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jags111 / efficiency-nodes-comfyui

A collection of ComfyUI custom nodes.- Awesome smart way to work with nodes!
https://civitai.com/models/32342
GNU General Public License v3.0
739 stars 76 forks source link

CUDA out of memory #154

Closed Flooosee closed 2 weeks ago

Flooosee commented 3 months ago

Whenever i plug the HighRes Scripts to the KSampler (efficient), it is demanding indecent amount of VRAM and runs out of memory. image If the Scripts is unpluged, everything continue without any problem. Im using Zluda to perform ComfyUI on AMD GPU.

Logs: Error occurred when executing KSampler (Efficient):

CUDA out of memory. Tried to allocate 40.50 GiB. GPU 0 has a total capacity of 15.98 GiB of which 11.34 GiB is free. Of the allocated memory 4.22 GiB is allocated by PyTorch, and 99.46 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables)

File "C:\SDNext\ComfyUI\execution.py", line 151, in recursive_execute output_data, output_ui = get_output_data(obj, input_data_all) File "C:\SDNext\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:\SDNext\ComfyUI\execution.py", line 74, in map_node_over_list results.append(getattr(obj, func)(slice_dict(input_data_all, i))) File "C:\SDNext\ComfyUI\custom_nodes\efficiency-nodes-comfyui-main\efficiency_nodes.py", line 713, in sample samples, images, gifs, preview = process_latent_image(model, seed, steps, cfg, sampler_name, scheduler, File "C:\SDNext\ComfyUI\custom_nodes\efficiency-nodes-comfyui-main\efficiency_nodes.py", line 601, in process_latent_image samples = KSampler().sample(latent_upscale_model, hires_seed, hires_steps, cfg, sampler_name, scheduler, File "C:\SDNext\ComfyUI\nodes.py", line 1344, in sample return common_ksampler(model, seed, steps, cfg, sampler_name, scheduler, positive, negative, latent_image, denoise=denoise) File "C:\SDNext\ComfyUI\nodes.py", line 1314, in common_ksampler samples = comfy.sample.sample(model, noise, steps, cfg, sampler_name, scheduler, positive, negative, latent_image, File "C:\SDNext\ComfyUI\custom_nodes\ComfyUI-Impact-Pack\modules\impact\sample_error_enhancer.py", line 22, in informative_sample raise e File "C:\SDNext\ComfyUI\custom_nodes\ComfyUI-Impact-Pack\modules\impact\sample_error_enhancer.py", line 9, in informative_sample return original_sample(args, kwargs) # This code helps interpret error messages that occur within exceptions but does not have any impact on other operations. File "C:\SDNext\ComfyUI\comfy\sample.py", line 37, in sample samples = sampler.sample(noise, positive, negative, 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:\SDNext\ComfyUI\comfy\samplers.py", line 755, in sample return sample(self.model, noise, positive, negative, cfg, self.device, sampler, sigmas, self.model_options, latent_image=latent_image, denoise_mask=denoise_mask, callback=callback, disable_pbar=disable_pbar, seed=seed) File "C:\SDNext\ComfyUI\comfy\samplers.py", line 657, in sample return cfg_guider.sample(noise, latent_image, sampler, sigmas, denoise_mask, callback, disable_pbar, seed) File "C:\SDNext\ComfyUI\comfy\samplers.py", line 644, in sample output = self.inner_sample(noise, latent_image, device, sampler, sigmas, denoise_mask, callback, disable_pbar, seed) File "C:\SDNext\ComfyUI\comfy\samplers.py", line 623, in inner_sample samples = sampler.sample(self, sigmas, extra_args, callback, noise, latent_image, denoise_mask, disable_pbar) File "C:\SDNext\ComfyUI\comfy\samplers.py", line 534, in sample samples = self.sampler_function(model_k, noise, sigmas, extra_args=extra_args, callback=k_callback, disable=disable_pbar, self.extra_options) File "c:\SDNext\automatic\venv\lib\site-packages\torch\utils_contextlib.py", line 115, in decorate_context return func(args, kwargs) File "C:\SDNext\ComfyUI\comfy\k_diffusion\sampling.py", line 154, in sample_euler_ancestral denoised = model(x, sigmas[i] * s_in, extra_args) File "C:\SDNext\ComfyUI\comfy\samplers.py", line 272, in call out = self.inner_model(x, sigma, model_options=model_options, seed=seed) File "C:\SDNext\ComfyUI\comfy\samplers.py", line 610, in call return self.predict_noise(*args, kwargs) File "C:\SDNext\ComfyUI\comfy\samplers.py", line 613, in predict_noise return sampling_function(self.inner_model, x, timestep, self.conds.get("negative", None), self.conds.get("positive", None), self.cfg, model_options=model_options, seed=seed) File "C:\SDNext\ComfyUI\comfy\samplers.py", line 258, in sampling_function out = calc_cond_batch(model, conds, x, timestep, model_options) File "C:\SDNext\ComfyUI\comfy\samplers.py", line 218, in calc_cond_batch output = model.apply_model(inputx, timestep, c).chunk(batch_chunks) File "C:\SDNext\ComfyUI\comfy\model_base.py", line 97, in apply_model model_output = self.diffusion_model(xc, t, context=context, control=control, transformer_options=transformer_options, *extra_conds).float() File "c:\SDNext\automatic\venv\lib\site-packages\torch\nn\modules\module.py", line 1511, in _wrapped_call_impl return self._call_impl(args, kwargs) File "c:\SDNext\automatic\venv\lib\site-packages\torch\nn\modules\module.py", line 1520, in _call_impl return forward_call(*args, kwargs) File "C:\SDNext\ComfyUI\comfy\ldm\modules\diffusionmodules\openaimodel.py", line 850, 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 "C:\SDNext\ComfyUI\comfy\ldm\modules\diffusionmodules\openaimodel.py", line 44, in forward_timestep_embed x = layer(x, context, transformer_options) File "c:\SDNext\automatic\venv\lib\site-packages\torch\nn\modules\module.py", line 1511, in _wrapped_call_impl return self._call_impl(*args, *kwargs) File "c:\SDNext\automatic\venv\lib\site-packages\torch\nn\modules\module.py", line 1520, in _call_impl return forward_call(args, kwargs) File "C:\SDNext\ComfyUI\comfy\ldm\modules\attention.py", line 633, in forward x = block(x, context=context[i], transformer_options=transformer_options) File "c:\SDNext\automatic\venv\lib\site-packages\torch\nn\modules\module.py", line 1511, in _wrapped_call_impl return self._call_impl(*args, kwargs) File "c:\SDNext\automatic\venv\lib\site-packages\torch\nn\modules\module.py", line 1520, in _call_impl return forward_call(*args, kwargs) File "C:\SDNext\ComfyUI\comfy\ldm\modules\attention.py", line 460, in forward return checkpoint(self._forward, (x, context, transformer_options), self.parameters(), self.checkpoint) File "C:\SDNext\ComfyUI\comfy\ldm\modules\diffusionmodules\util.py", line 191, in checkpoint return func(inputs) File "C:\SDNext\ComfyUI\comfy\ldm\modules\attention.py", line 520, in _forward n = self.attn1(n, context=context_attn1, value=value_attn1) File "c:\SDNext\automatic\venv\lib\site-packages\torch\nn\modules\module.py", line 1511, in _wrapped_call_impl return self._call_impl(args, kwargs) File "c:\SDNext\automatic\venv\lib\site-packages\torch\nn\modules\module.py", line 1520, in _call_impl return forward_call(*args, kwargs) File "C:\SDNext\ComfyUI\comfy\ldm\modules\attention.py", line 412, in forward out = optimized_attention(q, k, v, self.heads) File "C:\SDNext\ComfyUI\comfy\ldm\modules\attention.py", line 345, in attention_pytorch out = torch.nn.functional.scaled_dot_product_attention(q, k, v, attn_mask=mask, dropout_p=0.0, is_causal=False)

jags111 commented 3 months ago

will study and get back

jags111 commented 2 weeks ago

check your installation , dependencies, xformer, cuda etc and check for same with issues