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.