search

hako-mikan / sd-webui-negpip

Extension for Stable Diffusion web-ui enables negative prompt in prompt
GNU Affero General Public License v3.0
205 stars 16 forks source link

Conflict with Tiled Diffusion & VAE #28

Closed player99963 closed 10 months ago

player99963 commented 1 year ago

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

image

This issue was also posted on the other side. https://github.com/pkuliyi2015/multidiffusion-upscaler-for-automatic1111/issues/334

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.

hako-mikan commented 11 months ago

Fixed.