def betas_for_alpha_bar()

in consistencydecoder/__init__.py [0:0]

• 7 lines of code
• 2 McCabe index (conditional complexity)

def betas_for_alpha_bar(num_diffusion_timesteps, alpha_bar, max_beta=0.999):
    # from: https://github.com/openai/guided-diffusion/blob/22e0df8183507e13a7813f8d38d51b072ca1e67c/guided_diffusion/gaussian_diffusion.py#L45
    betas = []
    for i in range(num_diffusion_timesteps):
        t1 = i / num_diffusion_timesteps
        t2 = (i + 1) / num_diffusion_timesteps
        betas.append(min(1 - alpha_bar(t2) / alpha_bar(t1), max_beta))
    return torch.tensor(betas)