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