What are the fir and sde_vp kernels in ResnetBlock2D
Hi there,I saw there are different kernels used in theResnetBlock2D.github.comhuggingface/diffusers/blob/2dcf64b72a44dc748610c3eb51534b325df3bca9/src/diffusers/models/resnet.py#L431self.conv2 = torch.nn.Conv2d(out_channels, out_channels, kernel_size=3, stride=1, padding=1)if non_linearity == "swish":self.nonlinearity = lambda x: F.silu(x)elif non_linearity == "mish":self.nonlinearity = Mish()elif non_linearity == "silu":self.nonlinearity = nn.SiLU()self.upsample = self.downsample = Noneif self.up:if kernel == "fir":fir_kernel = (1, 3, 3, 1)self.upsample = lambda x: upsample_2d(x, kernel=fir_kernel)elif kernel == "sde_vp":self.upsample = partial(F.interpolate, scale_factor=2.0, mode="nearest")else:self.upsample = Upsample2D(in_channels, use_conv=False)elif self.down:if kernel == "fir":fir_kernel = (1, 3, 3, 1)Can anyone point me to the full names and papers/online materials to understand these kernels? Thanks!