[Bug]: RuntimeError: mat1 and mat2 shapes cannot be multiplied (2x2560 and 2816x1280）

[hjj-lmx]

Is there an existing issue for this?

• [X] I have searched the existing issues and checked the recent builds/commits

What happened?

Frequently reporting errors above

Steps to reproduce the problem

img2mg

What should have happened?

RuntimeError: mat1 and mat2 shapes cannot be multiplied (2x2560 and 2816x1280）

Sysinfo

RuntimeError: mat1 and mat2 shapes cannot be multiplied (2x2560 and 2816x1280）

What browsers do you use to access the UI ?

Google Chrome

Console logs

RuntimeError: mat1 and mat2 shapes cannot be multiplied (2x2560 and 2816x1280）

Additional information

No response

[vegetable-coder11]

well, Did the bug happen in Lora/networks.py?

[hjj-lmx]

好吧，这个 bug 发生在 Lora/networks.py 中吗？

Traceback (most recent call last): File "D:\stable-diffusion-webui\modules\call_queue.py", line 57, in f res = list(func(*args, kwargs)) File "D:\stable-diffusion-webui\modules\call_queue.py", line 36, in f res = func(*args, *kwargs) File "D:\stable-diffusion-webui\modules\img2img.py", line 208, in img2img processed = process_images(p) File "D:\stable-diffusion-webui\modules\processing.py", line 732, in process_images res = process_images_inner(p) File "D:\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:\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:\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:\stable-diffusion-webui\modules\sd_samplers_kdiffusion.py", line 188, 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:\stable-diffusion-webui\modules\sd_samplers_common.py", line 261, in launch_sampling return func() File "D:\stable-diffusion-webui\modules\sd_samplers_kdiffusion.py", line 188, 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:\stable-diffusion-webui\venv\lib\site-packages\torch\utils_contextlib.py", line 115, in decorate_context return func(*args, kwargs) File "D:\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:\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl return forward_call(args, kwargs) File "D:\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:\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl return forward_call(*args, kwargs) File "D:\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:\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:\stable-diffusion-webui\modules\sd_models_xl.py", line 37, in apply_model return self.model(x, t, cond) File "D:\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl return forward_call(*args, kwargs) File "D:\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:\stable-diffusion-webui\modules\sd_hijack_utils.py", line 28, in call return self.__orig_func(*args, kwargs) File "D:\stable-diffusion-webui\repositories\generative-models\sgm\modules\diffusionmodules\wrappers.py", line 28, in forward return self.diffusion_model( File "D:\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl return forward_call(*args, *kwargs) File "D:\stable-diffusion-webui\repositories\generative-models\sgm\modules\diffusionmodules\openaimodel.py", line 988, in forward emb = emb + self.label_emb(y) File "D:\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl return forward_call(args, kwargs) File "D:\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\container.py", line 217, in forward input = module(input) File "D:\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl return forward_call(*args, *kwargs) File "D:\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\container.py", line 217, in forward input = module(input) File "D:\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl return forward_call(args, **kwargs) File "D:\stable-diffusion-webui\extensions-builtin\Lora\networks.py", line 429, in network_Linear_forward return originals.Linear_forward(self, input) File "D:\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\linear.py", line 114, in forward return F.linear(input, self.weight, self.bias) RuntimeError: mat1 and mat2 shapes cannot be multiplied (2x2560 and 2816x1280)

[vegetable-coder11]

我也是遇到这个bug，我用的是SDXL1.0 refiner，可能是lora不适配SDXL？

[hjj-lmx]

我也遇到了这个bug，我用的是SDXL1.0 精炼机，可能是lora没有改装SDXL？

Lora was not enabled, only the model was placed in the project，Lora model name: sd_xl_offset_example-lora_1.0