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https://github.com/comfyanonymous/ComfyUI.git
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98155446bf
feat: remove custom js stuff since it just doesnt work well feat: add cond debugging feat: impls PoC refresh of custom_nodes + custom_node extensions feat: ignore workflows folder feat: add batch file to start application under windows feat: integrate reload custom node into refresh feat: update custom node ui feat: impl node change event handling !WIP! feat: add CustomNodeData class for reuse feat: remove all reloaded nodes for test purposes and save graph afterwards !WIP! feat: remove unused registeredNodes feat: comment out graph removal feat: comment on some functions for proper understanding and bookmarking (for now) feat: comment node execution location feat: add exception for IS_CHANGED issues feat: extend example_node README !WIP! feat: custom test nodes for now !WIP! feat: avoid refresh spam feat: add debug_cond custom_node with WIP ui feat: add hint for validating output_ui data feat: pass refresh button into combo function feat: impl output ui error feat: auto refresh nodes fix: various minor issues !WIP! feat: barebone JS scripting in BE for ui templating !WIP! feat: impl interrogation with clip feat: impl more debug samplers feat: change requirements.txt for transformers fix: __init__.py issues when importing custom_nodes feat: temp ignore 3rdparty code feat: add custom_nodes debug_latent and image_fx
51 lines
2.5 KiB
Python
51 lines
2.5 KiB
Python
import latent_preview
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from custom_nodes.debug_model import DebugModel
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from nodes import common_ksampler
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class TestSampler:
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SCHEDULERS = ["normal", "karras", "exponential", "sgm_uniform", "simple", "ddim_uniform"]
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SAMPLERS = ["euler", "euler_ancestral", "heun", "dpm_2", "dpm_2_ancestral",
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"lms", "dpm_fast", "dpm_adaptive", "dpmpp_2s_ancestral", "dpmpp_sde", "dpmpp_sde_gpu",
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"dpmpp_2m", "dpmpp_2m_sde", "dpmpp_2m_sde_gpu", "dpmpp_3m_sde", "dpmpp_3m_sde_gpu", "ddim", "uni_pc",
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"uni_pc_bh2"]
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@classmethod
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def INPUT_TYPES(s):
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return {"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": 8.0, "min": 0.0, "max": 100.0}),
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"sampler_name": (TestSampler.SAMPLERS,),
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"scheduler": (TestSampler.SCHEDULERS,),
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"positive": ("CONDITIONING",),
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"negative": ("CONDITIONING",),
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"latent_image": ("LATENT",),
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"denoise": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01}),
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"mixture": ("FLOAT", {"default": 0.5, "min": 0.0, "max": 1.0, "step": 0.1}),
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}
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}
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RETURN_TYPES = ("LATENT", "LATENT", "LATENT")
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FUNCTION = "sample"
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CATEGORY = "inflamously"
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def sample(self, model, seed, steps, cfg, sampler_name, scheduler, positive, negative, latent_image, denoise=1.0,
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mixture=1.0):
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a_val = common_ksampler(model, seed, round(steps / 2), cfg, sampler_name, scheduler, positive, negative,
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latent_image, denoise=.8)
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b_val = common_ksampler(model, seed + 1, round(steps / 2), cfg, sampler_name, scheduler, positive, negative,
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a_val[0], denoise=.9)
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x_val = common_ksampler(model, seed + 2, round(steps), cfg, sampler_name, scheduler, positive, negative, b_val[0], denoise=denoise)
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return (x_val[0], a_val[0], b_val[0])
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# c_val = [{"samples": None}]
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# c_val[0]["samples"] = (a_val[0]["samples"] * 0.5 * (1.0 - mixture)) + (b_val[0]["samples"] * 0.5 * (0.0 + mixture))
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# c_val[0]["samples"] = (a_val[0]["samples"] * (1.0 - mixture)) - (b_val[0]["samples"] * (0.0 + mixture))
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NODE_CLASS_MAPPINGS = {
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"TestSampler": TestSampler
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}
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