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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):
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
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