cm/karras_diffusion.py [564:578]:
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    indices = range(len(sigmas) - 1)
    if progress:
        from tqdm.auto import tqdm

        indices = tqdm(indices)

    for i in indices:
        sigma = sigmas[i]
        denoised = denoiser(x, sigma * s_in)
        d = to_d(x, sigma, denoised)
        if callback is not None:
            callback(
                {
                    "x": x,
                    "i": i,
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cm/karras_diffusion.py [696:710]:
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    indices = range(len(sigmas) - 1)
    if progress:
        from tqdm.auto import tqdm

        indices = tqdm(indices)

    for i in indices:
        sigma = sigmas[i]
        denoised = denoiser(x, sigma * s_in)
        d = to_d(x, sigma, denoised)
        if callback is not None:
            callback(
                {
                    "x": x,
                    "i": i,
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