Class SamplerDistanceBase

custom_samplers.py:263–356

    return x

class SamplerDistanceBase:
    _DISTANCE_OPTIONS = None # All options by default.
    _DISTANCE_PARAMS = {
        "resample": ("INT", {
            "default": 3, "min": -1, "max": 32, "step": 1,
            "tooltip": "0 all along gives Euler. 1 gives Heun.\nAnything starting from 2 will use the distance method.\n-1 will do remaining steps + 1 as the resample value. This can be pretty slow.",
        }),
        "resample_end": ("INT", {
            "default": -1, "min": -1, "max": 32, "step": 1,
            "tooltip": "How many resamples for the end. -1 means constant.",
        }),
        "cfgpp": ("BOOLEAN", {
            "default": True,
            "tooltip": "Controls whether to use CFG++ sampling. When enabled, you should set CFG to a fairly low value.",
        }),
        "eta": ("FLOAT", {
            "default": 0.0, "min": 0.0, "max": 32.0, "step": 0.01,
            "tooltip": "Controls the ancestralness of the main sampler steps. 0.0 means to use non-ancestral sampling. Note: May not work well with some of the other options.",
        }),
        "s_noise": ("FLOAT", {
            "default": 1.0, "min": -100.0, "max": 100.0, "step": 0.01,
            "tooltip": "Scale factor for ancestral noise added during sampling. Generally should be left at 1.0 and only has an effect when ancestral sampling is used.",
        }),
        "distance_step_eta": ("FLOAT", {
            "default": 0.0, "min": 0.0, "max": 32.0, "step": 0.01,
            "tooltip": "Experimental option that allows using ancestral sampling for the internal distance steps. When used, should generally be a fairly low value such as 0.25. 0.0 means to use non-ancestral sampling for the internal distance steps.",
        }),
        "distance_step_s_noise": ("FLOAT", {
            "default": 1.0, "min": -100.0, "max": 100.0, "step": 0.01,
            "tooltip": "Scale factor for ancestral noise added in the internal distance steps. Generally should be left at 1.0 and only has an effect when distance_step_eta is non-zero.",
        }),
        "use_softmax": ("BOOLEAN", {
            "default": False,
            "tooltip": "Rather than using a min/max normalization and an exponent will use a softmax instead.",
        }),
        "use_slerp": ("BOOLEAN", {
            "default": False,
            "tooltip": "Will SLERP the predictions instead of doing a weighted average. The difference is more obvious when using use_negative.",
        }),
        "perp_step": ("BOOLEAN", {
            "default": False,
            "tooltip": "Experimental, not yet recommended.",
        }),
        "use_negative": ("BOOLEAN", {
            "default": False,
            "tooltip": "Will use the negative prediction to prepare the distance scores. This tends to give images with less errors from my testing.",
        }),
        "smooth": ("BOOLEAN", {
            "default": False,
            "tooltip": "Not recommended, will make everything brighter. Not smoother.",
        }),
        "sharpen": ("BOOLEAN", {
            "default": False,
            "tooltip": "Not recommended, attempts to sharpen the results but instead tends to make things fuzzy.",
        }),
        "distance_first": ("INT", {
            "default": 0, "min": -10000, "max": 10000, "step": 1,
            "tooltip": "First step to use distance sampling. You can use negative values to count from the end. Note: Steps are zero-based.",