def METHOD_NAME(x, node_c):
    '''Returns the weights of dropping each feature. Meant to be used for sparse one-hot features only.
    Args:
        x (torch.Tensor): Tensor of shape [n_nodes, n_features] representing node features
        node_c (torch.Tensor): Tensor of shape [n_nodes] represnting node centralities
    Returns:
        A Tensor of shape [n_features] representing the weights for dropping each feature
    '''
    x = x.to(torch.bool).to(torch.float32)
    w = x.t() @ node_c
    w = w.log()
    s = (w.max() - w) / (w.max() - w.mean())
    return s