Kosinkadink
commented
3 months ago How "low" of a version are we talking? Nearest-exact is used even by vanilla comfy, so I recommend just updating pytorch.
Closed jkla139 closed 3 months ago
Kosinkadink
commented
3 months ago How "low" of a version are we talking? Nearest-exact is used even by vanilla comfy, so I recommend just updating pytorch.
Traceback (most recent call last): File "C:\Downloads\ComfyUI\execution.py", line 151, in recursive_execute output_data, output_ui = get_output_data(obj, input_data_all) File "C:\Downloads\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:\Downloads\ComfyUI\execution.py", line 74, in map_node_over_list results.append(getattr(obj, func)(slice_dict(input_data_all, i))) File "C:\Downloads\ComfyUI\nodes.py", line 1369, in sample return common_ksampler(model, seed, steps, cfg, sampler_name, scheduler, positive, negative, latent_image, denoise=denoise) File "C:\Downloads\ComfyUI\nodes.py", line 1339, in common_ksampler samples = comfy.sample.sample(model, noise, steps, cfg, sampler_name, scheduler, positive, negative, latent_image, File "C:\Downloads\ComfyUI\custom_nodes\ComfyUI-AnimateDiff-Evolved\animatediff\sampling.py", line 267, in motion_sample return orig_comfy_sample(model, noise, args, kwargs) File "C:\Downloads\ComfyUI\comfy\sample.py", line 100, 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:\Downloads\ComfyUI\comfy\samplers.py", line 705, 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:\Downloads\ComfyUI\comfy\samplers.py", line 610, in sample samples = sampler.sample(model_wrap, sigmas, extra_args, callback, noise, latent_image, denoise_mask, disable_pbar) File "C:\Downloads\ComfyUI\comfy\samplers.py", line 548, 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:\Users\admin\AppData\Roaming\Python\Python39\site-packages\torch\autograd\grad_mode.py", line 28, in decorate_context return func(args, kwargs) File "C:\Downloads\ComfyUI\comfy\k_diffusion\sampling.py", line 137, in sample_euler denoised = model(x, sigma_hat * s_in, extra_args) File "C:\Users\admin\AppData\Roaming\Python\Python39\site-packages\torch\nn\modules\module.py", line 1102, in call_impl return forward_call(*input, *kwargs) File "C:\Downloads\ComfyUI\comfy\samplers.py", line 286, in forward out = self.inner_model(x, sigma, cond=cond, uncond=uncond, cond_scale=cond_scale, model_options=model_options, seed=seed) File "C:\Users\admin\AppData\Roaming\Python\Python39\site-packages\torch\nn\modules\module.py", line 1102, in call_impl return forward_call(input, kwargs) File "C:\Downloads\ComfyUI\comfy\samplers.py", line 273, in forward return self.apply_model(*args, *kwargs) File "C:\Downloads\ComfyUI\comfy\samplers.py", line 270, in apply_model out = sampling_function(self.inner_model, x, timestep, uncond, cond, cond_scale, model_options=model_options, seed=seed) File "C:\Downloads\ComfyUI\comfy\samplers.py", line 250, in sampling_function cond_pred, uncond_pred = calc_cond_uncond_batch(model, cond, uncond, x, timestep, model_options) File "C:\Downloads\ComfyUI\comfy\samplers.py", line 198, in calc_cond_uncond_batch c['control'] = control.get_control(input_x, timestep, c, len(cond_or_uncond)) File "C:\Downloads\ComfyUI\custom_nodes\ComfyUI-Advanced-ControlNet\adv_control\utils.py", line 468, in get_control_inject return self.get_control_advanced(x_noisy, t, cond, batched_number) File "C:\Downloads\ComfyUI\custom_nodes\ComfyUI-Advanced-ControlNet\adv_control\control.py", line 32, in get_control_advanced return self.sliding_get_control(x_noisy, t, cond, batched_number) File "C:\Downloads\ComfyUI\custom_nodes\ComfyUI-Advanced-ControlNet\adv_control\control.py", line 61, in sliding_get_control self.cond_hint = comfy.utils.common_upscale(self.cond_hint_original, x_noisy.shape[3] 8, x_noisy.shape[2] * 8, 'nearest-exact', "center").to(dtype).to(self.device) File "C:\Downloads\ComfyUI\comfy\utils.py", line 422, in common_upscale return torch.nn.functional.interpolate(s, size=(height, width), mode=upscale_method) File "C:\Users\admin\AppData\Roaming\Python\Python39\site-packages\torch\nn\functional.py", line 3752, in interpolate raise NotImplementedError( NotImplementedError: Input Error: Only 3D, 4D and 5D input Tensors supported (got 4D) for the modes: nearest | linear | bilinear | bicubic | trilinear (got nearest-exact)