target linear node.
+    :return: Target linear Node weight layout.
+    """
     layer_attributes = node.layer_attributes
     port_id = _get_port_id_from_layer_attributes(layer_attributes)
     constant_layer_attrs = layer_attributes.constant_attributes[port_id]
@@ -102,20 +114,34 @@ def get_linear_weights_layout_from_node(node: NNCFNode) -> OVConvLayout:
     )
 
 
-def _get_port_id_from_layer_attributes(layer_attributes):
+def _get_port_id_from_layer_attributes(layer_attributes) -> int:
     port_ids = list(layer_attributes.constant_attributes.keys())
     assert len(port_ids) == 1
     return port_ids[0]
 
 
 def get_conv_weights_layout(ov_metatype: OVOpMetatype, weights_shape: Tuple[int, ...]) -> OVConvLayout:
+    """
+    Calculates weights layout for a target convolution node.
+
+    :param ov_metatype: Target convolution node OpenVINO metatype.
+    :param weights_shape: Shape of the target convolution node weight.
+    :return: Target convolution node weights layout.
+    """
     weights_layout = ov_metatype.const_layout
     kernel_size = weights_shape[len(weights_layout) :]
     weights_layout += [OVConvLayoutElem.SPATIAL] * len(kernel_size)
     return tuple(weights_layout)
 
 
 def get_linear_weights_layout(weights_shape: Tuple[int, ...], transpose: bool, port_id: int) -> OVConvLayout:
+    """
+    Calculates weights layout for a target linear node.
+
+    :param weights_shape: Shape of the target linear node weight.
+    :param port_id: Port id of the target liner node weights.
+    :return: Target linear node weight layout.
+    """
     weights_layout = [OVConvLayoutElem.SPATIAL] * (len(weights_shape) - 2)
     if len(weights_shape) > 1:
         if (transpose and port_id == 0) or (not transpose and port_id == 1):

nncf/quantization/algorithms/channel_alignment/algorithm.py

@@ -390,10 +390,10 @@ def get_statistic_points(self, model: TModel, graph: NNCFGraph) -> StatisticPoin
 
             channel_axis = conv_in.metatype.output_channel_axis
             activation_shape = list(range(len(graph.get_output_edges(node_in)[0].tensor_shape)))
-            reduction_shape = self._backend_entity.get_channel_agnostic_reduction_axes([channel_axis], activation_shape)
+            reduction_axes = self._backend_entity.get_channel_agnostic_reduction_axes([channel_axis], activation_shape)
 
             statistic_collector = self._backend_entity.get_statistic_collector(
-                tuple(reduction_shape), self._quantile, self.subset_size, self.inplace_statistics
+                reduction_axes, self._quantile, self.subset_size, self.inplace_statistics
             )
             statistic_container.add_statistic_point(
                 StatisticPoint(

nncf/quantization/algorithms/channel_alignment/backend.py

@@ -11,13 +11,12 @@
 
 from abc import abstractmethod
 from dataclasses import dataclass
-from typing import Any, Optional, Tuple, TypeVar
+from typing import Any, Tuple, TypeVar
 
 import numpy as np
 
 from nncf.common.graph import NNCFGraph
 from nncf.common.graph import NNCFNode
-from nncf.common.graph.layer_attributes import ConvolutionLayerAttributes
 from nncf.common.graph.transformations.commands import TargetPoint
 from nncf.common.graph.transformations.commands import TargetType
 from nncf.common.tensor_statistics.collectors import TensorStatisticCollectorBase