PixArt sigma
Mentioned in #19 Also removes old example sampler since updating it would be too much overhead. Pytorch attention is still wonky.
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@@ -7,7 +7,6 @@ from comfy import utils
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from .conf import pixart_conf, pixart_res
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from .lora import load_pixart_lora
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from .loader import load_pixart
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from .sampler import sample_pixart
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class PixArtCheckpointLoader:
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@classmethod
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@@ -141,44 +140,6 @@ class PixArtControlNetCond:
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cond[c][1]["cn_hint"] = latent["samples"] * 0.18215
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return (cond,)
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class PixArtDPMSampler:
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"""
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The sampler from the reference code.
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"""
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@classmethod
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def INPUT_TYPES(s):
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return {
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"required": {
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"model": ("MODEL", ),
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"seed": ("INT", {"default": 0, "min": 0, "max": 0xffffffffffffffff}),
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"steps": ("INT", {"default": 20, "min": 1, "max": 10000}),
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"cfg": ("FLOAT", {"default": 4.5, "min": 0.0, "max": 100.0, "step":0.5, "round": 0.01}),
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"noise_schedule": (["linear","squaredcos_cap_v2"],{"default":"linear"}),
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"noise_schedule_vp": (["linear","discrete"],{"default":"discrete"}),
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"positive": ("CONDITIONING", ),
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"negative": ("CONDITIONING", ),
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"latent_image": ("LATENT", ),
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}
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}
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RETURN_TYPES = ("LATENT",)
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FUNCTION = "sample"
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CATEGORY = "ExtraModels/PixArt"
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TITLE = "PixArt DPM Sampler [Reference]"
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def sample(self, model, seed, steps, cfg, noise_schedule, noise_schedule_vp, positive, negative, latent_image):
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samples = sample_pixart(
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model = model,
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seed = seed,
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steps = steps,
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cfg = cfg,
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positive = positive,
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negative = negative,
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latent_image = latent_image["samples"],
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noise_schedule = noise_schedule,
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noise_schedule_vp = noise_schedule_vp,
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)
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return ({"samples":samples},)
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class PixArtT5TextEncode:
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"""
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Reference code, mostly to verify compatibility.
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@@ -236,7 +197,6 @@ NODE_CLASS_MAPPINGS = {
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"PixArtCheckpointLoader" : PixArtCheckpointLoader,
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"PixArtResolutionSelect" : PixArtResolutionSelect,
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"PixArtLoraLoader" : PixArtLoraLoader,
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"PixArtDPMSampler" : PixArtDPMSampler,
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"PixArtT5TextEncode" : PixArtT5TextEncode,
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"PixArtResolutionCond" : PixArtResolutionCond,
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"PixArtControlNetCond" : PixArtControlNetCond,
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