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sample images in training (not fully tested)

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Kohya S
2023-02-27 17:48:32 +09:00
parent a28f9ae7a3
commit dd523c94ff
5 changed files with 209 additions and 6 deletions
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6
train_textual_inversion.py
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@@ -354,6 +354,8 @@ def train(args):
progress_bar.update(1)
global_step += 1
train_util.sample_images(accelerator, args, None, global_step, accelerator.device, vae, tokenizer, text_encoder, unet)
current_loss = loss.detach().item()
if args.logging_dir is not None:
logs = {"loss": current_loss, "lr": float(lr_scheduler.get_last_lr()[0])}
@@ -376,8 +378,6 @@ def train(args):
accelerator.wait_for_everyone()
updated_embs = unwrap_model(text_encoder).get_input_embeddings().weight[token_ids].data.detach().clone()
# d = updated_embs - bef_epo_embs
# print(bef_epo_embs.size(), updated_embs.size(), d.mean(), d.min())
if args.save_every_n_epochs is not None:
model_name = train_util.DEFAULT_EPOCH_NAME if args.output_name is None else args.output_name
@@ -399,6 +399,8 @@ def train(args):
if saving and args.save_state:
train_util.save_state_on_epoch_end(args, accelerator, model_name, epoch + 1)
train_util.sample_images(accelerator, args, epoch + 1, global_step, accelerator.device, vae, tokenizer, text_encoder, unet)
# end of epoch
is_main_process = accelerator.is_main_process