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v0xie / sd-webui-agentattention

Speed up image generation and improve image quality using Agent Attention.
GNU General Public License v3.0
39 stars 3 forks source link

Forge support? #13

Open slashedstar opened 2 months ago

slashedstar commented 2 months ago

With sdxl (pony/autismmix)

Moving model(s) has taken 1.28 seconds
  0%|                                                             | 0/20 [00:00<?, ?it/s]
Traceback (most recent call last):
  File "E:\blankforge\stable-diffusion-webui-forge\modules_forge\main_thread.py", line 37, in loop
    task.work()
  File "E:\blankforge\stable-diffusion-webui-forge\modules_forge\main_thread.py", line 26, in work
    self.result = self.func(*self.args, **self.kwargs)
  File "E:\blankforge\stable-diffusion-webui-forge\modules\txt2img.py", line 111, in txt2img_function
    processed = processing.process_images(p)
  File "E:\blankforge\stable-diffusion-webui-forge\modules\processing.py", line 752, in process_images
    res = process_images_inner(p)
  File "E:\blankforge\stable-diffusion-webui-forge\modules\processing.py", line 922, 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 "E:\blankforge\stable-diffusion-webui-forge\modules\processing.py", line 1275, in sample
    samples = self.sampler.sample(self, x, conditioning, unconditional_conditioning, image_conditioning=self.txt2img_image_conditioning(x))
  File "E:\blankforge\stable-diffusion-webui-forge\modules\sd_samplers_kdiffusion.py", line 251, 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 "E:\blankforge\stable-diffusion-webui-forge\modules\sd_samplers_common.py", line 263, in launch_sampling
    return func()
  File "E:\blankforge\stable-diffusion-webui-forge\modules\sd_samplers_kdiffusion.py", line 251, 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 "E:\blankforge\stable-diffusion-webui-forge\venv\lib\site-packages\torch\utils\_contextlib.py", line 115, in decorate_context
    return func(*args, **kwargs)
  File "E:\blankforge\stable-diffusion-webui-forge\repositories\k-diffusion\k_diffusion\sampling.py", line 594, in sample_dpmpp_2m
    denoised = model(x, sigmas[i] * s_in, **extra_args)
  File "E:\blankforge\stable-diffusion-webui-forge\venv\lib\site-packages\torch\nn\modules\module.py", line 1518, in _wrapped_call_impl
    return self._call_impl(*args, **kwargs)
  File "E:\blankforge\stable-diffusion-webui-forge\venv\lib\site-packages\torch\nn\modules\module.py", line 1527, in _call_impl
    return forward_call(*args, **kwargs)
  File "E:\blankforge\stable-diffusion-webui-forge\modules\sd_samplers_cfg_denoiser.py", line 182, in forward
    denoised = forge_sampler.forge_sample(self, denoiser_params=denoiser_params,
  File "E:\blankforge\stable-diffusion-webui-forge\modules_forge\forge_sampler.py", line 88, in forge_sample
    denoised = sampling_function(model, x, timestep, uncond, cond, cond_scale, model_options, seed)
  File "E:\blankforge\stable-diffusion-webui-forge\ldm_patched\modules\samplers.py", line 289, in sampling_function
    cond_pred, uncond_pred = calc_cond_uncond_batch(model, cond, uncond_, x, timestep, model_options)
  File "E:\blankforge\stable-diffusion-webui-forge\ldm_patched\modules\samplers.py", line 258, in calc_cond_uncond_batch
    output = model.apply_model(input_x, timestep_, **c).chunk(batch_chunks)
  File "E:\blankforge\stable-diffusion-webui-forge\ldm_patched\modules\model_base.py", line 90, in apply_model
    model_output = self.diffusion_model(xc, t, context=context, control=control, transformer_options=transformer_options, **extra_conds).float()
  File "E:\blankforge\stable-diffusion-webui-forge\venv\lib\site-packages\torch\nn\modules\module.py", line 1518, in _wrapped_call_impl
    return self._call_impl(*args, **kwargs)
  File "E:\blankforge\stable-diffusion-webui-forge\venv\lib\site-packages\torch\nn\modules\module.py", line 1568, in _call_impl
    result = forward_call(*args, **kwargs)
  File "E:\blankforge\stable-diffusion-webui-forge\ldm_patched\ldm\modules\diffusionmodules\openaimodel.py", line 867, in forward
    h = forward_timestep_embed(module, h, emb, context, transformer_options, time_context=time_context, num_video_frames=num_video_frames, image_only_indicator=image_only_indicator)
  File "E:\blankforge\stable-diffusion-webui-forge\ldm_patched\ldm\modules\diffusionmodules\openaimodel.py", line 55, in forward_timestep_embed
    x = layer(x, context, transformer_options)
  File "E:\blankforge\stable-diffusion-webui-forge\venv\lib\site-packages\torch\nn\modules\module.py", line 1518, in _wrapped_call_impl
    return self._call_impl(*args, **kwargs)
  File "E:\blankforge\stable-diffusion-webui-forge\venv\lib\site-packages\torch\nn\modules\module.py", line 1527, in _call_impl
    return forward_call(*args, **kwargs)
  File "E:\blankforge\stable-diffusion-webui-forge\ldm_patched\ldm\modules\attention.py", line 620, in forward
    x = block(x, context=context[i], transformer_options=transformer_options)
  File "E:\blankforge\stable-diffusion-webui-forge\venv\lib\site-packages\torch\nn\modules\module.py", line 1518, in _wrapped_call_impl
    return self._call_impl(*args, **kwargs)
  File "E:\blankforge\stable-diffusion-webui-forge\venv\lib\site-packages\torch\nn\modules\module.py", line 1527, in _call_impl
    return forward_call(*args, **kwargs)
  File "E:\blankforge\stable-diffusion-webui-forge\ldm_patched\ldm\modules\attention.py", line 447, in forward
    return checkpoint(self._forward, (x, context, transformer_options), self.parameters(), self.checkpoint)
  File "E:\blankforge\stable-diffusion-webui-forge\ldm_patched\ldm\modules\diffusionmodules\util.py", line 194, in checkpoint
    return func(*inputs)
TypeError: make_tome_block.<locals>.ToMeBlock._forward() takes from 2 to 3 positional arguments but 4 were given
make_tome_block.<locals>.ToMeBlock._forward() takes from 2 to 3 positional arguments but 4 were given
*** Error completing request
*** Arguments: ('task(8uaujpd8jrjr0si)', <gradio.routes.Request object at 0x000002960E6EB2E0>, 'car', '', [], 20, 'DPM++ 2M Karras', 1, 1, 7, 512, 512, False, 0.7, 2, 'Latent', 0, 0, 0, 'Use same checkpoint', 'Use same sampler', '', '', [], 0, False, '', 0.8, -1, False, -1, 0, 0, 0, True, False, 20, 4, 4, 0.4, 0.95, 2, 2, 0.4, 0.5, False, 2, False, 'NONE:0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0\nALL:1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1\nINS:1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0\nIND:1,0,0,0,1,1,1,0,0,0,0,0,0,0,0,0,0\nINALL:1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0\nMIDD:1,0,0,0,1,1,1,1,1,1,1,1,0,0,0,0,0\nOUTD:1,0,0,0,0,0,0,0,1,1,1,1,0,0,0,0,0\nOUTS:1,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1\nOUTALL:1,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1\nALL0.5:0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5', False, 0, 'values', '0,0.25,0.5,0.75,1', 'Block ID', 'IN05-OUT05', 'none', '', '0.5,1', 'BASE,IN00,IN01,IN02,IN03,IN04,IN05,IN06,IN07,IN08,IN09,IN10,IN11,M00,OUT00,OUT01,OUT02,OUT03,OUT04,OUT05,OUT06,OUT07,OUT08,OUT09,OUT10,OUT11', 1.0, 'black', '20', False, 'ATTNDEEPON:IN05-OUT05:attn:1\n\nATTNDEEPOFF:IN05-OUT05:attn:0\n\nPROJDEEPOFF:IN05-OUT05:proj:0\n\nXYZ:::1', False, False, ControlNetUnit(input_mode=<InputMode.SIMPLE: 'simple'>, use_preview_as_input=False, batch_image_dir='', batch_mask_dir='', batch_input_gallery=[], batch_mask_gallery=[], generated_image=None, mask_image=None, hr_option='Both', enabled=False, module='None', model='None', weight=1, image=None, resize_mode='Crop and Resize', processor_res=-1, threshold_a=-1, threshold_b=-1, guidance_start=0, guidance_end=1, pixel_perfect=False, control_mode='Balanced', save_detected_map=True), ControlNetUnit(input_mode=<InputMode.SIMPLE: 'simple'>, use_preview_as_input=False, batch_image_dir='', batch_mask_dir='', batch_input_gallery=[], batch_mask_gallery=[], generated_image=None, mask_image=None, hr_option='Both', enabled=False, module='None', model='None', weight=1, image=None, resize_mode='Crop and Resize', processor_res=-1, threshold_a=-1, threshold_b=-1, guidance_start=0, guidance_end=1, pixel_perfect=False, control_mode='Balanced', save_detected_map=True), ControlNetUnit(input_mode=<InputMode.SIMPLE: 'simple'>, use_preview_as_input=False, batch_image_dir='', batch_mask_dir='', batch_input_gallery=[], batch_mask_gallery=[], generated_image=None, mask_image=None, hr_option='Both', enabled=False, module='None', model='None', weight=1, image=None, resize_mode='Crop and Resize', processor_res=-1, threshold_a=-1, threshold_b=-1, guidance_start=0, guidance_end=1, pixel_perfect=False, control_mode='Balanced', save_detected_map=True), False, 7, 1, 'Constant', 0, 'Constant', 0, 1, 'enable', 'MEAN', 'AD', 1, False, 1.01, 1.02, 0.99, 0.95, False, 0.5, 2, False, 256, 2, 0, False, False, 3, 2, 0, 0.35, True, 'bicubic', 'bicubic', False, 0, 'anisotropic', 0, 'reinhard', 100, 0, 'subtract', 0, 0, 'gaussian', 'add', 0, 100, 127, 0, 'hard_clamp', 5, 0, 'None', 'None', False, 'MultiDiffusion', 768, 768, 64, 4, False, False, False, False, False, 'positive', 'comma', 0, False, False, 'start', '', 1, '', [], 0, '', [], 0, '', [], True, False, False, False, False, False, False, 0, False) {}
    Traceback (most recent call last):
      File "E:\blankforge\stable-diffusion-webui-forge\modules\call_queue.py", line 57, in f
        res = list(func(*args, **kwargs))
    TypeError: 'NoneType' object is not iterable

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LastTargaryen commented 2 months ago

I second this--like HE-LLLOOOOOOOOOOOOO we need this to work in forge please please please