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| author | Volpeon <git@volpeon.ink> | 2023-01-15 22:26:43 +0100 |
|---|---|---|
| committer | Volpeon <git@volpeon.ink> | 2023-01-15 22:26:43 +0100 |
| commit | 3f922880475c2c0a5679987d4a9a43606e838566 (patch) | |
| tree | 757746927e34aa7fddff1e44c837b489233029d7 /train_ti.py | |
| parent | Restored functional trainer (diff) | |
| download | textual-inversion-diff-3f922880475c2c0a5679987d4a9a43606e838566.tar.gz textual-inversion-diff-3f922880475c2c0a5679987d4a9a43606e838566.tar.bz2 textual-inversion-diff-3f922880475c2c0a5679987d4a9a43606e838566.zip | |
Added Dreambooth strategy
Diffstat (limited to 'train_ti.py')
| -rw-r--r-- | train_ti.py | 46 |
1 files changed, 23 insertions, 23 deletions
diff --git a/train_ti.py b/train_ti.py index 77dec12..2497519 100644 --- a/train_ti.py +++ b/train_ti.py | |||
| @@ -557,15 +557,6 @@ def main(): | |||
| 557 | else: | 557 | else: |
| 558 | optimizer_class = torch.optim.AdamW | 558 | optimizer_class = torch.optim.AdamW |
| 559 | 559 | ||
| 560 | optimizer = optimizer_class( | ||
| 561 | text_encoder.text_model.embeddings.temp_token_embedding.parameters(), | ||
| 562 | lr=args.learning_rate, | ||
| 563 | betas=(args.adam_beta1, args.adam_beta2), | ||
| 564 | weight_decay=args.adam_weight_decay, | ||
| 565 | eps=args.adam_epsilon, | ||
| 566 | amsgrad=args.adam_amsgrad, | ||
| 567 | ) | ||
| 568 | |||
| 569 | weight_dtype = torch.float32 | 560 | weight_dtype = torch.float32 |
| 570 | if args.mixed_precision == "fp16": | 561 | if args.mixed_precision == "fp16": |
| 571 | weight_dtype = torch.float16 | 562 | weight_dtype = torch.float16 |
| @@ -624,6 +615,29 @@ def main(): | |||
| 624 | args.sample_steps | 615 | args.sample_steps |
| 625 | ) | 616 | ) |
| 626 | 617 | ||
| 618 | trainer = partial( | ||
| 619 | train, | ||
| 620 | accelerator=accelerator, | ||
| 621 | unet=unet, | ||
| 622 | text_encoder=text_encoder, | ||
| 623 | vae=vae, | ||
| 624 | noise_scheduler=noise_scheduler, | ||
| 625 | train_dataloader=train_dataloader, | ||
| 626 | val_dataloader=val_dataloader, | ||
| 627 | dtype=weight_dtype, | ||
| 628 | seed=args.seed, | ||
| 629 | callbacks_fn=textual_inversion_strategy | ||
| 630 | ) | ||
| 631 | |||
| 632 | optimizer = optimizer_class( | ||
| 633 | text_encoder.text_model.embeddings.temp_token_embedding.parameters(), | ||
| 634 | lr=args.learning_rate, | ||
| 635 | betas=(args.adam_beta1, args.adam_beta2), | ||
| 636 | weight_decay=args.adam_weight_decay, | ||
| 637 | eps=args.adam_epsilon, | ||
| 638 | amsgrad=args.adam_amsgrad, | ||
| 639 | ) | ||
| 640 | |||
| 627 | if args.find_lr: | 641 | if args.find_lr: |
| 628 | lr_scheduler = None | 642 | lr_scheduler = None |
| 629 | else: | 643 | else: |
| @@ -642,20 +656,6 @@ def main(): | |||
| 642 | warmup_epochs=args.lr_warmup_epochs, | 656 | warmup_epochs=args.lr_warmup_epochs, |
| 643 | ) | 657 | ) |
| 644 | 658 | ||
| 645 | trainer = partial( | ||
| 646 | train, | ||
| 647 | accelerator=accelerator, | ||
| 648 | unet=unet, | ||
| 649 | text_encoder=text_encoder, | ||
| 650 | vae=vae, | ||
| 651 | noise_scheduler=noise_scheduler, | ||
| 652 | train_dataloader=train_dataloader, | ||
| 653 | val_dataloader=val_dataloader, | ||
| 654 | dtype=weight_dtype, | ||
| 655 | seed=args.seed, | ||
| 656 | callbacks_fn=textual_inversion_strategy | ||
| 657 | ) | ||
| 658 | |||
| 659 | trainer( | 659 | trainer( |
| 660 | optimizer=optimizer, | 660 | optimizer=optimizer, |
| 661 | lr_scheduler=lr_scheduler, | 661 | lr_scheduler=lr_scheduler, |
