Forward function for StyleGAN2GeneratorCSFT. Args: styles (list[Tensor]): Sample codes of styles. conditions (list[

Forward function for GFPGANv1Clean. Args: x (Tensor): Input images. return_latents (bool): Whether to return style

Normalize the style codes. Args: x (Tensor): Style codes with shape (b, c). Returns: Tensor: Normalized te

Forward function. Args: x (Tensor): Tensor with shape (b, c, h, w). style (Tensor): Tensor with shape (b, num_style

Forward function. Args: x (Tensor): Feature tensor with shape (b, c, h, w). style (Tensor): Tensor with shape (b, n

Forward function for StyleGAN2GeneratorClean. Args: styles (list[Tensor]): Sample codes of styles. input_is_latent

Args: image(Tensor): batch x 3 x height x width Returns: Tensor: batch x height x width x 3

Args: image(tensor): batch x height x width x 3 Returns: y(tensor): batch x height x width

Args: image(tensor): batch x height x width Returns: Tensor: batch x h*w/64 x h x w

Args: image(tensor): batch x height x width Returns: Tensor: batch x height x width

Args: image(tensor): batch x height x width Returns: Tensor: batch x height x width

Args: image(tensor): batch x height x width Returns: Tensor: batch x height x width

Args: image(tensor): batch x 3 x height x width Returns: dict(tensor): Compressed tensor with batch x h

Args: image(tensor): batch x height x width Returns: Tensor: batch x height x width

Args: image(tensor): batch x height x width Returns: Tensor: batch x height x width

Args: image(tensor): batch x height x width Returns: Tensor: batch x height x width

Args: patches(tensor) batch x height*width/64, height x width height(int) width(int) Retur

Args: y(tensor): y channel image cb(tensor): cb channel cr(tensor): cr channel Returns:

Args: image(tensor): batch x height x width x 3 Returns: Tensor: batch x 3 x height x width

Args: compressed(dict(tensor)): batch x h*w/64 x 8 x 8 imgh(int) imgw(int) factor(float)

Args: x (Tensor): Input image, bchw, rgb, [0, 1] quality(float): Quality factor for jpeg compression scheme.

Forward function. Args: x (Tensor): Input tensor with shape (n, c, h, w). Returns: Tensor: Forward res

Args: x: input features with shape of (num_windows*b, n, c) mask: (0/-inf) mask with shape of (num_windows, Wh*Ww,

x: b, h*w, c

Forward function of BasicVSR. Args: x: Input frames with shape (b, n, c, h, w). n is the temporal dimension / number of frames

Normalize the style codes. Args: x (Tensor): Style codes with shape (b, c). Returns: Tensor: Normalize

Forward function. Args: x (Tensor): Tensor with shape (b, c, h, w). style (Tensor): Tensor with shape (b, num_sty

Forward function. Args: x (Tensor): Feature tensor with shape (b, c, h, w). style (Tensor): Tensor with shape (b,

Forward function for StyleGAN2Generator. Args: styles (list[Tensor]): Sample codes of styles. input_is_latent (bo

Align neighboring frame features to the reference frame features. Args: nbr_feat_l (list[Tensor]): Neighboring feature list. I