Method forward

cdslib/core/nn/modules/linear.py:363–392

r""" Args: x (\*, in_features): input tensor dx (\*, in_features): same shape as x, or can be broadcast. if None, dx = 0. Returns: y (* out_features): :math:`y = W (x + dx) + b + b0`

(self, x: torch.Tensor, dx: torch.Tensor = None)

        )

    def forward(self, x: torch.Tensor, dx: torch.Tensor = None):
        r"""
        Args:
            x (\*, in_features):
                input tensor
            dx (\*, in_features):
                same shape as x, or can be broadcast.
                if None, dx = 0.

        Returns:
            y (* out_features):
                :math:`y = W (x + dx) + b + b0`

        """
        weight = self.scale * self.weight  # (cout, cin)

        if self.demodulate:
            demod = torch.rsqrt(weight.pow(2).sum(dim=1, keepdim=True) + self.eps)  # (cout, 1)
            weight = weight * demod

        y = F.linear(
            input=x + dx if dx is not None else x,
            weight=self.lr_multiplier * weight,
            bias=self.lr_multiplier * self.bias if self.bias is not None else None,
        )

        if self.fixed_bias is not None:
            y = y + self.fixed_bias

        return y