INNER CODE UNIT · Python

create_diffusion

TIGER-AI-Lab/AnyV2V · seine/diffusion/__init__.py:10

def create_diffusion(
    timestep_respacing,
    noise_schedule="linear", 
    use_kl=False,
    sigma_small=False,
    predict_xstart=False,
    # learn_sigma=True,
    learn_sigma=False, # for unet
    rescale_learned_sigmas=False,
    diffusion_steps=1000
):
    betas = gd.get_named_beta_schedule(noise_schedule, diffusion_steps)
    if use_kl:
        loss_type = gd.LossType.RESCALED_KL
    elif rescale_learned_sigmas:
        loss_type = gd.LossType.RESCALED_MSE
    else:
        loss_type = gd.LossType.MSE

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