def _initialize_weights()

in models/networks/vgg.py [0:0]

• 41 lines of code
• 14 McCabe index (conditional complexity)

    def _initialize_weights(self):
        for m in self.modules():
            if isinstance(m, nn.Conv2d):
                if m.last_layer:
                    assert m.kernel_size == (1, 1)
                    # Fully Connected Layer
                    i = 1
                    while hasattr(m, f"weight{i}"):
                        weight = getattr(m, f"weight{i}")
                        weight.data.normal_(0, 0.01)
                        bias = getattr(m, f"bias{i}", None)
                        if bias is not None:
                            bias.data.zero_()
                        i += 1
                else:
                    n = m.kernel_size[0] * m.kernel_size[1] * m.out_channels
                    i = 1
                    while hasattr(m, f"weight{i}"):
                        weight = getattr(m, f"weight{i}")
                        weight.data.normal_(0, math.sqrt(2.0 / n))
                        bias = getattr(m, f"bias{i}", None)
                        if bias is not None:
                            bias.data.zero_()
                        i += 1

            elif isinstance(m, (nn.modules.batchnorm._NormBase, nn.GroupNorm)):
                i = 1
                while hasattr(m, f"weight{i}"):
                    weight = getattr(m, f"weight{i}")
                    weight.data.fill_(0.5)
                    bias = getattr(m, f"bias{i}", None)
                    if bias is not None:
                        bias.data.zero_()
                    i += 1
            elif isinstance(m, nn.Linear):
                i = 1
                while hasattr(m, f"weight{i}"):
                    weight = getattr(m, f"weight{i}")
                    weight.data.normal_(0, 0.01)
                    bias = getattr(m, f"bias{i}", None)
                    if bias is not None:
                        bias.data.zero_()
                    i += 1