I am trying to understand a model implementation where there is this following layer. I don’t understand what the last line means.
class Model(nn.Module):
    def __init__(self,
                 num_class,
                 num_point,
                 num_person,
                 num_gcn_scales,
                 num_g3d_scales,
                 graph,
                 in_channels=3):
        super(Model, self).__init__()

        Graph = import_class(graph)
        A_binary = Graph().A_binary
        
        self.sgcn2 = nn.Sequential(
        MS_GCN(num_gcn_scales, c1, c1, A_binary, disentangled_agg=True),
        MS_TCN(c1, c2, stride=2),
        MS_TCN(c2, c2))
        self.sgcn2[-1].act = nn.Identity()

It looks like the model first perform spatial graph convolution followed by two temporal convolution. But what happens with this line       self.sgcn2[-1].act = nn.Identity()
Your suggestions will greatly help. Thanks.