Method forward

src/diffusers/models/downsampling.py:245–252

(self, hidden_states: torch.Tensor)

        return output

    def forward(self, hidden_states: torch.Tensor) -> torch.Tensor:
        if self.use_conv:
            downsample_input = self._downsample_2d(hidden_states, weight=self.Conv2d_0.weight, kernel=self.fir_kernel)
            hidden_states = downsample_input + self.Conv2d_0.bias.reshape(1, -1, 1, 1)
        else:
            hidden_states = self._downsample_2d(hidden_states, kernel=self.fir_kernel, factor=2)

        return hidden_states


# downsample/upsample layer used in k-upscaler, might be able to use FirDownsample2D/DirUpsample2D instead