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Use single progress bar while sampling #124

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Use single progress bar while sampling #124

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7 changes: 6 additions & 1 deletion scripts/trainer.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1142,6 +1142,10 @@ def save_and_sample_weights(step,context='checkpoint',save_model=True):
send_telegram_message(f"Generating samples for <b>{step}</b> {context}", args.telegram_chat_id, args.telegram_token)
except:
pass
n_sample = args.n_save_sample
if args.save_sample_controlled_seed:
n_sample += len(args.save_sample_controlled_seed)
progress_bar_sample = tqdm(range(len(prompts)*n_sample),desc="Generating samples")
for samplePrompt in prompts:
sampleIndex = prompts.index(samplePrompt)
#convert sampleIndex to number in words
Expand Down Expand Up @@ -1172,7 +1176,7 @@ def save_and_sample_weights(step,context='checkpoint',save_model=True):
depth = depth.astype(np.float32) / 255.0
depth = depth[None, None]
depth = torch.from_numpy(depth)
for i in tqdm(range(args.n_save_sample) if not args.save_sample_controlled_seed else range(args.n_save_sample+len(args.save_sample_controlled_seed)), desc="Generating samples"):
for i in range(n_sample):
#check if the sample is controlled by a seed
if i < args.n_save_sample:
if args.model_variant == 'inpainting':
Expand Down Expand Up @@ -1201,6 +1205,7 @@ def save_and_sample_weights(step,context='checkpoint',save_model=True):
images[0].save(os.path.join(sample_dir,sampleName, f"{sampleName}_controlled_seed_{str(seed)}.png"))
else:
images[0].save(os.path.join(sample_dir, f"{sampleName}_controlled_seed_{str(seed)}.png"))
progress_bar_sample.update(1)

if args.send_telegram_updates:
imgs = []
Expand Down