INNER CODE UNIT · Python

hist

Extraltodeus/ComfyUI-AutomaticCFG · nodes.py:98

    hist = hist / hist.sum()
    hist = hist[hist > 0]
    return -np.sum(hist * np.log2(hist))

def map_sigma(sigma, sigmax, sigmin):
    return 1 + ((sigma - sigmax) * (0 - 1)) / (sigmin - sigmax)

def center_latent_mean_values(latent, per_channel, mult):
    for b in range(len(latent)):
        if per_channel:
            for c in range(len(latent[b])):
                latent[b][c] -= latent[b][c].mean() * mult
        else:
            latent[b] -= latent[b].mean() * mult
    return latent

def get_denoised_ranges(latent, measure="hard", top_k=0.25):
    chans = []

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