DWPose in StableDiffusion Webui Forge (not A1111) #80
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What is your Forge Version? Mine is working fine. |
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It seems i can't make DWPose to work with webui Forge. Not even openpose is working. I get a bunch of errors like:
Traceback (most recent call last):
File "G:\StableDiffusion\Forge\webui\modules_forge\main_thread.py", line 37, in loop
task.work()
File "G:\StableDiffusion\Forge\webui\modules_forge\main_thread.py", line 26, in work
self.result = self.func(*self.args, **self.kwargs)
File "G:\StableDiffusion\Forge\webui\modules\txt2img.py", line 111, in txt2img_function
processed = processing.process_images(p)
File "G:\StableDiffusion\Forge\webui\modules\processing.py", line 752, in process_images
res = process_images_inner(p)
File "G:\StableDiffusion\Forge\webui\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 "G:\StableDiffusion\Forge\webui\extensions\sd-webui-comfyui\lib_comfyui\webui\patches.py", line 95, in p_sample_patch
x = original_function(*args, **kwargs)
File "G:\StableDiffusion\Forge\webui\modules\processing.py", line 1275, in sample
samples = self.sampler.sample(self, x, conditioning, unconditional_conditioning, image_conditioning=self.txt2img_image_conditioning(x))
File "G:\StableDiffusion\Forge\webui\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 "G:\StableDiffusion\Forge\webui\modules\sd_samplers_common.py", line 263, in launch_sampling
return func()
File "G:\StableDiffusion\Forge\webui\modules\sd_samplers_kdiffusion.py", line 251, in
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 "G:\StableDiffusion\Forge\system\python\lib\site-packages\torch\utils_contextlib.py", line 115, in decorate_context
return func(*args, **kwargs)
File "G:\StableDiffusion\Forge\webui\repositories\k-diffusion\k_diffusion\sampling.py", line 594, in sample_dpmpp_2m
denoised = model(x, sigmas[i] * s_in, **extra_args)
File "G:\StableDiffusion\Forge\system\python\lib\site-packages\torch\nn\modules\module.py", line 1518, in _wrapped_call_impl
return self.call_impl(*args, **kwargs)
File "G:\StableDiffusion\Forge\system\python\lib\site-packages\torch\nn\modules\module.py", line 1527, in call_impl
return forward_call(*args, **kwargs)
File "G:\StableDiffusion\Forge\webui\modules\sd_samplers_cfg_denoiser.py", line 182, in forward
denoised = forge_sampler.forge_sample(self, denoiser_params=denoiser_params,
File "G:\StableDiffusion\Forge\webui\modules_forge\forge_sampler.py", line 88, in forge_sample
denoised = sampling_function(model, x, timestep, uncond, cond, cond_scale, model_options, seed)
File "G:\StableDiffusion\Forge\webui\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 "G:\StableDiffusion\Forge\webui\ldm_patched\modules\samplers.py", line 252, in calc_cond_uncond_batch
c['control'] = control.get_control(input_x, timestep, control_cond, len(cond_or_uncond))
File "G:\StableDiffusion\Forge\webui\ldm_patched\modules\controlnet.py", line 273, in get_control
control = self.control_model(x=x_noisy.to(dtype), hint=self.cond_hint.to(self.device), timesteps=timestep.float(), context=context.to(dtype), y=y)
File "G:\StableDiffusion\Forge\system\python\lib\site-packages\torch\nn\modules\module.py", line 1518, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "G:\StableDiffusion\Forge\system\python\lib\site-packages\torch\nn\modules\module.py", line 1527, in _call_impl
return forward_call(*args, **kwargs)
File "G:\StableDiffusion\Forge\webui\ldm_patched\controlnet\cldm.py", line 305, in forward
h = module(h, emb, context)
File "G:\StableDiffusion\Forge\system\python\lib\site-packages\torch\nn\modules\module.py", line 1518, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "G:\StableDiffusion\Forge\system\python\lib\site-packages\torch\nn\modules\module.py", line 1527, in _call_impl
return forward_call(*args, **kwargs)
File "G:\StableDiffusion\Forge\webui\ldm_patched\ldm\modules\diffusionmodules\openaimodel.py", line 74, in forward
return forward_timestep_embed(self, *args, **kwargs)
File "G:\StableDiffusion\Forge\webui\ldm_patched\ldm\modules\diffusionmodules\openaimodel.py", line 55, in forward_timestep_embed
x = layer(x, context, transformer_options)
File "G:\StableDiffusion\Forge\system\python\lib\site-packages\torch\nn\modules\module.py", line 1518, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "G:\StableDiffusion\Forge\system\python\lib\site-packages\torch\nn\modules\module.py", line 1527, in _call_impl
return forward_call(*args, **kwargs)
File "G:\StableDiffusion\Forge\webui\ldm_patched\ldm\modules\attention.py", line 620, in forward
x = block(x, context=context[i], transformer_options=transformer_options)
File "G:\StableDiffusion\Forge\system\python\lib\site-packages\torch\nn\modules\module.py", line 1518, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "G:\StableDiffusion\Forge\system\python\lib\site-packages\torch\nn\modules\module.py", line 1527, in _call_impl
return forward_call(*args, **kwargs)
File "G:\StableDiffusion\Forge\webui\ldm_patched\ldm\modules\attention.py", line 447, in forward
return checkpoint(self._forward, (x, context, transformer_options), self.parameters(), self.checkpoint)
File "G:\StableDiffusion\Forge\webui\ldm_patched\ldm\modules\diffusionmodules\util.py", line 194, in checkpoint
return func(*inputs)
File "G:\StableDiffusion\Forge\webui\ldm_patched\ldm\modules\attention.py", line 547, in _forward
n = self.attn2(n, context=context_attn2, value=value_attn2, transformer_options=extra_options)
File "G:\StableDiffusion\Forge\system\python\lib\site-packages\torch\nn\modules\module.py", line 1518, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "G:\StableDiffusion\Forge\system\python\lib\site-packages\torch\nn\modules\module.py", line 1527, in _call_impl
return forward_call(*args, **kwargs)
File "G:\StableDiffusion\Forge\webui\ldm_patched\ldm\modules\attention.py", line 391, in forward
k = self.to_k(context)
File "G:\StableDiffusion\Forge\system\python\lib\site-packages\torch\nn\modules\module.py", line 1518, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "G:\StableDiffusion\Forge\system\python\lib\site-packages\torch\nn\modules\module.py", line 1527, in _call_impl
return forward_call(*args, **kwargs)
File "G:\StableDiffusion\Forge\webui\ldm_patched\modules\ops.py", line 96, in forward
return self.forward_ldm_patched_cast_weights(*args, **kwargs)
File "G:\StableDiffusion\Forge\webui\ldm_patched\modules\ops.py", line 92, in forward_ldm_patched_cast_weights
return torch.nn.functional.linear(input, weight, bias)
RuntimeError: mat1 and mat2 shapes cannot be multiplied (77x2048 and 768x320)
mat1 and mat2 shapes cannot be multiplied (77x2048 and 768x320)
*** Error completing request
*** Arguments: ('task(7iln8oruaqyegfz)', <gradio.routes.Request object at 0x0000023B98BD9E10>, 'Redhead girl, classy outfit, full body portrait', '', [], 6, 'DPM++ 2M Karras', 1, 1, 2, 1216, 832, False, 0.7, 2, 'Latent', 0, 0, 0, 'Use same checkpoint', 'Use same sampler', '', '', [], 0, False, '', 0.8, -1, False, -1, 0, 0, 0, '5c801b21-0f0a-4985-86e4-863eeab17138', True, {'postprocess_latent_txt2img': False, 'postprocess_txt2img': False, 'postprocess_image_txt2img': False, 'before_save_image_txt2img': 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=array([[[0, 0, 0],
*** [0, 0, 0],
*** [0, 0, 0],
*** ...,
*** [0, 0, 0],
*** [0, 0, 0],
*** [0, 0, 0]],
*** [[0, 0, 0],
*** [0, 0, 0],
*** [0, 0, 0],
*** ...,
*** [0, 0, 0],
*** [0, 0, 0],
*** [0, 0, 0]],
*** [[0, 0, 0],
*** [0, 0, 0],
*** [0, 0, 0],
*** ...,
*** [0, 0, 0],
*** [0, 0, 0],
*** [0, 0, 0]],
*** ...,
*** [[0, 0, 0],
*** [0, 0, 0],
*** [0, 0, 0],
*** ...,
*** [0, 0, 0],
*** [0, 0, 0],
*** [0, 0, 0]],
*** [[0, 0, 0],
*** [0, 0, 0],
*** [0, 0, 0],
*** ...,
*** [0, 0, 0],
*** [0, 0, 0],
*** [0, 0, 0]],
*** [[0, 0, 0],
*** [0, 0, 0],
*** [0, 0, 0],
*** ...,
*** [0, 0, 0],
*** [0, 0, 0],
*** [0, 0, 0]]], dtype=uint8), mask_image=None, hr_option='Both', enabled=True, module='openpose_full', model='control_v11p_sd15_openpose [cab727d4]', weight=1, image={'image': array([[[ 92, 86, 26],
*** [ 93, 87, 27],
*** [ 94, 88, 28],
*** ...,
*** [ 47, 65, 79],
*** [ 44, 62, 76],
*** [ 45, 63, 77]],
*** [[ 90, 84, 24],
*** [ 91, 85, 25],
*** [ 92, 86, 26],
*** ...,
*** [ 47, 65, 79],
*** [ 44, 62, 76],
*** [ 45, 63, 77]],
*** [[ 87, 81, 23],
*** [ 88, 82, 24],
*** [ 90, 84, 26],
*** ...,
*** [ 47, 65, 79],
*** [ 44, 62, 76],
*** [ 44, 62, 76]],
*** ...,
*** [[115, 117, 54],
*** [116, 117, 59],
*** [123, 126, 73],
*** ...,
*** [ 45, 53, 4],
*** [ 35, 44, 0],
*** [ 39, 47, 0]],
*** [[117, 120, 53],
*** [122, 124, 61],
*** [130, 133, 76],
*** ...,
*** [ 42, 48, 12],
*** [ 31, 37, 3],
*** [ 29, 34, 4]],
*** [[112, 116, 40],
*** [115, 118, 47],
*** [120, 125, 61],
*** ...,
*** [ 33, 36, 15],
*** [ 24, 27, 10],
*** [ 32, 34, 20]]], dtype=uint8), 'mask': array([[[0, 0, 0],
*** [0, 0, 0],
*** [0, 0, 0],
*** ...,
*** [0, 0, 0],
*** [0, 0, 0],
*** [0, 0, 0]],
*** [[0, 0, 0],
*** [0, 0, 0],
*** [0, 0, 0],
*** ...,
*** [0, 0, 0],
*** [0, 0, 0],
*** [0, 0, 0]],
*** [[0, 0, 0],
*** [0, 0, 0],
*** [0, 0, 0],
*** ...,
*** [0, 0, 0],
*** [0, 0, 0],
*** [0, 0, 0]],
*** ...,
*** [[0, 0, 0],
*** [0, 0, 0],
*** [0, 0, 0],
*** ...,
*** [0, 0, 0],
*** [0, 0, 0],
*** [0, 0, 0]],
*** [[0, 0, 0],
*** [0, 0, 0],
*** [0, 0, 0],
*** ...,
*** [0, 0, 0],
*** [0, 0, 0],
*** [0, 0, 0]],
*** [[0, 0, 0],
*** [0, 0, 0],
*** [0, 0, 0],
*** ...,
*** [0, 0, 0],
*** [0, 0, 0],
*** [0, 0, 0]]], dtype=uint8)}, resize_mode='Crop and Resize', processor_res=832, threshold_a=0.5, threshold_b=0.5, guidance_start=0, guidance_end=1, pixel_perfect=True, 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 "G:\StableDiffusion\Forge\webui\modules\call_queue.py", line 57, in f
res = list(func(*args, **kwargs))
TypeError: 'NoneType' object is not iterable
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