def init_model()

in models/modules/nn_base.py [0:0]

• 21 lines of code
• 10 McCabe index (conditional complexity)

    def init_model(self, model_init):
        """ Conv2d, BatchNorm2d, BatchNorm1d, Linear, """
        for m in self.modules():
            if isinstance(m, nn.Conv2d):
                if model_init == 'he_fout':
                    n = m.kernel_size[0] * m.kernel_size[1] * m.out_channels
                    m.weight.data.normal_(0, math.sqrt(2. / n))
                elif model_init == 'he_fin':
                    n = m.kernel_size[0] * m.kernel_size[1] * m.in_channels
                    m.weight.data.normal_(0, math.sqrt(2. / n))
                else:
                    raise NotImplementedError
                if m.bias is not None:
                    m.bias.data.zero_()
            elif isinstance(m, nn.BatchNorm2d) or isinstance(m, nn.BatchNorm1d):
                m.weight.data.fill_(1)
                m.bias.data.zero_()
            elif isinstance(m, nn.Linear):
                stdv = 1. / math.sqrt(m.weight.size(1))
                m.weight.data.uniform_(-stdv, stdv)
                if m.bias is not None:
                    m.bias.data.zero_()