SD报错信息

controlnet设置：

生成报错

Error completing request
Arguments: ('task(4w7lw0y6u6hjm6p)', 'a school uniform, ', 'worst quality, low quality, ', [], 20, 0, False, False, 1, 1, 7, -1.0, -1.0, 0, 0, 0, False, 768, 512, False, 0.7, 2, 'Latent', 0, 0, 0, [], 0, False, '', 0, False, False, 'LoRA', 'None', 1, 1, 'LoRA', 'None', 1, 1, 'LoRA', 'None', 1, 1, 'LoRA', 'None', 1, 1, 'LoRA', 'None', 1, 1, None, 'Refresh models', , , False, False, False, False, '1:1,1:2,1:2', '0:0,0:0,0:1', '0.2,0.8,0.8', 20, False, False, 'positive', 'comma', 0, False, False, '', 1, '', 0, '', 0, '', True, False, False, False, 0, None, False, None, False, 50) {}Traceback (most recent call last):
  File "I:\Program Files\stable-diffusion-webui-directml\stable-diffusion-webui-directml\modules\call_queue.py", line 56, in f
    res = list(func(*args, **kwargs))
  File "I:\Program Files\stable-diffusion-webui-directml\stable-diffusion-webui-directml\modules\call_queue.py", line 37, in f
    res = func(*args, **kwargs)
  File "I:\Program Files\stable-diffusion-webui-directml\stable-diffusion-webui-directml\modules\txt2img.py", line 56, in txt2img
    processed = process_images(p)
  File "I:\Program Files\stable-diffusion-webui-directml\stable-diffusion-webui-directml\modules\processing.py", line 503, in process_images
    res = process_images_inner(p)
  File "I:\Program Files\stable-diffusion-webui-directml\stable-diffusion-webui-directml\modules\processing.py", line 653, in process_images_inner
    samples_ddim = p.sample(conditioning=c, unconditional_conditioning=uc, seeds=seeds, subseeds=subseeds, subseed_strength=p.subseed_strength, prompts=prompts)
  File "I:\Program Files\stable-diffusion-webui-directml\stable-diffusion-webui-directml\modules\processing.py", line 869, in sample
    samples = self.sampler.sample(self, x, conditioning, unconditional_conditioning, image_conditioning=self.txt2img_image_conditioning(x))
  File "I:\Program Files\stable-diffusion-webui-directml\stable-diffusion-webui-directml\modules\sd_samplers_kdiffusion.py", line 358, in sample
    samples = self.launch_sampling(steps, lambda: self.func(self.model_wrap_cfg, x, extra_args={
  File "I:\Program Files\stable-diffusion-webui-directml\stable-diffusion-webui-directml\modules\sd_samplers_kdiffusion.py", line 234, in launch_sampling
    return func()
  File "I:\Program Files\stable-diffusion-webui-directml\stable-diffusion-webui-directml\modules\sd_samplers_kdiffusion.py", line 358, in 
    samples = self.launch_sampling(steps, lambda: self.func(self.model_wrap_cfg, x, extra_args={
  File "I:\Program Files\stable-diffusion-webui-directml\stable-diffusion-webui-directml\python\lib\site-packages\torch\autograd\grad_mode.py", line 27, in decorate_context
    return func(*args, **kwargs)
  File "I:\Program Files\stable-diffusion-webui-directml\stable-diffusion-webui-directml\repositories\k-diffusion\k_diffusion\sampling.py", line 150, in sample_euler_ancestral
    denoised = model(x, sigmas[i] * s_in, **extra_args)
  File "I:\Program Files\stable-diffusion-webui-directml\stable-diffusion-webui-directml\python\lib\site-packages\torch\nn\modules\module.py", line 1194, in _call_impl
    return forward_call(*input, **kwargs)
  File "I:\Program Files\stable-diffusion-webui-directml\stable-diffusion-webui-directml\modules\sd_samplers_kdiffusion.py", line 132, in forward
    x_out[a:b] = self.inner_model(x_in[a:b], sigma_in[a:b], cond=make_condition_dict([cond_in[a:b]], image_cond_in[a:b]))
  File "I:\Program Files\stable-diffusion-webui-directml\stable-diffusion-webui-directml\python\lib\site-packages\torch\nn\modules\module.py", line 1194, in _call_impl
    return forward_call(*input, **kwargs)
  File "I:\Program Files\stable-diffusion-webui-directml\stable-diffusion-webui-directml\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 "I:\Program Files\stable-diffusion-webui-directml\stable-diffusion-webui-directml\repositories\k-diffusion\k_diffusion\external.py", line 138, in get_eps
    return self.inner_model.apply_model(*args, **kwargs)
  File "I:\Program Files\stable-diffusion-webui-directml\stable-diffusion-webui-directml\modules\sd_hijack_utils.py", line 17, in 
    setattr(resolved_obj, func_path[-1], lambda *args, **kwargs: self(*args, **kwargs))
  File "I:\Program Files\stable-diffusion-webui-directml\stable-diffusion-webui-directml\modules\sd_hijack_utils.py", line 28, in __call__
    return self.__orig_func(*args, **kwargs)
  File "I:\Program Files\stable-diffusion-webui-directml\stable-diffusion-webui-directml\repositories\stable-diffusion-stability-ai\ldm\models\diffusion\ddpm.py", line 858, in apply_model
    x_recon = self.model(x_noisy, t, **cond)
  File "I:\Program Files\stable-diffusion-webui-directml\stable-diffusion-webui-directml\python\lib\site-packages\torch\nn\modules\module.py", line 1194, in _call_impl
    return forward_call(*input, **kwargs)
  File "I:\Program Files\stable-diffusion-webui-directml\stable-diffusion-webui-directml\repositories\stable-diffusion-stability-ai\ldm\models\diffusion\ddpm.py", line 1335, in forward
    out = self.diffusion_model(x, t, context=cc)
  File "I:\Program Files\stable-diffusion-webui-directml\stable-diffusion-webui-directml\python\lib\site-packages\torch\nn\modules\module.py", line 1194, in _call_impl
    return forward_call(*input, **kwargs)
  File "I:\Program Files\stable-diffusion-webui-directml\stable-diffusion-webui-directml\extensions\sd-webui-controlnet\scripts\hook.py", line 233, in forward2
    return forward(*args, **kwargs)
  File "I:\Program Files\stable-diffusion-webui-directml\stable-diffusion-webui-directml\extensions\sd-webui-controlnet\scripts\hook.py", line 176, in forward
    control = param.control_model(x=x_in, hint=param.hint_cond, timesteps=timesteps, context=context)
  File "I:\Program Files\stable-diffusion-webui-directml\stable-diffusion-webui-directml\python\lib\site-packages\torch\nn\modules\module.py", line 1194, in _call_impl
    return forward_call(*input, **kwargs)
  File "I:\Program Files\stable-diffusion-webui-directml\stable-diffusion-webui-directml\extensions\sd-webui-controlnet\scripts\cldm.py", line 115, in forward
    return self.control_model(*args, **kwargs)
  File "I:\Program Files\stable-diffusion-webui-directml\stable-diffusion-webui-directml\python\lib\site-packages\torch\nn\modules\module.py", line 1194, in _call_impl
    return forward_call(*input, **kwargs)
  File "I:\Program Files\stable-diffusion-webui-directml\stable-diffusion-webui-directml\extensions\sd-webui-controlnet\scripts\cldm.py", line 383, in forward
    h = module(h, emb, context)
  File "I:\Program Files\stable-diffusion-webui-directml\stable-diffusion-webui-directml\python\lib\site-packages\torch\nn\modules\module.py", line 1194, in _call_impl
    return forward_call(*input, **kwargs)
  File "I:\Program Files\stable-diffusion-webui-directml\stable-diffusion-webui-directml\repositories\stable-diffusion-stability-ai\ldm\modules\diffusionmodules\openaimodel.py", line 84, in forward
    x = layer(x, context)
  File "I:\Program Files\stable-diffusion-webui-directml\stable-diffusion-webui-directml\python\lib\site-packages\torch\nn\modules\module.py", line 1194, in _call_impl
    return forward_call(*input, **kwargs)
  File "I:\Program Files\stable-diffusion-webui-directml\stable-diffusion-webui-directml\repositories\stable-diffusion-stability-ai\ldm\modules\attention.py", line 334, in forward
    x = block(x, context=context[i])
  File "I:\Program Files\stable-diffusion-webui-directml\stable-diffusion-webui-directml\python\lib\site-packages\torch\nn\modules\module.py", line 1194, in _call_impl
    return forward_call(*input, **kwargs)
  File "I:\Program Files\stable-diffusion-webui-directml\stable-diffusion-webui-directml\repositories\stable-diffusion-stability-ai\ldm\modules\attention.py", line 269, in forward
    return checkpoint(self._forward, (x, context), self.parameters(), self.checkpoint)
  File "I:\Program Files\stable-diffusion-webui-directml\stable-diffusion-webui-directml\repositories\stable-diffusion-stability-ai\ldm\modules\diffusionmodules\util.py", line 114, in checkpoint
    return CheckpointFunction.apply(func, len(inputs), *args)
  File "I:\Program Files\stable-diffusion-webui-directml\stable-diffusion-webui-directml\repositories\stable-diffusion-stability-ai\ldm\modules\diffusionmodules\util.py", line 129, in forward
    output_tensors = ctx.run_function(*ctx.input_tensors)
  File "I:\Program Files\stable-diffusion-webui-directml\stable-diffusion-webui-directml\repositories\stable-diffusion-stability-ai\ldm\modules\attention.py", line 273, in _forward
    x = self.attn2(self.norm2(x), context=context) + x
  File "I:\Program Files\stable-diffusion-webui-directml\stable-diffusion-webui-directml\python\lib\site-packages\torch\nn\modules\module.py", line 1194, in _call_impl
    return forward_call(*input, **kwargs)
  File "I:\Program Files\stable-diffusion-webui-directml\stable-diffusion-webui-directml\modules\sd_hijack_optimizations.py", line 264, in sub_quad_attention_forward
    k = self.to_k(context_k)
  File "I:\Program Files\stable-diffusion-webui-directml\stable-diffusion-webui-directml\python\lib\site-packages\torch\nn\modules\module.py", line 1194, in _call_impl
    return forward_call(*input, **kwargs)
  File "I:\Program Files\stable-diffusion-webui-directml\stable-diffusion-webui-directml\extensions-builtin\Lora\lora.py", line 307, in lora_Linear_forward
    return torch.nn.Linear_forward_before_lora(self, input)
  File "I:\Program Files\stable-diffusion-webui-directml\stable-diffusion-webui-directml\python\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 (77x1024 and 768x320)