train_unconditional save restore unet parameters #2706
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williamberman
commented
Mar 16, 2023
Comment on lines
+668
to
+683
| unet = accelerator.unwrap_model(model) | ||
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| if args.use_ema: | ||
| ema_model.store(unet.parameters()) | ||
| ema_model.copy_to(unet.parameters()) | ||
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| pipeline = DDPMPipeline( | ||
| unet=unet, | ||
| scheduler=noise_scheduler, | ||
| ) | ||
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| pipeline.save_pretrained(args.output_dir) | ||
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| if args.use_ema: | ||
| ema_model.restore(unet.parameters()) | ||
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We have to make a separate pipeline here because it's not guaranteed that the pipeline set on line 633 is ever set. It's very likely that most people calling this script are never setting the save_model_epocs or save_images_epochs and they're always the same default values
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The documentation is not available anymore as the PR was closed or merged. |
patrickvonplaten
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Mar 16, 2023
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Looks good to me - thanks!
w4ffl35
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re: #2321