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import torch | |
def edit(latents, pca, edit_directions): | |
edit_latents = [] | |
for latent in latents: | |
for pca_idx, start, end, strength in edit_directions: | |
delta = get_delta(pca, latent, pca_idx, strength) | |
delta_padded = torch.zeros(latent.shape).to('cuda') | |
delta_padded[start:end] += delta.repeat(end - start, 1) | |
edit_latents.append(latent + delta_padded) | |
return torch.stack(edit_latents) | |
def get_delta(pca, latent, idx, strength): | |
# pca: ganspace checkpoint. latent: (16, 512) w+ | |
w_centered = latent - pca['mean'].to('cuda') | |
lat_comp = pca['comp'].to('cuda') | |
lat_std = pca['std'].to('cuda') | |
w_coord = torch.sum(w_centered[0].reshape(-1)*lat_comp[idx].reshape(-1)) / lat_std[idx] | |
delta = (strength - w_coord)*lat_comp[idx]*lat_std[idx] | |
return delta | |