nncf/common/pruning/utils.py
def identity_mask_propagation(node: NNCFNode, graph: NNCFGraph) -> None:
    """
    Propagates input mask through NNCFNode.

    :param node: Graph node to perform identity mask propagation on.
    :param graph: Graph to work with.
    """
    input_masks = get_input_masks(node, graph)
    if not input_masks:
        # In case for disconnected NNCFGraph
        input_masks = [None]
    assert len(input_masks) == 1
    node.data['output_mask'] = input_masks[0]

    Propagates input mask through NNCFNode.

    :param node: Graph node to perform identity mask propagation on.
    :param graph: Graph to work with.
    
Propagates input mask through NNCFNode.
Propagates input mask through NNCFNode .
def identity_mask_propagation(node: NNCFNode, graph: NNCFGraph) -> None:
    input_masks = get_input_masks(node, graph)
    if not input_masks:
        input_masks = [None]
    assert len(input_masks) == 1
    node.data['output_mask'] = input_masks[0]
def identity_mask_propagation ( node : NNCFNode , graph : NNCFGraph ) -> None : input_masks = get_input_masks ( node , graph ) if not input_masks : input_masks = [ None ] assert len ( input_masks ) == 1 node . data [ 'output_mask' ] = input_masks [ 0 ]
Propagates input mask through NNCFNode.
Propagates input mask through NNCFNode .
"""
    Propagates input mask through NNCFNode.

    :param node: Graph node to perform identity mask propagation on.
    :param graph: Graph to work with.
    """ # In case for disconnected NNCFGraph
node
NNCFNode
Graph node to perform identity mask propagation on.
Graph node to perform identity mask propagation on .
graph
NNCFGraph
Graph to work with.
Graph to work with .