Error in use of sampler LCA

[uzuuzu20002000]

Thank you vladmandic for all your help. I am impressed with the beautiful images you are able to generate.

I have built the environment in paperspace and am trying to generate it with Diffusers.
When I place LORA in the prompt and run it with LCA as the sampler, I get the following error.

KDiffusionSampler.init() takes 3 positional arguments but 4 were given

Is there some setting that is wrong?

※If I set the sampler to DEIS, etc., I can generate normally

I would be happy to receive your advice.

[vladmandic]

This sounds like an issue, so please create one and provide all details, especially log showing the error.

[uzuuzu20002000]

Thank you for contacting us.

18:23:30-979178 INFO Applying free-u: b1=1.2 b2=1.4 s1=0.9 s2=0.2
18:23:34-223765 INFO Applying LoRA: ['sdxl_lcm'] patch=0.00 load=3.24
18:23:34-225339 ERROR Exception: KDiffusionSampler.init() takes 3
positional arguments but 4 were given
18:23:34-227010 ERROR Arguments: args=('task(brsq5n31593xwl7)', "A woman's
bare hands open a doorknob; the background is a school
hallway, lora:sdxl_lcm:1.0", 'Watermark,', [], 20,
7, 7, True, False, False, 1, 1, 6, 6, 0.7, 1, -1.0,
-1.0, 0, 0, 0, 1024, 1024, True, 0.5, 2, 'ESRGAN
4x-UltraMix_Balanced', True, 20, 0, 0, 5, 0.8, '', '',
[], 0, 'from modules.processing import
process_images\n\np.width = 768\np.height =
768\np.batch_size = 2\np.steps = 10\n\nreturn
process_images(p)', 2, False, False, 'positive',
'comma', 0, False, False, '', 0, '', [], 0, '', [], 0,
'', [], False, True, False, False, False, False, 0,
False, False, {'ad_model': 'face_yolov8n.pt',
'ad_prompt': '', 'ad_negative_prompt': '',
'ad_confidence': 0.3, 'ad_mask_k_largest': 0,
'ad_mask_min_ratio': 0, 'ad_mask_max_ratio': 1,
'ad_x_offset': 0, 'ad_y_offset': 0, 'ad_dilate_erode':
4, 'ad_mask_merge_invert': 'None', 'ad_mask_blur': 4,
'ad_denoising_strength': 0.4, 'ad_inpaint_only_masked':
True, 'ad_inpaint_only_masked_padding': 32,
'ad_use_inpaint_width_height': False,
'ad_inpaint_width': 512, 'ad_inpaint_height': 512,
'ad_use_steps': False, 'ad_steps': 28,
'ad_use_cfg_scale': False, 'ad_cfg_scale': 7,
'ad_use_checkpoint': False, 'ad_checkpoint': 'Use same
checkpoint', 'ad_use_vae': False, 'ad_vae': 'Use same
VAE', 'ad_use_sampler': False, 'ad_sampler': 'Default',
'ad_use_noise_multiplier': False,
'ad_noise_multiplier': 1, 'ad_use_clip_skip': False,
'ad_clip_skip': 1, 'ad_restore_face': False,
'ad_controlnet_model': 'None', 'ad_controlnet_module':
'None', 'ad_controlnet_weight': 1,
'ad_controlnet_guidance_start': 0,
'ad_controlnet_guidance_end': 1, 'is_api': ()},
{'ad_model': 'None', 'ad_prompt': '',
'ad_negative_prompt': '', 'ad_confidence': 0.3,
'ad_mask_k_largest': 0, 'ad_mask_min_ratio': 0,
'ad_mask_max_ratio': 1, 'ad_x_offset': 0,
'ad_y_offset': 0, 'ad_dilate_erode': 4,
'ad_mask_merge_invert': 'None', 'ad_mask_blur': 4,
'ad_denoising_strength': 0.4, 'ad_inpaint_only_masked':
True, 'ad_inpaint_only_masked_padding': 32,
'ad_use_inpaint_width_height': False,
'ad_inpaint_width': 512, 'ad_inpaint_height': 512,
'ad_use_steps': False, 'ad_steps': 28,
'ad_use_cfg_scale': False, 'ad_cfg_scale': 7,
'ad_use_checkpoint': False, 'ad_checkpoint': 'Use same
checkpoint', 'ad_use_vae': False, 'ad_vae': 'Use same
VAE', 'ad_use_sampler': False, 'ad_sampler': 'Default',
'ad_use_noise_multiplier': False,
'ad_noise_multiplier': 1, 'ad_use_clip_skip': False,
'ad_clip_skip': 1, 'ad_restore_face': False,
'ad_controlnet_model': 'None', 'ad_controlnet_module':
'None', 'ad_controlnet_weight': 1,
'ad_controlnet_guidance_start': 0,
'ad_controlnet_guidance_end': 1, 'is_api': ()},
{'ad_model': 'None', 'ad_prompt': '',
'ad_negative_prompt': '', 'ad_confidence': 0.3,
'ad_mask_k_largest': 0, 'ad_mask_min_ratio': 0,
'ad_mask_max_ratio': 1, 'ad_x_offset': 0,
'ad_y_offset': 0, 'ad_dilate_erode': 4,
'ad_mask_merge_invert': 'None', 'ad_mask_blur': 4,
'ad_denoising_strength': 0.4, 'ad_inpaint_only_masked':
True, 'ad_inpaint_only_masked_padding': 32,
'ad_use_inpaint_width_height': False,
'ad_inpaint_width': 512, 'ad_inpaint_height': 512,
'ad_use_steps': False, 'ad_steps': 28,
'ad_use_cfg_scale': False, 'ad_cfg_scale': 7,
'ad_use_checkpoint': False, 'ad_checkpoint': 'Use same
checkpoint', 'ad_use_vae': False, 'ad_vae': 'Use same
VAE', 'ad_use_sampler': False, 'ad_sampler': 'Default',
'ad_use_noise_multiplier': False,
'ad_noise_multiplier': 1, 'ad_use_clip_skip': False,
'ad_clip_skip': 1, 'ad_restore_face': False,
'ad_controlnet_model': 'None', 'ad_controlnet_module':
'None', 'ad_controlnet_weight': 1,
'ad_controlnet_guidance_start': 0,
'ad_controlnet_guidance_end': 1, 'is_api': ()}, True,
False, 1, False, False, False, 1.1, 1.5, 100, 0.7,
False, False, True, False, False, 0,
'Gustavosta/MagicPrompt-Stable-Diffusion', '', False,
7, 100, 'Constant', 0, 'Constant', 0, 4, True, 'MEAN',
'AD', 1, <scripts.animatediff_ui.AnimateDiffProcess
object at 0x7f1a9c94e6b0>, False, 0, 1, 0, 'Version 2',
1.2, 0.9, 0, 0.5, 0, 1, 1.4, 0.2, 0, 0.5, 0, 1, 1, 1,
0, 0.5, 0, 1) kwargs={}
18:23:34-237751 ERROR gradio call: TypeError
╭───────────────────── Traceback (most recent call last) ──────────────────────╮
│ /notebooks/automatic/modules/call_queue.py:34 in f │
│ │
│ 33 │ │ │ try: │
│ ❱ 34 │ │ │ │ res = func(*args, **kwargs) │
│ 35 │ │ │ │ progress.record_results(id_task, res) │
│ │
│ /notebooks/automatic/modules/txt2img.py:66 in txt2img │
│ │
│ 65 │ if processed is None: │
│ ❱ 66 │ │ processed = processing.process_images(p) │
│ 67 │ p.close() │
│ │
│ /notebooks/automatic/modules/processing.py:739 in process_images │
│ │
│ 738 │ │ │ with context_hypertile_vae(p), context_hypertile_unet(p): │
│ ❱ 739 │ │ │ │ res = process_images_inner(p) │
│ 740 │ finally: │
│ │
│ /notebooks/automatic/modules/processing.py:888 in process_images_inner │
│ │
│ 887 │ │ │ │ from modules.processing_diffusers import process_diff │
│ ❱ 888 │ │ │ │ x_samples_ddim = process_diffusers(p, p.seeds, p.prom │
│ 889 │ │ │ else: │
│ │
│ /notebooks/automatic/modules/processing_diffusers.py:388 in │
│ process_diffusers │
│ │
│ 387 │ recompile_model() │
│ ❱ 388 │ update_sampler(shared.sd_model) │
│ 389 │ p.extra_generation_params['Pipeline'] = shared.sd_model.class. │
│ │
│ /notebooks/automatic/modules/processing_diffusers.py:383 in update_sampler │
│ │
│ 382 │ │ │ │ sampler = sd_samplers.all_samplers_map.get("UniPC") │
│ ❱ 383 │ │ │ sd_samplers.create_sampler(sampler.name, sd_model) │
│ 384 │ │ │ # TODO extra_generation_params add sampler options │
│ │
│ /notebooks/automatic/modules/sd_samplers.py:59 in create_sampler │
│ │
│ 58 │ elif shared.backend == shared.Backend.DIFFUSERS: │
│ ❱ 59 │ │ sampler = config.constructor(model) │
│ 60 │ │ if not hasattr(model, 'scheduler_config'): │
│ │
│ /notebooks/automatic/extensions/sd-webui-animatediff/scripts/animatediff_lcm │
│ .py:128 in │
│ │
│ 127 │ │ samplers_data_lcm = [ │
│ ❱ 128 │ │ │ sd_samplers_common.SamplerData(label, lambda model, funcna │
│ 129 │ │ │ for label, funcname, aliases, options in samplers_lcm │
│ │
│ /notebooks/automatic/extensions/sd-webui-animatediff/scripts/animatediff_lcm │
│ .py:109 in init │
│ │
│ 108 │ def init(self, funcname, sd_model, options=None): │
│ ❱ 109 │ │ super().init(funcname, sd_model, options) │
│ 110 │ │ self.model_wrap_cfg = CFGDenoiserLCM(self) │
╰──────────────────────────────────────────────────────────────────────────────╯
TypeError: KDiffusionSampler.init() takes 3 positional arguments but 4 were
given

[uzuuzu20002000]

[vladmandic]

animatediff is not supported with diffusers backend. disty already provided answer yesterday.

[uzuuzu20002000]

The animatediff is installed but not used.
Does this mean that uninstalling it will make it usable?
Sorry for my lack of understanding.

[Disty0]

Use LCM with Diffusers backend.
That LCM is from Animatediff extension.

[uzuuzu20002000]

Does this mean that it can only be used in animation? I apologize if I am greatly mistaken.

[vladmandic]

there are TWO LCM samplers. REAL one, created by SD.Next when in Diffusers mode and whatever AnimateDiff creates - which should be called "AnimateDiff LCM" instead of just "LCM". choose correct one.

[uzuuzu20002000]

Thank you very much.
I understand very well.
I will check and try.

And thank you so much.
I always support and appreciate your support.

[uzuuzu20002000]

I just realized that I did not communicate it properly.
Disty0 thank you so much!