def __init__()

in simsiam/builder.py [0:0]

• 17 lines of code
• 1 McCabe index (conditional complexity)

    def __init__(self, base_encoder, dim=2048, pred_dim=512):
        """
        dim: feature dimension (default: 2048)
        pred_dim: hidden dimension of the predictor (default: 512)
        """
        super(SimSiam, self).__init__()

        # create the encoder
        # num_classes is the output fc dimension, zero-initialize last BNs
        self.encoder = base_encoder(num_classes=dim, zero_init_residual=True)

        # build a 3-layer projector
        prev_dim = self.encoder.fc.weight.shape[1]
        self.encoder.fc = nn.Sequential(nn.Linear(prev_dim, prev_dim, bias=False),
                                        nn.BatchNorm1d(prev_dim),
                                        nn.ReLU(inplace=True), # first layer
                                        nn.Linear(prev_dim, prev_dim, bias=False),
                                        nn.BatchNorm1d(prev_dim),
                                        nn.ReLU(inplace=True), # second layer
                                        self.encoder.fc,
                                        nn.BatchNorm1d(dim, affine=False)) # output layer
        self.encoder.fc[6].bias.requires_grad = False # hack: not use bias as it is followed by BN

        # build a 2-layer predictor
        self.predictor = nn.Sequential(nn.Linear(dim, pred_dim, bias=False),
                                        nn.BatchNorm1d(pred_dim),
                                        nn.ReLU(inplace=True), # hidden layer
                                        nn.Linear(pred_dim, dim)) # output layer