[Bug]:

[saogalaxy]

Is there an existing issue for this?

• I have searched the existing issues and checked the recent builds/commits of both this extension and the webui

Have you read FAQ on README?

• I have updated WebUI and this extension to the latest version

What happened?

getting cuda error in auto1111 verison 1.9.4 this is a fresh install

Steps to reproduce the problem

check animated diff set frames to 8 all other settings to default and select motion mod.

What should have happened?

animated diff should run like normal before the clean os and version install.

Commit where the problem happens

webui: 1.9.4
extension:
version: 1.9.4  •  python: 3.10.11  •  torch: 2.1.2+cu121  •  xformers: 0.0.23.post1  •  gradio: 3.41.2  •  checkpoint: 16e6ae65a1

What browsers do you use to access the UI ?

Google Chrome

Command Line Arguments

--xformers

Console logs

2024-06-10 21:35:37,514 - AnimateDiff - INFO - AnimateDiff process start.
2024-06-10 21:35:37,514 - AnimateDiff - INFO - Loading motion module improvedHumansMotion_refinedHumanMovement.ckpt from D:\stable-diffusion-webui\extensions\sd-webui-animatediff\model\improvedHumansMotion_refinedHumanMovement.ckpt
2024-06-10 21:35:38,381 - AnimateDiff - INFO - Guessed improvedHumansMotion_refinedHumanMovement.ckpt architecture: MotionModuleType.AnimateDiffV2
2024-06-10 21:35:41,565 - AnimateDiff - INFO - Injecting motion module improvedHumansMotion_refinedHumanMovement.ckpt into SD1.5 UNet middle block.
2024-06-10 21:35:41,565 - AnimateDiff - INFO - Injecting motion module improvedHumansMotion_refinedHumanMovement.ckpt into SD1.5 UNet input blocks.
2024-06-10 21:35:41,565 - AnimateDiff - INFO - Injecting motion module improvedHumansMotion_refinedHumanMovement.ckpt into SD1.5 UNet output blocks.
2024-06-10 21:35:41,566 - AnimateDiff - INFO - Setting DDIM alpha.
2024-06-10 21:35:41,583 - AnimateDiff - INFO - Injection finished.
2024-06-10 21:35:41,584 - AnimateDiff - INFO - AnimateDiff + ControlNet will generate 16 frames.
  0%|                                                                                           | 0/58 [00:00<?, ?it/s]2024-06-10 21:35:42,285 - AnimateDiff - INFO - inner model forward hooked
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Exception in thread MemMon:
Traceback (most recent call last):
  File "C:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.3056.0_x64__qbz5n2kfra8p0\lib\threading.py", line 1016, in _bootstrap_inner
    self.run()
  File "D:\stable-diffusion-webui\modules\memmon.py", line 53, in run
    free, total = self.cuda_mem_get_info()
  File "D:\stable-diffusion-webui\modules\memmon.py", line 34, in cuda_mem_get_info
    return torch.cuda.mem_get_info(index)
  File "D:\stable-diffusion-webui\venv\lib\site-packages\torch\cuda\memory.py", line 663, in mem_get_info
    return torch.cuda.cudart().cudaMemGetInfo(device)
RuntimeError: CUDA error: device-side assert triggered
CUDA kernel errors might be asynchronously reported at some other API call, so the stacktrace below might be incorrect.
For debugging consider passing CUDA_LAUNCH_BLOCKING=1.
Compile with `TORCH_USE_CUDA_DSA` to enable device-side assertions.

*** Error completing request
*** Arguments: ('task(y98o4z2btpxu8b4)', <gradio.routes.Request object at 0x000002154F96E710>, 'full body, NSFW, shiny wet skin ,highres, masterpiece, perfect lighting, bloom, cinematic lighting best quality, ultra-detailed, highly detailed, contrasting shadows, sharpness, colorful, pretty nipples ,Onsen , pond surrounded by rocks, huge breasts:1.9,<lora:ShirakawaRuna by Raelina:0.7> ShirakawaRuna, 1girl, blonde hair, multicolored hair, bangs, one side up, long hair, blue eyes, hairclip, jewelry, earrings, gyaru  <lora:outfit-Implacable-pynoise:1> outfit-Implacablenun', ',bad-hands-5, bad-artist-anime bad-picture-chill-75v badhandv4 ng_deepnegative_v1_75t verybadimagenegative_v1.3,  censor bars , censor bar ,\nNegative prompt\n\n(worst quality, low quality:1.4), monochrome, lowres, bad anatomy, bad hands, text, error, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality, normal quality, jpeg artifacts, signature, watermark, username, blurry, deformed eyes, ((disfigured)), bad art, deformed((extra limbs)), ((duplicate)), morbid, mutilated, bad body, on hand with less than 5 fingers, crown , stacked torses, stacked hands, totem pole,', [], 1, 1, 7, 768, 768, False, 0.7, 2, 'Latent', 0, 0, 0, 'Use same checkpoint', 'Use same sampler', 'Use same scheduler', '', '', [], 0, 58, 'DPM++ 2M', 'Automatic', False, '', 0.8, -1, False, -1, 0, 0, 0, <scripts.animatediff_ui.AnimateDiffProcess object at 0x000002154F96CBB0>, ControlNetUnit(is_ui=True, input_mode=<InputMode.SIMPLE: 'simple'>, batch_images='', output_dir='', loopback=False, enabled=False, module='depth_anything', model='control_lora_rank128_v11f1p_sd15_depth_fp16 [09d26c32]', weight=1.0, image=None, resize_mode=<ResizeMode.INNER_FIT: 'Crop and Resize'>, low_vram=False, processor_res=512, threshold_a=0.5, threshold_b=0.5, guidance_start=0.0, guidance_end=1.0, pixel_perfect=True, control_mode=<ControlMode.BALANCED: 'Balanced'>, inpaint_crop_input_image=False, hr_option=<HiResFixOption.BOTH: 'Both'>, save_detected_map=True, advanced_weighting=None, effective_region_mask=None, pulid_mode=<PuLIDMode.FIDELITY: 'Fidelity'>, ipadapter_input=None, mask=None, batch_mask_dir=None, animatediff_batch=False, batch_modifiers=[], batch_image_files=[], batch_keyframe_idx=None), ControlNetUnit(is_ui=True, input_mode=<InputMode.SIMPLE: 'simple'>, batch_images='', output_dir='', loopback=False, enabled=False, module='none', model='None', weight=1.0, image=None, resize_mode=<ResizeMode.INNER_FIT: 'Crop and Resize'>, low_vram=False, processor_res=-1, threshold_a=-1.0, threshold_b=-1.0, guidance_start=0.0, guidance_end=1.0, pixel_perfect=False, control_mode=<ControlMode.BALANCED: 'Balanced'>, inpaint_crop_input_image=False, hr_option=<HiResFixOption.BOTH: 'Both'>, save_detected_map=True, advanced_weighting=None, effective_region_mask=None, pulid_mode=<PuLIDMode.FIDELITY: 'Fidelity'>, ipadapter_input=None, mask=None, batch_mask_dir=None, animatediff_batch=False, batch_modifiers=[], batch_image_files=[], batch_keyframe_idx=None), ControlNetUnit(is_ui=True, input_mode=<InputMode.SIMPLE: 'simple'>, batch_images='', output_dir='', loopback=False, enabled=False, module='none', model='None', weight=1.0, image=None, resize_mode=<ResizeMode.INNER_FIT: 'Crop and Resize'>, low_vram=False, processor_res=-1, threshold_a=-1.0, threshold_b=-1.0, guidance_start=0.0, guidance_end=1.0, pixel_perfect=False, control_mode=<ControlMode.BALANCED: 'Balanced'>, inpaint_crop_input_image=False, hr_option=<HiResFixOption.BOTH: 'Both'>, save_detected_map=True, advanced_weighting=None, effective_region_mask=None, pulid_mode=<PuLIDMode.FIDELITY: 'Fidelity'>, ipadapter_input=None, mask=None, batch_mask_dir=None, animatediff_batch=False, batch_modifiers=[], batch_image_files=[], batch_keyframe_idx=None), False, False, 'positive', 'comma', 0, False, False, 'start', '', 1, '', [], 0, '', [], 0, '', [], True, False, False, False, False, False, False, 0, False, None, None, False, None, None, False, None, None, False, 50) {}
    Traceback (most recent call last):
      File "D:\stable-diffusion-webui\modules\call_queue.py", line 57, in f
        res = list(func(*args, **kwargs))
      File "D:\stable-diffusion-webui\modules\call_queue.py", line 36, in f
        res = func(*args, **kwargs)
      File "D:\stable-diffusion-webui\modules\txt2img.py", line 109, in txt2img
        processed = processing.process_images(p)
      File "D:\stable-diffusion-webui\modules\processing.py", line 845, in process_images
        res = process_images_inner(p)
      File "D:\stable-diffusion-webui\extensions\sd-webui-controlnet\scripts\batch_hijack.py", line 48, in processing_process_images_hijack
        return getattr(processing, '__controlnet_original_process_images_inner')(p, *args, **kwargs)
      File "D:\stable-diffusion-webui\modules\processing.py", line 981, in process_images_inner
        samples_ddim = p.sample(conditioning=p.c, unconditional_conditioning=p.uc, seeds=p.seeds, subseeds=p.subseeds, subseed_strength=p.subseed_strength, prompts=p.prompts)
      File "D:\stable-diffusion-webui\modules\processing.py", line 1328, in sample
        samples = self.sampler.sample(self, x, conditioning, unconditional_conditioning, image_conditioning=self.txt2img_image_conditioning(x))
      File "D:\stable-diffusion-webui\modules\sd_samplers_kdiffusion.py", line 218, in sample
        samples = self.launch_sampling(steps, lambda: self.func(self.model_wrap_cfg, x, extra_args=self.sampler_extra_args, disable=False, callback=self.callback_state, **extra_params_kwargs))
      File "D:\stable-diffusion-webui\modules\sd_samplers_common.py", line 272, in launch_sampling
        return func()
      File "D:\stable-diffusion-webui\modules\sd_samplers_kdiffusion.py", line 218, in <lambda>
        samples = self.launch_sampling(steps, lambda: self.func(self.model_wrap_cfg, x, extra_args=self.sampler_extra_args, disable=False, callback=self.callback_state, **extra_params_kwargs))
      File "D:\stable-diffusion-webui\venv\lib\site-packages\torch\utils\_contextlib.py", line 115, in decorate_context
        return func(*args, **kwargs)
      File "D:\stable-diffusion-webui\repositories\k-diffusion\k_diffusion\sampling.py", line 594, in sample_dpmpp_2m
        denoised = model(x, sigmas[i] * s_in, **extra_args)
      File "D:\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1518, in _wrapped_call_impl
        return self._call_impl(*args, **kwargs)
      File "D:\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1527, in _call_impl
        return forward_call(*args, **kwargs)
      File "D:\stable-diffusion-webui\modules\sd_samplers_cfg_denoiser.py", line 256, in forward
        x_out[a:b] = self.inner_model(x_in[a:b], sigma_in[a:b], cond=make_condition_dict(c_crossattn, image_cond_in[a:b]))
      File "D:\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1518, in _wrapped_call_impl
        return self._call_impl(*args, **kwargs)
      File "D:\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1527, in _call_impl
        return forward_call(*args, **kwargs)
      File "D:\stable-diffusion-webui\extensions\sd-webui-animatediff\scripts\animatediff_infv2v.py", line 164, in mm_sd_forward
        x_in[_context], sigma_in[_context],
    RuntimeError: CUDA error: device-side assert triggered
    CUDA kernel errors might be asynchronously reported at some other API call, so the stacktrace below might be incorrect.
    For debugging consider passing CUDA_LAUNCH_BLOCKING=1.
    Compile with `TORCH_USE_CUDA_DSA` to enable device-side assertions.


---
Traceback (most recent call last):
  File "D:\stable-diffusion-webui\venv\lib\site-packages\gradio\routes.py", line 488, in run_predict
    output = await app.get_blocks().process_api(
  File "D:\stable-diffusion-webui\venv\lib\site-packages\gradio\blocks.py", line 1431, in process_api
    result = await self.call_function(
  File "D:\stable-diffusion-webui\venv\lib\site-packages\gradio\blocks.py", line 1103, in call_function
    prediction = await anyio.to_thread.run_sync(
  File "D:\stable-diffusion-webui\venv\lib\site-packages\anyio\to_thread.py", line 33, in run_sync
    return await get_asynclib().run_sync_in_worker_thread(
  File "D:\stable-diffusion-webui\venv\lib\site-packages\anyio\_backends\_asyncio.py", line 877, in run_sync_in_worker_thread
    return await future
  File "D:\stable-diffusion-webui\venv\lib\site-packages\anyio\_backends\_asyncio.py", line 807, in run
    result = context.run(func, *args)
  File "D:\stable-diffusion-webui\venv\lib\site-packages\gradio\utils.py", line 707, in wrapper
    response = f(*args, **kwargs)
  File "D:\stable-diffusion-webui\modules\call_queue.py", line 77, in f
    devices.torch_gc()
  File "D:\stable-diffusion-webui\modules\devices.py", line 81, in torch_gc
    torch.cuda.empty_cache()
  File "D:\stable-diffusion-webui\venv\lib\site-packages\torch\cuda\memory.py", line 159, in empty_cache
    torch._C._cuda_emptyCache()
RuntimeError: CUDA error: device-side assert triggered
CUDA kernel errors might be asynchronously reported at some other API call, so the stacktrace below might be incorrect.
For debugging consider passing CUDA_LAUNCH_BLOCKING=1.
Compile with `TORCH_USE_CUDA_DSA` to enable device-side assertions.

Additional information

No response

[zappityzap]

Does it work with one of the official motion modules? Try these: https://huggingface.co/conrevo/AnimateDiff-A1111/tree/main

edit: Might also try creating the JSON file described here: https://civitai.com/models/155528/improved-humans-motion-module?dialog=commentThread&commentId=267581

[saogalaxy]

its giving the same error using the official motion modules

2024-06-13 08:59:42,549 - AnimateDiff - INFO - AnimateDiff process start.
2024-06-13 08:59:42,549 - AnimateDiff - INFO - Loading motion module mm_sd15_v2.safetensors from D:\stable-diffusion-webui\extensions\sd-webui-animatediff\model\mm_sd15_v2.safetensors
Calculating sha256 for D:\stable-diffusion-webui\extensions\sd-webui-animatediff\model\mm_sd15_v2.safetensors: d3976a7dcd11d4f5202d5360c6f1996fc669d6114c530afb3dca4769cc6dd2b2
2024-06-13 08:59:43,242 - AnimateDiff - INFO - Guessed mm_sd15_v2.safetensors architecture: MotionModuleType.AnimateDiffV2
2024-06-13 08:59:46,334 - AnimateDiff - INFO - Injecting motion module mm_sd15_v2.safetensors into SD1.5 UNet middle block.
2024-06-13 08:59:46,335 - AnimateDiff - INFO - Injecting motion module mm_sd15_v2.safetensors into SD1.5 UNet input blocks.
2024-06-13 08:59:46,335 - AnimateDiff - INFO - Injecting motion module mm_sd15_v2.safetensors into SD1.5 UNet output blocks.
2024-06-13 08:59:46,335 - AnimateDiff - INFO - Setting DDIM alpha.
2024-06-13 08:59:46,341 - AnimateDiff - INFO - Injection finished.
2024-06-13 08:59:46,341 - AnimateDiff - INFO - AnimateDiff + ControlNet will generate 8 frames.
0%| | 0/35 [00:00<?, ?it/s]2024-06-13 08:59:47,677 - AnimateDiff - INFO - inner model forward hooked
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Exception in thread MemMon:
Traceback (most recent call last):
File "C:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.3056.0_x64__qbz5n2kfra8p0\lib\threading.py", line 1016, in _bootstrap_inner
0%| | 0/35 [00:00<?, ?it/s]
self.run()
File "D:\stable-diffusion-webui\modules\memmon.py", line 53, in run
free, total = self.cuda_mem_get_info()
File "D:\stable-diffusion-webui\modules\memmon.py", line 34, in cuda_mem_get_info
return torch.cuda.mem_get_info(index)
File "D:\stable-diffusion-webui\venv\lib\site-packages\torch\cuda\memory.py", line 663, in mem_get_info
return torch.cuda.cudart().cudaMemGetInfo(device)
RuntimeError: CUDA error: device-side assert triggered
CUDA kernel errors might be asynchronously reported at some other API call, so the stacktrace below might be incorrect.
For debugging consider passing CUDA_LAUNCH_BLOCKING=1.
Compile with TORCH_USE_CUDA_DSA to enable device-side assertions.

*** Error completing request
*** Arguments: ('task(f28gm25ufrnm3yz)', <gradio.routes.Request object at 0x00000245B6391870>, 'lora:chushou:0.8 masterpiece, best quality, hentai sex pose, tentacle sex, Suspension, sex from behind,tentacles, cum pool, huge breasts, spread legs, upside-down, ahegao, (mature female:1.6), cum in pussy NSFW, photorealistic ,cinematic lighting ,shadows, (masterpiece), best quality, expressive eyes, various expressions , huge firm breast, large breast, on a rocky cave black hair, skin tight,(red and white ruffle frilly trim Victorian strapless corset and thong , ruffle arm sleeves ), black fishnets stocking, ,muscular abs, slim thighs , <lora:Rogue Dd 1:0.8> rogue dd', 'paintings, sketches, child, loli, (worst quality:2), (low quality:2), (normal quality:2), lowres, normal quality, ((monochrome)), ((grayscale)), skin spots, acnes, skin blemishes', [], 1, 1, 7, 512, 512, False, 0.7, 2, 'Latent', 0, 0, 0, 'Use same checkpoint', 'Use same sampler', 'Use same scheduler', '', '', [], 0, 35, 'DPM++ SDE', 'Automatic', False, '', 0.8, -1, False, -1, 0, 0, 0, False, False, {'ad_model': 'face_yolov8n.pt', 'ad_model_classes': '', 'ad_tap_enable': True, 'ad_prompt': '<lora:Rogue Dd 1:1> rogue dd , smooth skin, ', 'ad_negative_prompt': 'blemishes ', 'ad_confidence': 0.3, 'ad_mask_k_largest': 0, 'ad_mask_min_ratio': 0, 'ad_mask_max_ratio': 1, 'ad_x_offset': 0, 'ad_y_offset': 0, 'ad_dilate_erode': 4, 'ad_mask_merge_invert': 'None', 'ad_mask_blur': 4, 'ad_denoising_strength': 0.4, 'ad_inpaint_only_masked': True, 'ad_inpaint_only_masked_padding': 32, 'ad_use_inpaint_width_height': False, 'ad_inpaint_width': 512, 'ad_inpaint_height': 512, 'ad_use_steps': False, 'ad_steps': 28, 'ad_use_cfg_scale': False, 'ad_cfg_scale': 7, 'ad_use_checkpoint': False, 'ad_checkpoint': 'Use same checkpoint', 'ad_use_vae': False, 'ad_vae': 'Use same VAE', 'ad_use_sampler': False, 'ad_sampler': 'DPM++ 2M', 'ad_scheduler': 'Use same scheduler', 'ad_use_noise_multiplier': False, 'ad_noise_multiplier': 1, 'ad_use_clip_skip': False, 'ad_clip_skip': 1, 'ad_restore_face': False, 'ad_controlnet_model': 'None', 'ad_controlnet_module': 'None', 'ad_controlnet_weight': 1, 'ad_controlnet_guidance_start': 0, 'ad_controlnet_guidance_end': 1, 'is_api': ()}, {'ad_model': 'None', 'ad_model_classes': '', 'ad_tap_enable': True, 'ad_prompt': '', 'ad_negative_prompt': '', 'ad_confidence': 0.3, 'ad_mask_k_largest': 0, 'ad_mask_min_ratio': 0, 'ad_mask_max_ratio': 1, 'ad_x_offset': 0, 'ad_y_offset': 0, 'ad_dilate_erode': 4, 'ad_mask_merge_invert': 'None', 'ad_mask_blur': 4, 'ad_denoising_strength': 0.4, 'ad_inpaint_only_masked': True, 'ad_inpaint_only_masked_padding': 32, 'ad_use_inpaint_width_height': False, 'ad_inpaint_width': 512, 'ad_inpaint_height': 512, 'ad_use_steps': False, 'ad_steps': 28, 'ad_use_cfg_scale': False, 'ad_cfg_scale': 7, 'ad_use_checkpoint': False, 'ad_checkpoint': 'Use same checkpoint', 'ad_use_vae': False, 'ad_vae': 'Use same VAE', 'ad_use_sampler': False, 'ad_sampler': 'DPM++ 2M', 'ad_scheduler': 'Use same scheduler', 'ad_use_noise_multiplier': False, 'ad_noise_multiplier': 1, 'ad_use_clip_skip': False, 'ad_clip_skip': 1, 'ad_restore_face': False, 'ad_controlnet_model': 'None', 'ad_controlnet_module': 'None', 'ad_controlnet_weight': 1, 'ad_controlnet_guidance_start': 0, 'ad_controlnet_guidance_end': 1, 'is_api': ()}, {'ad_model': 'None', 'ad_model_classes': '', 'ad_tap_enable': True, 'ad_prompt': '', 'ad_negative_prompt': '', 'ad_confidence': 0.3, 'ad_mask_k_largest': 0, 'ad_mask_min_ratio': 0, 'ad_mask_max_ratio': 1, 'ad_x_offset': 0, 'ad_y_offset': 0, 'ad_dilate_erode': 4, 'ad_mask_merge_invert': 'None', 'ad_mask_blur': 4, 'ad_denoising_strength': 0.4, 'ad_inpaint_only_masked': True, 'ad_inpaint_only_masked_padding': 32, 'ad_use_inpaint_width_height': False, 'ad_inpaint_width': 512, 'ad_inpaint_height': 512, 'ad_use_steps': False, 'ad_steps': 28, 'ad_use_cfg_scale': False, 'ad_cfg_scale': 7, 'ad_use_checkpoint': False, 'ad_checkpoint': 'Use same checkpoint', 'ad_use_vae': False, 'ad_vae': 'Use same VAE', 'ad_use_sampler': False, 'ad_sampler': 'DPM++ 2M', 'ad_scheduler': 'Use same scheduler', 'ad_use_noise_multiplier': False, 'ad_noise_multiplier': 1, 'ad_use_clip_skip': False, 'ad_clip_skip': 1, 'ad_restore_face': False, 'ad_controlnet_model': 'None', 'ad_controlnet_module': 'None', 'ad_controlnet_weight': 1, 'ad_controlnet_guidance_start': 0, 'ad_controlnet_guidance_end': 1, 'is_api': ()}, {'ad_model': 'None', 'ad_model_classes': '', 'ad_tap_enable': True, 'ad_prompt': '', 'ad_negative_prompt': '', 'ad_confidence': 0.3, 'ad_mask_k_largest': 0, 'ad_mask_min_ratio': 0, 'ad_mask_max_ratio': 1, 'ad_x_offset': 0, 'ad_y_offset': 0, 'ad_dilate_erode': 4, 'ad_mask_merge_invert': 'None', 'ad_mask_blur': 4, 'ad_denoising_strength': 0.4, 'ad_inpaint_only_masked': True, 'ad_inpaint_only_masked_padding': 32, 'ad_use_inpaint_width_height': False, 'ad_inpaint_width': 512, 'ad_inpaint_height': 512, 'ad_use_steps': False, 'ad_steps': 28, 'ad_use_cfg_scale': False, 'ad_cfg_scale': 7, 'ad_use_checkpoint': False, 'ad_checkpoint': 'Use same checkpoint', 'ad_use_vae': False, 'ad_vae': 'Use same VAE', 'ad_use_sampler': False, 'ad_sampler': 'DPM++ 2M', 'ad_scheduler': 'Use same scheduler', 'ad_use_noise_multiplier': False, 'ad_noise_multiplier': 1, 'ad_use_clip_skip': False, 'ad_clip_skip': 1, 'ad_restore_face': False, 'ad_controlnet_model': 'None', 'ad_controlnet_module': 'None', 'ad_controlnet_weight': 1, 'ad_controlnet_guidance_start': 0, 'ad_controlnet_guidance_end': 1, 'is_api': ()}, <scripts.animatediff_ui.AnimateDiffProcess object at 0x00000245B6390340>, ControlNetUnit(is_ui=True, input_mode=<InputMode.SIMPLE: 'simple'>, batch_images='', output_dir='', loopback=False, enabled=False, module='none', model='None', weight=1.0, image=None, resize_mode=<ResizeMode.INNER_FIT: 'Crop and Resize'>, low_vram=False, processor_res=-1, threshold_a=-1.0, threshold_b=-1.0, guidance_start=0.0, guidance_end=1.0, pixel_perfect=False, control_mode=<ControlMode.BALANCED: 'Balanced'>, inpaint_crop_input_image=False, hr_option=<HiResFixOption.BOTH: 'Both'>, save_detected_map=True, advanced_weighting=None, effective_region_mask=None, pulid_mode=<PuLIDMode.FIDELITY: 'Fidelity'>, ipadapter_input=None, mask=None, batch_mask_dir=None, animatediff_batch=False, batch_modifiers=[], batch_image_files=[], batch_keyframe_idx=None), ControlNetUnit(is_ui=True, input_mode=<InputMode.SIMPLE: 'simple'>, batch_images='', output_dir='', loopback=False, enabled=False, module='none', model='None', weight=1.0, image=None, resize_mode=<ResizeMode.INNER_FIT: 'Crop and Resize'>, low_vram=False, processor_res=-1, threshold_a=-1.0, threshold_b=-1.0, guidance_start=0.0, guidance_end=1.0, pixel_perfect=False, control_mode=<ControlMode.BALANCED: 'Balanced'>, inpaint_crop_input_image=False, hr_option=<HiResFixOption.BOTH: 'Both'>, save_detected_map=True, advanced_weighting=None, effective_region_mask=None, pulid_mode=<PuLIDMode.FIDELITY: 'Fidelity'>, ipadapter_input=None, mask=None, batch_mask_dir=None, animatediff_batch=False, batch_modifiers=[], batch_image_files=[], batch_keyframe_idx=None), ControlNetUnit(is_ui=True, input_mode=<InputMode.SIMPLE: 'simple'>, batch_images='', output_dir='', loopback=False, enabled=False, module='none', model='None', weight=1.0, image=None, resize_mode=<ResizeMode.INNER_FIT: 'Crop and Resize'>, low_vram=False, processor_res=-1, threshold_a=-1.0, threshold_b=-1.0, guidance_start=0.0, guidance_end=1.0, pixel_perfect=False, control_mode=<ControlMode.BALANCED: 'Balanced'>, inpaint_crop_input_image=False, hr_option=<HiResFixOption.BOTH: 'Both'>, save_detected_map=True, advanced_weighting=None, effective_region_mask=None, pulid_mode=<PuLIDMode.FIDELITY: 'Fidelity'>, ipadapter_input=None, mask=None, batch_mask_dir=None, animatediff_batch=False, batch_modifiers=[], batch_image_files=[], batch_keyframe_idx=None), False, False, 'positive', 'comma', 0, False, False, 'start', '', 1, '', [], 0, '', [], 0, '', [], True, False, False, False, False, False, False, 0, False, None, None, False, None, None, False, None, None, False, 50) {}
Traceback (most recent call last):
File "D:\stable-diffusion-webui\modules\call_queue.py", line 57, in f
res = list(func(*args, **kwargs))
File "D:\stable-diffusion-webui\modules\call_queue.py", line 36, in f
res = func(*args, **kwargs)
File "D:\stable-diffusion-webui\modules\txt2img.py", line 109, in txt2img
processed = processing.process_images(p)
File "D:\stable-diffusion-webui\modules\processing.py", line 845, in process_images
res = process_images_inner(p)
File "D:\stable-diffusion-webui\extensions\sd-webui-controlnet\scripts\batch_hijack.py", line 48, in processing_process_images_hijack
return getattr(processing, '__controlnet_original_process_images_inner')(p, *args, **kwargs)
File "D:\stable-diffusion-webui\modules\processing.py", line 981, in process_images_inner
samples_ddim = p.sample(conditioning=p.c, unconditional_conditioning=p.uc, seeds=p.seeds, subseeds=p.subseeds, subseed_strength=p.subseed_strength, prompts=p.prompts)
File "D:\stable-diffusion-webui\modules\processing.py", line 1328, in sample
samples = self.sampler.sample(self, x, conditioning, unconditional_conditioning, image_conditioning=self.txt2img_image_conditioning(x))
File "D:\stable-diffusion-webui\modules\sd_samplers_kdiffusion.py", line 218, in sample
samples = self.launch_sampling(steps, lambda: self.func(self.model_wrap_cfg, x, extra_args=self.sampler_extra_args, disable=False, callback=self.callback_state, **extra_params_kwargs))
File "D:\stable-diffusion-webui\modules\sd_samplers_common.py", line 272, in launch_sampling
return func()
File "D:\stable-diffusion-webui\modules\sd_samplers_kdiffusion.py", line 218, in
samples = self.launch_sampling(steps, lambda: self.func(self.model_wrap_cfg, x, extra_args=self.sampler_extra_args, disable=False, callback=self.callback_state, **extra_params_kwargs))
File "D:\stable-diffusion-webui\venv\lib\site-packages\torch\utils_contextlib.py", line 115, in decorate_context
return func(*args, **kwargs)
File "D:\stable-diffusion-webui\repositories\k-diffusion\k_diffusion\sampling.py", line 553, in sample_dpmpp_sde
denoised = model(x, sigmas[i] * s_in, **extra_args)
File "D:\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1518, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "D:\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1527, in _call_impl
return forward_call(*args, **kwargs)
File "D:\stable-diffusion-webui\modules\sd_samplers_cfg_denoiser.py", line 256, in forward
x_out[a:b] = self.inner_model(x_in[a:b], sigma_in[a:b], cond=make_condition_dict(c_crossattn, image_cond_in[a:b]))
File "D:\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1518, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "D:\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1527, in _call_impl
return forward_call(*args, **kwargs)
File "D:\stable-diffusion-webui\extensions\sd-webui-animatediff\scripts\animatediff_infv2v.py", line 164, in mm_sd_forward
x_in[_context], sigma_in[_context],
RuntimeError: CUDA error: device-side assert triggered
CUDA kernel errors might be asynchronously reported at some other API call, so the stacktrace below might be incorrect.
For debugging consider passing CUDA_LAUNCH_BLOCKING=1.
Compile with TORCH_USE_CUDA_DSA to enable device-side assertions.

---

Traceback (most recent call last):
File "D:\stable-diffusion-webui\venv\lib\site-packages\gradio\routes.py", line 488, in run_predict
output = await app.get_blocks().process_api(
File "D:\stable-diffusion-webui\venv\lib\site-packages\gradio\blocks.py", line 1431, in process_api
result = await self.call_function(
File "D:\stable-diffusion-webui\venv\lib\site-packages\gradio\blocks.py", line 1103, in call_function
prediction = await anyio.to_thread.run_sync(
File "D:\stable-diffusion-webui\venv\lib\site-packages\anyio\to_thread.py", line 33, in run_sync
return await get_asynclib().run_sync_in_worker_thread(
File "D:\stable-diffusion-webui\venv\lib\site-packages\anyio_backends_asyncio.py", line 877, in run_sync_in_worker_thread
return await future
File "D:\stable-diffusion-webui\venv\lib\site-packages\anyio_backends_asyncio.py", line 807, in run
result = context.run(func, *args)
File "D:\stable-diffusion-webui\venv\lib\site-packages\gradio\utils.py", line 707, in wrapper
response = f(args, **kwargs)
File "D:\stable-diffusion-webui\modules\call_queue.py", line 95, in f
mem_stats = {k: -(v//-(10241024)) for k, v in shared.mem_mon.stop().items()}
File "D:\stable-diffusion-webui\modules\memmon.py", line 92, in stop
return self.read()
File "D:\stable-diffusion-webui\modules\memmon.py", line 77, in read
free, total = self.cuda_mem_get_info()
File "D:\stable-diffusion-webui\modules\memmon.py", line 34, in cuda_mem_get_info
return torch.cuda.mem_get_info(index)
File "D:\stable-diffusion-webui\venv\lib\site-packages\torch\cuda\memory.py", line 663, in mem_get_info
return torch.cuda.cudart().cudaMemGetInfo(device)
RuntimeError: CUDA error: device-side assert triggered
CUDA kernel errors might be asynchronously reported at some other API call, so the stacktrace below might be incorrect.
For debugging consider passing CUDA_LAUNCH_BLOCKING=1.
Compile with TORCH_USE_CUDA_DSA to enable device-side assertions.

[saogalaxy]

tried with official models after deleting the venv and letting it rebuild now it's generating the black squares nan message

[saogalaxy]

saved the not working with 1.9.4 using official file and rebuild venv by deleting and relaunching automatic 1111. getting nans black output moving over to other issues to see if its got a soluction.