BNK Unsampler exceed allowed memory. (out of memory)

[jamesmgg]

I'm getting this error when loading 150 frames... seems kind of excessive. Any ideas on how to fix this?

Error occurred when executing BNK_Unsampler:

Allocation on device 0 would exceed allowed memory. (out of memory)
Currently allocated : 9.49 GiB
Requested : 9.89 GiB
Device limit : 23.99 GiB
Free (according to CUDA): 0 bytes
PyTorch limit (set by user-supplied memory fraction)
: 17179869184.00 GiB

File "/stable-diffusion/execution.py", line 154, in recursive_execute
output_data, output_ui = get_output_data(obj, input_data_all)
File "/stable-diffusion/execution.py", line 84, in get_output_data
return_values = map_node_over_list(obj, input_data_all, obj.FUNCTION, allow_interrupt=True)
File "/stable-diffusion/execution.py", line 77, in map_node_over_list
results.append(getattr(obj, func)(**slice_dict(input_data_all, i)))
File "/stable-diffusion/custom_nodes/ComfyUI_Noise/nodes.py", line 236, in unsampler
samples = sampler.sample(noise, positive, negative, cfg=cfg, latent_image=latent_image, force_full_denoise=False, denoise_mask=noise_mask, sigmas=sigmas, start_step=0, last_step=end_at_step, callback=callback)
File "/stable-diffusion/comfy/samplers.py", line 716, 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 "/stable-diffusion/comfy/samplers.py", line 622, in sample
samples = sampler.sample(model_wrap, sigmas, extra_args, callback, noise, latent_image, denoise_mask, disable_pbar)
File "/stable-diffusion/comfy/samplers.py", line 561, in sample
samples = self.sampler_function(model_k, noise, sigmas, extra_args=extra_args, callback=k_callback, disable=disable_pbar, **self.extra_options)
File "/opt/conda/lib/python3.10/site-packages/torch/utils/_contextlib.py", line 115, in decorate_context
return func(*args, **kwargs)
File "/stable-diffusion/comfy/k_diffusion/sampling.py", line 580, in sample_dpmpp_2m
denoised = model(x, sigmas[i] * s_in, **extra_args)
File "/opt/conda/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1518, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "/opt/conda/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1527, in _call_impl
return forward_call(*args, **kwargs)
File "/stable-diffusion/comfy/samplers.py", line 285, in forward
out = self.inner_model(x, sigma, cond=cond, uncond=uncond, cond_scale=cond_scale, model_options=model_options, seed=seed)
File "/opt/conda/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1518, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "/opt/conda/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1527, in _call_impl
return forward_call(*args, **kwargs)
File "/stable-diffusion/comfy/samplers.py", line 275, in forward
return self.apply_model(*args, **kwargs)
File "/stable-diffusion/comfy/samplers.py", line 272, in apply_model
out = sampling_function(self.inner_model, x, timestep, uncond, cond, cond_scale, model_options=model_options, seed=seed)
File "/stable-diffusion/comfy/samplers.py", line 252, in sampling_function
cond_pred, uncond_pred = calc_cond_uncond_batch(model, cond, uncond_, x, timestep, model_options)
File "/stable-diffusion/comfy/samplers.py", line 226, in calc_cond_uncond_batch
output = model.apply_model(input_x, timestep_, **c).chunk(batch_chunks)
File "/stable-diffusion/comfy/model_base.py", line 85, in apply_model
model_output = self.diffusion_model(xc, t, context=context, control=control, transformer_options=transformer_options, **extra_conds).float()
File "/opt/conda/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1518, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "/opt/conda/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1527, in _call_impl
return forward_call(*args, **kwargs)
File "/stable-diffusion/custom_nodes/SeargeSDXL/modules/custom_sdxl_ksampler.py", line 70, in new_unet_forward
x0 = old_unet_forward(self, x, timesteps, context, y, control, transformer_options, **kwargs)
File "/stable-diffusion/comfy/ldm/modules/diffusionmodules/openaimodel.py", line 854, 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 "/stable-diffusion/comfy/ldm/modules/diffusionmodules/openaimodel.py", line 46, in forward_timestep_embed
x = layer(x, context, transformer_options)
File "/opt/conda/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1518, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "/opt/conda/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1527, in _call_impl
return forward_call(*args, **kwargs)
File "/stable-diffusion/comfy/ldm/modules/attention.py", line 604, in forward
x = block(x, context=context[i], transformer_options=transformer_options)
File "/opt/conda/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1518, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "/opt/conda/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1527, in _call_impl
return forward_call(*args, **kwargs)
File "/stable-diffusion/comfy/ldm/modules/attention.py", line 431, in forward
return checkpoint(self._forward, (x, context, transformer_options), self.parameters(), self.checkpoint)
File "/stable-diffusion/comfy/ldm/modules/diffusionmodules/util.py", line 189, in checkpoint
return func(*inputs)
File "/stable-diffusion/comfy/ldm/modules/attention.py", line 541, in _forward
x = self.ff(self.norm3(x))
File "/opt/conda/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1518, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "/opt/conda/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1527, in _call_impl
return forward_call(*args, **kwargs)
File "/stable-diffusion/comfy/ldm/modules/attention.py", line 85, in forward
return self.net(x)
File "/opt/conda/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1518, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "/opt/conda/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1527, in _call_impl
return forward_call(*args, **kwargs)
File "/opt/conda/lib/python3.10/site-packages/torch/nn/modules/container.py", line 215, in forward
input = module(input)
File "/opt/conda/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1518, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "/opt/conda/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1527, in _call_impl
return forward_call(*args, **kwargs)
File "/stable-diffusion/comfy/ldm/modules/attention.py", line 64, in forward
x, gate = self.proj(x).chunk(2, dim=-1)
File "/opt/conda/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1518, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "/opt/conda/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1527, in _call_impl
return forward_call(*args, **kwargs)
File "/stable-diffusion/comfy/ops.py", line 28, in forward
return super().forward(*args, **kwargs)
File "/opt/conda/lib/python3.10/site-packages/torch/nn/modules/linear.py", line 114, in forward
return F.linear(input, self.weight, self.bias)

[yukselyusuf]

same issue

[orionfro]

same issue on first run, then working on second re-run.
console output : [rgthree] Using rgthree's optimized recursive execution.
mabye a problem with low VRAM mode ?

[alanhuang67]

same here...