@@ -166,7 +166,7 @@ def pretrain(args, loader, generator, discriminator, g_optim, d_optim, g_ema, en
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target_img = target_img .detach ()
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# g(z2)
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style_img , _ = generator ([real_zs [1 ]], None , input_is_latent = False , z_plus_latent = False , use_res = False )
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- style_img = target_img .detach ()
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+ style_img = style_img .detach ()
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# E(g(z2))
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_ , pspstyle = encoder (F .adaptive_avg_pool2d (style_img , 256 ), randomize_noise = False ,
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return_latents = True , z_plus_latent = True , return_z_plus_latent = False )
@@ -475,4 +475,4 @@ def pretrain(args, loader, generator, discriminator, g_optim, d_optim, g_ema, en
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args .iter = full_iter // 10
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pretrain (args , loader , generator , discriminator , g_optim , d_optim , g_ema , encoder , vggloss , device , inject_index = 6 , savemodel = False )
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args .iter = full_iter
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- pretrain (args , loader , generator , discriminator , g_optim , d_optim , g_ema , encoder , vggloss , device , inject_index = 5 )
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+ pretrain (args , loader , generator , discriminator , g_optim , d_optim , g_ema , encoder , vggloss , device , inject_index = 5 )
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