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Merge pull request #6648 from vladmandic/progress-description

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Set TQDM progress bar and state textinfo description
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AUTOMATIC1111 2023-01-11 19:04:54 +03:00 committed by GitHub
commit 6d7f3d1072
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3 changed files with 12 additions and 3 deletions
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4
modules/hypernetworks/hypernetwork.py
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@ -619,7 +619,9 @@ def train_hypernetwork(hypernetwork_name, learn_rate, batch_size, gradient_step,
epoch_num = hypernetwork.step // steps_per_epoch
epoch_step = hypernetwork.step % steps_per_epoch
pbar.set_description(f"[Epoch {epoch_num}: {epoch_step+1}/{steps_per_epoch}]loss: {loss_step:.7f}")
description = f"Training hypernetwork [Epoch {epoch_num}: {epoch_step+1}/{steps_per_epoch}]loss: {loss_step:.7f}"
pbar.set_description(description)
shared.state.textinfo = description
if hypernetwork_dir is not None and steps_done % save_hypernetwork_every == 0:
# Before saving, change name to match current checkpoint.
hypernetwork_name_every = f'{hypernetwork_name}-{steps_done}'

7
modules/textual_inversion/preprocess.py
View File

@ -135,7 +135,8 @@ def preprocess_work(process_src, process_dst, process_width, process_height, pre
params.process_caption_deepbooru = process_caption_deepbooru
params.preprocess_txt_action = preprocess_txt_action
for index, imagefile in enumerate(tqdm.tqdm(files)):
pbar = tqdm.tqdm(files)
for index, imagefile in enumerate(pbar):
params.subindex = 0
filename = os.path.join(src, imagefile)
try:
@ -143,6 +144,10 @@ def preprocess_work(process_src, process_dst, process_width, process_height, pre
except Exception:
continue
description = f"Preprocessing [Image {index}/{len(files)}]"
pbar.set_description(description)
shared.state.textinfo = description
params.src = filename
existing_caption = None

4
modules/textual_inversion/textual_inversion.py
View File

@ -476,7 +476,9 @@ def train_embedding(embedding_name, learn_rate, batch_size, gradient_step, data_
epoch_num = embedding.step // steps_per_epoch
epoch_step = embedding.step % steps_per_epoch
pbar.set_description(f"[Epoch {epoch_num}: {epoch_step+1}/{steps_per_epoch}]loss: {loss_step:.7f}")
description = f"Training textual inversion [Epoch {epoch_num}: {epoch_step+1}/{steps_per_epoch}]loss: {loss_step:.7f}"
pbar.set_description(description)
shared.state.textinfo = description
if embedding_dir is not None and steps_done % save_embedding_every == 0:
# Before saving, change name to match current checkpoint.
embedding_name_every = f'{embedding_name}-{steps_done}'