Conflict with NegPiP

[player99963]

When using NegPiP and Tiled Diffusion & VAE in i2i, the picture cannot be generated.

This issue was also posted on the other side.
hako-mikan/sd-webui-negpip#28

*** Error completing request
*** Arguments: ('task(txlkh92y0mixds7)', 0, '1girl,(flower:-1),', '', [], <PIL.Image.Image image mode=RGBA size=640x1024 at 0x24FB50ACD00>, None, None, None, None, None, None, 20, 'DPM++ 2M Karras', 4, 0, 1, 1, 1, 3, 1.5, 0.5, 0, 1024, 640, 1, 0, 0, 32, 0, '', '', '', [], False, [], '', <gradio.routes.Request object at 0x0000024F8A4C2320>, 0, False, '', 0.8, 3683106263, False, -1, 0, 0, 0, True, 'keyword prompt', 'keyword1, keyword2', 'None', 'textual inversion first', 'None', '0.7', 'None', True, 'MultiDiffusion', False, True, 1024, 1024, 96, 96, 48, 4, 'SwinIR_4x', 2, False, 10, 1, 1, 64, False, False, False, False, False, 0.4, 0.4, 0.2, 0.2, '', '', 'Background', 0.2, -1.0, False, 0.4, 0.4, 0.2, 0.2, '', '', 'Background', 0.2, -1.0, False, 0.4, 0.4, 0.2, 0.2, '', '', 'Background', 0.2, -1.0, False, 0.4, 0.4, 0.2, 0.2, '', '', 'Background', 0.2, -1.0, False, 0.4, 0.4, 0.2, 0.2, '', '', 'Background', 0.2, -1.0, False, 0.4, 0.4, 0.2, 0.2, '', '', 'Background', 0.2, -1.0, False, 0.4, 0.4, 0.2, 0.2, '', '', 'Background', 0.2, -1.0, False, 0.4, 0.4, 0.2, 0.2, '', '', 'Background', 0.2, -1.0, False, 3072, 192, True, True, True, False, True, False, 1, False, False, False, 1.1, 1.5, 100, 0.7, False, False, True, False, False, 0, 'Gustavosta/MagicPrompt-Stable-Diffusion', '', False, 'Use same checkpoint', 'Use same vae', 1, 0, 'None', 'None', False, False, False, 'Use same checkpoint', 'Use same vae', 'txt2img-1pass', 'None', '', '', 'Use same sampler', 'BMAB fast', 20, 7, 0.75, 0.5, 0.1, 0.9, False, False, 'Select Model', '', '', 'Use same sampler', 20, 7, 0.75, 4, 0.35, False, 50, 200, 0.5, False, True, 'stretching', 'bottom', 'None', 0.85, 0.75, False, 'Use same checkpoint', True, '', '', 'Use same sampler', 'BMAB fast', 20, 7, 0.75, 1, 0, 0, 1, 1, 1, 1, 0, 0, 0, None, False, 1, False, '', False, False, False, True, True, 4, 3, 0.1, 1, 1, 0, 0.4, 7, False, False, False, 'Score', 1, '', '', '', '', '', '', '', '', '', '', False, 512, 512, 7, 20, 4, 'Use same sampler', 'Only masked', 32, 'BMAB Face(Normal)', 0.4, 4, 0.35, False, 0.26, False, True, False, 'subframe', '', '', 0.4, 7, True, 4, 0.3, 0.1, 'Only masked', 32, '', False, False, False, 0.4, 0.1, 0.9, False, 'Inpaint', 0.85, 0.6, 30, False, True, 'None', 1.5, '', 'None', UiControlNetUnit(enabled=True, module='none', model='control_v11f1e_sd15_tile [a371b31b]', weight=1, image=None, resize_mode='Crop and Resize', low_vram=False, processor_res=-1, threshold_a=-1, threshold_b=-1, guidance_start=0, guidance_end=1, pixel_perfect=True, control_mode='ControlNet is more important', save_detected_map=True), True, '* CFG Scale should be 2 or lower.', True, True, '', '', True, 50, True, 1, 0, False, 4, 0.5, 'Linear', 'None', '

Recommended settings: Sampling Steps: 80-100, Sampler: Euler a, Denoising strength: 0.8

', 128, 8, ['left', 'right', 'up', 'down'], 1, 0.05, 128, 4, 0, ['left', 'right', 'up', 'down'], False, False, 'positive', 'comma', 0, False, False, '', '

Will upscale the image by the selected scale factor; use width and height sliders to set tile size

', 64, 0, 2, 1, '', [], 0, '', [], 0, '', [], True, False, False, False, 0, False, None, None, False, 50, '

Will upscale the image depending on the selected target size type

', 512, 0, 8, 32, 64, 0.35, 32, 0, True, 0, False, 8, 0, 0, 2048, 2048, 2) {}
Traceback (most recent call last):
File "D:\A1111 Web UI Autoinstaller\stable-diffusion-webui\modules\call_queue.py", line 57, in f
res = list(func(*args, **kwargs))
File "D:\A1111 Web UI Autoinstaller\stable-diffusion-webui\modules\call_queue.py", line 36, in f
res = func(*args, **kwargs)
File "D:\A1111 Web UI Autoinstaller\stable-diffusion-webui\modules\img2img.py", line 208, in img2img
processed = process_images(p)
File "D:\A1111 Web UI Autoinstaller\stable-diffusion-webui\modules\processing.py", line 732, in process_images
res = process_images_inner(p)
File "D:\A1111 Web UI Autoinstaller\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 "D:\A1111 Web UI Autoinstaller\stable-diffusion-webui\modules\processing.py", line 867, 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 "D:\A1111 Web UI Autoinstaller\stable-diffusion-webui\extensions\sd-webui-controlnet\scripts\hook.py", line 420, in process_sample
return process.sample_before_CN_hack(*args, **kwargs)
File "D:\A1111 Web UI Autoinstaller\stable-diffusion-webui\modules\processing.py", line 1528, in sample
samples = self.sampler.sample_img2img(self, self.init_latent, x, conditioning, unconditional_conditioning, image_conditioning=self.image_conditioning)
File "D:\A1111 Web UI Autoinstaller\stable-diffusion-webui\extensions\sd-webui-bmab\sd_bmab\sd_override\samper.py", line 67, in sample_img2img
samples = self.launch_sampling(t_enc + 1, lambda: self.func(self.model_wrap_cfg, xi, extra_args=self.sampler_extra_args, disable=False, callback=self.callback_state, **extra_params_kwargs))
File "D:\A1111 Web UI Autoinstaller\stable-diffusion-webui\modules\sd_samplers_common.py", line 261, in launch_sampling
return func()
File "D:\A1111 Web UI Autoinstaller\stable-diffusion-webui\extensions\sd-webui-bmab\sd_bmab\sd_override\samper.py", line 67, in
samples = self.launch_sampling(t_enc + 1, lambda: self.func(self.model_wrap_cfg, xi, extra_args=self.sampler_extra_args, disable=False, callback=self.callback_state, **extra_params_kwargs))
File "D:\A1111 Web UI Autoinstaller\stable-diffusion-webui\venv\lib\site-packages\torch\utils_contextlib.py", line 115, in decorate_context
return func(*args, **kwargs)
File "D:\A1111 Web UI Autoinstaller\stable-diffusion-webui\repositories\k-diffusion\k_diffusion\sampling.py", line 594, in sample_dpmpp_2m
denoised = model(x, sigmas[i] * s_in, **extra_args)
File "D:\A1111 Web UI Autoinstaller\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl
return forward_call(*args, **kwargs)
File "D:\A1111 Web UI Autoinstaller\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 "D:\A1111 Web UI Autoinstaller\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl
return forward_call(*args, **kwargs)
File "D:\A1111 Web UI Autoinstaller\stable-diffusion-webui\venv\lib\site-packages\torch\utils_contextlib.py", line 115, in decorate_context
return func(*args, **kwargs)
File "D:\A1111 Web UI Autoinstaller\stable-diffusion-webui\extensions\multidiffusion-upscaler-for-automatic1111\tile_utils\utils.py", line 249, in wrapper
return fn(*args, **kwargs)
File "D:\A1111 Web UI Autoinstaller\stable-diffusion-webui\extensions\multidiffusion-upscaler-for-automatic1111\tile_methods\multidiffusion.py", line 70, in kdiff_forward
return self.sample_one_step(x_in, org_func, repeat_func, custom_func)
File "D:\A1111 Web UI Autoinstaller\stable-diffusion-webui\extensions\multidiffusion-upscaler-for-automatic1111\tile_methods\multidiffusion.py", line 165, in sample_one_step
x_tile_out = repeat_func(x_tile, bboxes)
File "D:\A1111 Web UI Autoinstaller\stable-diffusion-webui\extensions\multidiffusion-upscaler-for-automatic1111\tile_methods\multidiffusion.py", line 65, in repeat_func
return self.sampler_forward(x_tile, sigma_tile, cond=cond_tile)
File "D:\A1111 Web UI Autoinstaller\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 "D:\A1111 Web UI Autoinstaller\stable-diffusion-webui\repositories\k-diffusion\k_diffusion\external.py", line 138, in get_eps
return self.inner_model.apply_model(*args, **kwargs)
File "D:\A1111 Web UI Autoinstaller\stable-diffusion-webui\modules\sd_hijack_utils.py", line 17, in
setattr(resolved_obj, func_path[-1], lambda *args, **kwargs: self(*args, **kwargs))
File "D:\A1111 Web UI Autoinstaller\stable-diffusion-webui\modules\sd_hijack_utils.py", line 28, in call
return self.__orig_func(*args, **kwargs)
File "D:\A1111 Web UI Autoinstaller\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 "D:\A1111 Web UI Autoinstaller\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl
return forward_call(*args, **kwargs)
File "D:\A1111 Web UI Autoinstaller\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 "D:\A1111 Web UI Autoinstaller\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl
return forward_call(*args, **kwargs)
File "D:\A1111 Web UI Autoinstaller\stable-diffusion-webui\extensions\sd-webui-controlnet\scripts\hook.py", line 827, in forward_webui
raise e
File "D:\A1111 Web UI Autoinstaller\stable-diffusion-webui\extensions\sd-webui-controlnet\scripts\hook.py", line 824, in forward_webui
return forward(*args, **kwargs)
File "D:\A1111 Web UI Autoinstaller\stable-diffusion-webui\extensions\sd-webui-controlnet\scripts\hook.py", line 731, in forward
h = module(h, emb, context)
File "D:\A1111 Web UI Autoinstaller\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl
return forward_call(*args, **kwargs)
File "D:\A1111 Web UI Autoinstaller\stable-diffusion-webui\repositories\stable-diffusion-stability-ai\ldm\modules\diffusionmodules\openaimodel.py", line 84, in forward
x = layer(x, context)
File "D:\A1111 Web UI Autoinstaller\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl
return forward_call(*args, **kwargs)
File "D:\A1111 Web UI Autoinstaller\stable-diffusion-webui\repositories\stable-diffusion-stability-ai\ldm\modules\attention.py", line 334, in forward
x = block(x, context=context[i])
File "D:\A1111 Web UI Autoinstaller\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl
return forward_call(*args, **kwargs)
File "D:\A1111 Web UI Autoinstaller\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 "D:\A1111 Web UI Autoinstaller\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 "D:\A1111 Web UI Autoinstaller\stable-diffusion-webui\venv\lib\site-packages\torch\autograd\function.py", line 506, in apply
return super().apply(*args, **kwargs) # type: ignore[misc]
File "D:\A1111 Web UI Autoinstaller\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 "D:\A1111 Web UI Autoinstaller\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 "D:\A1111 Web UI Autoinstaller\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl
return forward_call(*args, **kwargs)
File "D:\A1111 Web UI Autoinstaller\stable-diffusion-webui\extensions\sd-webui-negpip\scripts\negpip.py", line 330, in forward
return sub_forward(x, context, mask, additional_tokens, n_times_crossframe_attn_in_self,self.conds[0],self.contokens[0],self.unconds[0],self.untokens[0])
File "D:\A1111 Web UI Autoinstaller\stable-diffusion-webui\extensions\sd-webui-negpip\scripts\negpip.py", line 311, in sub_forward
context = torch.cat([context,conds],1)
RuntimeError: Sizes of tensors must match except in dimension 1. Expected size 8 but got size 1 for tensor number 1 in the list.