mirror of
https://github.com/vladmandic/automatic
synced 2026-08-27 07:31:01 +02:00
CalamitousFelicitousness
4d6f2b65c8
Batch matrix-matrix and Dynamic Attention BMM applied a legacy Attention processor to pipe.unet, which a diffusion transformer does not have, so they served unet models alone and said nothing elsewhere. The choices, the processor and its slice helper are removed, an unrecognized method now warns rather than selecting nothing, and a stored value is rewritten to Scaled-Dot-Product on load.
192 lines
7.7 KiB
Python
192 lines
7.7 KiB
Python
import logging
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import diffusers
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class OnlinePipeline(diffusers.DiffusionPipeline):
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pass
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logging_level = logging.getLogger("diffusers").level
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logging.getLogger("diffusers").setLevel(logging.ERROR)
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logging.getLogger("diffusers.modular_pipelines").setLevel(logging.ERROR)
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pipelines = {
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'Autodetect': None,
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'AutoPipeline': diffusers.AutoPipelineForText2Image,
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'Diffusion': diffusers.DiffusionPipeline,
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# standard diffusers pipelines
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'Stable Diffusion': getattr(diffusers, 'StableDiffusionPipeline', None),
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'Stable Diffusion Inpaint': getattr(diffusers, 'StableDiffusionInpaintPipeline', None),
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'Stable Diffusion Instruct': getattr(diffusers, 'StableDiffusionInstructPix2PixPipeline', None),
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'Stable Diffusion 1.5': getattr(diffusers, 'StableDiffusionPipeline', None),
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'Stable Diffusion 2': getattr(diffusers, 'StableDiffusionPipeline', None),
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'Stable Diffusion 2.x': getattr(diffusers, 'StableDiffusionPipeline', None),
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'Stable Diffusion Upscale': getattr(diffusers, 'StableDiffusionUpscalePipeline', None),
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'Stable Diffusion XL': getattr(diffusers, 'StableDiffusionXLPipeline', None),
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'Stable Diffusion XL Inpaint': getattr(diffusers, 'StableDiffusionXLInpaintPipeline', None),
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'Stable Diffusion XL Instruct': getattr(diffusers, 'StableDiffusionXLInstructPix2PixPipeline', None),
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'Stable Diffusion XL Refiner': getattr(diffusers, 'StableDiffusionXLImg2ImgPipeline', None),
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'Stable Cascade': getattr(diffusers, 'StableCascadeCombinedPipeline', None),
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'Stable Diffusion 3': getattr(diffusers, 'StableDiffusion3Pipeline', None),
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'Latent Consistency Model': getattr(diffusers, 'LatentConsistencyModelPipeline', None),
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'AuraFlow': getattr(diffusers, 'AuraFlowPipeline', None),
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'Chroma': getattr(diffusers, 'ChromaPipeline', None),
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'ChronoEdit': getattr(diffusers, 'ChronoEditPipeline', None),
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'CogView3': getattr(diffusers, 'CogView3PlusPipeline', None),
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'CogView4': getattr(diffusers, 'CogView4Pipeline', None),
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'Cosmos': getattr(diffusers, 'Cosmos2TextToImagePipeline', None),
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'DeepFloydIF': getattr(diffusers, 'IFPipeline', None),
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'ERNIEImage': getattr(diffusers, 'ErnieImagePipeline', None),
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'FLUX': getattr(diffusers, 'FluxPipeline', None),
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'FLUX2Klein': getattr(diffusers, 'Flux2KleinPipeline', None),
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'FLUX2': getattr(diffusers, 'Flux2Pipeline', None),
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'GLMImage': getattr(diffusers, 'GlmImagePipeline', None),
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'HiDream': getattr(diffusers, 'HiDreamImagePipeline', None),
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'HunyuanDiT': getattr(diffusers, 'HunyuanDiTPipeline', None),
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'HunyuanImage': getattr(diffusers, 'HunyuanImagePipeline', None),
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'JoyEdit': getattr(diffusers, 'JoyImageEditPipeline', None),
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'Kandinsky21': getattr(diffusers, 'KandinskyCombinedPipeline', None),
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'Kandinsky22': getattr(diffusers, 'KandinskyV22CombinedPipeline', None),
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'Kandinsky30': getattr(diffusers, 'Kandinsky3Pipeline', None),
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'Kandinsky50': getattr(diffusers, 'Kandinsky5T2IPipeline', None),
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'Kolors': getattr(diffusers, 'KolorsPipeline', None),
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'LongCat': getattr(diffusers, 'LongCatImagePipeline', None),
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'Lumina2': getattr(diffusers, 'Lumina2Pipeline', None),
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'LuminaNext': getattr(diffusers, 'LuminaText2ImgPipeline', None),
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'NucleusImage': getattr(diffusers, 'NucleusMoEImagePipeline', None),
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'OvisImage': getattr(diffusers, 'OvisImagePipeline', None),
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'OmniGen': getattr(diffusers, 'OmniGenPipeline', None),
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'PixArtAlpha': getattr(diffusers, 'PixArtAlphaPipeline', None),
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'PixArtSigma': getattr(diffusers, 'PixArtSigmaPipeline', None),
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'PRXPixel': getattr(diffusers, 'PRXPixelPipeline', None),
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'MiniMaxH3': getattr(diffusers, 'MiniMaxH3ModularPipeline', None),
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'Qwen': getattr(diffusers, 'QwenImagePipeline', None),
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'Sana': getattr(diffusers, 'SanaPipeline', None),
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'WanAI': getattr(diffusers, 'WanPipeline', None),
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'ZImage': getattr(diffusers, 'ZImagePipeline', None),
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# pipelines with custom code that is fetched online
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'InstaFlow': OnlinePipeline,
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'Anima': OnlinePipeline,
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# sdnext custom pipelines are dynamically imported and redefined later
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'Bria': None,
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'FLite': None,
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'FLEX': None,
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'HiDreamO1': None,
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'HunyuanImage3': None,
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'Ideogram4': None,
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'Krea2': None,
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'Lens': None,
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'LuminaDiMOO': None,
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'Meissonic': None,
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'OmniGen2': None,
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'SDXS': None,
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'SegMoE': None,
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'Step1XEdit': None,
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'UltraFlux': None,
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'VIBE': None,
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'XOmni': None,
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'ZetaChroma': None,
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'Boogu': None,
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'SeFi': None,
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'MageFlow': None,
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}
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logging.getLogger("diffusers").setLevel(logging_level)
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logging.getLogger("diffusers.modular_pipelines").setLevel(logging_level)
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def postprocessing_scripts():
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import modules.scripts_manager
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return modules.scripts_manager.scripts_postproc.scripts
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def sd_vae_items():
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import modules.sd_vae
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return ["Automatic", "Default"] + list(modules.sd_vae.vae_dict)
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def sd_taesd_items():
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import modules.vae.sd_vae_taesd
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return list(modules.vae.sd_vae_taesd.TAESD_MODELS.keys()) + list(modules.vae.sd_vae_taesd.CQYAN_MODELS.keys())
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def refresh_vae_list():
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import modules.sd_vae
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modules.sd_vae.refresh_vae_list()
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def sd_unet_items():
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import modules.sd_unet
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return ['Default'] + list(modules.sd_unet.unet_dict)
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def refresh_unet_list():
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import modules.sd_unet
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modules.sd_unet.refresh_unet_list()
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def sd_te_items():
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import modules.model_te
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predefined = ['Default']
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return predefined + list(modules.model_te.te_dict)
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def refresh_te_list():
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import modules.model_te
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modules.model_te.refresh_te_list()
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def list_crossattention():
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return [
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"Disabled",
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"Scaled-Dot-Product",
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"xFormers",
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]
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def get_pipelines():
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from modules.logger import log
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"""
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if hasattr(diffusers, 'OnnxStableDiffusionPipeline') and 'ONNX Stable Diffusion' not in list(pipelines):
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try:
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from modules.onnx_impl import initialize_onnx
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initialize_onnx()
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onnx_pipelines = {
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'ONNX Stable Diffusion': getattr(diffusers, 'OnnxStableDiffusionPipeline', None),
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'ONNX Stable Diffusion Img2Img': getattr(diffusers, 'OnnxStableDiffusionImg2ImgPipeline', None),
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'ONNX Stable Diffusion Inpaint': getattr(diffusers, 'OnnxStableDiffusionInpaintPipeline', None),
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'ONNX Stable Diffusion Upscale': getattr(diffusers, 'OnnxStableDiffusionUpscalePipeline', None),
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}
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except Exception as e:
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log.error(f'ONNX initialization error: {e}')
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onnx_pipelines = {}
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pipelines.update(onnx_pipelines)
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"""
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stats_builtin = 0
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stats_custom = 0
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for k, v in pipelines.copy().items():
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if k != 'Autodetect' and v is None:
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stats_custom += 1
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pipelines[k] = diffusers.DiffusionPipeline
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else:
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stats_builtin += 1
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if stats_custom > 0:
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log.debug(f'Pipelines init: diffusers={stats_builtin} custom={stats_custom}')
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return pipelines
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def get_repo(model):
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if model == 'StableDiffusionPipeline' or model == 'Stable Diffusion 1.5':
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return 'stable-diffusion-v1-5/stable-diffusion-v1-5'
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elif model == 'StableDiffusionXLPipeline' or model == 'Stable Diffusion XL':
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return 'stabilityai/stable-diffusion-xl-base-1.0'
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elif model == 'StableDiffusion3Pipeline' or model == 'Stable Diffusion 3':
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return 'stabilityai/stable-diffusion-3.5-medium'
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else:
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return None
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sdnq_quant_modes = ["int8", "uint8", "int6", "uint6", "uint5", "uint4", "uint3", "uint2", "float8_e4m3fn", "float8_e3m4fn", "float6_e3m2fn", "float5_e2m2fn", "float4_e2m1fn", "float3_e1m1fn", "float2_e1m0fn", "int16", "uint16", "float16"]
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sdnq_matmul_modes = ["disabled", "enabled", "int8", "uint8", "float8_e4m3fn", "float16"]
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