Could this error be related to the controlnet node?

[BlinkerHigh]

Was working fine initially, something might have broke after updating this node or comfyui.

Debug Logs model weight dtype torch.bfloat16, manual cast: None model_type FLUX ComfyUI.venv\lib\site-packages\transformers\tokenization_utils_base.py:1601: FutureWarning: clean_up_tokenization_spaces was not set. It will be set to True by default. This behavior will be depracted in transformers v4.45, and will be then set to False by default. For more details check this issue: https://github.com/huggingface/transformers/issues/31884 warnings.warn( Requested to load FluxClipModel_ Loading 1 new model loaded completely 0.0 9319.23095703125 True Requested to load AutoencodingEngine Loading 1 new model loaded completely 0.0 159.87335777282715 True Requested to load InstantXControlNetFluxFormat2 Requested to load Flux Loading 2 new models loaded completely 0.0 6298.041015625 True loaded completely 0.0 12119.472778320312 True

0% 0/30 [00:00<?, ?it/s]Requested to load AutoencodingEngine Loading 1 new model loaded completely 0.0 159.87335777282715 True Requested to load InstantXControlNetFluxFormat2 Requested to load Flux Loading 2 new models loaded completely 0.0 6298.041015625 True loaded completely 0.0 12119.472778320312 True ComfyUI.venv\lib\site-packages\diffusers\models\attention_processor.py:1848: UserWarning: 1Torch was not compiled with flash attention. (Triggered internally at C:\actions-runner_work\pytorch\pytorch\builder\windows\pytorch\aten\src\ATen\native\transformers\cuda\sdp_utils.cpp:555.) hidden_states = F.scaled_dot_product_attention(query, key, value, dropout_p=0.0, is_causal=False) 0% 0/30 [00:18<?, ?it/s] !!! Exception during processing !!! Allocation on device Traceback (most recent call last): File "ComfyUI\execution.py", line 317, in execute output_data, output_ui, has_subgraph = get_output_data(obj, input_data_all, execution_block_cb=execution_block_cb, pre_execute_cb=pre_execute_cb) File "ComfyUI\execution.py", line 192, in get_output_data return_values = _map_node_over_list(obj, input_data_all, obj.FUNCTION, allow_interrupt=True, execution_block_cb=execution_block_cb, pre_execute_cb=pre_execute_cb) File "ComfyUI\execution.py", line 169, in _map_node_over_list process_inputs(input_dict, i) File "ComfyUI\execution.py", line 158, in process_inputs results.append(getattr(obj, func)(inputs)) File "ComfyUI\comfy_extras\nodes_custom_sampler.py", line 612, in sample samples = guider.sample(noise.generate_noise(latent), latent_image, sampler, sigmas, denoise_mask=noise_mask, callback=callback, disable_pbar=disable_pbar, seed=noise.seed) File "ComfyUI\comfy\samplers.py", line 716, in sample output = self.inner_sample(noise, latent_image, device, sampler, sigmas, denoise_mask, callback, disable_pbar, seed) File "ComfyUI\comfy\samplers.py", line 695, in inner_sample samples = sampler.sample(self, sigmas, extra_args, callback, noise, latent_image, denoise_mask, disable_pbar) File "ComfyUI\comfy\samplers.py", line 600, in sample samples = self.sampler_function(model_k, noise, sigmas, extra_args=extra_args, callback=k_callback, disable=disable_pbar, self.extra_options) File "ComfyUI.venv\lib\site-packages\torch\utils_contextlib.py", line 116, in decorate_context return func(*args, kwargs) File "ComfyUI\comfy\k_diffusion\sampling.py", line 144, in sample_euler denoised = model(x, sigma_hat * s_in, *extra_args) File "ComfyUI\comfy\samplers.py", line 299, in call out = self.inner_model(x, sigma, model_options=model_options, seed=seed) File "ComfyUI\comfy\samplers.py", line 682, in call return self.predict_noise(args, kwargs) File "ComfyUI\comfy\samplers.py", line 685, 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 "ComfyUI\comfy\samplers.py", line 279, in sampling_function out = calc_cond_batch(model, conds, x, timestep, model_options) File "ComfyUI\custom_nodes\ComfyUI-TiledDiffusion.patches.py", line 4, in calc_cond_batch return calc_cond_batch_original_tiled_diffusion_f15f8412(model, conds, x_in, timestep, model_options) File "ComfyUI\comfy\samplers.py", line 202, in calc_cond_batch c['control'] = control.get_control(inputx, timestep, c, len(cond_or_uncond)) File "ComfyUI\comfy\controlnet.py", line 239, in get_control return self.control_merge(control, control_prev, output_dtype) File "ComfyUI\comfy\controlnet.py", line 152, in control_merge x = x.to(output_dtype) torch.OutOfMemoryError: Allocation on device

Got an OOM, unloading all loaded models. Prompt executed in 152.50 seconds