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Separate random to a variable, and make sure on device

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rockerBOO
2025-03-19 00:49:42 -04:00
parent 8e6817b0c2
commit 1eddac26b0
1 changed files with 4 additions and 3 deletions
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7
library/flux_train_utils.py
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@@ -466,11 +466,12 @@ def get_noisy_model_input_and_timesteps(
# Add noise to the latents according to the noise magnitude at each timestep
# (this is the forward diffusion process)
if args.ip_noise_gamma:
xi = torch.randn_like(latents, device=latents.device, dtype=dtype)
if args.ip_noise_gamma_random_strength:
noise_perturbation = (torch.rand(1, device=latents.device) * args.ip_noise_gamma) * torch.randn_like(noise)
ip_noise_gamma = (torch.rand(1, device=latents.device, dtype=dtype) * args.ip_noise_gamma)
else:
noise_perturbation = args.ip_noise_gamma * torch.randn_like(noise)
noisy_model_input += noise_perturbation
ip_noise_gamma = args.ip_noise_gamma
noisy_model_input += ip_noise_gamma * xi
return noisy_model_input.to(dtype), timesteps.to(dtype), sigmas