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laksjdjf / IPAdapter-ComfyUI

experimental
GNU General Public License v3.0
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When I use the IP adapter node with T2I Style Model, the black image is generated. #4

Open toyxyz opened 1 year ago

toyxyz commented 1 year ago

I tried to use the IP adapter node simultaneously with the T2I adapter_style, but only the black empty image was generated. There is no problem when each used separately. Also there is no problem when used simultaneously with Shuffle Control Net.

IP adapter workflow (8)

IP adapter + T2I adapter Style workflow (7)

T2I adapter Style workflow (6)

IP adapter + Shuffle Controlnet workflow (9)

`Error occurred when executing KSampler:

step must be nonzero

File "C:\ComfyUI_windows_portable\ComfyUI\execution.py", line 151, in recursive_execute output_data, output_ui = get_output_data(obj, input_data_all) File "C:\ComfyUI_windows_portable\ComfyUI\execution.py", line 81, in get_output_data return_values = map_node_over_list(obj, input_data_all, obj.FUNCTION, allow_interrupt=True) File "C:\ComfyUI_windows_portable\ComfyUI\execution.py", line 74, in map_node_over_list results.append(getattr(obj, func)(slice_dict(input_data_all, i))) File "C:\ComfyUI_windows_portable\ComfyUI\nodes.py", line 1206, in sample return common_ksampler(model, seed, steps, cfg, sampler_name, scheduler, positive, negative, latent_image, denoise=denoise) File "C:\ComfyUI_windows_portable\ComfyUI\nodes.py", line 1176, in common_ksampler samples = comfy.sample.sample(model, noise, steps, cfg, sampler_name, scheduler, positive, negative, latent_image, File "C:\ComfyUI_windows_portable\ComfyUI\custom_nodes\ComfyUI-Impact-Pack\modules\impact\hacky.py", line 22, in informative_sample raise e File "C:\ComfyUI_windows_portable\ComfyUI\custom_nodes\ComfyUI-Impact-Pack\modules\impact\hacky.py", line 9, in informative_sample return original_sample(*args, *kwargs) File "C:\ComfyUI_windows_portable\ComfyUI\comfy\sample.py", line 93, in sample samples = sampler.sample(noise, positive_copy, negative_copy, cfg=cfg, latent_image=latent_image, start_step=start_step, last_step=last_step, force_full_denoise=force_full_denoise, denoise_mask=noise_mask, sigmas=sigmas, callback=callback, disable_pbar=disable_pbar, seed=seed) File "C:\ComfyUI_windows_portable\ComfyUI\comfy\samplers.py", line 733, in sample samples = getattr(k_diffusionsampling, "sample{}".format(self.sampler))(self.model_k, noise, sigmas, extra_args=extra_args, callback=k_callback, disable=disable_pbar) File "C:\ComfyUI_windows_portable\python_embeded\lib\site-packages\torch\utils_contextlib.py", line 115, in decorate_context return func(args, kwargs) File "C:\ComfyUI_windows_portable\ComfyUI\comfy\k_diffusion\sampling.py", line 580, in sample_dpmpp_2m denoised = model(x, sigmas[i] * s_in, extra_args) File "C:\ComfyUI_windows_portable\python_embeded\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl return forward_call(*args, *kwargs) File "C:\ComfyUI_windows_portable\ComfyUI\comfy\samplers.py", line 323, in forward out = self.inner_model(x, sigma, cond=cond, uncond=uncond, cond_scale=cond_scale, cond_concat=cond_concat, model_options=model_options, seed=seed) File "C:\ComfyUI_windows_portable\python_embeded\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl return forward_call(args, kwargs) File "C:\ComfyUI_windows_portable\ComfyUI\comfy\k_diffusion\external.py", line 125, in forward eps = self.get_eps(input * c_in, self.sigma_to_t(sigma), kwargs) File "C:\ComfyUI_windows_portable\ComfyUI\comfy\k_diffusion\external.py", line 151, in get_eps return self.inner_model.apply_model(args, kwargs) File "C:\ComfyUI_windows_portable\ComfyUI\comfy\samplers.py", line 311, in apply_model out = sampling_function(self.inner_model.apply_model, x, timestep, uncond, cond, cond_scale, cond_concat, model_options=model_options, seed=seed) File "C:\ComfyUI_windows_portable\ComfyUI\comfy\samplers.py", line 289, in sampling_function cond, uncond = calc_cond_uncond_batch(model_function, cond, uncond, x, timestep, max_total_area, cond_concat, model_options) File "C:\ComfyUI_windows_portable\ComfyUI\comfy\samplers.py", line 263, in calc_cond_uncond_batch output = model_function(inputx, timestep, c).chunk(batch_chunks) File "C:\ComfyUI_windows_portable\ComfyUI\comfy\model_base.py", line 61, in apply_model return self.diffusion_model(xc, t, context=context, y=c_adm, control=control, transformer_options=transformer_options).float() File "C:\ComfyUI_windows_portable\python_embeded\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl return forward_call(args, kwargs) File "C:\ComfyUI_windows_portable\ComfyUI\comfy\ldm\modules\diffusionmodules\openaimodel.py", line 626, in forward h = forward_timestep_embed(module, h, emb, context, transformer_options) File "C:\ComfyUI_windows_portable\ComfyUI\comfy\ldm\modules\diffusionmodules\openaimodel.py", line 56, in forward_timestep_embed x = layer(x, context, transformer_options) File "C:\ComfyUI_windows_portable\python_embeded\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl return forward_call(*args, *kwargs) File "C:\ComfyUI_windows_portable\ComfyUI\comfy\ldm\modules\attention.py", line 696, in forward x = block(x, context=context[i], transformer_options=transformer_options) File "C:\ComfyUI_windows_portable\python_embeded\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl return forward_call(args, *kwargs) File "C:\ComfyUI_windows_portable\ComfyUI\comfy\ldm\modules\attention.py", line 528, in forward return checkpoint(self._forward, (x, context, transformer_options), self.parameters(), self.checkpoint) File "C:\ComfyUI_windows_portable\ComfyUI\comfy\ldm\modules\diffusionmodules\util.py", line 123, in checkpoint return func(inputs) File "C:\ComfyUI_windows_portable\ComfyUI\comfy\ldm\modules\attention.py", line 625, in _forward n = attn2_replace_patch[block_attn2](n, context_attn2, value_attn2, extra_options) File "C:\ComfyUI_windows_portable\ComfyUI\custom_nodes\IPAdapter-ComfyUI\ip_adapter.py", line 166, in forward ip_out = torch.nn.functional.scaled_dot_product_attention(q, ip_k, ip_v, attn_mask=None, dropout_p=0.0, is_causal=False)`

testFaze commented 11 months ago

I think I have found a workaround for this. You need to also apply a t2i style model to your negative prompt conditioning. You can weight this to zero so it won't do anything. I assume it must reshape an array or something, and there is no doubt a more elegant coding fix possible. But it works.