Incompatible with Regional Prompter about sd-webui-negpip

[hako-mikan]

NegPiP and Regional Prompter are designed to coexist. Please tell me what settings caused that error.

[ThereforeGames]

Apologies, my Regional Prompter extension was a couple versions behind and updating it appears to have fixed the error. I'll re-open this with more info if it comes up again. Thanks!

[ThereforeGames]

Actually, I may have spoken too soon. The issue occurs when using the "Base Prompt" feature of Regional Prompter along with a negative token. Example prompt:

character one and character two (worst quality:-1) ADDBASE character one BREAK character two

And here's a complete error log:

NegPiP enable, Positive:[3],Negative:None
  0%|                                                                                          | 0/20 [00:00<?, ?it/s]
*** Error completing request
*** Arguments: ('task(j5qkd9oqkeqqqbx)', 'character one and character two (worst quality:-1) ADDBASE character one BREAK character two', 'bestneg', [], 20, 'Restart', 1, 1, 7, 768, 512, False, 0.7, 2, 'Latent', 0, 0, 0, 'Use same checkpoint', 'Use same sampler', '', '', [], <gradio.routes.Request object at 0x000001F4222CA1D0>, 0, False, '', 0.8, 1649217773, False, -1, 0, 0, 0, False, False, 4, True, -1.0, True, 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': 'DPM++ 2M Karras', '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': 'DPM++ 2M Karras', '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': ()}, UiControlNetUnit(enabled=False, module='none', model='None', weight=1, image=None, resize_mode='Crop and Resize', low_vram=False, processor_res=512, threshold_a=64, threshold_b=64, guidance_start=0, guidance_end=1, pixel_perfect=False, control_mode='Balanced', save_detected_map=True), UiControlNetUnit(enabled=False, module='none', model='None', weight=1, image=None, resize_mode='Crop and Resize', low_vram=False, processor_res=512, threshold_a=64, threshold_b=64, guidance_start=0, guidance_end=1, pixel_perfect=False, control_mode='Balanced', save_detected_map=True), UiControlNetUnit(enabled=False, module='none', model='None', weight=1, image=None, resize_mode='Crop and Resize', low_vram=False, processor_res=512, threshold_a=64, threshold_b=64, guidance_start=0, guidance_end=1, pixel_perfect=False, control_mode='Balanced', save_detected_map=True), UiControlNetUnit(enabled=False, module='none', model='None', weight=1, image=None, resize_mode='Crop and Resize', low_vram=False, processor_res=512, threshold_a=64, threshold_b=64, guidance_start=0, guidance_end=1, pixel_perfect=False, control_mode='Balanced', save_detected_map=True), 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, False, True, 3, 4, 0.15, 0.3, 'bicubic', 0.5, 2, True, False, True, True, False, 'Matrix', 'Columns', 'Mask', 'Prompt', '1,1', '0.2', False, False, False, 'Attention', [False], '0', '0', '0.4', None, '0', '0', False, False, False, 'positive', 'comma', 0, False, False, 'start', '', 1, '', [], 0, '', [], 0, '', [], True, False, False, False, 0, False, None, None, False, None, None, False, None, None, False, None, None, False, 50, [], 30, '', 4, [], 1, '', '', '', '') {}
    Traceback (most recent call last):
      File "T:\code\python\automatic-stable-diffusion-webui\modules\call_queue.py", line 57, in f
        res = list(func(*args, **kwargs))
      File "T:\code\python\automatic-stable-diffusion-webui\modules\call_queue.py", line 36, in f
        res = func(*args, **kwargs)
      File "T:\code\python\automatic-stable-diffusion-webui\modules\txt2img.py", line 55, in txt2img
        processed = processing.process_images(p)
      File "T:\code\python\automatic-stable-diffusion-webui\modules\processing.py", line 734, in process_images
        res = process_images_inner(p)
      File "T:\code\python\automatic-stable-diffusion-webui\extensions\sd-webui-controlnet\scripts\batch_hijack.py", line 42, in processing_process_images_hijack
        return getattr(processing, '__controlnet_original_process_images_inner')(p, *args, **kwargs)
      File "T:\code\python\automatic-stable-diffusion-webui\modules\processing.py", line 869, in process_images_inner
        samples_ddim = p.sample(conditioning=p.c, unconditional_conditioning=p.uc, seeds=p.seeds, subseeds=p.subseeds, subseed_strength=p.subseed_strength, prompts=p.prompts)
      File "T:\code\python\automatic-stable-diffusion-webui\modules\processing.py", line 1145, in sample
        samples = self.sampler.sample(self, x, conditioning, unconditional_conditioning, image_conditioning=self.txt2img_image_conditioning(x))
      File "T:\code\python\automatic-stable-diffusion-webui\modules\sd_samplers_kdiffusion.py", line 235, in sample
        samples = self.launch_sampling(steps, lambda: self.func(self.model_wrap_cfg, x, extra_args=self.sampler_extra_args, disable=False, callback=self.callback_state, **extra_params_kwargs))
      File "T:\code\python\automatic-stable-diffusion-webui\modules\sd_samplers_common.py", line 268, in launch_sampling
        return func()
      File "T:\code\python\automatic-stable-diffusion-webui\modules\sd_samplers_kdiffusion.py", line 235, in <lambda>
        samples = self.launch_sampling(steps, lambda: self.func(self.model_wrap_cfg, x, extra_args=self.sampler_extra_args, disable=False, callback=self.callback_state, **extra_params_kwargs))
      File "T:\code\python\automatic-stable-diffusion-webui\venv\lib\site-packages\torch\utils\_contextlib.py", line 115, in decorate_context
        return func(*args, **kwargs)
      File "T:\code\python\automatic-stable-diffusion-webui\modules\sd_samplers_extra.py", line 71, in restart_sampler
        x = heun_step(x, old_sigma, new_sigma)
      File "T:\code\python\automatic-stable-diffusion-webui\modules\sd_samplers_extra.py", line 19, in heun_step
        denoised = model(x, old_sigma * s_in, **extra_args)
      File "T:\code\python\automatic-stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl
        return forward_call(*args, **kwargs)
      File "T:\code\python\automatic-stable-diffusion-webui\modules\sd_samplers_cfg_denoiser.py", line 169, in forward
        x_out = self.inner_model(x_in, sigma_in, cond=make_condition_dict(cond_in, image_cond_in))
      File "T:\code\python\automatic-stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl
        return forward_call(*args, **kwargs)
      File "T:\code\python\automatic-stable-diffusion-webui\repositories\k-diffusion\k_diffusion\external.py", line 112, in forward
        eps = self.get_eps(input * c_in, self.sigma_to_t(sigma), **kwargs)
      File "T:\code\python\automatic-stable-diffusion-webui\repositories\k-diffusion\k_diffusion\external.py", line 138, in get_eps
        return self.inner_model.apply_model(*args, **kwargs)
      File "T:\code\python\automatic-stable-diffusion-webui\modules\sd_hijack_utils.py", line 17, in <lambda>
        setattr(resolved_obj, func_path[-1], lambda *args, **kwargs: self(*args, **kwargs))
      File "T:\code\python\automatic-stable-diffusion-webui\modules\sd_hijack_utils.py", line 28, in __call__
        return self.__orig_func(*args, **kwargs)
      File "T:\code\python\automatic-stable-diffusion-webui\repositories\stable-diffusion-stability-ai\ldm\models\diffusion\ddpm.py", line 858, in apply_model
        x_recon = self.model(x_noisy, t, **cond)
      File "T:\code\python\automatic-stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl
        return forward_call(*args, **kwargs)
      File "T:\code\python\automatic-stable-diffusion-webui\repositories\stable-diffusion-stability-ai\ldm\models\diffusion\ddpm.py", line 1335, in forward
        out = self.diffusion_model(x, t, context=cc)
      File "T:\code\python\automatic-stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl
        return forward_call(*args, **kwargs)
      File "T:\code\python\automatic-stable-diffusion-webui\modules\sd_unet.py", line 91, in UNetModel_forward
        return original_forward(self, x, timesteps, context, *args, **kwargs)
      File "T:\code\python\automatic-stable-diffusion-webui\repositories\stable-diffusion-stability-ai\ldm\modules\diffusionmodules\openaimodel.py", line 797, in forward
        h = module(h, emb, context)
      File "T:\code\python\automatic-stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl
        return forward_call(*args, **kwargs)
      File "T:\code\python\automatic-stable-diffusion-webui\repositories\stable-diffusion-stability-ai\ldm\modules\diffusionmodules\openaimodel.py", line 84, in forward
        x = layer(x, context)
      File "T:\code\python\automatic-stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl
        return forward_call(*args, **kwargs)
      File "T:\code\python\automatic-stable-diffusion-webui\repositories\stable-diffusion-stability-ai\ldm\modules\attention.py", line 334, in forward
        x = block(x, context=context[i])
      File "T:\code\python\automatic-stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl
        return forward_call(*args, **kwargs)
      File "T:\code\python\automatic-stable-diffusion-webui\repositories\stable-diffusion-stability-ai\ldm\modules\attention.py", line 269, in forward
        return checkpoint(self._forward, (x, context), self.parameters(), self.checkpoint)
      File "T:\code\python\automatic-stable-diffusion-webui\repositories\stable-diffusion-stability-ai\ldm\modules\diffusionmodules\util.py", line 121, in checkpoint
        return CheckpointFunction.apply(func, len(inputs), *args)
      File "T:\code\python\automatic-stable-diffusion-webui\venv\lib\site-packages\torch\autograd\function.py", line 506, in apply
        return super().apply(*args, **kwargs)  # type: ignore[misc]
      File "T:\code\python\automatic-stable-diffusion-webui\repositories\stable-diffusion-stability-ai\ldm\modules\diffusionmodules\util.py", line 136, in forward
        output_tensors = ctx.run_function(*ctx.input_tensors)
      File "T:\code\python\automatic-stable-diffusion-webui\repositories\stable-diffusion-stability-ai\ldm\modules\attention.py", line 273, in _forward
        x = self.attn2(self.norm2(x), context=context) + x
      File "T:\code\python\automatic-stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl
        return forward_call(*args, **kwargs)
      File "T:\code\python\automatic-stable-diffusion-webui\extensions\sd-webui-regional-prompter\scripts\attention.py", line 403, in forward
        ox = matsepcalc(x, contexts, mask, True, 1)
      File "T:\code\python\automatic-stable-diffusion-webui\extensions\sd-webui-regional-prompter\scripts\attention.py", line 161, in matsepcalc
        out = main_forward(module, x, context, mask, divide, self.isvanilla,userpp =True,step = self.step, isxl = self.isxl, negpip = negpip)
      File "T:\code\python\automatic-stable-diffusion-webui\extensions\sd-webui-regional-prompter\scripts\attention.py", line 22, in main_forward
        context = torch.cat((context,conds),1)
    RuntimeError: Sizes of tensors must match except in dimension 1. Expected size 2 but got size 1 for tensor number 1 in the list.

I notice the log mentions other extensions like ControlNet and Adetailer, even though they're not active. I'm going to try disabling them entirely to see if it makes a difference.

[ThereforeGames]

Huh, okay. The other extensions don't matter - same error after disabling everything except NegPiP and RP.

But I figured out what's causing it... sort of.

It's a very specific negative prompt with four TI embeddings:

rfneg UnrealisticDream BadDream BeyondV3-neg

If I use any combination of 3 embeddings, or just regular words, it runs fine.

I also tried running it with a ton of other embeddings... and that works too. Example:

bad-hands-5 AloneCrapArt AloneRealityNeg2 BadNegAnatomyV1-neg difConsistency_negative_v2 epiCPhotoGasm-colorfulPhoto-neg

I can even include the 4 problematic embeddings at the end of another negative prompt without error...

But using those 4, in that specific order, with no other terms, breaks it. 🤨

---

EDIT: Those embeddings seem to work if I enable "common negative prompt", or disable that and use rfneg UnrealisticDream BadDream BeyondV3-neg BREAK rfneg UnrealisticDream BadDream BeyondV3-neg BREAK rfneg UnrealisticDream BadDream BeyondV3-neg. So, I would chalk this up to user error - at least to some extent.

[hako-mikan]

I tested with your settings in Web-UI 1.7.0.
There is no error, so bug may be fixed.
Please test it.