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fixed typo in example train_text_to_image.py (#3608)

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fixed typo
This commit is contained in:
Kashif Rasul
2023-06-02 17:24:54 +02:00
committed by GitHub
parent a6c7b5b6b7
commit f1d4743394
1 changed files with 4 additions and 4 deletions
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8
examples/text_to_image/train_text_to_image.py
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@@ -115,7 +115,7 @@ def log_validation(vae, text_encoder, tokenizer, unet, args, accelerator, weight
def parse_args():
parser = argparse.ArgumentParser(description="Simple example of a training script.")
parser.add_argument(
"--input_pertubation", type=float, default=0, help="The scale of input pretubation. Recommended 0.1."
"--input_perturbation", type=float, default=0, help="The scale of input perturbation. Recommended 0.1."
)
parser.add_argument(
"--pretrained_model_name_or_path",
@@ -830,8 +830,8 @@ def main():
noise += args.noise_offset * torch.randn(
(latents.shape[0], latents.shape[1], 1, 1), device=latents.device
)
if args.input_pertubation:
new_noise = noise + args.input_pertubation * torch.randn_like(noise)
if args.input_perturbation:
new_noise = noise + args.input_perturbation * torch.randn_like(noise)
bsz = latents.shape[0]
# Sample a random timestep for each image
timesteps = torch.randint(0, noise_scheduler.config.num_train_timesteps, (bsz,), device=latents.device)
@@ -839,7 +839,7 @@ def main():
# Add noise to the latents according to the noise magnitude at each timestep
# (this is the forward diffusion process)
if args.input_pertubation:
if args.input_perturbation:
noisy_latents = noise_scheduler.add_noise(latents, new_noise, timesteps)
else:
noisy_latents = noise_scheduler.add_noise(latents, noise, timesteps)