def __init__()

in model.py [0:0]

• 20 lines of code
• 3 McCabe index (conditional complexity)

    def __init__(self, architecture=[512,512,512], lr=1e-4, n=4, loss=nn.BCEWithLogitsLoss(reduction='none'),
            embed_dim=32, topk_count=10, cuda=True):
        super().__init__()

        self.local_layers = nn.ModuleList()
        self.lr = lr
        self.topk_count = topk_count

        # embed bytes into an embed_dim space
        self.embed = nn.Embedding(257, embed_dim, max_norm=1, padding_idx=0)

        # several layers of conv1d followed by prelu activations.
        # use weight norm instead of batch norm. we're doing weird things that will
        # throw off batchnorm.
        prev_h = embed_dim
        for h in architecture:
            self.local_layers.append(nn.utils.weight_norm(nn.Conv1d(prev_h, h, n)))
            self.local_layers.append(nn.PReLU(h))

            prev_h = h

        self.out_layer = nn.Conv1d(prev_h, 1, 1)

        self.loss = loss
        self.opt = torch.optim.Adam(self.parameters(), lr=self.lr)
        self.sched = torch.optim.lr_scheduler.StepLR(self.opt, 1000, 0.95)

        self.use_cuda = cuda
        if self.use_cuda:
            self.cuda()

        print(self)