Use ones_like

This commit is contained in:
rockerBOO
2025-03-18 18:44:21 -04:00
parent b425466e7b
commit a4f3a9fc1a

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@@ -423,7 +423,7 @@ def get_noisy_model_input_and_timesteps(
else:
ip_noise = args.ip_noise_gamma * torch.randn_like(latents)
else:
ip_noise = torch.zeros_like(latents)
ip_noise = torch.ones_like(latents)
if args.timestep_sampling == "uniform" or args.timestep_sampling == "sigmoid":
# Simple random t-based noise sampling